scholarly journals From Retrospective to Prospective: Integrated Value Representation in Frontal Cortex for Predictive Choice Behavior

2021 ◽  
Author(s):  
Kosuke Hamaguchi ◽  
Hiromi Takahashi-Aoki ◽  
Dai Watanabe
Keyword(s):  
Decision Making ◽  
Frontal Cortex ◽  
Choice Behavior ◽  
State Transition ◽  
Neural Circuit ◽  
The Past ◽  
Preparatory Activity ◽  
Action Value ◽  
The Brain ◽  
Different Sources

Animals must flexibly estimate the value of their actions to successfully adapt in a changing environment. The brain is thought to estimate action-value from two different sources, namely the action-outcome history (retrospective value) and the knowledge of the environment (prospective value). How these two different estimates of action-value are reconciled to make a choice is not well understood. Here we show that as a mouse learns the state-transition structure of a decision-making task, retrospective and prospective values become jointly encoded in the preparatory activity of neurons in the frontal cortex. Suppressing this preparatory activity in expert mice returned their behavior to a naive state. These results reveal the neural circuit that integrates knowledge about the past and future to support predictive decision-making.

Decision making: How the past guides the future in frontal cortex

2021 ◽  
Vol 31 (6) ◽  
pp. R303-R306
Author(s):  
Bharath Chandra Talluri ◽  
Anke Braun ◽  
T.H. Donner
Keyword(s):  
Decision Making ◽  
Frontal Cortex ◽  
The Past ◽  
The Future

scholarly journals Psychopathic individuals exhibit but do not avoid regret during counterfactual decision making

2016 ◽  
Vol 113 (50) ◽  
pp. 14438-14443 ◽  
Author(s):  
Arielle Baskin-Sommers ◽  
Allison M. Stuppy-Sullivan ◽  
Joshua W. Buckholtz
Keyword(s):  
Decision Making ◽  
Antisocial Behavior ◽  
Choice Behavior ◽  
Cost Benefit ◽  
Explanatory Models ◽  
Affective Deficits ◽  
Action Value ◽  
Stimulus Value ◽  
Incarceration History ◽  
The Relationship

Psychopathy is associated with persistent antisocial behavior and a striking lack of regret for the consequences of that behavior. Although explanatory models for psychopathy have largely focused on deficits in affective responsiveness, recent work indicates that aberrant value-based decision making may also play a role. On that basis, some have suggested that psychopathic individuals may be unable to effectively use prospective simulations to update action value estimates during cost–benefit decision making. However, the specific mechanisms linking valuation, affective deficits, and maladaptive decision making in psychopathy remain unclear. Using a counterfactual decision-making paradigm, we found that individuals who scored high on a measure of psychopathy were as or more likely than individuals low on psychopathy to report negative affect in response to regret-inducing counterfactual outcomes. However, despite exhibiting intact affective regret sensitivity, they did not use prospective regret signals to guide choice behavior. In turn, diminished behavioral regret sensitivity predicted a higher number of prior incarcerations, and moderated the relationship between psychopathy and incarceration history. These findings raise the possibility that maladaptive decision making in psychopathic individuals is not a consequence of their inability to generate or experience negative emotions. Rather, antisocial behavior in psychopathy may be driven by a deficit in the generation of forward models that integrate information about rules, costs, and goals with stimulus value representations to promote adaptive behavior.

Dynamical Foundations of the Neural Circuit for Bayesian Decision Making

2009 ◽  
Vol 102 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Kenji Morita
Keyword(s):  
Decision Making ◽  
Bayesian Inference ◽  
Neural Circuits ◽  
Neural Circuit ◽  
Bayesian Decision ◽  
Biophysical Modeling ◽  
Perceptual Decision Making ◽  
Basic Ideas ◽  
Bayesian Decision Making ◽  
The Brain

On the basis of accumulating behavioral and neural evidences, it has recently been proposed that the brain neural circuits of humans and animals are equipped with several specific properties, which ensure that perceptual decision making implemented by the circuits can be nearly optimal in terms of Bayesian inference. Here, I introduce the basic ideas of such a proposal and discuss its implications from the standpoint of biophysical modeling developed in the framework of dynamical systems.

