Model-based whole-brain perturbational landscape of neurodegenerative diseases

Autores
Sanz Perl Hernandez, Yonatan; Fittipaldi, María Sol; Gonzalez Campo, Cecilia; Moguilner, Sebastián; Cruzat, Josephine; Fraile Vazquez, Matias E.; Herzog, Rubén; Kringelbach, Morten L.; Deco, Gustavo; Prado, Pavel; Ibañez, Agustin Mariano; Tagliazucchi, Enzo Rodolfo
Año de publicación
2023
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The treatment of neurodegenerative diseases is hindered by lack of interventions capable of steering multimodal whole-brain dynamics towards patterns indicative of preserved brain health. To address this problem, we combined deep learning with a model capable of repro-ducing whole-brain functional connectivity in patients diagnosed with Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD). These models included disease-specific atrophy maps as priors to modulate local parameters, revealing increased stability of hippocampal and insular dynamics as signatures of brain atrophy in AD and bvFTD, respectively. Using variational autoencoders, we visualized different pathologies and their severity as the evolution of trajectories in a low-dimensional latent space. Finally, we perturbed the model to reveal key AD-and bvFTD-specific regions to induce transitions from pathological to healthy brain states. Overall, we obtained novel insights on disease progression and control by means of external stimulation, while identifying dynamical mechanisms that underlie functional alterations in neuro degeneration.
Fil: Sanz Perl Hernandez, Yonatan. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universitat Pompeu Fabra; España. Universidad de San Andrés; Argentina
Fil: Fittipaldi, María Sol. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina
Fil: Gonzalez Campo, Cecilia. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Moguilner, Sebastián. Universidad Adolfo Ibañez; Chile. University of California; Estados Unidos
Fil: Cruzat, Josephine. Universitat Pompeu Fabra; España. Universidad Adolfo Ibañez; Chile
Fil: Fraile Vazquez, Matias E.. Universidad de San Andrés; Argentina
Fil: Herzog, Rubén. Universidad Adolfo Ibañez; Chile
Fil: Kringelbach, Morten L.. University of Oxford; Reino Unido. University Aarhus; Dinamarca. Universidade do Minho; Portugal
Fil: Deco, Gustavo. Max Planck Institute For Human Cognitive And Brain Sciences; Alemania. Monash University; Australia. Institució Catalana de Recerca I Estudis Avançats; España. Universitat Pompeu Fabra; España
Fil: Prado, Pavel. Universidad San Sebastián; Chile. Universidad Adolfo Ibañez; Chile
Fil: Ibañez, Agustin Mariano. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of California; Estados Unidos. Trinity College Dublin; Irlanda
Fil: Tagliazucchi, Enzo Rodolfo. Universidad de Buenos Aires; Argentina. Universidad de San Andrés; Argentina. Universidad Adolfo Ibáñez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
Dementia
Neuroimaging
Modeling
fMRI
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:11336/228644
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/228644
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Model-based whole-brain perturbational landscape of neurodegenerative diseasesSanz Perl Hernandez, YonatanFittipaldi, María SolGonzalez Campo, CeciliaMoguilner, SebastiánCruzat, JosephineFraile Vazquez, Matias E.Herzog, RubénKringelbach, Morten L.Deco, GustavoPrado, PavelIbañez, Agustin MarianoTagliazucchi, Enzo RodolfoDementiaNeuroimagingModelingfMRIhttps://purl.org/becyt/ford/1.3https://purl.org/becyt/ford/1The treatment of neurodegenerative diseases is hindered by lack of interventions capable of steering multimodal whole-brain dynamics towards patterns indicative of preserved brain health. To address this problem, we combined deep learning with a model capable of repro-ducing whole-brain functional connectivity in patients diagnosed with Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD). These models included disease-specific atrophy maps as priors to modulate local parameters, revealing increased stability of hippocampal and insular dynamics as signatures of brain atrophy in AD and bvFTD, respectively. Using variational autoencoders, we visualized different pathologies and their severity as the evolution of trajectories in a low-dimensional latent space. Finally, we perturbed the model to reveal key AD-and bvFTD-specific regions to induce transitions from pathological to healthy brain states. Overall, we obtained novel insights on disease progression and control by means of external stimulation, while identifying dynamical mechanisms that underlie functional alterations in neuro degeneration.Fil: Sanz Perl Hernandez, Yonatan. