Abstract :

Exploration on complex decision making has extended from complex decision behaviourist approach to cognitive approach that focuses on complex decision processes that ensue prior to response. In neural computational simulations, each complex decision during complex decision task is represented by node of neural activity. Complex decision related neural activity has components of intensification of activity and complex decision inception for neural activity to overcome for complex decision to be completed. One way to investigate computational complex decision making is to scan positioning of complex decision behaviour leading to judgment point. Eye movements are central measure of complex decision. Eye movements are indissolubly linked to optical consideration as both are prime tools for choosing stimulating shares of chromatic prospects for enriched perceptual and rational processing. Investigating eye movements is expedient in providing evidence of orientation of complex decision behaviour replicating computational complex decision during complex decision formation. Role of eye movements, intentional or reflex, help in gaining, possessing and tracing visual inducements, during complex decision formation is not entirely clear. Current proof suggests that orientation of eye movement itself may not be an essential constituent. Rather, it can be as a result of intensification in contact to incitement as an e influential factor in complex decision formation. Purpose of present scholarship is to survey foregoing conclusions that eye movements have contributory stimulus on complex decision formation in a rational fashion. We review experiential studies that employ eye movement monitoring as process tracing and tracking method with gazing in complex decision - making research. Using Kowler model, we present an investigation that explains experimental methods and analysis with contemporary eye tracking savoir-faire. This proposal countenances a specific hypothesis about role of eye movements in complex decision; understanding how eye movements are premeditated, carried out notwithstanding recurrent vicissitudes in optical assortment that eye movement harvest. One major effort is understanding how should complex decision makers’ decide, deal with risks and uncertainties, create options better than originally available, potential responses to problems and evaluate strengths and weaknesses of each prospective action using apparatus of eye tracking / tracing and gazing.

Keywords :

Complex Decision, Eye Movements, Kowler Model, Optical Assortment, Eye Tracking / Tracing and Eye Gazing.

Introduction

Everyday life is full of complex decisions and choices. An important question for many researchers is how entrepreneur (s) makes (ophthalmic) complex decisions. Specifically, researchers are interested in the assumptions, beliefs, habits, and tactics that entrepreneur (s) use to make everyday complex decisions. Research suggests that the eye considers various sources of information before making a complex decision. However, how does it do this? In addition, why does the process sometimes go awry, causing us to make impulsive, indecisive, and confused complex decisions; the kinds that can lead to risky and potentially dangerous behaviours? Human behaviour is not the product of a single process, but rather reflects the interaction of different specialized subsystems. These systems, the idea goes, usually interact seamlessly to determine behaviour, but at times, they compete. Result is that eye sometimes argues with itself, as these distinct systems come to different conclusions about what we should do. Human behaviour, in general, is not under constant and detailed control of careful and accurate hedonic calculations, but is product of an unstable and irrational complex of reflex actions, impulses, instincts, habits, customs, fashion, and hysteria. For a long time, economists have argued that humans make complex decisions by obeying laws of rationality. Complex decisions are an inevitable part of human activities.

Expansion of ophthalmic parallels development of cognitive science. Neuro - ophthalmic has bridged contrasting fields of ophthalmic and psychology. Ophthalmic, psychology, and neuroscience are converging today into a single, unified discipline with ultimate aim of providing single, general theory of decision behaviour. This is the emerging field of neuro - ophthalmic in which consilience, accordance of two or more inductions drawn from different groups of phenomena, seems to be operating. Economists and psychologists are providing rich conceptual tools for understanding and modeling behaviour, while neurobiologists provide tools for the study of mechanism. The goal of this discipline is thus to understand the processes that connect sensation and action by revealing the neurobiological mechanisms by which complex decisions are made. Such union is almost exclusively attributable to changes within ophthalmic. Neuro - ophthalmic has inspired change because the important findings have posed more of a challenge to standard ophthalmic perspective. The important source of inspiration for neuro economist has been neuro judgment research, which can, in turn, be seen as an amalgamation of ideas from cognitive science and ophthalmic. Neuro - ophthalmic has primarily challenged customary ophthalmic postulation that complex decision-making is a unitary process a simple matter of integrated and coherent utility maximization suggesting instead that it is driven by interaction between automatic and controlled processes.

Despite substantial advances, question of how we design and how we ought to craft judgments and complex decisions has engaged researchers for decades, with different disciplines approaching the problem through characteristically different techniques. However, neuro - ophthalmic complex decision making has recently emerged as an inter-disciplinary effort to bridge this gap. It has sought to integrate ideas from fields of organisational psychology, neuroscience and neuro - ophthalmic in an effort to specify accurate models of choice and complex decision. Research investigates neural bases of complex decision predictability and value, central parameters in ophthalmic model of expected utility. Neuro - multiple - systems approach to complex decision - making, in turn, influences ophthalmic, a perspective strongly rooted in organisational psychology and neuroscience. Integration of these approaches and methodologies offers exciting potential for construction of near - accurate models of complex decision - making.

How do we make a complex decision? Many complex decision makers have a tendency to seek more information than required to make a good complex decision. When too much information is sought and obtained, one or more of several problems can arise. A delay in the complex decision occurs because of the time required to obtain and process the extra information. This delay could impair the effectiveness of the complex decision or solution. Information overload will occur. In this state, so much information is available that complex decision-making ability actually declines because the information in its entirety can no longer be managed or assessed appropriately. A major problem caused by information overload is forgetfulness. When too much information is taken into memory, especially in a short period, some of the information (often that received early on) will be pushed out.

Deciphering eye - environment transactions requires mechanistic understandings of the neurobiological processes that implement value-dependent complex decision-making. There is a crucial difference between ‘thinking about thinking’ and actually enhancing eye and mental processes by developing latent potential of each individual. Theoretical accounts posit that human eye accomplishes this through a series of neural computations, in which expected future reward of different complex decision options are compared with one another and then the option with highest expected value is selected. If human eye is often compared with a computer, one aspect is crucially missing. Humans define goals for information processing in computers, whereas goals for biological eyes are determined by need for survival in uncertain and competitive environments. How to handle the eyes behind entrepreneurialism in the age of dramatic change and growing uncertainty? What then are the coherent eye dynamics underlying prediction, control and complex decision-making?

Major part involves analysis of finite set of alternatives described in terms of some evaluative criteria. These may be benefit or cost in nature. Then, problem might be to rank these alternatives in terms of how attractive they are when all criteria are considered simultaneously. Another goal might be to find the best alternative or determine relative total priority of each alternative when all criteria are considered simultaneously. Solving such problems is focus of multi-criteria complex decision analysis. This is debated, as there are many methods that yield different results when applied on exactly the same data. This leads to formulation of a ‘neuro - ophthalmic complex decision making paradox’.

Problem Statement

Every complex decision is made within a complex decision environment, which is defined as the collection of information, alternatives, values, and preferences available at the time of the complex decision. An ideal complex decision environment would include all possible information, all of it accurate, and every possible alternative. However, both information and alternatives are constrained because the time and effort to gain information or identify alternatives are limited. The time constraint simply means that a complex decision must be made by a certain time. We all make complex decisions of varying importance every day, so the idea that complex decision-making can be a rather sophisticated art may at first seem strange. However, studies have shown that most entrepreneurs are much poorer at complex decision making than they think. An understanding of what complex decision-making involves, together with a few effective techniques, will help produce better complex decisions.

Making a complex decision implies that there are alternative choices to be considered, and in such a case we want not only to identify as many of these alternatives as possible but to choose the one that (1) has highest probability of success or effectiveness and (2) best fits with our goals, desires, lifestyle, values, and so on. Complex decision-making is the process of sufficiently reducing uncertainty and doubt about alternatives to allow a reasonable choice to be made from among them. This definition stresses the information-gathering function of complex decision-making. It should be noted here that uncertainty is reduced rather than eliminated. Very few complex decisions are made with absolute certainty because complete knowledge about all the alternatives is seldom possible. Thus, every complex decision involves a certain amount of risk. If there is no uncertainty, you do not have a complex decision; you have an algorithm--a set of steps or a recipe that is followed to bring about a fixed result. Emerging neuroscience evidence suggests that sound and rational neuro - ophthalmic complex decision making depends on prior accurate emotional processing. Somatic marker hypothesis provides a systems-level neuro-anatomical and cognitive framework for neuro - ophthalmic complex decision making and its influence by emotion. Key idea is that neuro - ophthalmic complex decision-making is a process that is influenced by marker signals. This influence can occur at multiple levels of operation, some of which occur consciously, and some of which occur non-consciously. The issues, because modern models ignore influence of emotions on neuro - ophthalmic complex decision-making, that crop up is;

• What computational mechanisms allow the eye to adapt to changing circumstances and remain fault-tolerant and robust?
• How (and where) are value and probability combined in eye and what is the dynamics of this computation?
• Under what circumstances do these various systems cooperate or compete?
• When there is competition, how and where is it adjudicated?
• Do higher-level deliberative processes rely similarly on multiple mechanisms, or a single, more tightly integrated (unitary) set of mechanisms?

Emerging neuro - ophthalmic science evidence suggests that sound and rational neuro - ophthalmic complex decision making depends on prior accurate emotional processing. Somatic marker hypothesis provides systems-level neuro - ophthalmic anatomical and cognitive framework for neuro - ophthalmic complex decision making and its influence. These occur at multiple levels of neuro-feedback operation. Some occur consciously and some occur non-consciously. The issues that crop up are; what happens when Clinicians change minds? What algorithms allow sensorimotor behaviours to be learned? What computational mechanisms allow eye to adapt changing circumstances? How (and where) are value and probability combined in eye and what is the dynamics of neuro-feedback? What neural systems track defined forms of utility? To what extent do utility computations generalize to complex decision, which are tasks that are more complex? How do systems that focus on immediate complex decision interact?

Neuro - Ophthalmic Perspectives

Neuro - ophthalmic has further bridged the once disparate fields of ophthalmic and psychology. Such convergence is almost exclusively attributable to changes within ophthalmic. Neuro - ophthalmic has inspired more change within ophthalmic than within psychology because the most important findings in Neuro - ophthalmic have posed more of a challenge to the standard ophthalmic perspective. Neuro - ophthalmic has primarily challenged the standard ophthalmic assumption that complex decision making is a unitary process-a simple matter of integrated and coherent utility maximization-suggesting instead that it is driven by the interaction between automatic and controlled processes. Despite substantial advances, the question of how we make complex decisions and judgments continues to pose important challenges for scientific research. Historically, different disciplines have approached this problem using different techniques and assumptions, with few unifying efforts made.

Neuro - ophthalmic has recently emerged as an inter-disciplinary effort to bridge this gap. The goal of neuro - ophthalmic is a mathematical theory of how the eye implements complex decisions that is tied to behaviour. This theory is likely to show some complex decisions for which rational-choice theory is a good approximation (particularly for evolutionarily sculpted or highly learned choices), to provide a deeper level of distinction among competing neuro alternatives, and to provide empirical inspiration for ophthalmic to incorporate more nuanced ideas about endogeneity of preferences, individual difference, emotions, endogenous regulation of states, and so forth. Research in neuroscience and psychology has begun to investigate neural bases of complex decision predictability and value, central parameters in the ophthalmic theory of expected utility. Ophthalmic, in turn, is being increasingly influenced by a multiple-systems approach to complex decision-making, a perspective strongly rooted in psychology and neuroscience. The integration of these disparate theoretical approaches and methodologies offers exciting potential for the construction of more accurate models of complex decision-making.

Neuro - ophthalmic seeks to ground ophthalmic theory in detailed neural mechanisms that are expressed mathematically and make neuro predictions. Neuro - ophthalmic uses knowledge about eye mechanisms to inform ophthalmic theory. It opens up the ‘black box’ of the eye, much as organizational ophthalmic opened up the theory of the organisation. The key insight for ophthalmic is that the eye is composed of multiple systems that interact. Controlled systems (‘executive function’) interrupt automatic ones. Eye evidence complicates standard assumptions about basic preference, to include homeostasis and other kinds of state-dependence, and shows emotional activation in ambiguous choice and strategic interaction.

We start with the premise that most basic complex decisions we make (e.g., in the form of choices or effort allocation) can be traced back in structure of macro-scale eye activity, as measured with modern neuroimaging apparatus. Typically, such responses involve many regions in the eye (from mid-eye to prefrontal cortices, through parietal and basal ganglia structures), who’s precise function in terms of motivational processes depends upon the context (e.g., specific task eye is solving). This context-dependency expresses itself through the (induced) specific plasticity of these eye networks, in parallel to phasic and tonic changes in neuro-modulator activity. In turn, this macro-scale reconfiguration of eye networks subtends learning and yield adaptive behaviour. In other words, it is very likely that goal-directed behaviour emerges from the very same interactions that shape the spatio-temporal dynamics of macro-scale eye networks. This means that understanding mechanics of motivational processes from the multimodal observation of eye activity (electrophysiology, fMRI) and neuro measurements (explicit choices, reaction times, autonomic arousal signals, grip force) poses the exciting challenge of quantitatively relating information processing to eye effective connectivity.

How are organisational and ophthalmic complex decisions making processes carried out in eye? Do we interpret research findings when neurological results conflict with self-report? Knowing how eye is working explains little about what mind produces; what we think, what we believe and how we craft complex decisions.’ What are the general implications of neuro ophthalmic? Neuroscience techniques permit to look inside eye while it experiences outcomes and crafts complex decisions. Neuro - ophthalmic uses techniques to ask how entrepreneur (s) craft complex decisions and examine implications. Central argument of this proposal is that Neuro - ophthalmic, organisational psychology and neuroscience each benefit from taking account of insights that other disciplines offer in understanding complex decision-making.

Questions that will be answered in this course include how to choose in tough situations where stakes are high, and there are multiple conflicting objectives? How should we plan? Why do projects often take longer and cost more than planned? How can we deal with risks and uncertainties involved in a complex decision? How can we create options that are better than the ones originally available? How can we become better complex decision makers? What resources will be invested in complex decision - making? What are the potential responses to a particular problem or opportunity? Who will make this complex decision? Every prospective action has strengths and weaknesses; how should they be evaluated? How will they decide? Which of the things that could happen would happen? The complex decision has been made. How can we ensure it will be carried out? Unfortunately, these are the very questions neuroscientists suspect are most crucial for understanding one of the most complex of human behaviours: how we complex decisions. Subsequent issues are,

• There is a need to attend as to how neuroscience can, and already has, benefited from Neuro - ophthalmic’ unitary perspective.
• How neuroscience has been enriched by taking account multiple specialized neural systems with potential research directions.

Research Issues

• How do eyes play a role in complex decision making?
• How does decision maker decide through ophthalmic estimates?

Aim and Objective(s)

Role of eye movements during complex decision construction is not entirely clear. In neural computational simulations of complex decision making, preference in judgment task is epitomised by corresponding protuberance of neural bustle. This activity has two idiosyncratic apparatuses: intensification of action and complex decision inception for action to overcome in order for choice to be made. A technique to review is to scan orientation of behaviour leading up to complex decision point. Investigating eye movements is expedient in providing substantiation of complex decision positioning of behaviour replicating computational complex decision. Eye movements reproduce escalatory complex decision significance, leading to gaze chute in which eye movements dynamically feed value of individual opportunities. Intention of this proposal is to shadow preceding suppositions that eye movements have causative stimulus on complex decision formation.

In organisational sciences, study of complex decision-making is an important preliminary step to provide a sound foundation for analysis of equilibrium in organisational systems. Neuro - ophthalmic analysis has been a fruitful development in this direction. In recent past, a new direction of research has emerged, studying interplay of complex decision making of single individual with entrepreneurial environment that surrounds him. Principal aim of proposed study is to model computational and neurobiological basis of value-based complex decision making by using tools from Neuro - ophthalmic and cognitive neuroscience. This proposal aims at two specific ways in which neuro - ophthalmic modeling can endeavour towards complex decision - making; first, incorporate neuroscience and organisational psychology of formal, rigorous ophthalmic modeling approach, and secondly, awareness of evidences for multiple systems involved in complex decision-making.

Statistical techniques embedding the above models for analyzing neuroimaging and neuro data. These probabilistic inversion schemes borrow from disciplines such as inverse problems, statistical physics and machine learning. If only, they are necessary to capture the inter-individual variability of neurophysiological and neuro responses. More generally, they are essential to root a principled approach to model comparison and selection, given experimental data. This is important to identify candidate psycho-physiological scenarios that have the ability to quantitatively explain concurrent neuroimaging and neuro data.

Focal point is to understand;

• Neural processes underlying how we craft complex decisions and choices.
• Understand mechanisms of complex decision-making using functional neuroimaging methodologies.
• Integrating interdisciplinary research towards contributing to complex decision neuroscience.

Objective is to put forward a model for neuro - ophthalmic complex decision, in which interaction between variables of neuro - ophthalmic complex decision processes are addressed via;

• How does eye assign value to different options under consideration?
• How does eye compare assigned values in order to design a choice?
• How is ‘process of valuation’ changed when control is exerted?
• How is value computed in complex / abstract domains?
• How can neuro - ophthalmic be applied to design solutions to real - time problems?

This plan ventures to speculate on neurobiological data and offer a model about relationship between human rationality, emotions and underlying neuro-ophthalmic. Emotions and neuro-ophthalmic underpinnings involved in complex decision - making would provide scaffolding for construction of cognition and for self-processes which undergird consciousness. This proposal would examine and compare tools of neural network modeling.

An ambition here is to construct a modeling framework general enough to relate the various experimental studies conducted in the group with each other, without compromising predictive power. One difficulty is to balance complexity of the above models with the sophistication of the experimental design and data analysis procedures. This simply means that these three aspects of the research have to be conducted in parallel. This joint effort towards a quantitative psycho-physiological understanding of motivation is what we term 'computational Neuro - ophthalmic. This work would attempt to explores socio-economic phenomena through individual action, complex decision-making, and reasoning processes, draw from such disciplines as philosophy, ophthalmic, complex decision-making, sociology, cognitive and social psychology, report on concept of mind of social actor, cognitive models of reasoning, complex decision-making and action, computational and neural models of socio-economic phenomena, etc.

Through computational approaches, attempt will be to clarify how neural soundings realize ‘mental sounding’ in clinician complex decision making. This work would attempt to explore phenomena through individual action, complex decision making, and reasoning processes on concept of cognitive models of complex decision - making. Principal aim of proposed study is to model neuro - ophthalmic basis of complex decision making by using tools from neurofeedback. Purpose is to elucidate principles and complex decision - making mechanism in eye interaction between variables of feedback processes. Focal point is to understand neural processes underlying how Clinicians craft complex decision and complex decision, understand mechanisms of complex decision making and integrating interdisciplinary research proposal towards contributing to neuro - ophthalmic complex decision.

Exploration on complex decision making has protracted from behaviourist methodology to cognitive approach that centres on complex decision processes. In neural computational simulations, each complex decision task is signified by protuberance of neural activity. Complex decision correlated neural activity has constituents of spiralling of activity and complex decision initiation for neural activity to overcome for complex decision to be completed. A way is to scan positioning of (complex decision maker) complex decision behaviour primary to complex decision point. Eye movements are crucial measure indistinctly concomitant to ocular reflection as both are chromatic prospects for rational processing. Investigating eye movements is expedient in providing evidence of orientation of (complex decision maker) complex decision behaviour reproducing computational complex decision in complex decision formation. Role of eye movements, deliberate or impulse, help in attainment, retaining and outlining optical stimuli, during (complex decision maker) complex decision formation is not clear. Proof suggests that orientation of eye movement may not be a critical constituent. It can be result of amplification in contact to incitement as a persuasive factor in (complex decision) formation.

Focus has remained on fundamental questions: what mechanisms keep gaze stable with either stationary or moving targets? How does motion of image on retina affect vision? Where do complex decision makers look, why and when performing complex task? How can world appear clear and stable despite continual movements of eyes? What determines complex decisions made about where to look? How are these complex decisions carried out? How do we maintain percept of clear and stable world despite occurrence of saccades? Purpose is to survey foregoing conclusions that eye movements have contributory stimulus on (complex decision maker) complex decision formation in rational fashion. This reviews experiential studies that employ eye movement monitoring as tracking method with gazing in (complex decision maker) complex decision - making research. This countenances a specific hypothesis about role of eye movements in complex decision; understanding how eye movements are premeditated, carried out notwithstanding recurrent vicissitudes in optical assortment that eye movement harvest. One major effort is understanding how should complex decision makers’ decide, deal with risks and uncertainties, create options better than originally available, potential responses to problems and evaluate strengths and weaknesses of each prospective action using apparatus of complex decision making, Kowlerian model, eye movement, process tracing, tracking method and gazing.