scholarly journals INTRODUCTION TO THE SPECIAL ISSUE OF ECONOMICS AND PHILOSOPHY ON NEUROECONOMICS

2008 ◽  
Vol 24 (3) ◽  
pp. 301-302 ◽  
Author(s):  
Giacomo Bonanno ◽  
Christian List ◽  
Bertil Tungodden ◽  
Peter Vallentyne
Keyword(s):  
Decision Making ◽  
Imaging Techniques ◽  
Brain Activity ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Special Issue ◽  
Individual Decision ◽  
The Past ◽  
Economic Choices ◽  
The Brain

The past fifteen years or so have witnessed considerable progress in our understanding of how the human brain works. One of the objectives of the fast-growing field of neuroscience is to deepen our knowledge of how the brain perceives and interacts with the external world. Advances in this direction have been made possible by progress in brain imaging techniques and by clinical data obtained from patients with localized brain lesions. A relatively new field within neuroscience is neuroeconomics, which focuses on individual decision making and aims to systematically classify and map the brain activity that correlates with decision-making that pertains to economic choices. Neuroeconomic studies rely heavily on functional magnetic resonance imaging (fMRI), which measures the haemodynamic response (that is, changes in the blood flow) related to neural activity in the brain.

scholarly journals The contribution of striatal pseudo-reward prediction errors to value-based decision-making

2017 ◽  
Author(s):  
Ernest Mas-Herrero ◽  
Guillaume Sescousse ◽  
Roshan Cools ◽  
Josep Marco-Pallarés
Keyword(s):  
Decision Making ◽  
Choice Behavior ◽  
Prediction Errors ◽  
Life Outcomes ◽  
Stimulus Response ◽  
Hierarchical Reinforcement Learning ◽  
Reward Prediction ◽  
Fmri Study ◽  
Reward Contingencies ◽  
The Brain

AbstractMost studies that have investigated the brain mechanisms underlying learning have focused on the ability to learn simple stimulus-response associations. However, in everyday life, outcomes are often obtained through complex behavioral patterns involving a series of actions. In such scenarios, parallel learning systems are important to reduce the complexity of the learning problem, as proposed in the framework of hierarchical reinforcement learning (HRL). One of the key features of HRL is the computation of pseudo-reward prediction errors (PRPEs) which allow the reinforcement of actions that led to a sub-goal before the final goal itself is achieved. Here we wanted to test the hypothesis that, despite not carrying any rewarding value per se, pseudo-rewards might generate a bias in choice behavior when reward contingencies are not well-known or uncertain. Second, we also hypothesized that this bias might be related to the strength of PRPE striatal representations. In order to test these ideas, we developed a novel decision-making paradigm to assess reward prediction errors (RPEs) and PRPEs in two studies (fMRI study: n = 20; behavioural study: n = 19). Our results show that overall participants developed a preference for the most pseudo-rewarding option throughout the task, even though it did not lead to more monetary rewards. fMRI analyses revealed that this preference was predicted by individual differences in the relative striatal sensitivity to PRPEs vs RPEs. Together, our results indicate that pseudo-rewards generate learning signals in the striatum and subsequently bias choice behavior despite their lack of association with actual reward.

Neuromarketing and Improved Understanding of Consumer Behaviour Through Brain-Based Neuro Activity

2021 ◽  
pp. 2150020
Author(s):  
Sami Alsmadi ◽  
Khaled Hailat
Keyword(s):  
Consumer Choice ◽  
Consumer Behaviour ◽  
Multidisciplinary Approach ◽  
Neural Circuit ◽  
Ethical Issues ◽  
Basic Knowledge ◽  
The Past ◽  
Marketing Activities ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain

Over the past three decades, there has been a growing interest in studying consumer behaviour directly through non-traditional, brain-based, approach using the basic knowledge of human neuroscience. This multidisciplinary approach has evolved into a new marketing branch, known as Neuromarketing, which goes inside the human brain to improve our knowledge of consumer behaviour. Neuromarketing traces neural circuit activities inside the brain using Magnetic Resonance Imaging (MRI) technology. This paper explores the existing literature on Neuromarketing to provide insights into the potential for improving our understanding of consumer behaviour. The paper concludes that Neuromarketing can offer a valuable opportunity to increase precision and validity of measuring consumer reactions to marketing activities, thus improve marketing knowledge of consumer choice behaviour. The paper also addresses the main ethical issues raised by critiques on the unprecedented access to consumers’ mind, and how advocates looked at such criticisms.

