Direct brain recordings reveal continuous encoding of structure in random stimuli

Autores
Fuhrer, Julian; Kyrre, Glette; Ivanovic, Jugoslav; Gunnar Larsson, Pål; Bekinschtein, Tristán Andrés; Kochen, Sara Silvia; Knight, Robert T.; Tørresen, Jim; Solbakk, Anne Kristin; Endestad, Tor; Blenkmann, Alejandro Omar
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The brain excels at processing sensory input, even in rich or chaotic environments. Mounting evidence attributes this to the creation of sophisticated internal models of the environment that draw on statistical structures in the unfolding sensory input. Understanding how and where this modeling takes place is a core question in statistical learning and predictive processing. In this context, we address the role of transitional probabilities as an implicit structure supporting the encoding of a random auditory stream. Leveraging information-theoretical principles and the high spatiotemporal resolution of intracranial electroencephalography, we analyzed the trial-by-trial high-frequency activity representation of transitional probabilities. This unique approach enabled us to demonstrate how the brain continuously encodes structure in random stimuli and revealed the involvement of a network outside of the auditory system, including hippocampal, frontal, and temporal regions. Linking the frame-works of statistical learning and predictive processing, our work illuminates an implicit process that can be crucial for the swift detection of patterns and unexpected events in the environment.
Fil: Fuhrer, Julian. University of Oslo; Noruega
Fil: Kyrre, Glette. University of Oslo; Noruega
Fil: Ivanovic, Jugoslav. University of Oslo; Noruega
Fil: Gunnar Larsson, Pål. University of Oslo; Noruega
Fil: Bekinschtein, Tristán Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Cambridge; Reino Unido
Fil: Kochen, Sara Silvia. Universidad Nacional Arturo Jauretche. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Provincia de Buenos Aires. Ministerio de Salud. Hospital Alta Complejidad en Red El Cruce Dr. Néstor Carlos Kirchner Samic. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos; Argentina
Fil: Knight, Robert T.. University of California at Berkeley; Estados Unidos
Fil: Tørresen, Jim. University of Oslo; Noruega
Fil: Solbakk, Anne Kristin. University of Oslo; Noruega. Helgeland Hospital; Noruega
Fil: Endestad, Tor. University of Oslo; Noruega. Helgeland Hospital; Noruega
Fil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Oslo; Noruega
Materia
EPILEPSIA
CEREBRO
INTRACEREBRAL
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/181252
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Direct brain recordings reveal continuous encoding of structure in random stimuliFuhrer, JulianKyrre, GletteIvanovic, JugoslavGunnar Larsson, PålBekinschtein, Tristán AndrésKochen, Sara SilviaKnight, Robert T.Tørresen, JimSolbakk, Anne KristinEndestad, TorBlenkmann, Alejandro OmarEPILEPSIACEREBROINTRACEREBRALhttps://purl.org/becyt/ford/3.2https://purl.org/becyt/ford/3The brain excels at processing sensory input, even in rich or chaotic environments. Mounting evidence attributes this to the creation of sophisticated internal models of the environment that draw on statistical structures in the unfolding sensory input. Understanding how and where this modeling takes place is a core question in statistical learning and predictive processing. In this context, we address the role of transitional probabilities as an implicit structure supporting the encoding of a random auditory stream. Leveraging information-theoretical principles and the high spatiotemporal resolution of intracranial electroencephalography, we analyzed the trial-by-trial high-frequency activity representation of transitional probabilities. This unique approach enabled us to demonstrate how the brain continuously encodes structure in random stimuli and revealed the involvement of a network outside of the auditory system, including hippocampal, frontal, and temporal regions. Linking the frame-works of statistical learning and predictive processing, our work illuminates an implicit process that can be crucial for the swift detection of patterns and unexpected events in the environment.Fil: Fuhrer, Julian. University of Oslo; NoruegaFil: Kyrre, Glette. University of Oslo; NoruegaFil: Ivanovic, Jugoslav. University of Oslo; NoruegaFil: Gunnar Larsson, Pål. University of Oslo; NoruegaFil: Bekinschtein, Tristán Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Cambridge; Reino UnidoFil: Kochen, Sara Silvia. Universidad Nacional Arturo Jauretche. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Provincia de Buenos Aires. Ministerio de Salud. Hospital Alta Complejidad en Red El Cruce Dr. Néstor Carlos Kirchner Samic. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos; ArgentinaFil: Knight, Robert T.. University of California at Berkeley; Estados UnidosFil: Tørresen, Jim. University of Oslo; NoruegaFil: Solbakk, Anne Kristin. University of Oslo; Noruega. Helgeland Hospital; NoruegaFil: Endestad, Tor. University of Oslo; Noruega. Helgeland Hospital; NoruegaFil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Oslo; NoruegaCold Spring Harbor Laboratory Press2021-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/181252Fuhrer, Julian; Kyrre, Glette; Ivanovic, Jugoslav; Gunnar Larsson, Pål; Bekinschtein, Tristán Andrés; et al.; Direct brain recordings reveal continuous encoding of structure in random stimuli; Cold Spring Harbor Laboratory Press; bioRxiv; 10-2021; 1-142692-8205CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.biorxiv.org/content/10.1101/2021.10.01.462295v2info:eu-repo/semantics/altIdentifier/doi/10.1101/2021.10.01.462295info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:04:36Zoai:ri.conicet.gov.ar:11336/181252instacron: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:34982025-09-03 10:04:37.101CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Direct brain recordings reveal continuous encoding of structure in random stimuli
title Direct brain recordings reveal continuous encoding of structure in random stimuli
spellingShingle Direct brain recordings reveal continuous encoding of structure in random stimuli
Fuhrer, Julian
EPILEPSIA
CEREBRO
INTRACEREBRAL
title_short Direct brain recordings reveal continuous encoding of structure in random stimuli
title_full Direct brain recordings reveal continuous encoding of structure in random stimuli
title_fullStr Direct brain recordings reveal continuous encoding of structure in random stimuli
title_full_unstemmed Direct brain recordings reveal continuous encoding of structure in random stimuli
title_sort Direct brain recordings reveal continuous encoding of structure in random stimuli
dc.creator.none.fl_str_mv Fuhrer, Julian
Kyrre, Glette
Ivanovic, Jugoslav
Gunnar Larsson, Pål
Bekinschtein, Tristán Andrés
Kochen, Sara Silvia
Knight, Robert T.