Eye Movement: this refers to voluntary or involuntary movement of eyes, helping in attaining, possessing and tracking optical impetuses. ‘Saccade’ is quick, concurrent movement of both eyes between two or more phases of fixation in same direction. Cohort of saccade may consider outcome of complex decision-making process. Functional models are based on accretion of corporeal corroboration in favour of various alternatives in sprint to (complex decision maker) complex decision threshold. Outcome is affected by variables such as value of sensory evidence, probability of alternative movements and reward associated with different movements. Salient progress has been made in studies of visual saccadic complex decision making, a system that is becoming a model for understanding (complex decision maker) complex decision making in general. In this, theoretical models of complex decision making are beginning to be used to describe computations (complex decision maker) eye must perform when it connects sensation and action (Glimcher; 2003).

Eye Tracking: eye tracking is process of measuring either point of gaze (where one is looking) or motion of eye relative to head. In unassuming terms, eye tracking is measurement of eye activity. Where do (complex decision makers) look? What do (complex decision makers) ignore? When do (complex decision makers) blink? How does pupil react to different stimuli? Application of (complex decision maker) eye movements to user interfaces; both for analysing interfaces, measuring usability and gaining insight into human performance and as actual (complex decision maker) control medium within human (complex decision maker) - mainframe dialogue.

Eye Gazing: (complex decision maker) eyes and (complex decision maker) gaze are important stimuli for (complex decision maker) interactions. Gaze means ‘to look steadily, intently and with fixed (attention). (Complex decision maker) eye region of represents special area due to extensive amount of (complex decision maker) information that can be extracted. Eye region carries information necessary for emotion recognition. Cognitive and (complex decision maker) behavioural neuro - complex decision science has recently witnessed explosion of scholarship investigating processing of (complex decision maker) eye region and gaze direction in various tasks and organisational situations. Due to extensive complexity, underlying neural systems subtending these (complex decision maker) processes are far from being agreed.

Hypothesis

Eyes, as platform of complex decision-making, are indispensable to dynamics of neuro - ophthalmic complex decision modeling. Hypothesis rejects attempts to limit human reasoning and neuro - complex decision making to mechanisms relying in an unrelated manner on either conditioning or cognition alone.

Research Methodology

Methodology proposes to incorporate Kowler (Rutgers University, USA) model states that eye movements are integral part of (complex decision maker) interactions with visual world. Tasks, inspecting contents of visual scene, require that complex decision makers bring eye swiftly and precisely to weighty and expedient positions. Eye movements accomplish this with virtually no overt effort or awareness. Model involves (complex decision maker) eye movements and connections between eye movements, perception and cognition. Model is devoted to understanding how eye movements are planned, how they are carried out, how to maintain percept of clear, stable and coherent world despite continual changes in visual array that eye movements produce. One major effort understands relationship between (complex decision maker) eye movements and (complex decision maker) attention, question of how (complex decision maker) attention is involved in eye movement control and how to attend to visual environment independently of movements of eye. Model emphasizes active integration of (complex decision maker) eye movement planning with ongoing visual and cognitive processes. The model incorporates components of visual (attention), eye movements, eye movements and their role in visual and (complex decision maker) cognitive process, (attention) during active visual (complex decision maker) tasks, oculomotor control, visual memory, and allocation of visual (attention), accuracy and precision of visual and cognitive processes in new directions for (complex decision maker) complex decision research.

Rationale

To date, management model of complex decision has not been informed by the way eye functions. Goal of studying complex decision behaviour is prediction. This research proposal would seek to develop theoretical models, based on axiomatic foundation of neurofeedback, which can predict clinician complex decision. These models would take as inputs state of external world and generate as outputs actual complex decision made by human choosers. For this reason, research proposal would aim towards achieving compact and abstract models of complex decision. Analysis of observations would include not only complex decision between options, per se, but additional neurofeedback data, including length of time taken to make complex decision, number of error in complex decision and psychophysical model(s).

Research Contributions

The study of complex decision making and problem solving has attracted attention. Expanded research proposal requires (model - based empirical) study of behavior and provide setting for basic research proposal on how ill-structured problems are, and can be, solved. Clinician neuro - complex decision making, which is much less well understood than individual complex decision - making and problem solving, can be studied with great profit using already established methods of inquiry, especially through intensive studies.

Neuro - ophthalmic management offers solution through series of measurements of eye activity at the time of complex decision. It provides conceptual and philosophical framework for understanding and conducting research at ophthalmic science, management and psychology spectrum. Neuro - ophthalmic management theory proposes to build eye-based models capable of predicting observed behaviour. Neuro - ophthalmic management will shed light on causes of behaviour (and neuro - ophthalmic anomalies) and help build theories capable of explaining and predicting complex decision. Measurement of eye activity provides information about underlying mechanisms eye during complex decision processes. Neuro - ophthalmic complex decision modelling would help when new information is inconsistent with goals. Combining the above disciplines gives interdisciplinary insight to define fundamentals of neuro - ophthalmic complex decision making.

• Neuro - ophthalmic offers a solution through an additional set of data obtained via a series of measurements of eye activity at the time of complex decisions,
• Provides a conceptual and philosophical framework for understanding and conducting neuro - ophthalmic research at the intersection of neuroscience, ophthalmic and psychology,
• Describes the first standard model for the choice process that links and spans neurobiological, psychological, and ophthalmic levels of analysis,
• Applies neuroscience to both neuro ophthalmic and neoclassical ophthalmic, and ties both fields to biological constraints in how we judge relative value and make choices,
• An important resource for researchers in disciplines ranging from ophthalmic to neuroscience, as well as to scholars of the theory of science and the development of interdisciplinary research,
• Experimental Neuro - ophthalmic can be seen as a subfield of experimental ophthalmic, where neuro data is enriched with eye data,
• Neuro - ophthalmic theory proposes to build eye-based models capable of predicting observed behaviour,
• New set of data provided by experimental Neuro - ophthalmic will shed light on the causes of behaviour (and therefore of the neuro anomalies) and help build new theories capable of explaining and predicting complex decisions,
• Measurement of eye activity provides information about the underlying mechanisms used by the eye during choice processes, In particular, it shows which eye regions are activated when a complex decision is made and how these regions interact with each other, This knowledge can then be used to build a model that represents this particular mechanism,
• Combining the above disciplines gives an interdisciplinary insight to define fundamentals of neuro - ophthalmic complex decision making that has eluded researchers working within each individual field.

Research Outcome

Complexly interlinked imaging technologies, new imaging technologies have motivated studies of internal order of mind. Interaction between entrepreneurial and science is not smooth with difference in perception and reasoning potentials on either side. It suggests fundamental change in how to think, observe and generate choices. Explorations have extended from neural soundings to stimulating shares of chromatic prospects for rational processing. Research proposal attempts would discuss findings to understand neuro - design and offer to answer issues in clinician preference dynamics. Research proposal attempts would conclude with distinctive propositions and presents directions for future research proposal. Research proposal attempts would aid rethinking foundations of clinician preference dynamics by providing alternative taxonomy for rational preference problems. This research proposal would open new vistas for future replicative studies.

Conclusion

What are the mechanisms that keep gaze stable with either stationary or moving targets? How does motion of (complex decision maker) cognitive image on retina affect vision? Where do (complex decision makers) look - and why - when performing complex (complex decision maker) task? How can the world appear clear and stable despite continual movements of (complex decision maker) eyes? (Complex decision maker) cognitive processes driving eye movements during (complex decision maker) complex decision making are not in any consequential way different from those in similar tasks. (Complex decision maker) eye movements in (complex decision maker) complex decision making are partially driven by (complex decision maker) task demands. Eye movements in (complex decision maker) complex decision making are partially driven by stimulus properties that bias (complex decision maker) information uptake in favor of visually salient stimuli. Eye movements do not have causal effect on (complex decision maker) preference formation. However, through properties inherent to visual system, such as stimulus-driven attention, (complex decision maker) eye movements do lead to down-stream effects on (complex decision maker) complex decision making. Complex decision makers optimize eye movements to reduce demand on (complex decision maker) memory and reduce number of fixations and length of saccades needed to complete (complex decision maker) complex decision task. Drivers of eye movements in (complex decision maker) complex decision making change dynamically within tasks (Orquin and Loose ; 2013). Attention should be paid for performing experimental procedures in order to evaluate usability, accuracy and reliability of eye tracking systems. Any (complex decision) model that aims to describe (complex decision maker) complex decision making must reflect that visual information play central role in complex decision dynamics.

