Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions
- Autores
- Phillips, Holly N.; Blenkmann, Alejandro Omar; Hughes, Laura E.; Bekinschtein, Tristán Andrés; Rowe, James B.
- Año de publicación
- 2015
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Brain function can be conceived as a hierarchy of generative models that optimizes predictions of sensory inputs and minimizes “surprise.” Each level of the hierarchy makes predictions of neural events at a lower level in the hierarchy, which returns a prediction error when these expectations are violated. We tested the generalization of this hypothesis to multiple sequential deviations, and we identified the most likely organization of the network that accommodates deviations in temporal structure of stimuli. Magnetoencephalography of healthy human participants during an auditory paradigm identified prediction error responses in bilateral primary auditory cortex, superior temporal gyrus, and lateral prefrontal cortex for deviation by frequency, intensity, location, duration, and silent gap. We examined the connectivity between cortical sources using a set of 21 generative models that embedded alternate hypotheses of frontotemporal network dynamics. Bayesian model selection provided evidence for two new features of functional network organization. First, an expectancy signal provided input to the prefrontal cortex bilaterally, related to the temporal structure of stimuli. Second, there are functionally significant lateral connections between superior temporal and/or prefrontal cortex. The results support a predictive coding hypothesis but go beyond previous work in demonstrating the generalization to multiple concurrent stimulus dimensions and the evidence for a temporal expectancy input at the higher level of the frontotemporal hierarchy. We propose that this framework for studying the brain's response to unexpected events is not limited to simple sensory tasks but may also apply to the neurocognitive mechanisms of higher cognitive functions and their disorders.
Fil: Phillips, Holly N.. University of Cambridge; Reino Unido
Fil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina
Fil: Hughes, Laura E.. University of Cambridge; Reino Unido
Fil: Bekinschtein, Tristán Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Cambridge; Reino Unido
Fil: Rowe, James B.. University of Cambridge; Reino Unido - Materia
-
Dynamic causal modeling
Magnetoencephalography
Mismatch negativity
Prediction and prediction error - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/17795
Ver los metadatos del registro completo
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Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensionsPhillips, Holly N.Blenkmann, Alejandro OmarHughes, Laura E.Bekinschtein, Tristán AndrésRowe, James B.Dynamic causal modelingMagnetoencephalographyMismatch negativityPrediction and prediction errorhttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Brain function can be conceived as a hierarchy of generative models that optimizes predictions of sensory inputs and minimizes “surprise.” Each level of the hierarchy makes predictions of neural events at a lower level in the hierarchy, which returns a prediction error when these expectations are violated. We tested the generalization of this hypothesis to multiple sequential deviations, and we identified the most likely organization of the network that accommodates deviations in temporal structure of stimuli. Magnetoencephalography of healthy human participants during an auditory paradigm identified prediction error responses in bilateral primary auditory cortex, superior temporal gyrus, and lateral prefrontal cortex for deviation by frequency, intensity, location, duration, and silent gap. We examined the connectivity between cortical sources using a set of 21 generative models that embedded alternate hypotheses of frontotemporal network dynamics. Bayesian model selection provided evidence for two new features of functional network organization. First, an expectancy signal provided input to the prefrontal cortex bilaterally, related to the temporal structure of stimuli. Second, there are functionally significant lateral connections between superior temporal and/or prefrontal cortex. The results support a predictive coding hypothesis but go beyond previous work in demonstrating the generalization to multiple concurrent stimulus dimensions and the evidence for a temporal expectancy input at the higher level of the frontotemporal hierarchy. We propose that this framework for studying the brain's response to unexpected events is not limited to simple sensory tasks but may also apply to the neurocognitive mechanisms of higher cognitive functions and their disorders.Fil: Phillips, Holly N.. University of Cambridge; Reino UnidoFil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; ArgentinaFil: Hughes, Laura E.. University of Cambridge; Reino UnidoFil: Bekinschtein, Tristán Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Cambridge; Reino UnidoFil: Rowe, James B.. University of Cambridge; Reino UnidoSociety for Neuroscience2015-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/17795Phillips, Holly N.; Blenkmann, Alejandro Omar; Hughes, Laura E.; Bekinschtein, Tristán Andrés; Rowe, James B.; Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions; Society for Neuroscience; Journal of Neuroscience; 35; 25; 6-2015; 9255-92640270-64741529-2401enginfo:eu-repo/semantics/altIdentifier/doi/10.1523/JNEUROSCI.5095-14.2015info:eu-repo/semantics/altIdentifier/url/http://www.jneurosci.org/content/35/25/9255info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4478247/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:50:07Zoai:ri.conicet.gov.ar:11336/17795instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:50:07.664CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions |
title |
Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions |
spellingShingle |
Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions Phillips, Holly N. Dynamic causal modeling Magnetoencephalography Mismatch negativity Prediction and prediction error |
title_short |
Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions |
title_full |
Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions |
title_fullStr |
Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions |
title_full_unstemmed |
Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions |
title_sort |
Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions |
dc.creator.none.fl_str_mv |