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universitat Pompeu Fabra; España. Universidad de San Andrés; ArgentinaFil: Fittipaldi, María Sol. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; ArgentinaFil: Gonzalez Campo, Cecilia. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Moguilner, Sebastián. Universidad Adolfo Ibañez; Chile. University of California; Estados UnidosFil: Cruzat, Josephine. Universitat Pompeu Fabra; España. Universidad Adolfo Ibañez; ChileFil: Fraile Vazquez, Matias E.. Universidad de San Andrés; ArgentinaFil: Herzog, Rubén. Universidad Adolfo Ibañez; ChileFil: Kringelbach, Morten L.. University of Oxford; Reino Unido. University Aarhus; Dinamarca. Universidade do Minho; PortugalFil: Deco, Gustavo. Max Planck Institute For Human Cognitive And Brain Sciences; Alemania. Monash University; Australia. Institució Catalana de Recerca I Estudis Avançats; España. Universitat Pompeu Fabra; EspañaFil: Prado, Pavel. Universidad San Sebastián; Chile. Universidad Adolfo Ibañez; ChileFil: Ibañez, Agustin Mariano. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of California; Estados Unidos. Trinity College Dublin; IrlandaFil: Tagliazucchi, Enzo Rodolfo. Universidad de Buenos Aires; Argentina. Universidad de San Andrés; Argentina. Universidad Adolfo Ibáñez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaeLife Sciences Publications Ltd2023-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/228644Sanz Perl Hernandez, Yonatan; Fittipaldi, María Sol; Gonzalez Campo, Cecilia; Moguilner, Sebastián; Cruzat, Josephine; et al.; Model-based whole-brain perturbational landscape of neurodegenerative diseases; eLife Sciences Publications Ltd; eLife; 12; e83970; 6-2023; 1-252050-084XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.7554/elife.83970info:eu-repo/semantics/altIdentifier/url/https://elifesciences.org/articles/83970info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:22:54Zoai:ri.conicet.gov.ar:11336/228644instacron: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:34982025-09-10 13:22:54.372CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Model-based whole-brain perturbational landscape of neurodegenerative diseases
title Model-based whole-brain perturbational landscape of neurodegenerative diseases
spellingShingle Model-based whole-brain perturbational landscape of neurodegenerative diseases
Sanz Perl Hernandez, Yonatan
Dementia
Neuroimaging
Modeling
fMRI
title_short Model-based whole-brain perturbational landscape of neurodegenerative diseases
title_full Model-based whole-brain perturbational landscape of neurodegenerative diseases
title_fullStr Model-based whole-brain perturbational landscape of neurodegenerative diseases
title_full_unstemmed Model-based whole-brain perturbational landscape of neurodegenerative diseases
title_sort Model-based whole-brain perturbational landscape of neurodegenerative diseases
dc.creator.none.fl_str_mv Sanz Perl Hernandez, Yonatan
Fittipaldi, María Sol
Gonzalez Campo, Cecilia
Moguilner, Sebastián
Cruzat, Josephine
Fraile Vazquez, Matias E.
Herzog, Rubén
Kringelbach, Morten L.
Deco, Gustavo
Prado, Pavel
Ibañez, Agustin Mariano
Tagliazucchi, Enzo Rodolfo
author Sanz Perl Hernandez, Yonatan
author_facet Sanz Perl Hernandez, Yonatan
Fittipaldi, María Sol
Gonzalez Campo, Cecilia
Moguilner, Sebastián
Cruzat, Josephine
Fraile Vazquez, Matias E.
Herzog, Rubén
Kringelbach, Morten L.
Deco, Gustavo
Prado, Pavel
Ibañez, Agustin Mariano
Tagliazucchi, Enzo Rodolfo
author_role author
author2 Fittipaldi, María Sol
Gonzalez Campo, Cecilia
Moguilner, Sebastián
Cruzat, Josephine
Fraile Vazquez, Matias E.
Herzog, Rubén
Kringelbach, Morten L.