References

• Abdellaoui, M., Luce, D. R., Machina, M. J., and Munier, B. (Eds.) (2007). Uncertainty and Risk: Mental, Formal, Experimental Representations. Theory and Decision Library. Springer.
• Adelson E. H. Movshon J. A. (1982). Phenomenal Coherence of Moving Visual Patterns. Nature, 300, 523–525.
• Aggleton, John P., Ed., The Amygdala: A Functional Analysis (2nd Edn, Oxford: Oxford University Press, 2000).
• Araujo, C., Kowler, E. And Pavel, M. (2001) Eye Movements During Visual Search: The Costs Of Choosing The Optimal Path. Vision Research, 41, 3613-3625.
• Ashby, N. J. S., Glöckner, A., And Dickert, S. (2011). Conscious And Unconscious Thought In Risky Choice: Testing Capacity Principle And Appropriate Weighting Principle Of Unconscious Thought Theory. Frontiers in Psychology, 2, 261.
• Ayal, S., Hochman, G., and Zakay, D. (2011). ‘Two Sides of The Same Coin: Information Processing Style And Reverse Biases’. Judgment and Decision Making, 6, 295-306.
• Ayal, S., Rusou, Z., Zakay, D., and Hochman, G. (2015). ‘Determinants Of Judgment And Decision Making Quality: The Interplay Between Information Processing Style And Situational Factors’. Frontiers In Psychology, 6:1088.
• Ayal, S., Rusou, Z., Zakay, D., and Hochman, G. (2015). Determinants Of Judgment And Decision Making Quality: The Interplay Between Information Processing Style And Situational Factors. Frontiers in Psychology, 6:1088.
• Ayal, S., Zakay, D., and Hochman, G. (2012). ‘Deliberative Adjustments Of Intuitive Anchors: The Case Of Diversification Behavior’. Synthese, 189, 131-145 (A Special Issue On Psychological Models Or (Ir)Rational And Decision Making)
• Baars, B. J. (1986). The Cognitive Revolution in Psychology. New York: Guilford Press.
• Bahcall, D.O. And Kowler, E. (1999) Attentional Interference At Small Spatial Separations. Vision Research, 39, 71-86.
• Bahcall, D.O. And Kowler, E. (1999) Illusory Shifts In Perceived Visual Direction Accompany Adaptation Of Saccadic Eye Movements. Nature, 400, 864-866.
• Bahcall, D.O. And Kowler, E. (2000) The Control Of Saccadic Adaptation: Implications For The Scanning Of Natural Visual Scenes. Vision Research, 40, 2779-2796.
• Ballard D. H. Hayhoe M. M. Li F. Whitehead S. D. (1992). Hand-Eye Coordination during Sequential Tasks. Philosophical Transaction of The Royal Society Of London B: Biological Sciences, 337, 331–338.
• Ballard D. H. Hayhoe M. M. Pelz J. B. (1995). Memory Representations in Natural Tasks. Journal Of Cognitive Neuroscience, 7, 66–80.
• Ballard D. H. Sprague N. (2005). Modeling the Brain's Operating System. In Brain, Vision, And Artificial Intelligence, Proceedings (Vol. 3704, Pp. 347–366). Berlin, Germany: Springer-Verlag.
• Ballard D. H. Sprague N. (2006). Modeling the Brain's Operating System Using Virtual Humanoids [Proceedings Paper]. International Journal of Pattern Recognition and Artificial Intelligence, 20, 797–815.
• Band, G.P.H., Ridderinkhof, K.R. And Segalowitz, S. (2002). Explaining Neurocognitive Aging:Is One Factor Enough? Brain and Cognition, 49, 259 - 267.
• Bandura, A. (1977). Self-Efficacy: Toward A Unifying Theory of Behavioural Change. Psychological Review, 84, 191-215.
• Barany, D. A., Della-Maggiore, V., Viswanathan, S., Cieslak, M., Grafton, S. T. (2014). Feature Interactions Enable Decoding Of Sensorimotor Transformations For Goal-Directed Movement. Journal Of Neuroscience, 34, 6860-6873.
• Baron, J. (2004). Normative Models Of Judgment And Decision Making. In D. J. Koehler And N. Harvey (Eds.), Blackwell Handbook Of Judgment And Decision Making (Pp. 19-36). London, Uk: Blackwell.
• Bayerl P. Neumann H. (2007). A Fast Biologically Inspired Algorithm For Recurrent Motion Estimation. Ieee Transactions On Pattern Analysis And Machine Intelligence, 29, 246–260.
• Beach, L. R., And Mitchell, T. R. (1978). A Contingency Model For The Selection Of Decision Strategies. Academy Of Management Review, 3, 439-449.
• Bechara, A. (2011). ‘Human Emotions In Decision Making: Are They Useful Or Disruptive,’ In Neuroscience Of Decision Making, Eds O. Vartanian And D. R. Mandel (New York And Hove: Psychology Press), 73–95.
• Bechara, A., And Damasio, D. R. (2005). The Somatic Marker Hypothesis: A Neural Theory Of Economic Decision. Games Econ. Behav. 52, 336 - 372.
• Bechara, A., Damasio, H., And Damasio, A. R. (2000). Emotion, Decision Making And The Orbitofrontal Cortex. Cereb.Cortex 10, 295–307.
• Bechara, Antoine, Antonio R. Damasio, Hanna Damasio, And Steven W. Anderson, ‘Insensitivity To Future Consequences Following Damage To Human Prefrontal Cortex’, Cognition, 50 / 1-3 (1994), 7-15.
• Ben Zur, H., And Breznitz, S. J. (1981). The Effect Of Time Pressure On Risky Choice Behavior. Acta Psychologica, 47, 89-104.
• Bender, J., Tark, K.-J., Reuter, B., Kathmann, N., And Curtis, C. E. (2013). Differential Roles Of Frontal And Parietal Cortices In The Control Of Saccades. Brain And Cognition, 83, 1-9.
• Bennett, M. R., And Hacker, P. M. S. (2003). Philosophical Foundations Of Neuroscience. Oxford: Blackwell.
• Bernheim, B.D., 2009, On The Potential Of Neuroeconomics: A Critical (But Hopeful) Appraisal, American Economic Journal: Microeconomics, 1, 1-41.
• Berntson, Gary G. And John T. Cacioppo, Eds., Handbook Of Neuroscience For The Behavioral Sciences, I (Hoboken, Nj: Wiley, 2009).
• Berryhill M. E. Chiu T. Hughes H. C. (2006). Smooth Pursuit Of Nonvisual Motion. Journal Of Neurophysiology, 96, 461–465.
• Betsch, T., And Pohl, D. (2002). Tversky And Kahneman’s Availability Approach To Frequency Judgement: A Critical Analysis. In P. Sedlmeier And T. Betsch (Eds.), Etc.: Frequency Processing And Cognition (Pp. 109–119). Oxford, England: Oxford University Press.
• Betsch, T., And Glöckner, A. (2010). Intuition In Judgment And Decision Making: Extensive Thinking Without Effort. Psychological Inquiry, 21, 279–294.
• Betsch, T., Glöckner, A., And Haberstroh, S. (2000). Commerce: A Micro-World Simulation To Study Routine Maintenance And Deviation In Repeated Decision Making. Methods Of Psychological Research, 5.
• Bettman, J. R., Johnson, E. J., And Payne, J. W. (1990). A Componential Analysis Of Cognitive Effort In Choice. Organizational Behavior And Human Decision Processes, 45, 111-139.
• Betz T. Kietzmann T. C. Wilming N. König P. (2010). Investigating Task-Dependent Top-Down Effects On Overt Visual Attention. Journal Of Vision, 10, (3):15, 1–14.
• Beutter B. R. Stone L. S. (1998). Human Motion Perception And Smooth Eye Movements Show Similar Directional Biases For Elongated Apertures. Vision Research, 38, 1273–1286.
• Beutter B. R. Stone L. S. (2000). Motion Coherence Affects Human Perception And Pursuit Similarly. Visual Neuroscience, 17, 139–153.
• Bhutani N., S. Ray, A. And Murthy A. Is Saccade Averaging Determined By Visual Processing Or Movement Planning? J. Neurophysiology. 108: 3161-3171 (2012).
• Bickel, W. K., Jarmolowicz, D. P., Mueller, E. T., And Gatchalian, K. M. (2011a). The Neurodecision Managerial Economic Behavioural Economics And Neuroeconomics Of Reinforcer Pathologies: Implications For Etiology And Treatment Of Addiction. Curr. Psychiatry Rep. 13, 406–415.
• Bickel, W. K., Jones, B. A., Landes, R. D., Christensen, D. R., Jackson, L., And Mancino, M. (2010). Hypothetical Intertemporal Choice And Real Economic Neurodecision Managerial Economic Behaviour: Delay Discounting Predicts Voucher Redemptions During Contingency-Management Procedures. Exp. Clin. Psychopharmacol. 18, 546–552.
• Bickel, W. K., Mueller, E. T., And Jarmolowicz, D. P. (2012b). ‘The Neurodecision Managerial Economic Behavioural Economics Of Reinforcer Pathologies: Novel Approaches To Addictive Disorders,’ Inapa Addiction Syndrome Handbook, Ed H. J. Shaffer (Washington, Dc: American Psychological Association), 333–363.
• Bindemann M. (2010). Scene And Screen Center Bias Early Eye Movements In Scene Viewing. Vision Research, 50, 2577–2587.
• Binmore, K. And Shaked, A., 2010, Experimental Economics: Where Next? Journal Of Economic Behavior And Organization, 73, 87-100.
• Blanke M. Harsch L. Knoll J. Bremmer F. (2010). Spatial Perception During Pursuit Initiation. Vision Research, 50, 2714–2720.
• Böckenholt, U., And Kroeger, K. (1993). Time Pressure Effects In Multi-Attribute Binary Choices. In O. Svenson and A. J. Maule (Eds.), Time Pressure And Stress In Human Judgment And Decision Making (Pp. 195-214). New York: Plenum Press.
• Bradu, C., Orquin, J. L., And Thøgersen, J. (2014). The Mediated Influence Of A Traceability Label On Consumer’s Willingness To Buy The Labelled Product. Journal Of Business Ethics, 124(2), 283-295.
• Braun D. I. Mennie N. Rasche C. Schütz A. C. Hawken M. J. Gegenfurtner K. R. (2008). Smooth Pursuit Eye Movements to Isoluminant Targets. Journal Of Neurophysiology, 100, 1287–1300.
• Brenner E. Smeets J. B. Van Den Berg A. V. (2001). Smooth Eye Movements And Spatial Localisation. Vision Research, 41, 2253–2259.
• Britten K. H. Shadlen M. N. Newsome W. T. Movshon J. A. (1992). The Analysis Of Visual Motion: A Comparison Of Neuronal And Psychophysical Performance. Journal Of Neuroscience, 12, 4745–4765.
• Brouwer A. M. Franz V. H. Gegenfurtner K. R. (2009). Differences In Fixations Between Grasping And Viewing Objects. Journal Of Vision, 9, (1):18, 1–24.
• Brown B. (1972a). Dynamic Visual Acuity, Eye Movements And Peripheral Acuity For Moving Targets. Vision Research, 12, 305–321.
• Brown B. (1972b). The Effect Of Target Contrast Variation On Dynamic Visual Acuity And Eye Movements. Vision Research, 12, 1213–1224.
• Brown, H. R., And Friston, K. J. (2013). The Functional Anatomy Of Attention: A Dcm Study. Frontiers In Human Neuroscience, 7:784.
• Bruce C. J. Goldberg M. E. (1985). Primate Frontal Eye Fields: I Single Neurons Discharging Before Saccades. Journal Of Neurophysiology, 53, 603–635.
• Busemeyer, J., And Johnson, J. (In Press). Computational Models Of Decision Making. In D.Kohler And N. Harvey (Eds.) Handbook Of Judgment And Decision Making. Blackwell.
• Buss, D. (1999). Evolutionary Psychology: The New Science Of The Mind. Needham Heights,Ma: Allyn And Bacon.
• Butzer F. Ilg U. J. Zanker J. M. (1997). Smooth-Pursuit Eye Movements Elicited By First-Order And Second-Order Motion. Experimental Brain Research, 115, 61–70.
• Camerer, C. And M. Weber (1992). ‘Recent Developments In Modeling Preferences - Uncertainty And Ambiguity.’ Journal Of Risk And Uncertainty 5(4): 325-370.
• Camerer, C. F., And Johnson, E. J. (1991). The Process-Performance Paradox In Expert Judgment: How Can Experts Know So Much And Predict So Badly? In K. A. Ericsson And J. Smith (Eds.), Towards A General Theory Of Expertise: Prospects And Limits (Pp. 195217). New York: Cambridge University Press.
• Camerer, C.F. And Loewenstein G., 2003, Behavioral Economics: Past, Present, Future, In Advances In Behavioral Economics, Princeton University Press.
• Camerer, C.F., Ho, T.-H. And Chong, J.-K., 2004, A Cognitive Hierarchy Model Of Games, Quarterly Journal Of Economics, 119, 861-98.
• Camerer, C.F., Loewenstein, G. And Prelec, D., 2005, Neuroeconomics: How Neuroscience Can Inform Economics, Journal Of Economic Literature, 34, 9-64.
• Castet E. Masson G. S. (2000). Motion Perception During Saccadic Eye Movements. Nature Neuroscience, 3, 177–183.
• Chang, C. C. And Yang, F. Y. (2010). Exploring The Cognitive Loads Of High-School Students As They Learn Concepts In Web-Based Environments. Computers And Education, 55, 673-680。Chang, C. Y., Chang, Y. H., Yang, F. Y. (2008). Exploring Secondary Science Teachers' Perceptions On The Goals Of Earth Science Education In Taiwan, International Journal Of Science Education, 31, 2315-2334。
• Chartrand, T., Shiv, B., Huber J. And Tanner, R. (2008), ‘Nonconscious Goals And Consumer Choice,’ Journal Of Consumer Research, Vol. 35 (2), 189-201.
• Chater, N., Oaksford, M., Nakisa, R. And Redington, M. (2003). Fast, Frugal And Rational: How Rational Norms Explain Behavior. Organizational Behavior And Human Decision Processes, 90, 63-86.
• Chawla, M., And Miyapuram, K. P. (2016, September). Common Neural Coding Across Domains Of Decision Making Identified By Meta-Analysis. In Front. Neuroinform. Conference Abstract: Neuroinformatics.
• Chawla, M., And Miyapuram, K. P. (2018). Context-Sensitive Computational Mechanisms Of Decision Making. Journal Of Experimental Neuroscience.
• Chen, Y. C., And Yang, F. Y. (2014). Probing The Relationship Between Process Of Spatial Problems Solving And Science Learning – An Eye Tracking Approach. International Journal Of Science And Mathematics Education, 12, 579-603。
• Cohen J. D., Braver T. S., And Brown J. W. (2002). Computational Perspectives On Dopamine Function In Prefrontal Cortex. Current Opinion In Neurobiology, 12, 223-229.
• Cojuharenco, I., Cornelissen, G., And Karelaia, N. (2011). Self-Construal And Socially Responsible Consumer Behavior. Na - Advances In Consumer Research, Vol. 38, Eds. Darren W. Dahl, Gita V. Johar, And Stijn M.J. Van Osselaer. Duluth, Mn: Association For Consumer Research.
• Cojuharenco, I., Cornelissen, G., And Karelaia, N. (2016). Yes, I Can: Feeling Connected To Others Increases Perceived Consumer Effectiveness And Socially Responsible Behavior. Journal Of Environmental Psychology, 48, 75-86.
• Collewijn H. Kowler E. (2008). The Significance Of Microsaccades For Vision And Oculomotor Control. Journal Of Vision, 8, (14):20, 1–21.
• Collewijn, H., Steinman, R.M., Erkelens, C.J., Pizlo, Z., Kowler, E., And Van Der Steen, J. (1992). Binocular Gaze Control Under Free-Head Conditions. In Vestibular And Brain Stem Control Of Eye, Head And Body Movements. (Edited By Shimazu, H. And Shinoda, Y.) Japan Scientific Society, Tokyo And S. Karger, Basel. Pp 203-220.
• Damasio, A. R. (1994). Descartes’ Error: Emotion, Reason And The Human Brain. New York: Putnam.
• Damasio, Antonio R., Descartes' Error: Emotion, Reason, And The Human Brain (New York: Putnam, 1994).
• Damasio, Hanna, Thomas Grabowski, Randall Frank, Albert M. Galaburda, And Antonio R. Damasio, ‘The Return Of Phineas Gage: Clues About The Brain From The Skull Of A Famous Patient’, Science, 264 / 5162 (1994), 1102-5.
• Daniel Tranel, Hanna Damasio, And Antonio R. Damasio, ‘Fear and The Human Amygdala’, Journal Of Neuroscience, 15 / 9 (1995), 5879-91.
• Das, S., Satpathy, J. and Das, A. (2016). How A Farmer Decides? Some Neuro - Operables, International Journal on Research and Development - A Management Review (IJRDMR), Vol. 05, Issue 4, Pp: 18 - 25, ISSN: 2319 - 5479, Bhubaneswar, India. (International)
• Debarati B., Narayanan, S., V. S. C. Pammi (2013). Dissociable Effects Of Emotion On Decision Making Under Uncertainty, Neuroscience Of Decision Making, 1-8.
• Deo, M. and Satpathy, J. (2018). Hematological Insight into Entrepreneurial Decision, 71st All India Commerce Conference, 20-22 Dec, Department of Commerce, Osmania University, Hyderabad, India. (National).
• E.H. Zandstra, K.P. Miyapuram, P.N. Tobler. (2013). Understanding Consumer Decisions Using Behavioural Economics. Progress In Brain Research, 202:197-211.
• Eeraj Kumar, Jaison A. Manjaly, K.P. Miyapuram. (2014) Feedback About Action Performed Can Alter The Sense Of Self Agency, Frontiers In Psychology (Consciousness Research), 5:145.
• Epelboim J. Steinman R. M. Kowler E. Pizlo Z. Erkelens C. J. Collewijn H. (1997). Gaze-Shift Dynamics In Two Kinds Of Sequential Looking Tasks. Vision Research, 37, 2597–2607.
• Epelboim, J. And Kowler, E. (1993). Slow Control With Eccentric Targets: Evidence Against A Position-Corrective Model. Vision Research, 33, 361-380.
• Epelboim, J., Kowler, E., Steinman, R.M., Collewijn, H., Erkelens, C.J., And Pizlo, Z. (1995) When Push Comes To Shove: Compensation For Passive Perturbations Of The Head During Natural Gaze Shifts. Journal Of Vestibular Research, 5, 421-442.
• Epelboim, J., Steinman, R.M., Kowler, E., Edwards, M., Pizlo, Z., Erkelens, C.J. And Collewijn, H. (1995) The Function Of Visual Search And Memory In Sequential Looking Tasks. Vision Research, 35, 3401-3422.
• Epelboim, J., Steinman, R.M., Kowler, E., Pizlo, Z., Erkelens, C.J., And Collewijn, H. (1997) Gaze Shift Dynamics In Two Kinds Of Sequential Looking Tasks. Vision Research, 37, 2597-2607.
• Evgeniou, T., Fang, L., Hogarth, R. M., And Karelaia, N. (2013). Competitive Dynamics In Forecasting: The Interaction Of Skill And Uncertainty. Journal Of Behavioral Decision Making, 26(4), 375-384.
• Fitzsimons, G. And Shiv, B (2001), ‘Non-Conscious And Contaminative Effects Of Hypothetical Questions On Subsequent Decision Making,’ Journal Of Consumer Research, 28 (September), 224-238.
• Fitzsimons, G. Et Al. (2002), ‘Non-Conscious Influences On Consumer Choice,’ Marketing Letters, 13 (3), 267-277.
• Gao, L., Wheeler, C., And Shiv, B. (2009), ‘The Shaken Self: Product Choice As A Means To Restore Self-View Certainty,’ Journal Of Consumer Research, Vol. 36 (June), 29-38.
• Glimcher P. (2016) ‘Proximate Mechanisms Of Individual Decision - Making Behavior’ From ‘Complexity And Evolution: Toward A New Synthesis For Economics,’ David S. Wilson And Alan Kirman, Eds. 2016. Strüngmann Forum Reports, Vol. 19, Series Ed. J. Lupp. Cambridge, Ma: Mit Press. Isbn 978 - 0 - 262 - 03538 - 5.
• Glimcher P. W. (2003). Decisions, Uncertainty, And The Brain: The Science Of Neuroeconomics. Cambridge, Ma: Mit Press.
• Glimcher P. W. (2009). Choice: Towards A Standard Back-Pocket Model. In Glimcher P. W. Camerer C. Poldrack R. A. Fehr E. (Eds.), Neuroeconomics: Decision Making And The Brain (Pp. 501–519). New York: Academic Press.
• Glimcher P. W. (2010). Foundations Of Neuroeconomic Analysis. Oxford, Uk: Oxford University Press.
• Glimcher P. W. Camerer C. Poldrack R. A. Fehr E. (Eds.) (2008). Neuroeconomics: Decision Making And The Brain. New York: Academic Press.
• Glimcher P.W. (2011). Understanding Dopamine And Reinforcement Learning: The Dopamine Reward Prediction Error Hypothesis. Proc Natl Acad Sci, 108 Suppl 3: 15647 - 15654
• Glimcher, P.W Et Al. (1993) Effects Of Low - Frequency Stimulation Of The Superior Colliculus On Spontaneous And Visually Guided Saccades. J Neurophysiol. 69: 953 - 964.
• Glimcher, P.W Et Al. (1993) Representation Of Averaging Saccades In The Superior Colliculus Of The Monkey. Exp. Brain Res. 95: 429 - 435.
• Glimcher, P.W Et Al. (1997) Response Properties Of Saccade - Related Burst Neurons In The Central Mesencephalic Reticular Formation. J. Neurophysiol. 78: 2164 - 2175.
• Glimcher, P.W Et Al. (1997) Responses Of Intra - Parietal Neurons To Saccadic Targets And Visual Distractors. J. Neurophysiol. 78: 1574 - 1589.
• Glimcher, P.W Et Al. (1998) Response Fields Of Intra - Parietal Neurons Quantified With Multiple Saccadic Targets. Exp. Brain Res. 121: 65 - 75.
• Glimcher, P.W Et Al. (1999) A Quantitative Analysis Of Substantia Nigra Pars Reticulata Activity During A Visually - Guided Saccade Task. J. Neurophysiol. 82: 3458 - 75
• Glimcher, P.W Et Al. (1999) Neural Correlates Of Decision Variables In Parietal Cortex. Nature. 400: 233 - 238.
• Glimcher, P.W Et Al. (2000). Attending To Contrast. Neuron. 26(3): 548 - 550.
• Glimcher, P.W Et Al. (2000). Contextual Modulation Of Substantia Nigra Pars Reticulata Neurons. Journal Of Neurophysiology. 83(5): 3042 - 3048.
• Glimcher, P.W Et Al. (2001) Application Of Neurosonography To Experimental Physiology. Journal Of Neuroscience Methods. 108: 131 - 44.
• Glimcher, P.W Et Al. (2001) Stimulus Probability Redirects Spatial Attention: An Enhancement Of Sensitivity In Humans And Monkeys. Vision Research. 41: 57 - 75. Glimcher, P.W Et Al. (2004) Activity In Posterior Parietal Cortex Is Correlated With The Subjective Desireability Of An Action. Neuron. 44: 365 - 378.
