Neurally-constrained modeling of human gaze strategies in a change blindness task.

Despite possessing the capacity for selective attention, we often fail to notice the obvious. We investigated participants' (n = 39) failures to detect salient changes in a change blindness experiment. Surprisingly, change detection success varied by over two-fold across participants. These var...

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Autores principales:	Akshay Jagatap, Simran Purokayastha, Hritik Jain, Devarajan Sridharan
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/88025648654441fd94af1bfd74448d03
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spelling	oai:doaj.org-article:88025648654441fd94af1bfd74448d032021-12-02T19:58:01ZNeurally-constrained modeling of human gaze strategies in a change blindness task.1553-734X1553-735810.1371/journal.pcbi.1009322https://doaj.org/article/88025648654441fd94af1bfd74448d032021-08-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009322https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Despite possessing the capacity for selective attention, we often fail to notice the obvious. We investigated participants' (n = 39) failures to detect salient changes in a change blindness experiment. Surprisingly, change detection success varied by over two-fold across participants. These variations could not be readily explained by differences in scan paths or fixated visual features. Yet, two simple gaze metrics-mean duration of fixations and the variance of saccade amplitudes-systematically predicted change detection success. We explored the mechanistic underpinnings of these results with a neurally-constrained model based on the Bayesian framework of sequential probability ratio testing, with a posterior odds-ratio rule for shifting gaze. The model's gaze strategies and success rates closely mimicked human data. Moreover, the model outperformed a state-of-the-art deep neural network (DeepGaze II) with predicting human gaze patterns in this change blindness task. Our mechanistic model reveals putative rational observer search strategies for change detection during change blindness, with critical real-world implications.Akshay JagatapSimran PurokayasthaHritik JainDevarajan SridharanPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 8, p e1009322 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Akshay Jagatap Simran Purokayastha Hritik Jain Devarajan Sridharan Neurally-constrained modeling of human gaze strategies in a change blindness task.
description	Despite possessing the capacity for selective attention, we often fail to notice the obvious. We investigated participants' (n = 39) failures to detect salient changes in a change blindness experiment. Surprisingly, change detection success varied by over two-fold across participants. These variations could not be readily explained by differences in scan paths or fixated visual features. Yet, two simple gaze metrics-mean duration of fixations and the variance of saccade amplitudes-systematically predicted change detection success. We explored the mechanistic underpinnings of these results with a neurally-constrained model based on the Bayesian framework of sequential probability ratio testing, with a posterior odds-ratio rule for shifting gaze. The model's gaze strategies and success rates closely mimicked human data. Moreover, the model outperformed a state-of-the-art deep neural network (DeepGaze II) with predicting human gaze patterns in this change blindness task. Our mechanistic model reveals putative rational observer search strategies for change detection during change blindness, with critical real-world implications.
format	article
author	Akshay Jagatap Simran Purokayastha Hritik Jain Devarajan Sridharan
author_facet	Akshay Jagatap Simran Purokayastha Hritik Jain Devarajan Sridharan
author_sort	Akshay Jagatap
title	Neurally-constrained modeling of human gaze strategies in a change blindness task.
title_short	Neurally-constrained modeling of human gaze strategies in a change blindness task.
title_full	Neurally-constrained modeling of human gaze strategies in a change blindness task.
title_fullStr	Neurally-constrained modeling of human gaze strategies in a change blindness task.
title_full_unstemmed	Neurally-constrained modeling of human gaze strategies in a change blindness task.
title_sort	neurally-constrained modeling of human gaze strategies in a change blindness task.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/88025648654441fd94af1bfd74448d03
work_keys_str_mv	AT akshayjagatap neurallyconstrainedmodelingofhumangazestrategiesinachangeblindnesstask AT simranpurokayastha neurallyconstrainedmodelingofhumangazestrategiesinachangeblindnesstask AT hritikjain neurallyconstrainedmodelingofhumangazestrategiesinachangeblindnesstask AT devarajansridharan neurallyconstrainedmodelingofhumangazestrategiesinachangeblindnesstask
_version_	1718375788972081152

Neurally-constrained modeling of human gaze strategies in a change blindness task.

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