Deco, Gustavo
Prado, Pavel
Ibañez, Agustin Mariano
Tagliazucchi, Enzo Rodolfo
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Dementia
Neuroimaging
Modeling
fMRI
topic Dementia
Neuroimaging
Modeling
fMRI
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The treatment of neurodegenerative diseases is hindered by lack of interventions capable of steering multimodal whole-brain dynamics towards patterns indicative of preserved brain health. To address this problem, we combined deep learning with a model capable of repro-ducing whole-brain functional connectivity in patients diagnosed with Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD). These models included disease-specific atrophy maps as priors to modulate local parameters, revealing increased stability of hippocampal and insular dynamics as signatures of brain atrophy in AD and bvFTD, respectively. Using variational autoencoders, we visualized different pathologies and their severity as the evolution of trajectories in a low-dimensional latent space. Finally, we perturbed the model to reveal key AD-and bvFTD-specific regions to induce transitions from pathological to healthy brain states. Overall, we obtained novel insights on disease progression and control by means of external stimulation, while identifying dynamical mechanisms that underlie functional alterations in neuro degeneration.
Fil: Sanz Perl Hernandez, Yonatan. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universitat Pompeu Fabra; España. Universidad de San Andrés; Argentina
Fil: Fittipaldi, María Sol. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina
Fil: Gonzalez Campo, Cecilia. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Moguilner, Sebastián. Universidad Adolfo Ibañez; Chile. University of California; Estados Unidos
Fil: Cruzat, Josephine. Universitat Pompeu Fabra; España. Universidad Adolfo Ibañez; Chile
Fil: Fraile Vazquez, Matias E.. Universidad de San Andrés; Argentina
Fil: Herzog, Rubén. Universidad Adolfo Ibañez; Chile
Fil: Kringelbach, Morten L.. University of Oxford; Reino Unido. University Aarhus; Dinamarca. Universidade do Minho; Portugal
Fil: Deco, Gustavo. Max Planck Institute For Human Cognitive And Brain Sciences; Alemania. Monash University; Australia. Institució Catalana de Recerca I Estudis Avançats; España. Universitat Pompeu Fabra; España
Fil: Prado, Pavel. Universidad San Sebastián; Chile. Universidad Adolfo Ibañez; Chile
Fil: Ibañez, Agustin Mariano. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of California; Estados Unidos. Trinity College Dublin; Irlanda
Fil: Tagliazucchi, Enzo Rodolfo. Universidad de Buenos Aires; Argentina. Universidad de San Andrés; Argentina. Universidad Adolfo Ibáñez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description The treatment of neurodegenerative diseases is hindered by lack of interventions capable of steering multimodal whole-brain dynamics towards patterns indicative of preserved brain health. To address this problem, we combined deep learning with a model capable of repro-ducing whole-brain functional connectivity in patients diagnosed with Alzheimer’s disease (AD) and behavioral variant frontotemporal dementia (bvFTD). These models included disease-specific atrophy maps as priors to modulate local parameters, revealing increased stability of hippocampal and insular dynamics as signatures of brain atrophy in AD and bvFTD, respectively. Using variational autoencoders, we visualized different pathologies and their severity as the evolution of trajectories in a low-dimensional latent space. Finally, we perturbed the model to reveal key AD-and bvFTD-specific regions to induce transitions from pathological to healthy brain states. Overall, we obtained novel insights on disease progression and control by means of external stimulation, while identifying dynamical mechanisms that underlie functional alterations in neuro degeneration.
publishDate 2023
dc.date.none.fl_str_mv 2023-06
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/11336/228644
Sanz Perl Hernandez, Yonatan; Fittipaldi, María Sol; Gonzalez Campo, Cecilia; Moguilner, Sebastián; Cruzat, Josephine; et al.; Model-based whole-brain perturbational landscape of neurodegenerative diseases; eLife Sciences Publications Ltd; eLife; 12; e83970; 6-2023; 1-25
2050-084X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/228644
identifier_str_mv Sanz Perl Hernandez, Yonatan; Fittipaldi, María Sol; Gonzalez Campo, Cecilia; Moguilner, Sebastián; Cruzat, Josephine; et al.; Model-based whole-brain perturbational landscape of neurodegenerative diseases; eLife Sciences Publications Ltd; eLife; 12; e83970; 6-2023; 1-25
2050-084X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.7554/elife.83970
info:eu-repo/semantics/altIdentifier/url/https://elifesciences.org/articles/83970
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 eLife Sciences Publications Ltd
publisher.none.fl_str_mv eLife Sciences Publications Ltd
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_ 1842981262370799616
score 12.48226

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