• Glimcher, P.W Et Al. (2004) Eye Position And Memory Saccade Related Responses In Substantia Nigra Pars Reticulata. Experimental Brain Research. 154: 428 - 441.
• Glimcher, P.W Et Al. (2004) Neuroeconomics: The Concilience Of Brain And Decision. Science. 306: 447 - 452.
• Glimcher, P.W Et Al. (2004) Situating the Superior Colliculus Within The Gaze Control Network. In: Hall, W.C., And Moschovakis, A. (Eds.) The Superior Colliculus: New Approaches For Studying Sensorimotor Integration. Boca Raton, Fl: Crc Press
• Glimcher, P.W Et Al. (2005) Dynamic Response - By - Response Models Of Matching Behavior In Rhesus Monkeys. Journal Of The Experimental Analysis Of Behavior, 84(3): 555 - 79, 2005.
• Glimcher, P.W Et Al. (2005) Indeterminacy In Brain And Behavior. Annual Review Of Psychology. 56: 25 - 56.
• Glimcher, P.W Et Al. (2005) Midbrain Dopamine Neurons Encode A Quantitative Reward Prediction Error Signal. Neuron. 47: 129 - 141.
• Glimcher, P.W Et Al. (2005) Physiological Utility Theory And The Neuroeconomics Of Choice. Games And Economic Behavior. 52: 213 - 56.
• Glimcher, P.W Et Al. (2005) Topographic Organization For Delayed Saccades In Human Posterior Parietal Cortex. J Neurophysiology. 94: 1372 - 1384.
• Glimcher, P.W Et Al. (2005). Rethinking The Thalamus. Nat Neurosci. 8(8): 983 - 4.
• Glimcher, P.W Et Al. (2006) Are Heuristics A Problem Or A Solution? In: Engel, C And Gigerenzer, G. (Eds.) Heuristics And The Law. Cambridge, Ma: Mit Press.
• Glimcher, P.W Et Al. (2006) Cognitive Neuroscience And Law. Current Opinion In Neurobiology. 16: 130 - 134.
• Glimcher, P.W Et Al. (2006) Cognitive Neuroscience Editorial Overview. Current Opinion In Neurobiology. 16: 127 - 129.
• Glimcher, P.W Et Al. (2006) Sustained Activity In Topographic Areas Of Human Posterior Parietal Cortex During Memory - Guided Saccades. The Journal Of Neuroscience. 26(19): 5098 - 5108.
• Glimcher, P.W Et Al. (2007) Neuroeconomic Studies Of Impulsivity: Now Or Just As Soon As Possible? American Economic Review. 97(2): 142 - 147.
• Glimcher, P.W Et Al. (2007) Specificity Of Human Cortical Areas For Reaches And Saccades. The Journal Of Neuroscience. 27(17): 4687 - 4696.
• Glimcher, P.W Et Al. (2007). Action And Outcome Encoding In The Primate Caudate Nucleus. The Journal Of Neuroscience. 27(52): 14502 - 14514.
• Glimcher, P.W Et Al. (2007). Statistics Of Midbrain Dopamine Neuron Spike Trains In The Awake Primate. The Journal Of Neurophysiology. 98(3): 1428 – 1439.
• Glimcher, P.W Et Al. (2007). The Neural Correlates Of Subjective Value During Intertemporal Choice. Nat Neuroscience. 10(12): 1625 - 1633.
• Glimcher, P.W Et Al. (2008). Value Representations In The Primate Striatum During Matching Behavior. Neuron. 58: 451 - 463.
• Glimcher, P.W Et Al. (2009). The Neurobiology Of Decision: Consensus And Controversy. Neuron. 63(6): 733 - 745.
• Glimcher, P.W Et Al. (2009). Visual Processing, Learning And Feedback In The Primate Eye Movement System. Trends In Neurosciences. 32(11): 583 - 590.
• Glimcher, P.W Et Al. (2010), An ‘As Soon As Possible’ Effect In Human Intertemporal Decision Making: Behavioral Evidence And Neural Mechanisms. Journal Of Neurophysiology, 103: 2513 - 2531.
• Glimcher, P.W Et Al. (2010). Measuring Beliefs And Rewards: A Neuroeconomic Approach. The Quarterly Journal Of Economics, 125(3): 923 - 960
• Glimcher, P.W Et Al. (2010). Neural Representation Of Subjective Value Under Risk And Ambiguity. Journal Of Neurophysiology. 103(2):1036 - 47.
• Glimcher, P.W Et Al. (2010). Separating Value From Choice: Delay Discounting Activity In The Lateral Intraparietal Area. Journal Of Neuroscience, 30(16): 5498 - 5507.
• Glimcher, P.W Et Al. (2010). Testing The Reward Prediction Error Hypothesis With An Axiomatic Model. Journal Of Neuroscience, 30(40): 13525 - 13536
• Glimcher, P.W Et Al. (2011). Choice From Non - Choice: Predicting Consumer Preferences From Blood Oxygenation Level - Dependent Signals Obtained During Passive Viewing. Journal Of Neuroscience, 31(1): 118 - 125
• Glimcher, P.W Et Al. (2011). Comparing Apples And Oranges: Using Reward - Specific And Reward - General Subjective Value Representation In The Brain. J Neurosci, 31(41): 14693 - 14707
• Glimcher, P.W Et Al. (2011). Planning, Memory, And Decision Making. In Randolf Menzel And Julia Fischer (Eds.), Animal Thinking: Contemporary Issues In Comparative Cognition (121 - 147). Cambridge, Ma: Mit Press.
• Glimcher, P.W Et Al. (2011). Reward Value - Based Gain Control: Divisive Normalization In Parietal Cortex. J Neurosci, 31(29): 10627 - 10639
• Glimcher, P.W Et Al. (2012) Adolescents' Risk Taking Behavior Is Driven By Tolerance To Ambiguity. Proceedings Of The National Academy Of Sciences Of The United States Of America, 109 (42): 17135 - 17140
• Glimcher, P.W Et Al. (2012) Measuring The Subjective Value Of Risky And Ambiguous Options Using Experimental Economics And Functional Mri Methods. Journal Of Visualized Experiments. , Exp. (67), E3724.
• Glimcher, P.W Et Al. (2012). Efficient Coding And The Neural Representation Of Value. Ann. N.Y. Acad. Sci., (1251): 13 - 32.
• Glimcher, P.W Et Al. (2012). Set - Size Effects And The Neural Representation Of Value. In Raymond J. Dolan And Tali Sharot (Eds.), Neuroscience Of Preference And Choice: Cognitive And Neural Mechanisms (143 - 169). London: Academic Press.
• Glimcher, P.W Et Al. (2013). Like Cognitive Function, Decision Making Across The Life Span Shows Profound Age - Related Changes. Pnas.
• Glimcher, P.W Et Al. (2013). Neuroeconomics. In H. Pashler (Ed.), Encyclopedia Of The Mind (Vol. 14, Pp.565 - 569). Thousand Oaks, Ca: Sage Publications.
• Glimcher, P.W Et Al. (2013). Normalization Is A General Neural Mechanism For Context - Dependent Decision Making. Proc Natl Acad Sci U S A, 110: 6129 - 6144.
• Glimcher, P.W Et Al. (2013). State Dependendent Valuation: The Effect Of Deprivation On Risk Preferences. Plos One,
• Glimcher, P.W Et Al. (2014) Absence Of Spatial Tuning In The Orbitofrontal Cortex. Plos One
• Glimcher, P.W Et Al. (2014) Dynamic Divisive Normalization Predicts Time - Varying Value Coding In Decision - Related Circuits. J Neurosci.
• Glimcher, P.W Et Al. (2014). Neuroanatomy Predicts Individual Risk Attitudes. The Journal Of Neuroscience.
• Glimcher, P.W Et Al. (2014). Phasic Dopamine Release In The Rat Nucleus Accumbens Symmetrically Encodes A Reward Prediction Error Term. The Journal Of Neuroscience.
• Glimcher, P.W Et Al. (2014). The Temporal Dynamics Of Cortical Normalization Models Of Decision - Making. Letters In Biomathematics
• Glimcher, P.W Et Al. (2015) Adaptive Neural Coding: From Biological To Behavioral Decision - Making. Curr Opin Behav Sci.
• Glimcher, P.W Et Al. (2015) The Measurement Of Subjective Value And Its Relation To Contigent Valuation And Environmental Public Goods. Plos One.
• Glimcher, P.W Et Al. (2015) Using Big Data To Understand The Human Condition: The Kavli Human Project. Big Data.
• Glimcher, P.W Et Al. (2015) Modulation Of Saccade Vigor During Value - Based Decision Making. The Journal Of Neuroscience.
• Glimcher, P.W Et Al. (2016) Common Value Representation - A Neuroeconomics Perspective. In Brosch, T., Sander, D. (Ed.) Handbook Of Value: Perspective From Economics, Neuroscience, Philosophy, Psychology And Sociology (Pp.85 - 118). Oxford: Oxford University Press.
• Glimcher, P.W Et Al. (2016) Emotion And Decision - Making Under Uncertainty: Arousal Predicts Increased Gambling During Ambiguity But Not Risk. Journal Of Experimental Psychology: General, Volume 145 (10), 1255 - 1262.
• Glimcher, P.W Et Al. (2016) Impairment Of Decision - Making In Multiple - Sclerosis: A Neuroeconomic Approach. Multiple Sclerosis Journal 1 - 10.
• Glimcher, P.W Et Al. (2016) Neuroeconomics. In Kagel, J. H., And Roth, A. E. (Eds.). (2016). The Handbook Of Experimental Economics, Volume 2 (Pp.153 - 216). Princeton: Princeton University Press.
• Glimcher, P.W Et Al. (2016) Oculomatic: High Speed, Reliable And Accurate Open - Source Eye Tracking For Humans And Non - Human Primates. Journal Of Neuroscience Methods.
• Glimcher, P.W Et Al. (2016) The Impact Of Menstrual Cycle Phase On Economic Choice And Rationality. Plos One.
• Glimcher, P.W Et Al. (2016) Unexpected But Incidental Positive Outcomes Predict Real - World Gambling. Psychological Science.
• Glimcher, P.W Et Al. (2016). Neuroanatomy Accounts For Age - Related Changes In Risk Preferences. Nature Communications 7, 3822.
• Glimcher, P.W Et Al. (2017). Normalized Value Coding Explains Dynamic Adaptation In The Human Valuation Process. Proceedings Of The National Academy Of Sciences, 201715293.
• Glimcher, P.W Et Al. (2017). Propranolol Reduces Reference - Dependence In Intertemporal Choice. Social Cognitive And Affective Neuroscience, 12(9), 1394 - 1401.
• Glimcher, P.W Et Al. (2017). The Reduction Of Ventrolateral Prefrontal Cortex Gray Matter Volume Correlates With Loss Of Economic Rationality In Aging. Journal Of Neuroscience, 37(49), 12068 - 12077.
• Glimcher, P.W Et Al. (2018). A Neuroeconomist's Perspective On Thinking About The Future. In Oettingen, G., Sevincer, T., And Gollwitzer, P.M (Eds.). The Psychology Of Thinking About The Future. New York: The Guilford Press.
• Glimcher, P.W Et Al. (2018). Computational Psychiatry Of Impulsivity And Risk: How Risk And Time Preferences Interact In Health And Disease. Philosophical Transactions Of The Royal Society B: Biological Sciences, 374.
• Glimcher, P.W Et Al. (2018). Free Choice Shapes Normalized Value Signals In Medial Orbitofrontal Cortex. Nature Communications, 9(1), 162.
• Glimcher, P.W Et Al. (2018). Multiple Timescales Of Normalized Value Coding Underlie Adaptive Choice Behavior. Nature Communications, 9, 3206.
• Glimcher, P.W Et Al. (2018). Risk Preferences Impose A Hidden Distortion On Measures Of Choice Impulsivity. Plos One13(1): E0191357.
• Glimcher, P.W Et Al. (2018). The Neurobiological Model Of Decision Making. In S. Chen, M. Kaboudan, And Y. Du (Authors), The Oxford Handbook Of Computational Economics And Finance (Pp. 688 - 713). New York: Oxford University Press.
• Glimcher, P.W. (2001) Making Choices: The Neurophysiology Of Visual - Saccadic Decision Making. Trends In Neuroscience. 24: 654 - 659
• Glimcher, P.W. (2002) Decisions, Decisions, Decisions: Choosing A Neurobiological Theory Of Choice. Neuron. 36: 323 - 332.
• Glimcher, P.W. (2003) The Neurobiology Of Visual Saccadic Decision Making. Annual Review Of Neuroscience. 26: 133 - 179.
• Glimcher, P.W. (2008). The Neurobiology Of Individual Decision Making, Dualism, And Legal Accountability. In: Engel, C., And Singer,W. (Eds.) Better Than Conscious? Implications For Performance And Institutional Analysis. Strüngmann Forum Report 1. Cambridge, Ma: Mit Press.
• Glimcher, P.W. (2008). Understanding Risk: A Guide For The Perplexed. Cognitive, Affective, And Behavioral Neuroscience. 8(4): 348 - 354.
• Glimcher, P.W. (2009). Choice: Towards A Standard Back - Pocket Model. In: Glimcher, P.W., Camerer, C.F., Fehr, E., And Poldrack, R.A. (Eds.) Neuroeconomics: Decision Making And The Brain. New York: Academic Press, Pp.503 - 521.
• Glimcher, P.W. (2009). Introduction: A Brief History Of Neuroeconomics. In: Glimcher, P.W., Camerer, C.F., Fehr, E., And Poldrack, R.A. (Eds.) Neuroeconomics: Decision Making And The Brain. New York: Academic Press, Pp.1 - 12.
• Glimcher, P.W. (2009). Neuroeconomics And The Study Of Valuation. In: Gazzaniga , M.S. (Ed.) The Cognitive Neurosciences, Fourth Edition. Cambridge, Ma: The Mit Press, Pp. 1085 - 1092.
• Glimcher, P.W. (2009). Neuroscience, Psychology, And Economic Behavior: The Emerging Field Of Neuroeconomics. In: Tommasi, L., Peterson, M.A., And Nadel, L. (Eds.) Cognitive Biology: Evolutionary And Developmental Perspectives On Mind, Brain, And Behavior. Cambridge, Ma: The Mit Press, Pp. 261 - 278.
• Glimcher, P.W. (2015) Understanding The Hows And Whys Of Decision - Making: From Expected Utility To Divisive Normalization Cold Spring Harbor Laboratory Press.
• Glöckner, A. (2006). Automatische Prozesse Bei Entscheidungen. Hamburg, Germany: Kovac.
• Glöckner, A. (2007). Does Intuition Beat Fast And Frugal Heuristics? A Systematic Empirical Analysis. In H. Plessner, C. Betsch, And T. Betsch (Eds.), Intuition In Judgment And Decision Making (Pp. 309–325). Mahwah, Nj: Lawrence Erlbaum.
• Glöckner, A. (2008). How Evolution Outwits Bounded Rationality: The Efficient Interaction Of Automatic And Deliberate Processes In Decision Making And Implications For Institutions. In C. Engel And W. Singer (Eds.), Better Than Conscious? Decision Making, The Human Mind, And Implications For Institutions (Pp. 259–284). Cambridge, Ma: Mit Press.
• Glöckner, A. (2009). „Neurorecht’ Ohne Psychologie? Die Rolle Verhaltenswissenschaftlicher Betrachtungsebenen Bei Der Ableitung Rechtspolitischer Empfehlungen. In S. Schleim, T. M. Spranger, And H. Walter (Eds.), Von Der Neuroethik Zum Neurorecht? (Pp. 104–131). Göttingen, Germany: Vandenhoeck And Ruprecht.
• Glöckner, A. (2009). Investigating Intuitive And Deliberate Processes Statistically: The Multiple-Measure Maximum Likelihood Strategy Classification Method. Judgment And Decision Making, 4, 186–199. [Data And Materials]
• Glöckner, A. (2010). Multiple Measure Strategy Classification: Outcomes, Decision Times And Confidence Ratings. In A. Glöckner And C. L. M. Witteman (Eds.), Foundations For Tracing Intuition: Challenges And Methods (Pp. 83–105). London, Uk: Psychology Press And Routledge.
• Glöckner, A. (2016). Psychology And Disaster: Why We Do Not See Looming Disasters And How Our Way Of Thinking Causes Them. Global Policy, 7, 16–24.
• Glöckner, A. (2016). The Irrational Hungry Judge Effect Revisited: Simulations Reveal That The Magnitude Of The Effect Is Overestimated. Judgment And Decision Making, 11, 601–610.
• Glöckner, A. (In Press). Der Mensch Im Spannungsfeld Zwischen (Begrenzter) Rationalität, Eigeninteresse Und Kooperation: Welches Wesen Adressiert Das Recht? In A. Funke And U. Schmalke (Eds.), Menschenbilder Im Recht.
• Glöckner, A., And Betsch, T. (2008). Do People Make Decisions Under Risk Based On Ignorance? An Empirical Test Of The Priority Heuristic Against Cumulative Prospect Theory. Organizational Behavior And Human Decision Processes, 107, 75–95.
• Glöckner, A., And Betsch, T. (2008). Modeling Option And Strategy Choices With Connectionist Networks: Towards An Integrative Model Of Automatic And Deliberate Decision Making. Judgment And Decision Making, 3, 215–228.
• Glöckner, A., And Betsch, T. (2008). Multiple-Reason Decision Making Based On Automatic Processing. Journal Of Experimental Psychology: Learning, Memory, And Cognition, 34, 1055–1075.
• Glöckner, A., And Betsch, T. (2010). Accounting For Critical Evidence While Being Precise And Avoiding The Strategy Selection Problem In A Parallel Constraint Satisfaction Approach: A Reply To Marewski (2010). Journal Of Behavioral Decision Making, 23, 468–472.
• Glöckner, A., And Betsch, T. (2011). The Empirical Content Of Theories In Judgment And Decision Making: Shortcomings And Remedies. Judgment And Decision Making, 6, 711–721.
• Glöckner, A., And Betsch, T. (2012). Decisions Beyond Boundaries: When More Information Is Processed Faster Than Less. Acta Psychologica, 139, 532–542.
• Glöckner, A., And Bröder, A. (2011). Processing Of Recognition Information And Additional Cues: A Model-Based Analysis Of Choice, Confidence, And Response Time. Judgment And Decision Making, 6, 23–42.
• Glöckner, A., And Bröder, A. (2014). Cognitive Integration Of Recognition Information And Additional Cues In Memory-Based Decisions. Judgment And Decision Making, 9, 35–50. [Data]
• Glöckner, A., And Ebert, I. D. (2011). Legal Intuition And Expertise. In M. Sinclair (Ed.), Handbook Of Intuition Research (Pp. 157–167). Northampton, Ma: Edward Elgar Publishing.
• Glöckner, A., And Engel, C. (2013). Can We Trust Intuitive Jurors? Standards Of Proof And The Probative Value Of Evidence In Coherence-Based Reasoning. Journal Of Empirical Legal Studies, 10, 230–252.
• Glöckner, A., And Englich, B. (2015). When Relevance Matters. Social Psychology, 46, 4–12.
• Glöckner, A., And Grüner, K. (2003). Effizientes Online-Verfahren Für Die Personalentwicklung: 360° Führungsfeedback. Planung And Analyse, 2, 85–90.
• Glöckner, A., And Herbold, A.-K. (2011). An Eye-Tracking Study On Information Processing In Risky Decisions: Evidence For Compensatory Strategies Based On Automatic Processes. Journal Of Behavioral Decision Making, 24, 71–98.
• Glöckner, A., And Hilbig, B. E. (2011). Editorial: Methodology In Judgment And Decision Making Research. Judgment And Decision Making, 6, 705–710.
• Glöckner, A., And Hilbig, B. E. (2012). Risk Is Relative: Risk Aversion Yields Cooperation Rather Than Defection In Cooperation-Friendly Environments. Psychonomic Bulletin And Review, 19, 546–553.
• Glöckner, A., And Hochman, G. (2011). ‘The Interplay Of Experience-Based Affective And Probabilistic Cues In Decision Making: Arousal Increases When Experience And Additional Cues Are Inconsistent’. Experimental Psychology, 58, 132-141.
• Glöckner, A., And Hochman, G. (2011). The Interplay Of Experience-Based Affective And Probabilistic Cues In Decision Making: Arousal Increases When Experience And Additional Cues Are Inconsistent. Experimental Psychology, 58, 132-141.
• Glöckner, A., And Hochman, G. (2011). The Interplay Of Experience-Based Affective And Probabilistic Cues In Decision Making. Experimental Psychology, 58, 132–141.
• Glöckner, A., And Hodges, S. D. (2011). Parallel Constraint Satisfaction In Memory-Based Decisions. Experimental Psychology, 58, 180–195.
• Glöckner, A., And Jekel, M. (In Press). Testing Cognitive Models By A Joint Analysis Of Multiple Dependent Measures. In M. Schulte-Mecklenbeck Et Al. (Eds.), Handbook Of Process Tracing.
• Glöckner, A., And Landsberg, M. (2011). Der Schöffe Entscheidet: Eine Empirische Studie Zum Entscheidungsverhalten Von Schöffen. Richter Ohne Robe, 23, 44–47.
• Glöckner, A., And Moritz, S. (2009). A Fine-Grained Analysis Of The Jumping-To-Conclusions Bias In Schizophrenia: Data-Gathering, Response Confidence, And Information Integration. Judgment And Decision Making, 4, 587–600.
• Glöckner, A., And Pachur, T. (2012). Cognitive Models Of Risky Choice: Parameter Stability And Predictive Accuracy Of Prospect Theory. Cognition, 123, 21–32.
• Glöckner, A., And Schönfeldt, K. (2009). Ich Überlege. Mein Bauch Entscheidet? - Intuition Und Entscheidung. Richter Ohne Robe, 21, 60–61.
• Glöckner, A., And Towfigh, E. (2010). Geschicktes Glücksspiel: Die Sportwette Als Grenzfall Des Glücksspielrechts. Juristenzeitung, 65(21), 1027–1035.
• Glöckner, A., And Towfigh, E. V. (2015). Entscheidungen Zwischen „Intuition’ Und „Rationalität’. Deutsche Richterzeitung, 7/8, 14–17.
• Glöckner, A., And Towfigh, E. V. (2016). Messgenauigkeit Und Fairness In Staatsprüfungen: Aktuelle Studien Zeigen Gruppen-Unterschiede In Juristischen Examina Auf. Anwaltsblatt, 10, 706–709.
• Glöckner, A., And Witteman, C. L. M. (2010). Beyond Dual-Process Models: A Categorisation Of Processes Underlying Intuitive Judgement And Decision Making. Thinking And Reasoning, 16, 1–25.
• Glöckner, A., And Witteman, C. L. M. (2010). Foundations For Tracing Intuition: Models, Findings, Categorizations. In A. Glöckner And C. L. M. Witteman (Eds.), Foundations For Tracing Intuition: Challenges And Methods (Pp. 1–23). London, Uk: Psychology Press And Routledge.
• Glöckner, A., And Witteman, C. L. M. (2010). Foundations For Tracing Intuition: Challenges And Methods. London, Uk: Psychology Press And Routledge.
