Decision Making: Neural and Behavioural Approaches

Decision Making: Neural and Behavioural Approaches

1st Edition - January 10, 2013

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  • Editors: V. S. Chandrasekhar Pammi, Narayanan Srinivasan
  • eBook ISBN: 9780444626073
  • Hardcover ISBN: 9780444626042

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This well-established international series examines major areas of basic and clinical research within neuroscience, as well as emerging and promising subfields.This volume explores interdisciplinary research on decision making taking a neural and behavioural approach

Key Features

  • Leading authors review the state-of-the-art in their field of investigation, and provide their views and perspectives for future research
  • Chapters are extensively referenced to provide readers with a comprehensive list of resources on the topics covered
  • All chapters include comprehensive background information and are written in a clear form that is also accessible to the non-specialist


Neuroscientists, psychologists, neurologists

Table of Contents

  • Advisory Editors




    Chapter 1. Surprise

    1 Shifting reference points

    2 Loss aversion

    3 Errors in beliefs

    4 Cross-cultural differences in surprise

    5 Conclusion


    Chapter 2. The impact of affect on willingness-to-pay and desired-set-size

    1 Affect and economic decisions: Background

    2 Affect and economic decisions: New experiment

    3 Discussion: Affect and rationality


    Chapter 3. Role of affect in decision making

    1 Introduction

    2 Affect in decision making

    3 Theoretical frameworks

    4 Incidental emotions and decision making

    5 Method

    6 Results

    7 Discussion

    8 Concluding remarks


    Further Reading

    Chapter 4. Mind the gap? Description, experience, and the continuum of uncertainty in risky choice

    1 What is the description–experience choice “gap”?

    2 What are the causes of the description–experience choice “gap”?

    3 Where do we go from here?


    Chapter 5. The boundaries of instance-based learning theory for explaining decisions from experience

    1 The boundaries of instance-based learning theory to explaining decisions from experience

    2 Instance-based learning theory

    3 IBLT and IBL models

    4 The IBL model of repeated risky choice

    5 What the IBL model explains and what it does not explain

    6 What the IBL model explains

    7 The payoff variability, underweighting of rare events, and loss rate effects

    8 What the IBL model does not explain

    9 Conclusions


    Chapter 6. The experience–description gap and the role of the inter decision interval

    1 Under-representation, mere presentation, dynamic beliefs, and estimated risk

    2 The role of the inter decision interval

    3 Discussion


    Chapter 7. Attention in preferential choice

    1 Introduction

    2 Preferential choice and revealed preference

    3 Attention: A key variable in decision making

    4 Role of attention in information selection

    5 The effect of attentional scope on preferential choices

    6 Conclusions


    Chapter 8. Spoken language and the decision to move the eyes: To what extent are language-mediated eye movements automatic?

    1 Introduction

    2 Automaticity

    3 Concluding remarks


    Chapter 9. The influence of probability format on elicited certainty equivalents

    1 Introduction

    2 The experiment

    3 Results

    4 Conclusion


    Chapter 10. On the evaluation of cultural and environmental public goods, and its implications for social innovation

    1 Introduction

    2 Factors that are economically relevant but psychologically irrelevant

    3 Factors that are economically irrelevant but psychologically relevant

    4 Public policy and decision sciences

    5 Conclusions


    Chapter 11. The effect of analytic and experiential modes of thought on moral judgment

    1 Introduction

    2 Methods

    3 Results

    4 Discussion


    Chapter 12. Understanding consumer decisions using behavioral economics

    1 Introduction

    2 Intertemporal choice and delayed gratification

    3 Cognitive modulation of immediate rewards

    4 Boosting delayed rewards

    5 Experiment into boosting delayed rewards

    6 Conclusions and future directions


    Chapter 13. Contextual and social influences on valuation and choice

    1 Introduction: The importance of context

    2 Context changes valuation

    3 Social context

    4 Conclusion


    Chapter 14. Understanding decision neuroscience: A multidisciplinary perspective and neural substrates

    1 Introduction

    2 Multidisciplinary approaches in decision making research

    3 Psychological theories of decision making

    4 Economic theories of decision making

    5 The anatomy of decision making: A building blocks approach

    6 Neural substrates of building blocks of decision making and top-down influences

    7 Conclusions and directions for future research


    Chapter 15. Why bother with the brain? A role for decision neuroscience in understanding strategic variability