scholarly journals Quantifying the Landscape of Decision Making From Spiking Neural Networks

2021 ◽  
Vol 15 ◽  
Author(s):  
Leijun Ye ◽  
Chunhe Li
Keyword(s):  
Decision Making ◽  
Visual Motion ◽  
Neural Circuit ◽  
First Passage Time ◽  
Passage Time ◽  
State Transitions ◽  
Perceptual Decision Making ◽  
Transition Mechanism ◽  
Decision Making System ◽  
The Brain

The decision making function is governed by the complex coupled neural circuit in the brain. The underlying energy landscape provides a global picture for the dynamics of the neural decision making system and has been described extensively in the literature, but often as illustrations. In this work, we explicitly quantified the landscape for perceptual decision making based on biophysically-realistic cortical network with spiking neurons to mimic a two-alternative visual motion discrimination task. Under certain parameter regions, the underlying landscape displays bistable or tristable attractor states, which quantify the transition dynamics between different decision states. We identified two intermediate states: the spontaneous state which increases the plasticity and robustness of changes of minds and the “double-up” state which facilitates the state transitions. The irreversibility of the bistable and tristable switches due to the probabilistic curl flux demonstrates the inherent non-equilibrium characteristics of the neural decision system. The results of global stability of decision-making quantified by barrier height inferred from landscape topography and mean first passage time are in line with experimental observations. These results advance our understanding of the stochastic and dynamical transition mechanism of decision-making function, and the landscape and kinetic path approach can be applied to other cognitive function related problems (such as working memory) in brain networks.

Truth Matters: Cognitive Integrity as an Intervention for Self-Deception

2017 ◽  
Author(s):  
Eugenia Isabel Gorlin ◽  
Michael W. Otto
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Autonomous Agents ◽  
Therapeutic Interventions ◽  
Empirical Validation ◽  
The Past ◽  
Adaptive Problem

To live well in the present, we take direction from the past. Yet, individuals may engage in a variety of behaviors that distort their past and current circumstances, reducing the likelihood of adaptive problem solving and decision making. In this article, we attend to self-deception as one such class of behaviors. Drawing upon research showing both the maladaptive consequences and self-perpetuating nature of self-deception, we propose that self-deception is an understudied risk and maintaining factor for psychopathology, and we introduce a “cognitive-integrity”-based approach that may hold promise for increasing the reach and effectiveness of our existing therapeutic interventions. Pending empirical validation of this theoretically-informed approach, we posit that patients may become more informed and autonomous agents in their own therapeutic growth by becoming more honest with themselves.

Neuro-Clinical Signatures of Language Impairments: A Theoretical Framework for Function-to-structure Mapping in Clinics

2020 ◽  
Vol 20 (9) ◽  
pp. 800-811 ◽  
Author(s):  
Ferath Kherif ◽  
Sandrine Muller
Keyword(s):  
Brain Mapping ◽  
Theoretical Framework ◽  
Brain Regions ◽  
Language Impairments ◽  
Structure Mapping ◽  
Language Functions ◽  
The Past ◽  
Language Recovery ◽  
The Brain ◽  
Bow Tie

In the past decades, neuroscientists and clinicians have collected a considerable amount of data and drastically increased our knowledge about the mapping of language in the brain. The emerging picture from the accumulated knowledge is that there are complex and combinatorial relationships between language functions and anatomical brain regions. Understanding the underlying principles of this complex mapping is of paramount importance for the identification of the brain signature of language and Neuro-Clinical signatures that explain language impairments and predict language recovery after stroke. We review recent attempts to addresses this question of language-brain mapping. We introduce the different concepts of mapping (from diffeomorphic one-to-one mapping to many-to-many mapping). We build those different forms of mapping to derive a theoretical framework where the current principles of brain architectures including redundancy, degeneracy, pluri-potentiality and bow-tie network are described.

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