• Glöckner, A., Betsch, T., And Schindler, N. (2010). Coherence Shifts In Probabilistic Inference Tasks. Journal Of Behavioral Decision Making, 23, 439–462.
• Glöckner, A., Fiedler, S., And Renkewitz, F. (2018). Belastbare Und Effiziente Wissenschaft: Strategische Ausrichtung Von Forschungsprozessen Als Weg Aus Der Replikationskrise. Psychologische Rundschau, 69, 22–36.
• Glöckner, A., Fiedler, S., Hochman, G., Ayal, S., And Hilbig, B. E. (2012). Processing Differences Between Descriptions And Experience: A Comparative Analysis Using Eye-Tracking And Physiological Measures. Frontiers In Psychology 3:173. (A Special Issue On The Neuroscience And Psychophysiology Of Experience-Based Decisions)
• Glöckner, A., Fiedler, S., Hochman, G., Ayal, S., And Hilbig, B. E. (2012). Processing Differences Between Descriptions And Experience: A Comparative Analysis Using Eye-Tracking And Physiological Measures. Frontiers In Psychology, 3:173.
• Glöckner, A., Fiedler, S., Hochman, G., Ayal, S., And Hilbig, B. E. (2012) ‘Processing Differences Between Descriptions And Experience: A Comparative Analysis Using Eye-Tracking And Physiological Measures’. Frontiers In Psychology 3:173. (A Special Issue On The Neuroscience And Psychophysiology Of Experience-Based Decisions)
• Glöckner, A., Heinen, T., Johnson, J. G., And Raab, M. (2012). Network Approaches For Expert Decisions In Sports. Human Movement Science, 31, 318–333.
• Glöckner, A., Hilbig, B. E., And Jekel, M. (2014). What Is Adaptive About Adaptive Decision Making? A Parallel Constraint Satisfaction Account. Cognition, 133, 641–666.
• Glöckner, A., Hilbig, B. E., Henninger, F., And Fiedler, S. (2016). The Reversed Description-Experience Gap: Disentangling Sources Of Presentation Format Effects In Risky Choice. Journal Of Experimental Psychology: General, 145, 486–508.
• Glöckner, A., Irlenbusch, B., Kube, S., Nicklisch, A., And Normann, H.-T. (2011). Leading With(Out) Sacrifice? A Public-Goods Experiment With A Privileged Player. Economic Inquiry, 49, 591–597.
• Glöckner, A., Kube, S., And Nicklisch, A. (2018). The Joint Benefits Of Observed And Unobserved Social Sanctions. Journal Of Behavioral And Experimental Economics, 75, 105–116.
• Glöckner, A., Tontrup, S., And Bechtold, S. (2015). Disentangling Psychological Sources Of Overpricing In Anticommons Dilemmas: Strategic Incentives, Endowment Effects, And Interdependence Of Outcomes. Journal Of Behavioral Decision Making, 28, 224–238.
• Glöckner, A., Towfigh, E., And Traxler, C. (2013). Development Of Legal Expertise. Instructional Science, 41, 989–1007.
• Goyal, S., Miyapuram, K. P., And Lahiri, U. (2015, November). Predicting Consumer's Behavior Using Eye Tracking Data. In Soft Computing And Machine Intelligence (Iscmi), 2015 Second International Conference On (Pp. 126-129). Ieee.
• Goyal, S., Miyapuram, K.P. (2017). Risk Attitude In Gain And Loss Domain With And Without Feedback: A Study On Indian Population, Society For Judgement And Decision Making, Vancouver, November 10-14, 2017.
• Graham, D. J., Orquin, J. L., And Visschers, V. H. (2012). Eye Tracking And Nutrition Label Use: A Review Of The Literature And Recommendations For Label Enhancement. Food Policy, 37(4), 378-382.
• Guillén, L., Mayo, M., And Karelaia, N. (2018). Appearing Self-Confident And Getting Credit For It: Why It May Be Easier For Men Than Women To Gain Influence At Work. Human Resource Management, 57(4), 839-854.
• He, P. And Kowler, E. (1989). The Role Of Location Probability In The Programming Of Saccades: Implications For ‘Center-Of-Gravity’ Tendencies. Vision Research, 29, 1165-1181.
• He, P. And Kowler, E. (1991). Saccadic Localization Of Eccentric Forms. Journal Of The Optical Society Of America, A, 8, 440-449.
• He, P. And Kowler, E. (1992). The Role Of Saccades In The Perception Of Texture Patterns. Vision Research, 32, 2151-2163.
• Hikosaka O. (2007). Basal Ganglia Mechanisms Of Reward-Oriented Eye Movement. Annals Of The New York Academy Of Sciences, 1104, 229–249.
• Hikosaka O. Nakamura K. Nakahara H. (2006). Basal Ganglia Orient Eyes To Reward. Journal Of Neurophysiology, 95, 567–584.
• Hikosaka O. Takikawa Y. Kawagoe R. (2000). Role Of The Basal Ganglia In The Control Of Purposive Saccadic Eye Movements. Physiological Review, 80, 953–978.
• Hilke, P. Et Al. (2009), ‘Repetitive Transcranial Magnetic Stimulation Over The Right Dorsolateral Prefrontal Cortex Decreases Valuations During Food Choices’, European Journal Of Neuroscience, 30 (10), 1980 - 1988.
• Hilke, P. Et Al. (2005), ‘Evidence For A Neural Correlate Of A Framing Effect: Bias - Specific Activity In The Ventromedial Prefrontal Cortex During Credibility Judgments’, Brain Research Bulletin, 67 (5), 413 - 421.
• Hilke, P. Et Al. (2005), ‘Neuroeconomics: Overview From An Economic Perspective’, Brain Research Bulletin, 67 (5), 343 - 354.
• Hilke, P. Et Al. (2005), ‘Non - Linear Responses Within The Medial Prefrontal Cortex Reveal When Specific Implicit Information Influences Economic Decision - Making’, Journal Of Neuroimaging, 15 (2), 171 - 182.
• Hilke, P. Et Al. (2007), ‘Orbitofrontal Cortex Encodes Willingness To Pay In Everyday Economic Transactions’, Journal Of Neuroscience, 27(37), 9984 - 9988.
• Hilke, P. Et Al. (2008), ‘How Choice Ambiguity Modulates Activity In Brain Areas Representing Brand Preference: Evidence From Consumer Neuroscience’, Journal Consumer Behavior, 7(4 - 5), 360 - 367.
• Hilke, P. Et Al. (2008), ‘Neural Correlates Of Decision - Making’, In: Engel, Christoph And Singer, Wolf (Eds.): ‘Better Than Conscious? Decision Making, The Human Mind, And Implications For Institutions’. Mit Press, 125 - 154.
• Hilke, P. Et Al. (2009), ‘How Neuroscience Can Inform Consumer Research’, Ieee Trans Neural Syst Rehabil Eng, 16(6): 532 - 538.
• Hilke, P. Et Al. (2010), ‘Aversive Goal Values Are Negatively Encoded In The Mofc At The Time Of Decision - Making’, Journal Of Neuroscience, 30 (32), 10799 - 10808.
• Hilke, P. Et Al. (2011), ‘Dissociating Valuation And Saliency Signals During Decision - Making’, Cerebral Cortex, 21(1), 95 - 102.
• Hilke, P. Et Al. (2012), ‘Branding The Brain – A Critical Review’, Journal Of Consumer Psychology, 22 (1), 18 – 36.
• Hilke, P. Et Al. (2012), ‘Decision Neuroscience And Consumer Decision Making’, Marketing Letters, 23, 473 - 485.
• Hilke, P. Et Al. (2012), ‘Regulatory Self - Control Involves A Transfer Of Behavioral Control From Vmpfc To Dlpfc Valuation Systems’, Journal Of Neuroscience, 32 (39), 13543–13554.
• Hochman, G., And Ariely, D. (2015). ‘Behavioral Economics’. In Scott, R. A., And Kosslyn, S. M. (Eds.), Emerging Trends In The Social And Behavioral Sciences. Wiely Inc.
• Hochman, G., And Ayal, S. (2013). ‘Behavioral Economics’. In Oxford Bibliographies In Psychology. Ed. Dana S. Dunn. New York: Oxford University
• Hochman, G., And Erev, I. (2013). ‘The Partial Reinforcement Extinction Effect And The Contingent Sampling Hypothesis’. Psychonomic Bulletin And Review, 20, 1336-1342.
• Hochman, G., And Yechiam, E. (2011). ‘Loss Aversion In The Eye And In The Heart: The Autonomic Nervous System’s Responses To Losses’. Journal Of Behavioral Decision Making, 24, 140-156.
• Hochman, G., Ayal, S., And Ariely, D. (2014). ‘Keeping Your Gains Close But Your Money Closer: The Effect Of Prepayment On Choice And Performance’. Journal Of Economic Behavior And Organization, 107, 582-594.
• Hochman, G., Ayal, S., And Glöckner, A. (2010). Physiological Arousal In Processing Recognition Information: Ignoring Or Integrating Cognitive Cues. Judgment And Decision Making, 5, 285-299.
• Hochman, G., Glöckner, A., And Yechiam, E. (2010). Physiological Measures In Identifying Decision Strategies. In A. Glöckner And C. L. M. Witteman (Eds.), Tracing Intuition: Recent Methods In Measuring Intuitive And Deliberate Processes In Decision Making. London: Psychology Press And Routledge
• Hoffman, G., Forlizzi, J., Ayal, S., Steinfeld, A., Antanitis, J., Hochman, G., Hochendoner, E., And Finkenaur, J. (2015). Robot Presence And Human Honesty: Experimental Evidence. Proceedings Of The 10th Acm/Ieee International Conference On Human-Robot Interaction (Hri'15).
• Hogarth, R. M, And Karelaia, N. (2006). Take-The Best And Other Simple Strategies: Why And When They Work 'Well' In Binary Choice. Theory And Decision, 61, 205-249.
• Hogarth, R. M., And Karelaia, N. (2005). Ignoring Information In Binary Choice With Continuous Variables: When Is Less ‘More’? Journal Of Mathematical Psychology, 49/2, 115-124.
• Hogarth, R. M., And Karelaia, N. (2005). Simple Models For Multi-Attribute Choice With Many Alternatives: When It Does And Does Not Pay To Face Tradeoffs With Binary Attributes. Management Science, 51(12), 1860-1872.
• Hogarth, R. M., And Karelaia, N. (2006). Regions Of Rationality: Maps For Bounded Agents. Decision Analysis, 3(3), 124-144.
• Hogarth, R. M., And Karelaia, N. (2007). Heuristic And Linear Models Of Judgment: Matching Rules And Environments. Psychological Review, 114(3), 733-758.
• Hogarth, R. M., And Karelaia, N. (2012). Entrepreneurial Success And Failure: Confidence And Fallible Judgment. Organization Science, 23(6), 1733-1747.
• Hogarth, R. M., Karelaia, N., And Trujillo, C. (2012). When Should I Quit? Gender Differences In Exiting Competitions. Journal Of Economic Behavior And Organization, 83(1), 136-150.
• Huang, R. T., Tang, T. W., Lee, Y. P., And Yang, F. Y. (2017). Does Proactive Personality Matter In Mobile Learning? Australasian Journal Of Educational Technology, 33(2), 86-96.
• Itti L. Braun J. Lee D. K. Koch C. (1998). A Model Of Early Visual Processing. In Jordan M. I. Kearns M. J. Solla S. A. (Eds.), Advances In Neural Information Processing Systems (Vol. 10, P. 173). Cambridge, Ma: The Mit Press.
• Itti L. Koch C. (2000). A Saliency-Based Search Mechanism For Overt And Covert Shifts Of Visual Attention. Vision Research, 40, 1489–1506.
• Itti L. Koch C. (2001). Computational Modelling Of Visual Attention. Nature Reviews Neuroscience, 2, 194–203.
• Itti L. Koch C. Niebur E. (1998). A Model Of Saliency-Based Visual Attention For Rapid Scene Analysis. Ieee Transactions On Pattern Analysis And Machine Intelligence, 20, 1254–1259.
• Iyengar, S.S. Et Al. (2001). What Drives Whom? A Cultural Perspective On Human Agency. Social Cognition, 19 (3), 269 - 294.
• Iyengar, S.S. Et Al. (2002). Choice And Its Consequences: On The Costs And Benefits Of Selfdetermination. In Tesser, A. (Ed.) Self And Motivation: Emerging Psychological Perspectives (71 - 96). Washington, D.C.: American Psychological Association.
• Iyengar, S.S. Et Al. (2003). Rethinking The Value Of Choice: Considering Cultural Mediators Of Intrinsic Motivation. In Murphy - Berman, V. And Berman, J. (Eds.). Cross - Cultural Differences In Perspectives On The Self: Vol. 49. Nebraska Symposium On Motivation (146 - 191). London: University Of Nebraska Press.
• Iyengar, S.S. Et Al. (2004). Managers’ Theories Of Subordinates: A Cross - Cultural Examination Of Manager Perceptions Of Motivation And Appraisal Of Performance. Organizational Behavior And Human Decision Processes, 93 (1), 47 - 61.
• Iyengar, S.S. Et Al. (2004). Person Perception In The Heat Of Conflict: Negative Trait Attributions Affect Procedural Preferences And Account For Situational And Cultural Differences. Asian Journal Of Social Psychology, 7 (2), 127 - 147.
• Iyengar, S.S. Et Al. (2004). The Psychological Pleasure And Pain Of Choosing: When People Prefer Choosing At The Cost Of Subsequent Satisfaction. Journal Of Personality And Social Psychology, 87 (3), 312 - 326.
• Iyengar, S.S. Et Al. (2005). Appraising The Unusual: Framing Effects And Moderators Of Uniqueness - Seeking And Social Projection. Journal Of Experimental Social Psychology, 41 (3), 271 - 282.
• Iyengar, S.S. Et Al. (2005). Intrinsic And Extrinsic Motivational Orientations In The Classroom: Age Differences And Academic Correlates. Journal Of Educational Psychology, 97 (2), 184 - 196.
• Iyengar, S.S. Et Al. (2005). Positive Illusions Of Preference Consistency: How Remaining Eluded By One's Preferences Yields Greater Subjective Well - Being And Decision Outcomes. Organizational Behavior And Human Decision Processes, 98 (1), 66 - 87.
• Iyengar, S.S. Et Al. (2006) Empowerment Through Choice?: A Critical Analysis Of The Effects Of Choice In Organizations. In Staw, B. (Ed.), Research On Organizational Behavior, Vol. 27 (41 - 79). Usa: Elsevier.
• Iyengar, S.S. Et Al. (2006). Doing Better But Feeling Worse: Looking For The ‘Best’ Job Undermines Satisfaction. Psychological Science, 17 (2), 143 - 150. Reprinted In Lesko, W. (Ed.), Readings In Social Psychology: General, Classic, And Contemporary Selections (7th Edition,) Allyn And Bacon, (2008).
• Iyengar, S.S. Et Al. (2006). Gender Differences In Mate Selection: Evidence From A Speed Dating Experiment. Quarterly Journal Of Economics, 121 (2), 673 - 697.
• Iyengar, S.S. Et Al. (2008). Creativity As A Matter Of Choice: Prior Experience And Task Instruction As Boundary Conditions For The Positive Effect Of Choice On Creativity. Journal Of Creative Behavior, 42 (3), 164 - 180.
• Iyengar, S.S. Et Al. (2009). Tragic Choices: Autonomy And Emotional Responses To Medical Decisions. Journal Of Consumer Research, 36 (3), 337 - 352.
• Iyengar, S.S. Et Al. (2010). Born To Choose: The Origins And Value Of The Need For Control. Trends In Cognitive Science, 14 (10), 457 - 463.
• Iyengar, S.S. Et Al. (2010). Choice Proliferation, Simplicity Seeking, And Asset Allocation. Journal Of Public Economics, 94 (7 - 8), 530 - 539.
• Iyengar, S.S. Et Al. (2010). Medium Of Exchange Matters: What’s Fair For Goods Is Unfair For Money. Psychological Science, 21 (2), 159 - 162.
• Iyengar, S.S. Et Al. (2010). Order In Product Customization Decisions: Evidence From Field Experiments. Journal Of Political Economy, 118 (2), 274 - 299.
• Jekel, M., And Glöckner, A. (2018). How To Identify Strategy Use And Adaptive Strategy Selection: The Crucial Role Of Chance Correction In Weighted Compensatory Strategies. Journal Of Behavioral Decision Making, 31, 265–279.
• Jekel, M., And Glöckner, A. (2018). Meaningful Model Comparisons Have To Include Reasonable Competing Models And Also All Data: A Rejoinder To Rieskamp (2018). Journal Of Behavioral Decision Making, 31, 289–293.
• Jekel, M., Fiedler, S., And Glöckner, A. (2011). Diagnostic Task Selection For Strategy Classification In Judgment And Decision Making: Theory, Validation, And Implementation In R. Judgment And Decision Making, 6, 782–799.
• Jekel, M., Nicklisch, A., And Glöckner, A. (2010). Implementation Of The Multiple-Measure Maximum Likelihood Strategy Classification Method In R: Addendum To Glöckner (2009) And Practical Guide For Application. Judgment And Decision Making, 5, 54–63. [Data And Materials]
• Jekel, M., Glöckner, A., And Bröder, A. (2018). A New And Unique Prediction For Cue-Search In A Parallel-Constraint Satisfaction Network Model: The Attraction Search Effect. Psychological Review, 125, 744–768.
• Jekel, M., Glöckner, A., Bröder, A., And Maydych, V. (2014). Approximating Rationality Under Incomplete Information: Adaptive Inferences For Missing Cue Values Based On Cue-Discrimination. Judgment And Decision Making, 9, 129–147. [Data And Materials]
• Jekel, M., Glöckner, A., Fiedler, S., And Bröder, A. (2012). The Rationality Of Different Kinds Of Intuitive Decision Processes. Synthese, 189, 147–160.
• Jensen, B. B., Orquin, J., And Bech-Larsen, T. (2014). What Distinguishes Passive Recipients From Active Decliners Of Sales Flyers?. Journal Of Retailing And Consumer Services, 21(1), 1-8.
• K.P. Miyapuram, P.N. Tobler, L. Gregorios-Pippas, W. Schultz. (2012) Bold Responses In Reward Regions To Hypothetical And Imaginary Monetary Rewards. Neuroimage 59(2):1692-1699.
• K.P. Miyapuram, V.S.C. Pammi. (2013). Understanding Decision Neuroscience – A Multidisciplinary Perspective And Neural Substrates. Progress In Brain Research, 202:239-66.
• Kahneman (Eds.), Heuristics And Biases: The Psychology Of Intuitive Judgment (Pp.686-715). Cambridge: Cambridge University Press.
• Kahneman D. (2003). A Psychological Perspective On Economics. American Economic Review, 93, 162 - 168.
• Kahneman, D. (1963). The Semantic Differential And The Structure Of Inferences Among Attributes. American Journal Of Psychology, 76, 554 - 567.
• Kahneman, D. (1965). Control Of Spurious Association And The Reliability Of The Controlled Variable. Psychological Bulletin, 64, 326 - 329.
• Kahneman, D. (1965). Exposure Duration And Effective Figure - Ground Contrast. Quarterly Journal Of Experimental Psychology, 17, 308 - 314.
• Kahneman, D. (1967). An Onset - Onset Law For One Case Of Apparent Motion And Metacontrast. Perception And Psychophysics, 2, 577 - 584.
• Kahneman, D. (1968). Effects Of Verbalization And Incentive On The Pupillary Response To Mental Activity. Canadian Journal Of Psychology, 22, 186 - 196.
• Kahneman, D. (1968). Methods, Findings And Theory In Studies Of Visual Masking. Psychological Bulletin, 70, 404 - 425.
• Kahneman, D. (1970). Remarks On Attention Control. Acta Psychologica, 33, Attention And Performance Iii (A.F. Sanders, Ed.) , 118 - 131.
• Kahneman, D. (1971). Changes In Pupil Size And Visual Discrimination During Mental Effort. In J.R. Pierce And J.R. Levene (Eds.), Visual Science: Proceedings Of The 1968 International Symposium. Bloomington, In : Indiana University Press.
• Kahneman, D. (1973). Attention And Effort. Prentice-Hall: Englewoodcliffs, N.J.
• Kahneman, D. (1974). Cognitive Limitations And Public Decision Making. In Science And Absolute Values: Proceedings Of The Third International Conference On The Unity Of The Sciences (1261 - 1281). London: International Cultural Foundation.
• Kahneman, D. (1975). Effort, Recognition And Recall In Auditory Attention. In P.M.A. Rabbitt And S. Dornic (Eds.), Attention And Performance V (65 - 80). New York : Academic Press.
• Kahneman, D. (1979). Mechanisms That Produce Critical Durations. The Behavioral And Brain Sciences, 2, 265 - 266.
• Kahneman, D. (1980). Human Engineering Of Decisions. In M. Kranzberg (Ed.), Ethics In An Age Of Pervasive Technology (190 - 192). Boulder, Co : Westview Press.
• Kahneman, D. (1988). Experimental Economics: A Psychological Perspective. In R. Tietz, W. Albers And R. Selten (Eds.), Bounded Rational Behavior In Experimental Games And Markets (Pp. 11 - 18). Berlin : Springer - Verlag.
• Kahneman, D. (1991). Judgment And Decision Making: A Personal View. Psychological Science, 2, 142 - 145.
• Kahneman, D. (1992). Reference Points, Anchors, Norms, And Mixed Feelings. Organizational Behavior And Human Decision Processes, 51, 296 - 312.
• Kahneman, D. (1994). New Challenges To The Rationality Assumption. Journal Of Institutional And Theoretical Economics, 150, 18 - 36.
• Kahneman, D. (1995). Varieties Of Counterfactual Thinking. In N.J. Roese And J.M. Olson (Eds.), What Might Have Been: The Social Psychology Of Counterfactual Thinking (Pp. 375 - 396). Hillsdale , Nj : Erlbaum.
• Kahneman, D. (2000). A Psychological Point Of View: Violations Of Rational Rules As A Diagnostic Of Mental Processes [Commentary On Stanovich And West]. Behavioral And Brain Sciences, 23, 681 - 683.
• Kahneman, D. (2000). Evaluation By Moments: Past And Future. In D. Kahneman And A. Tversky (Eds.), Choices, Values And Frames (Pp. 693 - 708). New York : Cambridge University Press And The Russell Sage Foundation.
• Kahneman, D. (2000). Experienced Utility And Objective Happiness: A Moment - Based Approach. In D. Kahneman And A. Tversky (Eds.), Choices, Values And Frames (Pp. 673 - 692). New York : Cambridge University Press And The Russell Sage Foundation.
• Kahneman, D. (2003). A Perspective On Judgment And Choice: Mapping Bounded Rationality. American Psychologist, 58, 697 - 720.
