Individual differences in social information gathering revealed through Bayesian hierarchical models

As studies of the neural circuits underlying choice expand to include more complicated behaviors, analysis of behaviors elicited in laboratory paradigms has grown increasingly difficult. Social behaviors present a particular challenge, since inter- and intra-individual variation are expected to play...

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Main Authors: John ePearson, Karli K Watson, Jeffrey T Klein, R Becket Ebitz, Michael L Platt
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-09-01
Series:Frontiers in Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00165/full
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author John ePearson
John ePearson
John ePearson
Karli K Watson
Karli K Watson
Karli K Watson
Jeffrey T Klein
R Becket Ebitz
R Becket Ebitz
R Becket Ebitz
Michael L Platt
Michael L Platt
Michael L Platt
Michael L Platt
author_facet John ePearson
John ePearson
John ePearson
Karli K Watson
Karli K Watson
Karli K Watson
Jeffrey T Klein
R Becket Ebitz
R Becket Ebitz
R Becket Ebitz
Michael L Platt
Michael L Platt
Michael L Platt
Michael L Platt
author_sort John ePearson
collection DOAJ
description As studies of the neural circuits underlying choice expand to include more complicated behaviors, analysis of behaviors elicited in laboratory paradigms has grown increasingly difficult. Social behaviors present a particular challenge, since inter- and intra-individual variation are expected to play key roles. However, due to limitations on data collection, studies must often choose between pooling data across all subjects or using individual subjects' data in isolation. Hierarchical models mediate between these two extremes by modeling individual subjects as drawn from a population distribution, allowing the population at large to serve as prior information about individuals' behavior. Here, we apply this method to data collected across multiple experimental sessions from a set of rhesus macaques performing a social information valuation task. We show that, while the values of social images vary markedly between individuals and between experimental sessions for the same individual, individuals also differentially value particular categories of social images. Furthermore, we demonstrate covariance between values for image categories within individuals and find evidence suggesting that magnitudes of stimulus values tend to diminish over time.
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spelling doaj.art-7118b91c5b6745cbbd6451a18034dcaa2022-12-22T02:53:43ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2013-09-01710.3389/fnins.2013.0016559275Individual differences in social information gathering revealed through Bayesian hierarchical modelsJohn ePearson0John ePearson1John ePearson2Karli K Watson3Karli K Watson4Karli K Watson5Jeffrey T Klein6R Becket Ebitz7R Becket Ebitz8R Becket Ebitz9Michael L Platt10Michael L Platt11Michael L Platt12Michael L Platt13Duke University Medical CenterCenter for Cognitive NeuroscienceDuke Institute for Brain SciencesDuke University Medical CenterCenter for Cognitive NeuroscienceDuke Institute for Brain SciencesUniversity of North CarolinaDuke University Medical CenterCenter for Cognitive NeuroscienceDuke Institute for Brain SciencesDuke University Medical CenterCenter for Cognitive NeuroscienceDuke Institute for Brain SciencesDuke UniversityAs studies of the neural circuits underlying choice expand to include more complicated behaviors, analysis of behaviors elicited in laboratory paradigms has grown increasingly difficult. Social behaviors present a particular challenge, since inter- and intra-individual variation are expected to play key roles. However, due to limitations on data collection, studies must often choose between pooling data across all subjects or using individual subjects' data in isolation. Hierarchical models mediate between these two extremes by modeling individual subjects as drawn from a population distribution, allowing the population at large to serve as prior information about individuals' behavior. Here, we apply this method to data collected across multiple experimental sessions from a set of rhesus macaques performing a social information valuation task. We show that, while the values of social images vary markedly between individuals and between experimental sessions for the same individual, individuals also differentially value particular categories of social images. Furthermore, we demonstrate covariance between values for image categories within individuals and find evidence suggesting that magnitudes of stimulus values tend to diminish over time.http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00165/fullsocial neuroscienceforagingBayesian Modelsinformation foragingpay-per-view
spellingShingle John ePearson
John ePearson
John ePearson
Karli K Watson
Karli K Watson
Karli K Watson
Jeffrey T Klein
R Becket Ebitz
R Becket Ebitz
R Becket Ebitz
Michael L Platt
Michael L Platt
Michael L Platt
Michael L Platt
Individual differences in social information gathering revealed through Bayesian hierarchical models
Frontiers in Neuroscience
social neuroscience
foraging
Bayesian Models
information foraging
pay-per-view
title Individual differences in social information gathering revealed through Bayesian hierarchical models
title_full Individual differences in social information gathering revealed through Bayesian hierarchical models
title_fullStr Individual differences in social information gathering revealed through Bayesian hierarchical models
title_full_unstemmed Individual differences in social information gathering revealed through Bayesian hierarchical models
title_short Individual differences in social information gathering revealed through Bayesian hierarchical models
title_sort individual differences in social information gathering revealed through bayesian hierarchical models
topic social neuroscience
foraging
Bayesian Models
information foraging
pay-per-view
url http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00165/full
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