    1 Introduction

    2 Neural correlates of strategic control

    3 Using decision neuroscience to inform models of cognitive neuroscience: The case of cognitive control

    4 Effects of SD on decision preferences

    5 Conclusions


    Chapter 16. Neural coding of computational factors affecting decision making

    1 Basic computations involved in decision making

    2 Monkey Electrophysiology: Midbrain dopaminergic neurons and the computation of subjective value, uncertainty, and prediction error

    3 Computation of uncertainty signals in the human brain

    4 Separate valuation systems for making decisions related to delay and effort costs

    5 A common neural currency in the human brain?

    6 One or several reward systems? Specific orbitofrontal regions code experienced value for primary and secondary rewards

    7 From perceptual decision making to value-based decision making

    8 Variation in dopamine genes influence reward processing

    9 Conclusions


    Chapter 17. Brain mechanisms controlling decision making and motor planning

    1 Introduction

    2 Evidence for accumulator models

    3 Extending accumulator models to account for saccade plan modification

    4 Conclusion


    Chapter 18. Development of cognitive and affective control networks and decision making

    1 Introduction

    2 Cognitive control and decision making

    3 Conflict monitoring, conflict adaptation, and decision making

    4 Dissociation between cognitive and affective control networks

    5 Role of cognitive and affective control networks in decision making

    6 Development of cognitive and affective control networks

    7 Study 1

    8 Experiment 1: ANT as a measure of perceptual decision process involved in conflict resolution

    9 Experiment 2: ANT with emotional facial expressions

    10 Study 2

    11 Effect of the development of cognitive and affective control on decision making

    12 Concluding remarks and directions for future research


    Chapter 19. An attentional theory of emotional influences on risky decisions

    1 Introduction: Overweighting of small probabilities

    2 Influences of affect

    3 Current and future theoretical work

    4 Current and future experimental work

    5 General discussion


    Further Reading

    Chapter 20. A model of the neural substrates for exploratory dynamics in basal ganglia

    1 Introduction

    2 A BG model that exhibits Go/Explore/NoGo regimes

    3 The three-regime model of BG applied to Parkinsonian reaching movements

    4 Modeling the role of BG in willed action

    5 Discussion


    Chapter 21. The effect of novelty on reinforcement learning


    1 Introduction

    2 Methods

    3 Computational models of reinforcement learning

    4 Results

    5 Discussion


    Chapter 22. Medial prefrontal cortex and the adaptive regulation of reinforcement learning parameters

    1 Introduction

    2 The MPFC as a regulator of decision making

    3 Computational principles of metalearning

    4 Methods: Computational model

    5 Results (I): Deterministic task

    6 Results (II): Probabilistic task

    7 Results (III): Human–robot interaction game

    8 Conclusions


    Chapter 23. Relativized hierarchical decomposition of Markov decision processes

    1 Introduction

    2 Background

    3 MDP homomorphisms

    4 Abstraction in hierarchical systems

    5 Illustrative example

    6 Modeling selective attention and schemas

    7 Conclusion




Product details

  • No. of pages: 536
  • Language: English
  • Copyright: © Elsevier 2013
  • Published: January 10, 2013
  • Imprint: Elsevier
  • eBook ISBN: 9780444626073
  • Hardcover ISBN: 9780444626042

About the Serial Volume Editors

V. S. Chandrasekhar Pammi

Narayanan Srinivasan

Narayanan Srinivasan, Ph.D., is currently Professor and Head at the Centre of Behavioural and Cognitive Sciences (CBCS), University of Allahabad. Dr. Srinivasan was a visiting scientist at the Riken Brain Science Institute from 2006-2012. He has a Master degree in Electrical Engineering from Indian Institute of Science and PhD in Psychology from University of Georgia. He worked as a postdoctoral fellow at the University of Louisville. He also worked at the Nanyang Technological University in Singapore for two years before joining one of the first centres for Cognitive Science in India. He has been working at CBCS for the past fourteen years. He is interested in understanding mental processes, especially attention, emotions, consciousness and meditation using multiple methodologies. Dr. Srinivasan has edited seven books and three special issues. He has more than hundred and forty publications. Dr. Srinivasan is a fellow of Association for Psychological Science. He was the Editor-in-chief of International Journal of Mind, Brain, and Cognition. He is currently an associate editor of Neuroscience of Consciousness, Royal Society Open Science, Frontiers in Cognitive Science, PsyCh journal, and Cognitive Processing and a member of the editorial board of Connection Science and Journal of Cultural Cognitive Science.

Affiliations and Expertise

Professor and Head, Centre of Behavioural and Cognitive Sciences, University of Allahabad, India

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