• Kahneman, D. (2003). Maps Of Bounded Rationality: A Perspective On Intuitive Judgment And Choice. In T. Frangsmyr [Nobel Foundation], (Ed.), Les Prix Nobel: The Nobel Prizes 2002 (Pp. 449 - 489). Stockholm: The Nobel Foundation.
• Kahneman, D. (2003). Maps Of Bounded Rationality: Psychology For Behavioral Economics. American Economic Review, 93, 1449 - 1475.
• Kahneman, D. (2014). A New Etiquette For Replication. Social Psychology, 45(4), 310 - 311.
• Kahneman, D. And Tversky, A., 1979, Prospect Theory: An Analysis Of Decision Under Risk, Econometrica, 47, 263-91.
• Kahneman, D. Et Al. (1962). Validity And Nonlinear Heteroscedastic Models. Personnel Psychology, 15, 1 - 11.
• Kahneman, D. Et Al. (1963). Visual Resolution And Contour Interaction. Journal Of The Optical Society Of America, 53, 1026 - 1032.
• Kahneman, D. Et Al. (1966). Pupil Diameter And Load On Memory. Science, 154, 1583 - 1585.
• Kahneman, D. Et Al. (1966). Pupillary Changes In Two Memory Tasks. Psychonomic Science, 5, 371 - 372.
• Kahneman, D. Et Al. (1967). Critical Duration For The Resolution Of Form: Centrally Or Peripherally Determined? Journal Of Experimental Psychology, 73, 323 - 327.
• Kahneman, D. Et Al. (1967). Perceptual Deficit During A Mental Task. Science, 157, 218 - 219.
• Kahneman, D. Et Al. (1967). Pupillary Responses In A Pitch - Discrimination Task. Perception And Psychophysics, 2, 101 - 105.
• Kahneman, D. Et Al. (1968). Effects Of Grouping On The Pupillary Response In A Short - Term Memory Task. Quarterly Journal Of Experimental Psychology, 20, 309 - 311.
• Kahneman, D. Et Al. (1969). Incentive Effects And Pupillary Changes In Association Learning. Journal Of Experimental Psychology, 79, 312 - 318.
• Kahneman, D. Et Al. (1969). Pupillary, Heart Rate, And Skin Resistance Changes During A Mental Task. Journal Of Experimental Psychology, 79, 164 - 167.
• Kahneman, D. Et Al. (1970). Stroboscopic Motion: Effects Of Duration And Interval. Perception And Psychophysics, 8, 161 - 164.
• Kahneman, D. Et Al. (1971). Belief In The Law Of Small Numbers. Psychological Bulletin, 76, 105 - 110.
• Kahneman, D. Et Al. (1971). Changes In Pupil Size And Rehearsal Strategies In A Short - Term Memory Task. Quarterly Journal Of Experimental Psychology, 23, 187 - 196.
• Kahneman, D. Et Al. (1971). Evidence Of Alternative Strategies Of Sentence Retention. Quarterly Journal Of Experimental Psychology, 23, 197 - 213.
• Kahneman, D. Et Al. (1972). Subjective Probability: A Judgment Of Representativeness. Cognitive Psychology, 3, 430 - 454.
• Kahneman, D. Et Al. (1973). Availability: A Heuristic For Judging Frequency And Probability. Cognitive Psychology, 207 - 232.
• Kahneman, D. Et Al. (1973). On The Psychology Of Prediction. Psychological Review, 80, 237 - 25l.
• Kahneman, D. Et Al. (1973). Relation Of A Test Of Attention To Road Accidents. Journal Of Applied Psychology, 58, 113 - 115.
• Kahneman, D. Et Al. (1974). Reaction Time In Focused And In Divided Attention. Journal Of Experimental Psychology, 103, 393 - 399.
• Kahneman, D. Et Al. (1974). Judgment Under Uncertainty: Heuristics And Biases. Science, 185, 1124 - 1131.
• Kahneman, D. Et Al. (1977). Capacity Sharing And Refractoriness In Successive Reactions. Perceptual And Motor Skills, 44, 327 - 335.
• Kahneman, D. Et Al. (1977). Causal Thinking In Judgment Under Uncertainty. In R. Butts And J. Hintekka (Eds.), Basic Problems In Methodology And Linguistics (Pp. 167 - 190). Dordrecht , Holland : D. Reidel Publishing Company.
• Kahneman, D. Et Al. (1977). Effects Of Visual Grouping On Immediate Recall And Selective Attention. In S. Dornic (Ed.), Attention And Performance Vi (Pp. 307 - 332). Hillsdale , Nj : Erlbaum.
• Kahneman, D. Et Al. (1979). Intuitive Prediction: Biases And Corrective Procedures. Management Science, 12, 313 - 327.
• Kahneman, D. Et Al. (1979). Prospect Theory: An Analysis Of Decision Under Risk. Econometrica, 47, 263 - 291.
• Kahneman, D. Et Al. (1980). Causal Schemas In Judgments Under Uncertainty. In M. Fishbein (Ed.), Progress In Social Psychology (Pp. 49 - 72). Hillsdale, Nj : Erlbaum.
• Kahneman, D. Et Al. (1981). Perceptual Organization And Attention. In M. Kubovy And J.R. Pomerantz(Eds.), Perceptual Organization (Pp. 181 - 211). Hillsdale , Nj : Erlbaumkahneman, D. Et Al. (1982). On The Study Of Statistical Intuitions. Cognition, 11, 123 - 141.
• Kahneman, D. Et Al. (1981). The Framing Of Decisions And The Psychology Of Choice. Science, 211, 453 - 458.
• Kahneman, D. Et Al. (1982). Evidential Impact Of Base Rates. In D. Kahneman, P. Slovic And A. Tversky (Eds.), Judgment Under Uncertainty: Heuristics And Biases (Pp. 153 - 160). New York : Cambridge University Press.
• Kahneman, D. Et Al. (1982). Judgments Of And By Representativeness. In D. Kahneman, P. Slovic And A. Tversky (Eds.), Judgment Under Uncertainty: Heuristics And Biases (Pp. 84 - 98). New York : Cambridge University Press.
• Kahneman, D. Et Al. (1982). The Psychology Of Preferences. Scientific American, 246, 160 - 173.
• Kahneman, D. Et Al. (1982). The Simulation Heuristic. In D. Kahneman, P. Slovic And A. Tversky (Eds.), Judgment Under Uncertainty: Heuristics And Biases (Pp. 201 - 208). New York : Cambridge University Press.
• Kahneman, D. Et Al. (1982). Variants Of Uncertainty. Cognition, 11, 143 - 157.
• Kahneman, D. Et Al. (1983). Extensional Vs. Intuitive Reasoning: The Conjunction Fallacy In Probability Judgment. Psychological Review, 90, 293 - 3l5.
• Kahneman, D. Et Al. (1983). Perceptual Objects And The Cost Of Filtering. Perception And Psychophysics, 33, 527 - 532.
• Kahneman, D. Et Al. (1983). Tests Of The Automaticity Of Reading: Dilution Of Stroop Effects By Color - Irrelevant Stimuli. Journal Of Experimental Psychology: Human Perception And Performance, 9, 497 - 509.
• Kahneman, D. Et Al. (1983). The Cost Of Visual Filtering. Journal Of Experimental Psychology: Human Perception And Performance, 9, 510 - 522.
• Kahneman, D. Et Al. (1984). Changing Views Of Attention And Automaticity. In R. Parasuraman, D.R. Davies And J. Beatty (Eds.), Variants Of Attention (Pp. 29 - 61). New York : Academic Press.
• Kahneman, D. Et Al. (1984). Choices, Values And Frames. American Psychologist, 39, 341 - 350.
• Kahneman, D. Et Al. (1986). Fairness And The Assumptions Of Economics. Journal Of Business, 59, S285 - S300.
• Kahneman, D. Et Al. (1986). Norm Theory: Comparing Reality To Its Alternatives. Psychological Review, 93, 136 - 153.
• Kahneman, D. Et Al. (1986). Rational Choice And The Framing Of Decisions. Journal Of Business, 59, S251 - S278.
• Kahneman, D. Et Al. (1990). Predicting Utility. In R.M. Hogarth (Ed.), Insights In Decision Making: A Tribute To Hillel J. Einhorn (Pp. 295 - 310). Chicago , Il : University Of Chicago Press.
• Kahneman, D. Et Al. (1990). Propensities And Counterfactuals: The Loser That Almost Won. Journal Of Personality And Social Psychology, 59, 1101 - 1110.
• Kahneman, D. Et Al. (1990). The Causes Of Preference Reversal. American Economic Review, 80, 204 - 217.
• Kahneman, D. Et Al. (1991). Economic Analysis And The Psychology Of Utility: Applications To Compensation Policy. American Economic Review, 81, 341 - 352.
• Kahneman, D. Et Al. (1991). Loss Aversion In Riskless Choice: A Reference - Dependent Model. Quarterly Journal Of Economics, 106, 1039 - 1061.
• Kahneman, D. Et Al. (1991). Notes On The Psychology Of Utility. In J.E. Roemer And J.E. Elster (Eds.), Interpersonal Comparisons Of Well - Being (Pp. 127 - 163). New York : Cambridge University Press.
• Kahneman, D. Et Al. (1991). Anomalies: The Endowment Effect, Loss Aversion, And Status Quo Bias. The Journal Of Economic Perspectives, 5, 193 - 206.
• Kahneman, D. Et Al. (1992). Advances In Prospect Theory: Cumulative Representation Of Uncertainty. Journal Of Risk And Uncertainty, 5, 297 - 323.
• Kahneman, D. Et Al. (1992). Correlation, Causation And Inference In Surveys Of Life Satisfaction. Social Indicators, 27, 221 - 234.
• Kahneman, D. Et Al. (1992). Experiences Extended Across Time: Evaluation Of Moments And Episodes. Journal Of Behavioral Decision Making, 5, 169 - 186.
• Kahneman, D. Et Al. (1992). Predicting A Changing Taste. Journal Of Behavioral Decision Making, 5, 187 - 200.
• Kahneman, D. Et Al. (1992). The Reviewing Of Object Files: Object - Specific Integration Of Information. Cognitive Psychology, 24, 175 - 219.
• Kahneman, D. Et Al. (1992). Valuing Public Goods: The Purchase Of Moral Satisfaction. Journal Of Environmental Economics And Management, 22, 57 - 70.
• Kahneman, D. Et Al. (1993). Duration Neglect In Retrospective Evaluations Of Affective Episodes. Journal Of Personality And Social Psychology, 65, 45 - 55.
• Kahneman, D. Et Al. (1993). Stated Willingness To Pay For Public Goods: A Psychological Analysis. Psychological Science, 4, 310 - 315.
• Kahneman, D. Et Al. (1993). Timid Choices And Bold Forecasts: A Cognitive Perspective On Risk Taking. Management Science, 39, 17 - 31.
• Kahneman, D. Et Al. (1993). When More Pain Is Preferred To Less: Adding A Better End. Psychological Science, 4, 401 - 405.
• Kahneman, D. Et Al. (1994). Determinants Of Stated Willingness To Pay For Public Goods: A Study In The Headline Method. Journal Of Risk And Uncertainty, 9, 5 - 38.
• Kahneman, D. Et Al. (1994). How The Method And Scope Of Public Funding Affects Willingness To Pay For Public Goods. Public Opinion Quarterly, 58, 48 - 67.
• Kahneman, D. Et Al. (1995). Conflict Resolution: A Cognitive Perspective. In K. Arrow, R.H. Mnookin, L. Ross, A. Tversky, And R. Wilson (Eds.), Barriers To Conflict Resolution (Pp. 44 - 61). New York : Norton.
• Kahneman, D. Et Al. (1995). Framing The Jury: Cognitive Perspectives On Pain And Suffering Awards. Virginia Law Review, 81, 1341 - 1420.
• Kahneman, D. Et Al. (1995). Measures Of Anchoring In Estimation Tasks. Personality And Social Psychology Bulletin, 21, 1161 - 1166.
• Kahneman, D. Et Al. (1996). On The Reality Of Cognitive Illusions: A Reply To Gigerenzer's Critique. Psychological Review, 103, 582 - 591.
• Kahneman, D. Et Al. (1997). How People Value The Environment: Attitudes Versus Economic Values. In M.H. Bazerman, D.M. Messick, A.E. Tenbrunsel And K.A. Wade - Benzoni, (Eds.), Environment, Ethics, And Behavior: The Psychology Of Environmental Valuation And Degradation (Pp. 33 - 51). San Francisco , Ca : The New Lexington Press.
• Kahneman, D. Et Al. (1997). The Effect Of Myopia And Loss Aversion On Risk Taking: An Experimental Test. Quarterly Journal Of Economics, 112, 647 - 661.
• Kahneman, D. Et Al. (1998). Aspects Of Investor Psychology. The Journal Of Portfolio Management, 24, 52 - 65.
• Kahneman, D. Et Al. (1998). Assessing Punitive Damages. Yale Law Journal, 107, 2071 - 2153.
• Kahneman, D. Et Al. (1998). Referendum Contingent Valuation, Anchoring And Willingness To Pay For Public Goods. Resource And Energy Economics, 20, 85 - 116.
• Kahneman, D. Et Al. (1999). Economic Preferences Or Attitude Expressions? An Analysis Of Dollar Responses To Public Issues. Journal Of Risk And Uncertainty, 19, 220 - 242.
• Kahneman, D. Et Al. (1999). The Effect Of Stress On The Suppression Of Erroneous Competing Responses. Anxiety, Stress And Coping, 12, 455 - 476.
• Kahneman, D. Et Al. (2000). Determinants Of The Remembered Utility Of Aversive Sounds. Journal Of Experimental Psychology: General, 129, 27 - 42.
• Kahneman, D. Et Al. (2000). Joint Comment On ‘When Does Duration Matter In Judgment And Decision Making?’ (Ariely And Loewenstein, 2000). Journal Of Experimental Psychology: General, 129, 524 - 529.
• Kahneman, D. Et Al. (2000). Living With Uncertainty: Attractiveness And Resolution Timing. Journal Of Behavioral Decision Making, 13, 179 - 190.
• Kahneman, D. Et Al. (2001). Do Frequency Representations Eliminate Conjunction Effects? An Exercise In Adversarial Collaboration. Psychological Science, 12, 269 - 275.
• Kahneman, D. Et Al. (2001). Functional Imaging Of Neural Responses To Expectancy And Experience Of Monetary Gains And Losses. Neuron, 30, 619 - 639.
• Kahneman, D. Et Al. (2001). Making Low Probabilities Useful. Journal Of Risk And Uncertainty, 23, 103 - 120.
• Kahneman, D. Et Al. (2002). Judgment Heuristics: Human Strengths Or Human Weaknesses? In L. Aspinwall And U. Staudinger, (Eds.), A Psychology Of Human Strengths: Perspectives On An Emerging Field (Pp. 165 - 178). Washington , D.C. : Apa Books.
• Kahneman, D. Et Al. (2002). Predictably Incoherent Judgments. Stanford Law Review, 54, 1153 - 1215.
• Kahneman, D. Et Al. (2002). Representativeness Revisited: Attribute Substitution In Intuitive Judgment. In T. Gilovich, D. Griffin And D. Kahneman (Eds.), Heuristics And Biases: The Psychology Of Intuitive Judgment (Pp.49 - 81). New York : Cambridge University Press.
• Kahneman, D. Et Al. (2003). Delusions Of Success: How Optimism Undermines Executives' Decisions. Harvard Business Review, 81, 56 - 63.
• Kahneman, D. Et Al. (2004). Toward National Well - Being Accounts. American Economic Review, 94, 429 - 434.
• Kahneman, D. Et Al. (2005). A Model Of Heuristic Judgment. In K.J. Holyoak And R.G. Morrison (Eds.), The Cambridge Handbook Of Thinking And Reasoning (Pp. 267 - 293). New York : Cambridge University Press.
• Kahneman, D. Et Al. (2005). Experienced Utility As A Standard Of Policy Evaluation. Environmental And Resource Economics, 32, 161 - 81.
• Kahneman, D. Et Al. (2005). How Do Intentions Affect Loss Aversion? Journal Of Marketing Research, 42, 139 - 140.
• Kahneman, D. Et Al. (2005). Testing Competing Models Of Loss Aversion: An Adversarial Collaboration. Journal Of Public Economics, 89, 1561 - 1580.
• Kahneman, D. Et Al. (2006). An Experiment In Decision Analysis In Israel In 1975. Studies In Intelligence, 50(4) , 11 - 19.
• Kahneman, D. Et Al. (2006). Developments In The Measurement Of Subjective Well - Being. Journal Of Economic Perspectives, 20, 3 - 24.
• Kahneman, D. Et Al. (2007). Frames And Brains: Elicitation And Control Of Response Tendencies . Trends In Cognitive Sciences, 11, 45 - 46.
• Kahneman, D. Et Al. (2007, January / February). Why Hawks Win. Foreign Policy, 158, 34 - 38.
• Kahneman, D. Et Al. (2008). Interpretations Of Utility And Their Implications For The Valuation Of Health. The Economic Journal, 118, 215 - 234.
• Kahneman, D. Et Al. (2009). Conditions For Intuitive Expertise A Failure To Disagree. American Psychologist, 64(6), 515 - 526.
• Kahneman, D. Et Al. (2009). Memories Of Yesterday's Emotions: Does The Valence Of Experience Affect The Memory - Experience Gap? Emotion, 9(6), 885 - 891.
• Kahneman, D. Et Al. (2010) A Comparison Of Affect Ratings Obtained With Ecological Momentary Assessment And The Day Reconstruction Method. Social Indicators Research, 99(2), 269 - 283.
• Kahneman, D. Et Al. (2010) Associative Processes In Intuitive Judgment. Trends In Congnitive Sciences, 14(10), 435 - 440.
• Kahneman, D. Et Al. (2010) Comparing Gains And Losses. Psychological Science, 21(10), 1438 - 1445.
• Kahneman, D. Et Al. (2010). Elaborating A Simpler Theory Of Anchoring. Journal Of Consumer Psychology, 20(1), 17 - 19.
• Kahneman, D. Et Al. (2011) Before You Make That Big Decision ... Harvard Business Review, 89(6), 50 - 60.
• Kahneman, D. Et Al. (2016). Reducing Noise In Decision Making. Harvard Business Review, 94(12), 18 - 18.
• Kahneman, D. Et Al. Kahneman, D. (1999). Choosing Less - Preferred Experiences For The Sake Of Variety. Journal Of Consumer Research, 26, 1 - 15.
• Kahneman, D., And Norman, J. (1964). The Time - Intensity Relation In Visual Perception As A Function Of Observer's Task. Journal Of Experimental Psychology, 6, 215 - 220.
• Karelaia, N. (2006). Thirst For Confirmation In Multi-Attribute Choice: Does Search For Consistency Impair Decision Performance? Organizational Behavior And Human Decision Processes, 100, 128-143.
• Karelaia, N. (2008). Book Review: ‘Straight Choices. The Psychology Of Decision Making.’ By Newell, B. N., Lagnado, D. A., And Shanks, D. R. Psychology Press, Taylor And Francis Group, Hove And New York, 2007. Journal Of Economic Psychology, 29(3), 372-374.
• Karelaia, N. (2009). Book Review: ‘Predictably Irrational: The Hidden Forces That Shape Our Decisions.’ By Dan Ariely. Harper, 2008. Academy Of Management Perspectives, 23(1), 86-88.
• Karelaia, N. (2013). Book Review: ‘Ecological Rationality: Intelligence In The World.’ By Peter M. Todd, Gerd Gigerenzer, And The Abc Research Group. Oxford University Press, Journal Of Economic Psychology, 34, 306-308.
• Karelaia, N., And Guillén, L. (2014). Me, A Woman And A Leader: Positive Social Identity And Identity Conflict. Organizational Behavior And Human Decision Processes, 125, 204-219.
• Karelaia, N., And Hogarth R. M. (2010). The Attraction Of Uncertainty: Interactions Between Skill And Levels Of Uncertainty In Market-Entry Games. Journal Of Risk And Uncertainty, 41(2), 141-166.
• Karelaia, N., And Hogarth, R. M. (2008). Determinants Of Linear Judgment: A Meta-Analysis Of Lens Studies. Psychological Bulletin, 134(3), 404-426.
• Karelaia, N., And Keck, S. (2013). When Deviant Leaders Are Punished More Than Non-Leaders: The Role Of Deviance Severity. Journal Of Experimental Social Psychology, 49(5), 783-796.
• Karelaia, N., And Reb, J. (2015). Improving Decision Making Through Mindfulness. In Mindfulness In Organizations, Reb, J., And Atkins, P. (Eds.), Cambridge University Press.
• Karmakar, S. and Satpathy, J. (2018). Human Capital: Neuro - Based Analysis of Three Indian States, Proceedings of Golden Jubilee Conference (OEA Journal), 50th Annual Conference, Orissa Economics Association, 10 Feb 2018, Nabakrushna Choudhury Centre for Development Studies, Bhubaneswar, India (National).
• Keck, S., And Karelaia, N. (2012). Does Competition Foster Trust? The Role Of Tournament Incentives. Experimental Economics, 15(1), 204-228.
• Khurana B. Kowler E. (1987). Shared Attentional Control Of Smooth Eye Movement And Perception. Vision Research, 27, 1603–1618.
• Khurana, B. And Kowler, E. (1987). Shared Attentional Control Of Smooth Eye Movements And Perception. Vision Research, 27, 1603-1618.
• Martins, A. J., Kowler, E. And Palmer, C. (1985). Smooth Pursuit Of Small Amplitude Sinusoidal Motion. Journal Of The Optical Society Of America, A, 2, 234-242.
• Klucharev V. Et Al. (2013). Brain Mechanisms Of Persuasion: How 'Expert Power' Modulates Memory And Attitudes. Soc Cogn Affect Neurosci. 2008 Dec;3(4):353-66.
• Klucharev V. Et Al. (2013). Downregulation Of The Posterior Medial Frontal Cortex Prevents Social Conformity. J Neurosci 31:11934-11940
• Klucharev V. Et Al. (2013). Ecg Monitoring In Patients With Perceived Electrical Hypersensitivity. Int J Psychophysiol. 2003 Sep;49(3):227-35.
• Klucharev V. Et Al. (2013). Effect Of Emotional Context In Auditory-Cortex Processing. Int J Psychophysiol. 2007 Sep;65(3):261-71.
• Klucharev V. Et Al. (2013). Electrophysiological Correlates Of Trigger Mechanisms Of Emotional Reactions In The Temporal Lobe Of The Human Brain. Fiziol Cheloveka. 1998 Marapr;24(2):5-15.
• Klucharev V. Et Al. (2013). Electrophysiological Indicators Of Phonetic And Non-Phonetic Multisensory Interactions During Audiovisual Speech Perception Brain Res Cogn Brain Res. 2003 Dec; 18(1):65-75.
• Klucharev V. Et Al. (2013). Electrophysiological Precursors Of Social Conformity. Soc Cogn Affect Neurosci. (2013, In Print) Advance Access Published July 4, 2012
• Klucharev V. Et Al. (2013). Evoked Potentials Of The Cerebral Cortex During The Comparison Of Visual Stimuli / Human Physiology, Vol. 26, No. 2, 2000 January–February, P. 136-141.
• Klucharev V. Et Al. (2013). Interaction Of Gaze Direction And Facial Expressions Processing: Erp Study. Neuroreport March 22, 2004, Volume 15, Issue 4, P. 621-626
