Task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.

<h4>Background</h4>The variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing tasks, detection and individuation, and explore whether differences in task demands lead to diff...

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Autores principales:	Adrian Nestor, Jean M Vettel, Michael J Tarr
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2008
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/f4f70469a59645b7b7b805c355a56813
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spelling	oai:doaj.org-article:f4f70469a59645b7b7b805c355a568132021-11-25T06:17:59ZTask-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.1932-620310.1371/journal.pone.0003978https://doaj.org/article/f4f70469a59645b7b7b805c355a568132008-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19112516/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>The variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing tasks, detection and individuation, and explore whether differences in task demands lead to differences both in the features most effective for automatic recognition and in the featural codes recruited by neural processing.<h4>Methodology/principal findings</h4>Our study appeals to a computational framework characterizing the features representing object categories as sets of overlapping image fragments. Within this framework, we assess the extent to which task-relevant information differs across image fragments. Based on objective differences we find among task-specific representations, we test the sensitivity of the human visual system to these different face descriptions independently of one another. Both behavior and functional magnetic resonance imaging reveal effects elicited by objective task-specific levels of information. Behaviorally, recognition performance with image fragments improves with increasing task-specific information carried by different face fragments. Neurally, this sensitivity to the two tasks manifests as differential localization of neural responses across the ventral visual pathway. Fragments diagnostic for detection evoke larger neural responses than non-diagnostic ones in the right posterior fusiform gyrus and bilaterally in the inferior occipital gyrus. In contrast, fragments diagnostic for individuation evoke larger responses than non-diagnostic ones in the anterior inferior temporal gyrus. Finally, for individuation only, pattern analysis reveals sensitivity to task-specific information within the right "fusiform face area".<h4>Conclusions/significance</h4>OUR RESULTS DEMONSTRATE: 1) information diagnostic for face detection and individuation is roughly separable; 2) the human visual system is independently sensitive to both types of information; 3) neural responses differ according to the type of task-relevant information considered. More generally, these findings provide evidence for the computational utility and the neural validity of fragment-based visual representation and recognition.Adrian NestorJean M VettelMichael J TarrPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 3, Iss 12, p e3978 (2008)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Adrian Nestor Jean M Vettel Michael J Tarr Task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.
description	<h4>Background</h4>The variety of ways in which faces are categorized makes face recognition challenging for both synthetic and biological vision systems. Here we focus on two face processing tasks, detection and individuation, and explore whether differences in task demands lead to differences both in the features most effective for automatic recognition and in the featural codes recruited by neural processing.<h4>Methodology/principal findings</h4>Our study appeals to a computational framework characterizing the features representing object categories as sets of overlapping image fragments. Within this framework, we assess the extent to which task-relevant information differs across image fragments. Based on objective differences we find among task-specific representations, we test the sensitivity of the human visual system to these different face descriptions independently of one another. Both behavior and functional magnetic resonance imaging reveal effects elicited by objective task-specific levels of information. Behaviorally, recognition performance with image fragments improves with increasing task-specific information carried by different face fragments. Neurally, this sensitivity to the two tasks manifests as differential localization of neural responses across the ventral visual pathway. Fragments diagnostic for detection evoke larger neural responses than non-diagnostic ones in the right posterior fusiform gyrus and bilaterally in the inferior occipital gyrus. In contrast, fragments diagnostic for individuation evoke larger responses than non-diagnostic ones in the anterior inferior temporal gyrus. Finally, for individuation only, pattern analysis reveals sensitivity to task-specific information within the right "fusiform face area".<h4>Conclusions/significance</h4>OUR RESULTS DEMONSTRATE: 1) information diagnostic for face detection and individuation is roughly separable; 2) the human visual system is independently sensitive to both types of information; 3) neural responses differ according to the type of task-relevant information considered. More generally, these findings provide evidence for the computational utility and the neural validity of fragment-based visual representation and recognition.
format	article
author	Adrian Nestor Jean M Vettel Michael J Tarr
author_facet	Adrian Nestor Jean M Vettel Michael J Tarr
author_sort	Adrian Nestor
title	Task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.
title_short	Task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.
title_full	Task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.
title_fullStr	Task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.
title_full_unstemmed	Task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.
title_sort	task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.
publisher	Public Library of Science (PLoS)
publishDate	2008
url	https://doaj.org/article/f4f70469a59645b7b7b805c355a56813
work_keys_str_mv	AT adriannestor taskspecificcodesforfacerecognitionhowtheyshapetheneuralrepresentationoffeaturesfordetectionandindividuation AT jeanmvettel taskspecificcodesforfacerecognitionhowtheyshapetheneuralrepresentationoffeaturesfordetectionandindividuation AT michaeljtarr taskspecificcodesforfacerecognitionhowtheyshapetheneuralrepresentationoffeaturesfordetectionandindividuation
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Task-specific codes for face recognition: how they shape the neural representation of features for detection and individuation.

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