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Neural event segmentation of continuous experience in human infants

How infants experience the world is fundamental to understanding their cognition and development. A key principle of adult experience is that, despite receiving continuous sensory input, we perceive this input as discrete events. Here we investigate such event segmentation in infants and how it diff...

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Autores principales: Yates, Tristan S., Skalaban, Lena J., Ellis, Cameron T., Bracher, Angelika J., Baldassano, Christopher, Turk-Browne, Nicholas B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618143/
https://www.ncbi.nlm.nih.gov/pubmed/36252007
http://dx.doi.org/10.1073/pnas.2200257119
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author Yates, Tristan S.
Skalaban, Lena J.
Ellis, Cameron T.
Bracher, Angelika J.
Baldassano, Christopher
Turk-Browne, Nicholas B.
author_facet Yates, Tristan S.
Skalaban, Lena J.
Ellis, Cameron T.
Bracher, Angelika J.
Baldassano, Christopher
Turk-Browne, Nicholas B.
author_sort Yates, Tristan S.
collection PubMed
description How infants experience the world is fundamental to understanding their cognition and development. A key principle of adult experience is that, despite receiving continuous sensory input, we perceive this input as discrete events. Here we investigate such event segmentation in infants and how it differs from adults. Research on event cognition in infants often uses simplified tasks in which (adult) experimenters help solve the segmentation problem for infants by defining event boundaries or presenting discrete actions/vignettes. This presupposes which events are experienced by infants and leaves open questions about the principles governing infant segmentation. We take a different, data-driven approach by studying infant event segmentation of continuous input. We collected whole-brain functional MRI (fMRI) data from awake infants (and adults, for comparison) watching a cartoon and used a hidden Markov model to identify event states in the brain. We quantified the existence, timescale, and organization of multiple-event representations across brain regions. The adult brain exhibited a known hierarchical gradient of event timescales, from shorter events in early visual regions to longer events in later visual and associative regions. In contrast, the infant brain represented only longer events, even in early visual regions, with no timescale hierarchy. The boundaries defining these infant events only partially overlapped with boundaries defined from adult brain activity and behavioral judgments. These findings suggest that events are organized differently in infants, with longer timescales and more stable neural patterns, even in sensory regions. This may indicate greater temporal integration and reduced temporal precision during dynamic, naturalistic perception.
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spelling pubmed-96181432023-04-17 Neural event segmentation of continuous experience in human infants Yates, Tristan S. Skalaban, Lena J. Ellis, Cameron T. Bracher, Angelika J. Baldassano, Christopher Turk-Browne, Nicholas B. Proc Natl Acad Sci U S A Biological Sciences How infants experience the world is fundamental to understanding their cognition and development. A key principle of adult experience is that, despite receiving continuous sensory input, we perceive this input as discrete events. Here we investigate such event segmentation in infants and how it differs from adults. Research on event cognition in infants often uses simplified tasks in which (adult) experimenters help solve the segmentation problem for infants by defining event boundaries or presenting discrete actions/vignettes. This presupposes which events are experienced by infants and leaves open questions about the principles governing infant segmentation. We take a different, data-driven approach by studying infant event segmentation of continuous input. We collected whole-brain functional MRI (fMRI) data from awake infants (and adults, for comparison) watching a cartoon and used a hidden Markov model to identify event states in the brain. We quantified the existence, timescale, and organization of multiple-event representations across brain regions. The adult brain exhibited a known hierarchical gradient of event timescales, from shorter events in early visual regions to longer events in later visual and associative regions. In contrast, the infant brain represented only longer events, even in early visual regions, with no timescale hierarchy. The boundaries defining these infant events only partially overlapped with boundaries defined from adult brain activity and behavioral judgments. These findings suggest that events are organized differently in infants, with longer timescales and more stable neural patterns, even in sensory regions. This may indicate greater temporal integration and reduced temporal precision during dynamic, naturalistic perception. National Academy of Sciences 2022-10-17 2022-10-25 /pmc/articles/PMC9618143/ /pubmed/36252007 http://dx.doi.org/10.1073/pnas.2200257119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Yates, Tristan S.
Skalaban, Lena J.
Ellis, Cameron T.
Bracher, Angelika J.
Baldassano, Christopher
Turk-Browne, Nicholas B.
Neural event segmentation of continuous experience in human infants
title Neural event segmentation of continuous experience in human infants
title_full Neural event segmentation of continuous experience in human infants
title_fullStr Neural event segmentation of continuous experience in human infants
title_full_unstemmed Neural event segmentation of continuous experience in human infants
title_short Neural event segmentation of continuous experience in human infants
title_sort neural event segmentation of continuous experience in human infants
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9618143/
https://www.ncbi.nlm.nih.gov/pubmed/36252007
http://dx.doi.org/10.1073/pnas.2200257119
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