• Klucharev V. Et Al. (2013). Monitor Jitter And Human-Computer Interaction Displays 2000, Volume 21, Issue 5, Pages 173-177.
• Klucharev V. Et Al. (2013). Neurobiological Mechanisms Of The Depletion Of Natural Resources: ‘Tragedy Of The Commons’. (Submitted)
• Klucharev V. Et Al. (2013). Orderly Cortical Representation Of Vowel Categories Presented By Multiple Exemplars. Brain Res Cogn Brain Res. 2004 Nov;21(3):342-50.
• Klucharev V. Et Al. (2013). Reinforcement Learning Signal Predicts Social Conformity. Neuron. 2009 Jan 15;61(1):140-51. Klucharev V, Smidts A, Fernández G. Brain Mechanisms Of Persuasion: How 'Expert Power' Modulates Memory And Attitudes. Soc Cogn Affect Neurosci. 2008 Dec;3(4):353-66.
• Klucharev V. Et Al. (2013). Reinforcement Learning Signal Predicts Social Conformity. Neuron. 2009 Jan 15;61(1):140-51.
• Klucharev V. Et Al. (2013). Study Of The Brain Organization Of Creativity. Part Ii. Positron Emission Tomography. Fiziol Cheloveka. 2000 Sep-Oct;26(5):12-8.
• Klucharev V. Et Al. (2013). The Cerebral Organization Of Creativity. I. The Development Of A Psychological Test Fiziol Cheloveka. 2000 Mar-Apr;26(2):5-9. In Russian.
• Klucharev V. Et Al. (2013). The Effect Of Repetitive Electrical Stimulation On The Motor Evoked Hemodynamic Responses. Int J Neurosci. 2006 Mar;116(3):331-49.
• Klucharev V. Et Al. (2013). The Influence Of Emotionally Significant Visual Stimuli On Cortical Evoked Potentials / Human Physiology, Vol. 26, No. 1, 2000 January–February, P.1- 8.
• Klucharev V. Et Al. (2013). The Influence Of Weak Electromagnetic Fields On The Stability Of A Computer Monitor Image: Possible Consequences For An Operator / Human Physiology, Vol. 26, No. 2, 2000 January–February, P. 296-300.
• Klucharev V. Et Al. (2013). The Neural Underpinnings Of Informational Cascades - An Fmri Study Of Probability Updating In A Social Context. (In Preparation).
• Kowler E. (1989). Cognitive Expectations, Not Habits, Control Anticipatory Smooth Oculomotor Pursuit. Vision Research, 29, 1049–1057.
• Kowler E. (2011). Eye Movements: The Past 25 Years. Vision Research, 51, 1457–1483.
• Kowler E. Anderson E. Dosher B. Blaser E. (1995). The Role Of Attention In The Programming Of Saccades. Vision Research, 35, 1897–1916.
• Kowler E. Mckee S. P. (1987). Sensitivity Of Smooth Eye Movement To Small Differences In Target Velocity. Vision Research, 27, 993–1015.
• Kowler E. Steinman R. M. (1979a). The Effect Of Expectations On Slow Oculomotor Control: I. Periodic Target Steps. Vision Research, 19, 619–632.
• Kowler E. Steinman R. M. (1979b). The Effect Of Expectations On Slow Oculomotor Control: Ii. Single Target Displacements. Vision Research, 19, 633–646.
• Kowler E. Steinman R. M. (1979c). Miniature Saccades: Eye Movements That Do Not Count. Vision Research, 19, 105–108.
• Kowler, E. (1989). Cognitive Expectations, Not Habits, Control Anticipatory Smooth Oculomotor Pursuit. Vision Research, 29, 1049-1057.
• Kowler, E. (1990). The Role Of Visual And Cognitive Processes In The Control Of Eye Movement. In Eye Movements And Their Role In Visual And Cognitive Processes. (Edited By Kowler, E.) Elsevier, Amsterdam.
• Kowler, E. (1991). The Stability Of Gaze And Its Implications For Vision. In: Eye Movements (Volume 9 Of Vision And Visual Dysfunction) (Edited By Carpenter, R.H.S.). Macmillan Press, London.
• Kowler, E. (1995) Cogito Ergo Moveo: Cognitive Control Of Eye Movement. In Exploratory Vision: The Active Eye. (Edited By Landy, M., Maloney, L. And Pavel, M.) Springer-Verlag.
• Kowler, E. (1995) Eye Movement. In: Invitation To Cognitive Science, Vol. 2. (Edited By Kosslyn, S.). Mit Press.
• Kowler, E. (1999) Eye Movements And Visual Attention. In: Mit Encyclopedia Of Cognitive Science.
• Kowler, E. And Anton, S. (1987). Reading Twisted Text: Implications For The Role Of Saccades. Vision Research, 27, 45-60.
• Kowler, E. And Blaser, E. (1995) The Accuracy And Precision Of Saccades To Small And Large Targets. Vision Research, 35, 1741-1754.
• Kowler, E. And Martins, A. J. (1982). Eye Movements Of Preschool Children. Science, 215, 997-999.
• Kowler, E. And Martins, A. J. (1983). Eye Movements Of Preschool Children (Technical Comment). Science, 222, 75-77.
• Kowler, E. And Mckee, S. M. (1987). Sensitivity Smooth Eye Movements To Small Differences In Target Velocity. Vision Research, 27, 993-1015.
• Kowler, E. And Sperling, G. (1980). Transient Stimulation Does Not Aid Visual Search: Implications For The Role Of Saccades. Perception And Psychophysics, 27, 1-10.
• Kowler, E. And Sperling, G. (1983). Abrupt Onsets Do Not Aid Visual Search. Perception And Psychophysics, 34, 307-313.
• Kowler, E. And Steinman, R. M. (1977). The Role Of Small Saccades In Counting. Vision Research, 17, 141-146.
• Kowler, E. And Steinman, R. M. (1979). Miniature Saccades: Eye Movements That Do Not Count. Vision Research, 19, 105-108.
• Kowler, E. And Steinman, R. M. (1979). The Effect Of Expectations On Slow Oculomotor Control--I: Periodic Target Steps. Vision Research, 19, 619-632
• Kowler, E. And Steinman, R. M. (1979). The Effect Of Expectations On Slow Oculomotor Control--Ii: Single Target Displacements. Vision Research, 9, 633-646
• Kowler, E. And Steinman, R. M. (1980). Small Saccades Serve No Useful Purpose. Vision Research, 20, 273-276.
• Kowler, E. And Steinman, R. M. (1981). The Effect Of Expectations On Slow Oculomotor Control-Iii: Guessing Unpredictable Target Displacements. Vision Research, 21, 191-203.
• Kowler, E., Aitkin, C.D., Ross, N.M., Santos, E.M. And Zhao, M. (2014). The Importance Of Prediction And Anticipation In The Control Of Smooth Pursuit Eye Movements. Journal Of Vision, 14(5):10, 1-16.
• Kowler, E., And Zingale, C. (1985). Smooth Eye Movements As Indicators Of Selective Attention. In Attention And Performance Xi (Eds. Posner, M. I. And Marin, O. S.M.) L. Erlbaum, Hillsdale, Nj.
• Kowler, E., Anderson, E., Dosher, B. And Blaser, E. (1995) The Role Of Attention In The Programming Of Saccades. Vision Research, 35, 1897-1916.
• Kowler, E., Martins, A. J., And Pavel, M. (1984). The Effect Of Expectations On Slow Oculomotor Control--Iv: Anticipatory Smooth Eye Movements Depend On Prior Target Motions. Vision Research, 24, 197-210.
• Kowler, E., Murphy, B. J. And Steinman, R. M. (1978). Velocity Matching During Smooth Pursuit Of Different Targets On Different Backgrounds. Vision Research, 18, 603-605.
• Kowler, E., Pizlo, Z., Zhu, G.L., Erkelens, C., Steinman, R.M., And Collewijn, H. (1991). Coordination Of Head And Eyes During The Performance Of Natural (And Unnatural) Visual Tasks. In The Head-Neck Sensory Motor System, (Edited By Berthoz, A., Graf, W., And Vidal, P.P.) Oxford University Press, N.Y.
• Kowler, E., Van Der Steen, J., Tamminga, E. P., And Collewijn, H. (1984). Voluntary Selection Of The Target For Smooth Eye Movements In The Presence Of Superimposed, Full-Field Stationary And Moving Stimuli, Vision Research, 24, 1789-1798
• Lai, M. L., Tsai, M. J., Yang, F. Y., Hsu, C. Y., Liu, T. C., Lee, S. W. Y., Lee, M. H., Chiou, G. L., Liang, J. C., And Tsai, C. C. (2013). A Review Of Using Eye-Tracking Technology In Exploring Learning From 2000 To 2012. Educational Research Review, 10, 90- 115. (Ssci)
• Lai, M. L., Tsai, M. J., Yang, F. Y., Hsu, C. Y., Liu, T. C., Lee, S. W. Y., Lee, M. H., Chiou, G. L., Liang, J. C., And Tsai, C. C. (2013). A Review Of Using Eye-Tracking Technology In Exploring Learning From 2000 To 2012. Educational Research Review, 10, 90- 115.。
• Lin, Y. T., Wu, C. C., Lin, Y. C., H. T. Y., Yang, F. Y., And Chang, C. H. (2016). Tracking Students’ Cognitive Processes During Program Debugging – An Eye-Movement Approach. Ieee Transactions On Education, 59(3), 175-186。
• Litt, A., Pirouz, D., And Shiv, B. (2012), ‘Neuroscience And Addictive Consumption,’ In Transformative Consumer Research For Personal And Collective Well Being: Reviews And Frontiers, Eds. David Mick, Simone Pettigrew, Connie Pechmann And Julie Ozanne, Taylor And Francis.
• Litt, A., Plassmann, H., Shiv, B., And Rangel, A. (2010), ‘Dissociating Valuation And Saliency Signals During Decision-Making,’ Cerebral Cortex, Vol. 21 (1), 95-102.
• M. Chawla, And K.P. Miyapuram, Comparison Of Meta-Analysis Approaches For Neuroimaging Studies Of Reward Processing: A Case Study. Ijcnn 2015: 1-5 {Talk}
• Mcgowan, J., Kowler, E., Sharma, A. And Chubb, C. (1998) Saccadic Localization Of Random Dot Targets. Vision Research, 38, 895-909.
• Melcher, D. And Kowler, E. (1999) Shape, Surfaces And Saccades. Vision Research, 39, 2929-2946.
• Melcher, D. And Kowler, E. (2001) Visual Scene Memory And The Guidance Of Saccadic Eye Movements. Vision Research, 41, 3597-3611.
• Mishra, B.P. and Satpathy, J. (2017). How Managers Decide, Journal of Personnel Focus, ISSN: 2229 - 6506, Vol. 13, Issue (1), July, Pp: 01 - 28, Bhubaneswar, India (National)
• Mishra, S. and Satpathy, J. (2014). Neuro Management Perspective in Stress Dynamics: (Empirical Evidence among Working Women in Odisha, India), International Interdisciplinary Congress on Women, University of Hyderabad, the IICW 2014, August 20, 2014, Hyderabad, India. (International)
• Mishra, S. and Satpathy, J. (2014). Reflections On Neuropsychological - Decision Making, 3rd International Conference on Managing Human Resources at the Workplace, 05 - 06 December, Mysore, India. (International)
• Mishra, S. and Satpathy, J. (2018). Reflections on Neuro - Competency in Power Sector, Odisha Journal of Social Science, Vol 5. (2), July Edition, Pp: 05 - 30, Bhubaneswar, Odisha, India. (National).
• Miyapuram, K.P., Pamnani, U., Doya, K., Bapi, R.S. Inter Subject Correlation Of Brain Activity During Visuo-Motor Sequence Learning, 21st International Conference On Neural Information Processing (Iconip2014).
• Mogilner, C., Iyengar, S., And Shiv, B. (2013), ‘Eternal Quest For The Best: Sequential (Vs. Simultaneous) Option Presentation Undermines Choice Confidence,’ Simultaneously Vs. Sequentially Presented Options On Chooser Commitment.’ Conditionally Accepted - Journal Of Consumer Research, Vol. 39 (April), 1300-1312.
• Murphy, B. J., Kowler, E. And Steinman, R. M. (1975). Slow Oculomotor Control In The Presence Of Moving Backgrounds. Vision Research, 15, 1263-1268.
• Murthy A And A. L. Humphrey. Inhibitory Contributions To Spatiotemporal Receptive-Field Structure And Direction Selectivity In Simple Cells Of Cat Area 17. J. Neurophysiology 81,1212-1224 (1999).
• Murthy A, A. B. Saul And A. L. Humphrey. Laminar Differences In The Spatiotemporal Structure Of Simple Cell Receptive Fields In Cat Area 17. Visual Neuroscience 15, 1-18 (1998)
• Murthy A, K. G. Thompson And J. D. Schall (2001). Dynamic Dissociation Of Visual Selection From Saccade Programming. J. Neurophysiology 86, 2634-2637 (2001).
• Murthy A, Ray S, Shorter Sm, Schall Jd,Thompson Kg. Neural Control Of Visual Search By Frontal Eye Field: Effects Of Unexpected Target Displacement On Visual Selection And Saccade Preparation J. Neurophysiology101: 2485-2507 (2009).
• Murthy A. Neural Control Of Eye Movements. Iete Journal Of Research. 49: 135-144 (2003).
• Murthy, A., Ray, S., Shorter-Jacobi, S.M., Schall, J.D. And K.G.Thompson . Frontal Eye Field Contributions To Rapid Corrective Saccades. J. Neurophysiology 97: 1457-1469 (2007).
• Naqvi, N. Shiv, B., And Bechara, A., (2006), ‘The Role Of Emotion In Decision Making: A Cognitive Neuroscience Perspective,’ Current Directions In Psychological Science, Vol. 15 (5), 260-264.
• Narendran, S. and Satpathy, J. (2015). Economics of Science and Technology, Conference Proceedings, TECHMA 2015, Institute of Technology Management, DRDO, 26 - 27 October, Mussoorie, India. (National)
• Orquin, J. L. (2014). A Brunswik Lens Model Of Consumer Health Judgments Of Packaged Foods. Journal Of Consumer Behaviour, 13(4), 270-281.
• Orquin, J. L., And Lagerkvist, C. J. (2015). Effects Of Salience Are Both Short-And Long-Lived. Acta Psychologica, 160, 69-76. Pdf
• Orquin, J. L., And Loose, S. M. (2013). Attention And Choice: A Review On Eye Movements In Decision Making. Acta Psychologica, 144(1), 190-206.
• Orquin, J. L., And Scholderer, J. (2015). Consumer Judgments Of Explicit And Implied Health Claims On Foods: Misguided But Not Misled. Food Policy, 51, 144-157.
• Orquin, J. L., Ashby, N. J., And Clarke, A. D. (2015). Areas Of Interest As A Signal Detection Problem In Behavioral Eye‐Tracking Research. Journal Of Behavioral Decision Making.
• Orquin, J. L., Bagger, M. P., And Loose, S. M. (2013). Learning Affects Top Down And Bottom Up Modulation Of Eye Movements In Decision Making. Judgment And Decision Making, 8(6), 700.
• Orquin, J. L., Jeppesen, H. B., Scholderer, J., And Haugtvedt, C. (2014). Attention To Advertising And Memory For Brands Under Alcohol Intoxication. Frontiers In Psychology, 5.
• Orquin, J., And Scholderer, J. (2011). Attention To Health Cues On Product Packages. Journal Of Eye Tracking, Visual Cognition And Emotion, (1).
• Peschel, A. O., And Orquin, J. L. (2013). A Review Of The Findings And Theories On Surface Size Effects On Visual Attention. Frontiers In Psychology, 4.
• R.S. Bapi, K.P. Miyapuram, F.X. Graydon, K. Doya. (2006). Fmri Investigation Of Cortical And Subcortical Networks In The Learning Of Abstract And Effector-Specific Representations Of Motor Sequences. Neuroimage, 32(2):714-727. {Editor’s Choice Award For The Year 2006}
• Ramakrishnan A, Chokhandre S, Murthy A. Voluntary Control Of Multi-Saccade Gaze Shifts During Movement Preparation And Execution J. Neurophysiology 103:2400-16 (2010)
• Ramakrishnan, A. And Murthy A. Brain Mechanisms For Decision-Making And Motor Control. Progress In Brain Research 202:321-45 (2013).
• Ramakrishnan, A., Sureshbabu Ramakrishnan And Murthy A. Understanding How The Brain Changes Its Mind: Microstimulation In The Macaque Frontal Eye Field Reveals How Saccade Plans Are Changed. Journal Of Neuroscience. 32(13):4457- 4472 (2012).
• Satpathy, J and Mohapatra, B.B. (2015). Peep into Behavioural Science of Choice, International Journal on Research and Development - A Management Review (IJRDMR), Vol. 4, Issue 4, Pp: 69 - 78, ISSN: 2319 - 5479, Bhubaneswar, India. (International)
• Satpathy, J and Pati, P. (2016). Unmapped Territory in Neruodecision Modeling, International Journal on Research and Development - A Management Review (IJRDMR), Vol. 5, Issue 3, Pp: 15 - 29, ISSN: 2319 - 5479, Bhubaneswar, India. (International).
• Satpathy, J. (2012). Neuro - Economic Actors in Organisational Decision Making: An Anthology, Proceedings of National Conference on Perspectives on Employment Relations, Dated December 22 - 23, Berhampur University, India. (National)
• Satpathy, J. (2013). Issues in Neuro - Management Decision Making, International Journal of Business Management, Vol.2, Issue. 02, December 2012. ISSN: 2231 - 5470, India. (International)
• Satpathy, J. (2014). Random Perspectives in Worker - Employer Indenture, 5th National HR Conclave on Psychological Contract: A Competitive Advantage, Sponsored by KIIT School of Management and National HRD Network, 23 August , KIIT University, Bhubaneswar, India. (National)
• Satpathy, J. (2015). Anthology on Managerial Neuro - Decision VUCA Architecture, Proceedings of KSOM’s 8th National Management Convention on The Endless Pursuit of Winning in the VUCA Environment, KIIT School of Management, January 30 - 31, 2015, Bhubaneswar, India. (National)
• Satpathy, J. (2015). Inquiry into Neuro - Managerial Decision Making, ICICBBS Conference, Indo-Canadian International Conference of Business and Behavioural Sciences, Society of Management and Behavioral Sciences (SMBS), 01 April (Accepted), Goa, India. (International)
• Satpathy, J. (2015). Neuro - Based Decision Making Challenges for Project Manager, Conference Proceedings, TECHMA 2015, Institute of Technology Management, DRDO, 26 - 27 October, Mussoorie, India. (National)
• Satpathy, J. (2015). Neuro - Perspective In Managerial Decision - Making Efficacy, International Journal of Multidisciplinary and Academic Research (SSIJMAR) Vol. 04, No. 03, June, (ISSN 2278 - 5973), India. (International)
• Satpathy, J. (2015). Random Thoughts on Managerial Behavioural Competence, Conference Proceedings, TECHMA 2015, Institute of Technology Management, DRDO, 26 - 27 October, Mussoorie, India. (National)
• Satpathy, J. (2015). Research Note on Cognitive - Underpinning in Neuro - Managerial Decision Modeling, Impact Factor 5. 09, ITIHAS - The Journal of Indian Management, ISSN 2249 - 7803, Vol. 5, No. IV, Oct - Dec 2015, Hyderabad, India. (National)
• Satpathy, J. (2018). Neuro - Based Decisions in Global Business Undercurrents, IMS International Conference on Indian Trade and Commerce: Past, Present and Future, March 18, Bhubaneswar, India (International).
• Satpathy, J. (2019). Neuro - Optometric Decision Estimates in Managing Creative Organization (Poster), 4th Coller Conference on Behavioral Economics (CCBE), June 19 and 20, Center for Behavior Change, Tel Aviv University, Israel
• Satpathy, J. and Das, A. (2016). Neuro - Contemplation on Managerial Decision, International Journal on Research and Development - A Management Review (IJRDMR), Vol. 05, Issue 04, Pp: 29 - 32, ISSN: 2319 - 5479, Bhubaneswar, India. (International)
• Satpathy, J. and Datta, T. (2014). Contributions to Neuro - Decision Computational Modeling, 41st Annual Conference of Orissa Mathematical Society and International Conference on Industrial Mathematics and Scientific Computing, No. ICIMSC14/OMS41/06, 4 - 5 January 2014, Department of Mathematics, School of Applied Sciences, KIIT University, Bhubaneswar, India. (International)
• Satpathy, J. and et. al. (2018). Thoughts on Managerial Skills, , National Institute of Personnel Management, Utkal Chapter, Vol. 14, Issue No. 1, ISSN No. 2229 - 6506, Pp: 01 - 06, January 2018, Bhubaneswar, India (National).
• Satpathy, J. and Gankar, S.S. (2016). Neuro - Geometry in Managerial Decision Dynamics, KHOJ: Journal of Indian Management Research and Practices (ISSN No.0976-8262) and Proceedings (GE - International Journal of Management Research) of International Conference on Emerging Trends in Management and Technology 2016 (ICETMT-2016), 23rd and 24th December, MIT School of Management, Pune in collaboration with Savitribai Phule Pune University, Pune, India. Concurrently published in International Journal on Research and Development - A Management Review (IJRDMR), Vol. 5, Issue 04, Pp: 40 - 47, ISSN: 2319 - 5479, Bhubaneswar, India. (International)
• Satpathy, J. and Gankar, S.S. (2017). Brain - Eye Coadjuvancy in Managerial Decision Dynamics, Proceedings of National Research Conference - 2017 (NCBMSSH - 2017), Khoj: Journal of Indian Management Research and Practices, ISSN: 0976 – 8262, Pp: 11 - 38, MIT School of Management, 21 - 22 Dec 2017, Pune, India (National).
• Satpathy, J. and Gankar, S.S. (2017). No Food, No Water: What Decision Making? (Study in North - East India), Proceedings of National Conference on Poverty and Rural Development in India with Special Reference to North Eastern Region, 16 - 17 Sep 2017, Department of Economics, Debraj Roy College, Golaghat, Assam, India (National)
• Satpathy, J. and Gohain, A. (2018). Socio - Genetic Matrices in Decision Diminuendos (Case Study in North - East India), Proceedings of UGC - Sponsored National Seminar on Development of Marginalized Sections in North East India: Its Problems and Prospects, Department of Sociology, 10 - 11 Jan 2018, Khowang College, Dibrugarh, India (National).