Phillips, Holly N. Blenkmann, Alejandro Omar Hughes, Laura E. Bekinschtein, Tristán Andrés Rowe, James B. |
author |
Phillips, Holly N. |
author_facet |
Phillips, Holly N. Blenkmann, Alejandro Omar Hughes, Laura E. Bekinschtein, Tristán Andrés Rowe, James B. |
author_role |
author |
author2 |
Blenkmann, Alejandro Omar Hughes, Laura E. Bekinschtein, Tristán Andrés Rowe, James B. |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Dynamic causal modeling Magnetoencephalography Mismatch negativity Prediction and prediction error |
topic |
Dynamic causal modeling Magnetoencephalography Mismatch negativity Prediction and prediction error |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/3.1 https://purl.org/becyt/ford/3 |
dc.description.none.fl_txt_mv |
Brain function can be conceived as a hierarchy of generative models that optimizes predictions of sensory inputs and minimizes “surprise.” Each level of the hierarchy makes predictions of neural events at a lower level in the hierarchy, which returns a prediction error when these expectations are violated. We tested the generalization of this hypothesis to multiple sequential deviations, and we identified the most likely organization of the network that accommodates deviations in temporal structure of stimuli. Magnetoencephalography of healthy human participants during an auditory paradigm identified prediction error responses in bilateral primary auditory cortex, superior temporal gyrus, and lateral prefrontal cortex for deviation by frequency, intensity, location, duration, and silent gap. We examined the connectivity between cortical sources using a set of 21 generative models that embedded alternate hypotheses of frontotemporal network dynamics. Bayesian model selection provided evidence for two new features of functional network organization. First, an expectancy signal provided input to the prefrontal cortex bilaterally, related to the temporal structure of stimuli. Second, there are functionally significant lateral connections between superior temporal and/or prefrontal cortex. The results support a predictive coding hypothesis but go beyond previous work in demonstrating the generalization to multiple concurrent stimulus dimensions and the evidence for a temporal expectancy input at the higher level of the frontotemporal hierarchy. We propose that this framework for studying the brain's response to unexpected events is not limited to simple sensory tasks but may also apply to the neurocognitive mechanisms of higher cognitive functions and their disorders. Fil: Phillips, Holly N.. University of Cambridge; Reino Unido Fil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Biología Celular y Neurociencia "Prof. Eduardo de Robertis". Universidad de Buenos Aires. Facultad de Medicina. Instituto de Biología Celular y Neurociencia; Argentina Fil: Hughes, Laura E.. University of Cambridge; Reino Unido Fil: Bekinschtein, Tristán Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Cambridge; Reino Unido Fil: Rowe, James B.. University of Cambridge; Reino Unido |
description |
Brain function can be conceived as a hierarchy of generative models that optimizes predictions of sensory inputs and minimizes “surprise.” Each level of the hierarchy makes predictions of neural events at a lower level in the hierarchy, which returns a prediction error when these expectations are violated. We tested the generalization of this hypothesis to multiple sequential deviations, and we identified the most likely organization of the network that accommodates deviations in temporal structure of stimuli. Magnetoencephalography of healthy human participants during an auditory paradigm identified prediction error responses in bilateral primary auditory cortex, superior temporal gyrus, and lateral prefrontal cortex for deviation by frequency, intensity, location, duration, and silent gap. We examined the connectivity between cortical sources using a set of 21 generative models that embedded alternate hypotheses of frontotemporal network dynamics. Bayesian model selection provided evidence for two new features of functional network organization. First, an expectancy signal provided input to the prefrontal cortex bilaterally, related to the temporal structure of stimuli. Second, there are functionally significant lateral connections between superior temporal and/or prefrontal cortex. The results support a predictive coding hypothesis but go beyond previous work in demonstrating the generalization to multiple concurrent stimulus dimensions and the evidence for a temporal expectancy input at the higher level of the frontotemporal hierarchy. We propose that this framework for studying the brain's response to unexpected events is not limited to simple sensory tasks but may also apply to the neurocognitive mechanisms of higher cognitive functions and their disorders. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-06 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://hdl.handle.net/11336/17795 Phillips, Holly N.; Blenkmann, Alejandro Omar; Hughes, Laura E.; Bekinschtein, Tristán Andrés; Rowe, James B.; Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions; Society for Neuroscience; Journal of Neuroscience; 35; 25; 6-2015; 9255-9264 0270-6474 1529-2401 |
url |
http://hdl.handle.net/11336/17795 |
identifier_str_mv |
Phillips, Holly N.; Blenkmann, Alejandro Omar; Hughes, Laura E.; Bekinschtein, Tristán Andrés; Rowe, James B.; Hierarchical organization of frontotemporal networks for the prediction of stimuli across multiple dimensions; Society for Neuroscience; Journal of Neuroscience; 35; 25; 6-2015; 9255-9264 0270-6474 1529-2401 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1523/JNEUROSCI.5095-14.2015 info:eu-repo/semantics/altIdentifier/url/http://www.jneurosci.org/content/35/25/9255 info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4478247/ |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/ |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Society for Neuroscience |
publisher.none.fl_str_mv |
Society for Neuroscience |
dc.source.none.fl_str_mv |
reponame:CONICET Digital (CONICET) instname:Consejo Nacional de Investigaciones Científicas y Técnicas |
reponame_str |
CONICET Digital (CONICET) |
collection |
CONICET Digital (CONICET) |
instname_str |
Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.name.fl_str_mv |
CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas |
repository.mail.fl_str_mv |
dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar |
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1844613546512482304 |
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13.070432 |