Tørresen, Jim
Solbakk, Anne Kristin
Endestad, Tor
Blenkmann, Alejandro Omar
author Fuhrer, Julian
author_facet Fuhrer, Julian
Kyrre, Glette
Ivanovic, Jugoslav
Gunnar Larsson, Pål
Bekinschtein, Tristán Andrés
Kochen, Sara Silvia
Knight, Robert T.
Tørresen, Jim
Solbakk, Anne Kristin
Endestad, Tor
Blenkmann, Alejandro Omar
author_role author
author2 Kyrre, Glette
Ivanovic, Jugoslav
Gunnar Larsson, Pål
Bekinschtein, Tristán Andrés
Kochen, Sara Silvia
Knight, Robert T.
Tørresen, Jim
Solbakk, Anne Kristin
Endestad, Tor
Blenkmann, Alejandro Omar
author2_role author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv EPILEPSIA
CEREBRO
INTRACEREBRAL
topic EPILEPSIA
CEREBRO
INTRACEREBRAL
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.2
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv The brain excels at processing sensory input, even in rich or chaotic environments. Mounting evidence attributes this to the creation of sophisticated internal models of the environment that draw on statistical structures in the unfolding sensory input. Understanding how and where this modeling takes place is a core question in statistical learning and predictive processing. In this context, we address the role of transitional probabilities as an implicit structure supporting the encoding of a random auditory stream. Leveraging information-theoretical principles and the high spatiotemporal resolution of intracranial electroencephalography, we analyzed the trial-by-trial high-frequency activity representation of transitional probabilities. This unique approach enabled us to demonstrate how the brain continuously encodes structure in random stimuli and revealed the involvement of a network outside of the auditory system, including hippocampal, frontal, and temporal regions. Linking the frame-works of statistical learning and predictive processing, our work illuminates an implicit process that can be crucial for the swift detection of patterns and unexpected events in the environment.
Fil: Fuhrer, Julian. University of Oslo; Noruega
Fil: Kyrre, Glette. University of Oslo; Noruega
Fil: Ivanovic, Jugoslav. University of Oslo; Noruega
Fil: Gunnar Larsson, Pål. University of Oslo; Noruega
Fil: Bekinschtein, Tristán Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Cambridge; Reino Unido
Fil: Kochen, Sara Silvia. Universidad Nacional Arturo Jauretche. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Provincia de Buenos Aires. Ministerio de Salud. Hospital Alta Complejidad en Red El Cruce Dr. Néstor Carlos Kirchner Samic. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos; Argentina
Fil: Knight, Robert T.. University of California at Berkeley; Estados Unidos
Fil: Tørresen, Jim. University of Oslo; Noruega
Fil: Solbakk, Anne Kristin. University of Oslo; Noruega. Helgeland Hospital; Noruega
Fil: Endestad, Tor. University of Oslo; Noruega. Helgeland Hospital; Noruega
Fil: Blenkmann, Alejandro Omar. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of Oslo; Noruega
description The brain excels at processing sensory input, even in rich or chaotic environments. Mounting evidence attributes this to the creation of sophisticated internal models of the environment that draw on statistical structures in the unfolding sensory input. Understanding how and where this modeling takes place is a core question in statistical learning and predictive processing. In this context, we address the role of transitional probabilities as an implicit structure supporting the encoding of a random auditory stream. Leveraging information-theoretical principles and the high spatiotemporal resolution of intracranial electroencephalography, we analyzed the trial-by-trial high-frequency activity representation of transitional probabilities. This unique approach enabled us to demonstrate how the brain continuously encodes structure in random stimuli and revealed the involvement of a network outside of the auditory system, including hippocampal, frontal, and temporal regions. Linking the frame-works of statistical learning and predictive processing, our work illuminates an implicit process that can be crucial for the swift detection of patterns and unexpected events in the environment.
publishDate 2021
dc.date.none.fl_str_mv 2021-10
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/11336/181252
Fuhrer, Julian; Kyrre, Glette; Ivanovic, Jugoslav; Gunnar Larsson, Pål; Bekinschtein, Tristán Andrés; et al.; Direct brain recordings reveal continuous encoding of structure in random stimuli; Cold Spring Harbor Laboratory Press; bioRxiv; 10-2021; 1-14
2692-8205
CONICET Digital
CONICET
url http://hdl.handle.net/11336/181252
identifier_str_mv Fuhrer, Julian; Kyrre, Glette; Ivanovic, Jugoslav; Gunnar Larsson, Pål; Bekinschtein, Tristán Andrés; et al.; Direct brain recordings reveal continuous encoding of structure in random stimuli; Cold Spring Harbor Laboratory Press; bioRxiv; 10-2021; 1-14
2692-8205
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.biorxiv.org/content/10.1101/2021.10.01.462295v2
info:eu-repo/semantics/altIdentifier/doi/10.1101/2021.10.01.462295
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 Cold Spring Harbor Laboratory Press
publisher.none.fl_str_mv Cold Spring Harbor Laboratory Press
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
_version_ 1842269865983868928
score 13.13397

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