• Satpathy, J. and Hejmadi, A. (2018). Decision Signatures in Managerial Brain Architecture (Poster), Proceedings of NeuroPsychoEconomics Conference, Pp: 61, May 24 - 25, Zurich, Switzerland. (International).
• Satpathy, J. and Hejmadi, A. (2019). Electrodermal Traces in Decision Making, Proceedings of National Seminar on Technology, Innovation, Policy Initiatives and Entrepreneurship Development (NSTIPED - 2019), 30th - 31st Jan 2019, Parala Maharaja Engineering College, BPUT University, Berhampur, Odisha, India (National).
• Satpathy, J. and Hejmadi, A. (2019). Neuro - Optometric Decision Estimates in Managing Creative Organisation, Proceedings of National Seminar on Managing Resource through Creativity for Generating Opportunities in 21st Century, Pp: 30 - 55, ISBN Number: 978 - 81 - 922746 - 9 - 0, S B Patil Institute of Management, Pune University, 18 -19 Jan 2019, Pune, India (National). Concurrently published under the title NEURO-OCULARDECISION GUESTIMATES in Odisha Journal of Social Science, Vol 6. (1), January Edition, Pp: 103 - 115, Bhubaneswar, Odisha, India. (National).
• Satpathy, J. and Hejmadi, A., Subhashree P. and Mishra, S. (2018). Decision Monikers in Managerial Eyes, Proceedings of International Conference on Contemporary Issues in Business Innovation, Technology and Social Sciences, Gautam Buddha University, 01 - 02 June 2018, June 2018, Noida (UP), India (International).
• Satpathy, J. and Mallik, B. (2017). Mathematical Exposition on Eye Movements in Decision Dynamics, Proceedings of International Conference on Mathematical Sciences in Engineering Applications (ICMSEA - 2017), Dept. of Mathematics, Centurion, University, 22 - 24 Dec 2017, Vishakhapatnam, India (International).
• Satpathy, J. and Mallik, B. (2018). Hematological Judgement in Entrepreneurial Decision, Proceedings of International Conference on Management, Sciences, Engineering and Applications (ICMSEA - 2018), Dept. of Mathematics, Centurion University, Odisha; Kaziranga University, Assam and University of Perpetual Help, Philippines, 20 - 22 Dec 2018, Vishakhapatnam, India (International). Concurrently published in International Journal of Management, Technology and Engineering, ISSN No: 2249-7455, Volume 8, Issue XII, Pp: 2849 - 2863, December, India (International).
• Satpathy, J. and Mallik, B. (2018). Mathematical Exposition on Eye Movements in Decision Dynamics, Proceedings of International Conference on Mathematical Sciences in Engineering Applications (ICMSEA - 2017), Dept. of Mathematics, Centurion, University, 22 - 24 Dec 2017, Vishakhapatnam, India (International). Concurrently published in International Journal of Management, Technology and Engineering, ISSN No: 2249-7455, Volume 8, Issue XII, Pp: 3245 - 3254, December, India (International).
• Satpathy, J. and Mishra, B.P. (2017). Managerial Neuro - Hybrid Decision Architecture, Imperial Journal of Interdisciplinary Research (IJIR), Vol. 3, Issue 10, ISSN: 2454 - 1362, Pp: 245 - 292, UAE (International)
• Satpathy, J. and Mishra, B.P. (2017). Review on Neuromanagerial Decision Crescendos, Imperial Journal of Interdisciplinary Research (IJIR), Vol. 3, Issue 9, ISSN: 2454 - 1362, Pp: 65 - 115, UAE (International)
• Satpathy, J. and Mishra, S. (2014). Paradigm Tectonics in Neuro - Choice Making, 3rd International Conference on Managing Human Resources at the Workplace, 05 - 06 December, Mysore, India. (International)
• Satpathy, J. and Mishra,S. (2018). Cognitive Competence ‘Agent’ in Organisational Decisions, Proceedings of National Conference on Business Transformation Through Strategy And Innovation (BTTSI-2018), BIITM Institute, Biju Patnaik University of Technology, 11 July 2018, , Bhubaneswar (Odisha), India (National).
• Satpathy, J. and Patri, M. (2016). Cognitive Underpinning in Neuro - Managerial Decision Making (Poster), NeuroPsychoEconomics Conference, June 2-3, 2016, Bonn, Germany. (International)
• Satpathy, J. and Rajpurohit, J. S. (2018). Triguna Geometry in Effective Economic Behaviour, National Seminar on Relevance of Triguna Theory in Contemporary World, 03 - 04 Oct 2018, Indian Institute of Advanced Study, Shimla, India. (National).
• Satpathy, J. and Shukla, O.P. (2018). Neuroreductionist Approaches to Development (Case Study on Uttar Pradesh, Proceedings of International Seminar on Developmental Challenges of India after Twenty Five Years of Economic Reforms, 16 - 18 March, 2018, Department of Economics, Banaras Hindu University, Banaras, India (International).
• Satpathy, J. and Singh, S. (2017). Romancing Neurodecision Making, Imperial Journal of Interdisciplinary Research (IJIR), Vol. 3, Issue 4, ISSN: 1556-1583, Pp: 2171 - 2198, UAE]. (International).
• Satpathy, J. and Tiwari, P. (2014). Neuro Based Challenges in Techno - Managerial Training, National Conference on the Dynamics of Education to Employment Journey, Feb 21 - 22 2014, Pp: 26, KIIT University, Bhubaneswar, India. (National)
• Satpathy, J. et. al. (2017). Neuro - Organisational Decision Comportment, Proceedings of UGC - sponsored National Conference on ‘Future Employment Relations in India: Role of Stakeholders’, Dept. of Industrial Relations and Personnel Management, Berhampur University, 18 - 19 March 2017, Berhampur-760007, Odisha, India (National)
• Satpathy, J. Gankar, S.S. and Narendran, S. (2017). Neuro - Mechanisms in Decision Making by Farmer (Study in Poverty - Prone Rural Areas of North - East India), Proceedings of National Conference on Poverty and Rural Development in India with Special Reference to North Eastern Region, 16 - 17 Sep 2017, Department of Economics, Debraj Roy College, Golaghat, Assam, India (National)
• Satpathy, J., Das, A. and Das, S. (2016). Exposition on Eye Movements in Managerial Decision, Proceedings of UGC - Sponsored International Conference on Cross - Cultural Dimension of Management, Dept. of Business Administration, Berhampur University, 24 - 25 Nov 2016, India. (International)
• Satpathy, J., Das, A., Suneetha, N., Sturman, M. and Das, S. (2016). Crafting Neuro Economic - Managerial Decisions, International Journal of Trend in Research and Development, Volume 03(05), ISSN: 2394-9333, Pp: 469 - 478, India. [Concurrently published in FMU Journal of Management, Fakir Mohan University Balasore Journal No. IV, Issue I, Pp: 20 -32, India (National) and Imperial Journal of Interdisciplinary Research (IJIR), Vol. II, Issue 11, ISSN: 2454-1362, Pp: 2171 - 2198, UAE]. (International)]
• Satpathy, J., Hejmadi, A. and Padmaja, B. (2019), Oculo - Peep Into Decision Foundation, Proceedings of National Seminar on 'Human Dimension In Information Age', 21 - 22 Feb 2019, Acharya Nagarjuna University, Ongole, Andhra Pradesh, India (National).
• Satpathy, J., Hejmadi, A., Mishra, D. and Singh, S. (2018). Managerial Eyes for Business Decisions, FMU Journal of Management, Department of Business Management, Vol. 5 and 6, March 2018, Balasore, India (National).
• Satpathy, J., Mishra, S. and Mahapatra, B. B. (2014). Neuro - Perspectives in Sustainable Progression, Proceedings of UGC - Sponsored National Seminar on Management Practices and Sustainable Development, 23 - 24 March, F M University, Balasore, Odisha, India. (National)
• Satpathy, J., Mishra, S. and Rath, B. P. (2014). Explorations in Neuro - Decision Making, Odisha Journal of Social Science, Vol. I (1), Pp: 101 - 111, Odisha, India. (National)
• Satpathy, J., Mohapatra, B.B. and Sturman, M. (2015). Managerial Neuro - Choice Mechanism, International Journal on Research and Development: A Management Review (IJRDMR), Volume: 4 Issue: 1, ISSN (Print): 2321- 5747, Bhubaneswar, India. (International)
• Schütz A. C. Braun D. I. Gegenfurtner K. R. (2007). Contrast Sensitivity During The Initiation Of Smooth Pursuit Eye Movements. Vision Research, 47, 2767–2777.
• Schütz A. C. Braun D. I. Gegenfurtner K. R. (2009). Object Recognition During Foveating Eye Movements. Vision Research, 49, 2241–2253.
• Schütz A. C. Braun D. I. Kerzel D. Gegenfurtner K. R. (2008). Improved Visual Sensitivity During Smooth Pursuit Eye Movements. Nature Neuroscience, 11, 1211–1216.
• Schütz A. C. Braun D. I. Movshon J. A. Gegenfurtner K. R. (2010). Does The Noise Matter Effects Of Different Kinematogram Types On Smooth Pursuit Eye Movements And Perception. Journal Of Vision, 10, (13):26, 1–22.
• Schütz A. C. Delipetkos E. Braun D. I. Kerzel D. Gegenfurtner K. R. (2007). Temporal Contrast Sensitivity During Smooth Pursuit Eye Movements. Journal Of Vision, 7, (13):3, 1–15.
• Schütz A. C. Gegenfurtner K. R. (2010). Dynamic Integration Of Saliency And Reward Information For Saccadic Eye Movements. Journal Of Vision, 10, (7):551, 551.
• Schütz A. C. Morrone M. C. (2010). Compression Of Time During Smooth Pursuit Eye Movements. Vision Research, 50, 2702–2713.
• Sela, A. And Shiv, B. (2009), ‘Unraveling Priming: When Does The Same Prime Activate A Goal Versus A Trait?’ Journal Of Consumer Research, Vol. 36 (October), 418-43328.
• Shiv, B. And Fedorikhin, A. (1999), ‘Heart And Mind In Conflict: Interplay Of Affect And Cognition In Consumer Decision Making,’ Journal Of Consumer Research, 26 (December), 278-282.
• Shiv, B. And Fedorikhin, A. (2002), ‘Spontaneous Versus Controlled Influences Of Stimulus-Based Affect On Choice Behavior,’ Organizational Behavior And Human Decision Processes, 87 (March), 342-370.
• Shiv, B. And J. Huber (2000), ‘The Impact Of Anticipating Satisfaction On Choice,’ Journal Of Consumer Research, 27 (September), 202-216.
• Shiv, B. Et Al. (2005), ‘Decision Neuroscience,’ Marketing Letters, Vol. 16 (3/4), 375- 386.
• Shiv, B., ‘Emotions, Decisions And The Brain (2007),’ Journal Of Consumer Psychology, Vol. 17 (3), 174-178.
• Shiv, B., Loewenstein, G., And Bechara, A. (2005), ‘The Dark Side Of Emotion In Decision-Making: When Individuals With Decreased Emotional Reactions Make More Advantageous Decisions,’ Cognitive Brain Research, 23 (April), 85-92.
• Shiv, B., Loewenstein, G., Bechara, A., Damasio, H., And Damasio, A. (2005), ‘Investment Behavior And The Negative Side Of Emotion,’ Psychological Science, 16 (June), 435-439.
• Steinman, R.M., Kowler, E. And Collewijn, H. (1990). New Directions For Oculomotor Research. Vision Research, 30, 1845-1864.
• Tiwari, P., Satpathy, J. and Mishra, S. (2014). Cognitive ‘Paths’ in Techno - Managerial Continuum: Some Human Resource Perspectives, Proceedings of UGC - Sponsored National Seminar on Management Practices and Sustainable Development, 23 - 24 March, F M University, Balasore, Odisha, India. (National)
• Tsai, C. C. And Yang, F. Y. (2011). Editorial: Research About Science Learning In Asian Countries. The Asia-Pacific Education Reearch, 20, 201-206.。
• Tversky, A. (1972). Elimination By Aspects: A Theory Of Choice. Psychological Review, 79,281-299.
• Tversky, A., And Kahneman, D. (1973). Availability: A Heuristic For Judging Frequency And Probability. Cognitive Psychology, 5, 207-232.
• Tversky, A., And Kahneman, D. (1974, September 27). Judgment Under Uncertainty: Heuristics And Biases. Science, 185, 1124–1131.
• Tymula, A. Et Al. (2013). Like Cognitive Function, Decision Making Across The Life Span Shows Profound Age - Related Changes. Proceedings Of The National Academy Of Sciences Of The United States Of America, 110(42), 17143 - 17148.
• Tymula, A. Et Al. (2014). Neuroanatomy Predicts Individual Risk Attitudes. Journal Of Neuroscience, 34(37), 12394 - 12401.
• Tymula, A. Et Al. (2016). Context - Dependency In Valuation. Current Opinion In Neurobiology, 40, 59 - 65.
• Tymula, A. Et Al. (2016). Neuroanatomy Accounts For Age - Related Changes In Risk Preferences. Nature Communications, 7, 1 - 5.
• Tymula, A. Et Al. (2017). Let The Sunshine In? The Effects Of Luminance On Economic Preferences, Choice Consistency And Dominance Violations. Plos One, 12(8), 1 - 26.
• Tymula, A. Et Al. (2017). The Reduction Of Ventrolateral Prefrontal Cortex Grey Matter Volume Correlates With Loss Of Economic Rationality In Aging. Journal Of Neuroscience, 37(49), 12068 - 12077.
• Tymula, A. Et Al. (2018). Free Choice Shapes Normalized Value Signals In Medial Orbitofrontal Cortex. Nature Communications, 9(1), 1 - 11.
• Tymula, A. Et Al. (2019). An Experimental Comparison Of Risky And Riskless Choice - Limitations Of Prospect Theory And Expected Utility Theory. American Economic Journal: Microeconomics, Forthcoming (2019).
• V.S.C. Pammi, K.P. Miyapuram, Ahmed, K. Samejima, R.S. Bapi, K. Doya. (2012). Changing The Structure Of Complex Visuo-Motor Sequences Selectively Activates The Fronto-Parietal Network. Neuroimage 59(2):1180-1189. { = Equal Contribution}
• Viraj Mavani, Shanmuganathan Raman, Krishna P. Miyapuram:Facial Expression Recognition Using Visual Saliency And Deep Learning. Iccv Workshops 2017: 2783-2788
• Vishwanath, D. And Kowler, E. (2003) Localization Of Shapes: Eye Movements And Perception Compared. Vision Research, 43, 1637-1653.
• Vishwanath, D. And Kowler, E. (2004) Saccadic Localization In The Presence Of Cues To Three-Dimensional Shape. Journal Of Vision, 4, 445-458.
• Vishwanath, D., Kowler, E. And Feldman, J. (2000) Saccadic Localization Of Occluded Targets. Vision Research, 40, 2797-2811.
• Weller J. A., Levin, I., Shiv, B. And Bechara A. (2007), ‘Neural Basis Of Adaptive Decision Making In Risky Gains And Losses,’ Psychological Science, Vol. 18 (11), 958- 964.
• Weller, J., Levin, I., Shiv, B. And Bechara A. (2009), ‘The Effects Of Insula Damage On Decision Making For Risky Gains And Losses, Social Neuroscience, Vol. 4 (August), 347- 358.
• Yang, F. Y. (2017). Examining The Reasoning Of Conflicting Science Information From The Information Processing Perspective – An Eye Movement Analysis. Journal Of Research In Science Teaching, 10, 1347-1372.
• Yang, F. Y. (2004). Exploring High School Students’ Use Of Theory And Evidence In A Life Context: The Role Of Scientific Thinking In Environmental Science Decision-Making. International Journal Of Science Education, 26, 1345-1364.。
• Yang, F. Y. (2005). Student Views Concerning Evidence And The Expert In Reasoning A Socio-Scientific Issue And Personal Epistemology. Educational Studies, 31, 65-84。
• Yang, F. Y. (2017). Examining The Reasoning Of Conflicting Science Information From The Information Processing Perspective – An Eye Movement Analysis. Journal Of Research In Science Teaching. Published Online.
• Yang, F. Y. (2017). Instructional Suggestions Supporting Science Learning In Digital Environments Based On A Review Of Eye Tracking Studies Journal Of Educational Technology And Society，2(2)。
• Yang, F. Y. And Anderson, O. R. (2003). Senior High School Students' Preference And Reasoning Modes About Nuclear Energy Use. International Journal Of Science Education, 25, 221-244。
• Yang, F. Y. And Chang, C. C. (2009). Examining High-School Students' Preferences Toward Learning Environments, Personal Beliefs And Concept Learning In Web-Based Contexts. Computers And Education, 52, 848-857.。
• Yang, F. Y. And Tsai, C. C. (2008). Investigating Learner Preferences And Beliefs About Learning N The Web-Based Context. Computers And Education, 50, 1284-1303
• Yang, F. Y. And Tsai, C. C. (2010). Reasoning On The Science-Related Uncertain Issues And Epistemological Perspectives Among Children. Instructional Science, 4, 325-3254.
• Yang, F. -Y., Chang, C. C., Chen, L. L., And Chen, Y. C. (2016). Exploring Learners’ Beliefs About Science Reading And Scientific Epistemic Beliefs, And Their Relations With Science Text Understanding. International Journal Of Science Education, 39(10), 1591-1606.
• Yang, F. Y., Chang, C. Y., And Hsu, Y. S. (2008). Teacher Views About The Constructivist Instruction And Personal Epistemology – A National Study In Taiwan. Educational Studies, 34, 527-542.。
• Yang, F. Y., Chang, C. Y., Jien, W. R., Jien, Y. T. Tseng, Y. H. (2013). Tracking Learners’ Visual Attention During A Multimedia Presentation In A Real Classroom. Computers And Education, 62, 208-220. (Ssci)
• Yang, F. Y., Chang, C. Y., Jien, W. R., Jien, Y. T. Tseng, Y. H. (2013). Tracking Learners’ Visual Attention During A Multimedia Presentation In A Real Classroom. Computers And Education, 62, 208-220.。
• Yang, F. Y., Huang, R. T., Tsai, I. J. (2016). The Effects Of Epistemic Beliefs In Science And Gender Difference On University Students' Science-Text Reading: An Eye-Tracking Study. International Journal Of Science And Mathematics Education, 14, 473-498. (Ssci)
• Yang, F. Y., Tsai, M. L., Chiou, G. L., Lee, S. W. Y., Chang, C. C., And Chen, L. L. (2018). Instructional Suggestions Supporting Science Learning In Digital Environments Based On A Review Of Eye Tracking Studies. Educational Technology And Society, 21 (2), 28-45.
• Yang, F. Y., Tsai, M. L., Chiou, G. L., Lee, S. W. Y., Chang, C. C., And Chen, L. L. (Accepted). Instructional Suggestions Supporting Science Learning In Digital Environments Based On A Review Of Eye Tracking Studies. Educational Technology And Society。
• Yang, F. Y., Tseng, J. S. And Lin, M. H. (2012). The Interaction Between Junior-High Students’ Academic And Social Motivations And The Influences Of The Motivational Factors On Science Performance. The Asia-Pacific Educational Researcher, 21, 92-106。Tsai, M. J., Hou, H. T., Lai, M. L., Liu, W. Y. And Yang, F. Y. (2011). Visual Attention For Solving Multiple-Choice Science Problem: An Eye-Tracking Analysis. Computers And Education, 58, 375-385.。
• Yang, F.-Y., Chen, Y. H., Tsai, M.-J. (2013) How University Students Evaluate Online Information About A Socio-Scientific Issue And The Relationship With Their Epistemic Beliefs.. Educational Technology And Society, 16(3), 385-399. (Ssci).
• Yang, F.-Y., Chen, Y. H., Tsai, M.-J. (2013) How University Students Evaluate Online Information About A Socio-Scientific Issue And The Relationship With Their Epistemic Beliefs.. Educational Technology And Society, 16(3), 385-399.。
• Yang, F.Y., Liu, Ｓ.-Y., Hsu, C.-Y., Chiou, G.-L., Wu, H.-K., Wu, Y.-T., Chen, S.-F., Liang, J.-C., Tsai, M.-J., Lee, S. W.-Y., Lee, M.-H., Lin, C.-L., Chu, R.-J., Tsai, C.-C. (In Press). High School Students’ Epistemic Knowledge Of Science And Its Relation To Learner Factors In Science Learning. Research In Science Education.
• Yechiam, E., And Hochman G. (2013). ‘Losses As Modulators Of Attention: Review And Analysis Of The Unique Effects Of Losses Over Gains’. Psychological Bulletin, 139, 497-518.
• Yechiam, E., And Hochman G. (2013). Losses As Modulators Of Attention: Review And Analysis Of The Unique Effects Of Losses Over Gains. Psychological Bulletin, 139, 497-518.
• Yechiam, E., And Hochman, G. (2013). Loss-Aversion Or Loss-Attention: The Impact Of Losses On Cognitive Performance. Cognitive Psychology, 66, 212-231.
• Yechiam, E., And Hochman, G. (2014). ‘Loss Attention In A Dual Task Setting’. Psychological Science, 25, 494-502.
• Yechiam, E., And Hochman, G. (2014). Loss Attention In A Dual Task Setting. Psychological Science, 25, 494-502.
• Yechiam, E., Ashby, N. J. S., And Hochman, G. (In Press). Are We Attracted By Losses? Boundary Conditions For The Approach And Avoidance Effects Of Losses. Journal Of Experimental Psychology: Learning, Memory, And Cognition. Book Chapters:
• Yechiam, E., Retzer, M., Telpaz, A., And Hochman, G. (2015). ‘Losses As Ecological Guides: Minor Losses Lead To Maximization And Not To Avoidance’. Cognition, 139, 10-17.
• Yechiam, E., Retzer, M., Telpaz, A., And Hochman, G. (2015). Losses As Ecological Guides: Minor Losses Lead To Maximization And Not To Avoidance. Cognition, 139, 10-17.
• Yechiam, E., Telpaz, A., And Hochman, G. (2014). “Loss Aversion As Response Distortion: The Complaint Bias”. Decision, 1, 147-160. Guy Hochman Curriculum Vitae – March 2018
• Zingale, C. And Kowler, E. (1987). Planning Sequences Of Saccades. Vision Research, 27, 1327-1341.