scholarly journals Foraging optimally in social neuroscience: computations and methodological considerations

2020 ◽  
Author(s):  
Anthony S Gabay ◽  
Matthew A J Apps
Keyword(s):  
Optimal Solution ◽  
Social Neuroscience ◽  
Neural Mechanisms ◽  
Marginal Value Theorem ◽  
Marginal Value ◽  
Methodological Considerations ◽  
Influential Theory ◽  
A Current ◽  
Neuroimaging Techniques ◽  
Foraging Decision

Abstract Research in social neuroscience has increasingly begun to use the tools of computational neuroscience to better understand behaviour. Such approaches have proven fruitful for probing underlying neural mechanisms. However, little attention has been paid to how the structure of experimental tasks relates to real-world decisions, and the problems that brains have evolved to solve. To go significantly beyond current understanding, we must begin to use paradigms and mathematical models from behavioural ecology, which offer insights into the decisions animals must make successfully in order to survive. One highly influential theory—marginal value theorem (MVT)—precisely characterises and provides an optimal solution to a vital foraging decision that most species must make: the patch-leaving problem. Animals must decide when to leave collecting rewards in a current patch (location) and travel somewhere else. We propose that many questions posed in social neuroscience can be approached as patch-leaving problems. A richer understanding of the neural mechanisms underlying social behaviour will be obtained by using MVT. In this ‘tools of the trade’ article, we outline the patch-leaving problem, the computations of MVT and discuss the application to social neuroscience. Furthermore, we consider the practical challenges and offer solutions for designing paradigms probing patch leaving, both behaviourally and when using neuroimaging techniques.

scholarly journals Foraging Optimally in Social Neuroscience: Computations and Methodological considerations

2019 ◽  
Author(s):  
Anthony Gabay ◽  
Matthew A J Apps
Keyword(s):  
Optimal Solution ◽  
Social Neuroscience ◽  
Neural Mechanisms ◽  
Marginal Value Theorem ◽  
Marginal Value ◽  
Methodological Considerations ◽  
Influential Theory ◽  
A Current ◽  
Neuroimaging Techniques ◽  
Foraging Decision

Research in social neuroscience has increasingly begun to use the tools of computational neuroscience to better understand behaviour. Such approaches have proven fruitful for probing underlying neural mechanisms. However, little attention has been paid to how the structure of experimental tasks relates to real-world decisions, and the problems that brains have evolved to solve. To go significantly beyond current understanding, we must begin to use paradigms and mathematical models from behavioural ecology, which offer insights into the decisions animals must make successfully in order to survive. One highly influential theory – Marginal Value Theorem (MVT) – precisely characterises and provides an optimal solution to a vital foraging decision that most species must make: the patch leaving problem. Animals must decide when to leave collecting rewards in a current patch (location) and travel somewhere else. We propose that many questions posed in social neuroscience can be approached as patch-leaving problems. A richer understanding of the neural mechanisms underlying social behaviour will be obtained by using MVT. In this ‘tools of the trade’ article, we outline the patch-leaving problem, the computations of MVT, and discuss is application to social neuroscience. Furthermore, we consider practical challenges and offer solutions for designing paradigms probing patch-leaving, both behaviourally and when using neuroimaging techniques.

scholarly journals Functional neuroimaging studies of the effects of psychotherapy

2014 ◽  
Vol 16 (1) ◽  
pp. 75-81 ◽  
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Behavioral Changes ◽  
Neural Mechanisms ◽  
Psychological Interventions ◽  
Emotional States ◽  
Major Depressive ◽  
Psychotherapeutic Interventions ◽  
Functional Brain Activity ◽  
Neuroimaging Techniques

It has been long established that psychological interventions can markedly alter patients' thinking patterns, beliefs, attitudes, emotional states, and behaviors. Little was known about the neural mechanisms mediating such alterations before the advent of functional neuroimaging techniques. Since the turn of the new millenium, several functional neuroimaging studies have been conducted to tackle this important issue. Some of these studies have explored the neural impact of various forms of psychotherapy in individuals with major depressive disorder. Other neuroimaging studies have investigated the effects of psychological interventions for anxiety disorders. I review these studies in the present article, and discuss the putative neural mechanisms of change in psychotherapy. The findings of these studies suggest that mental and behavioral changes occurring during psychotherapeutic interventions can lead to a normalization of functional brain activity at a global level.

Optimal Giving-Up Times and the Marginal Value Theorem

1982 ◽  
Vol 119 (4) ◽  
pp. 511-529 ◽  
Author(s):  
James N. McNair
Keyword(s):  
Marginal Value Theorem ◽  
Marginal Value

scholarly journals Wild Bornean orangutan ( Pongo pygmaeus wurmbii ) feeding rates and the Marginal Value Theorem

2020 ◽  
Vol 82 (10) ◽  
Author(s):  
Andrea L. DiGiorgio ◽  
Elizabeth M. Upton ◽  
Tri Wahyu Susanto ◽  
Cheryl D. Knott
Keyword(s):  
Pongo Pygmaeus ◽  
Marginal Value Theorem ◽  
Feeding Rates ◽  
Marginal Value ◽  
Bornean Orangutan ◽  
Pongo Pygmaeus Wurmbii

The Cognitive Neuroscience of Source Monitoring

2015 ◽  
Author(s):  
Karen J. Mitchell
Keyword(s):  
Source Monitoring ◽  
Brain Activity ◽  
Historical Context ◽  
Neural Mechanisms ◽  
Multiple Features ◽  
Neural Architecture ◽  
Big Picture ◽  
Key Issues ◽  
Neuroimaging Techniques

Source monitoring is a metamemory function that includes processes for encoding and organizing the content of memories, and processes that selectively revive, cumulate, and evaluate that content in the service of making attributions about the origin of the information (e.g., perception vs imagination). Neuroimaging techniques, especially functional magnetic resonance imaging (fMRI), are encouraging rapid developments in understanding the neural mechanisms supporting source monitoring. This chapter reviews current findings, placing them in historical context. It highlights key issues of particular relevance, including: neural reinstatement—the match between brain activity at encoding and later remembering; the role of lateral parietal cortex in cumulating multiple features and attending to information during remembering; functional specificity of the prefrontal cortex with respect to cognitive control; and identifying functional networks that support source monitoring. Suggestions are made for clarifying the big picture and increasing the specificity of our understanding of source monitoring and its neural architecture.

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