The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations
Large variability exists across brain regions in health and disease, considering their cellular and molecular composition, connectivity, and function. Large-scale whole-brain models comprising coupled brain regions provide insights into the underlying dynamics that shape complex patterns of spontane...
Gespeichert in:
Veröffentlicht in: | Network neuroscience (Cambridge, Mass.) Mass.), 2023-06, Vol.7 (2), p.632-660 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 660 |
---|---|
container_issue | 2 |
container_start_page | 632 |
container_title | Network neuroscience (Cambridge, Mass.) |
container_volume | 7 |
creator | Perl, Yonatan Sanz Zamora-Lopez, Gorka Montbrió, Ernest Monge-Asensio, Martí Vohryzek, Jakub Fittipaldi, Sol Campo, Cecilia González Moguilner, Sebastián Ibañez, Agustín Tagliazucchi, Enzo Yeo, B. T. Thomas Kringelbach, Morten L. Deco, Gustavo |
description | Large variability exists across brain regions in health and disease, considering their cellular and molecular composition, connectivity, and function. Large-scale whole-brain models comprising coupled brain regions provide insights into the underlying dynamics that shape complex patterns of spontaneous brain activity. In particular, biophysically grounded mean-field whole-brain models in the asynchronous regime were used to demonstrate the dynamical consequences of including regional variability. Nevertheless, the role of heterogeneities when brain dynamics are supported by synchronous oscillating state, which is a ubiquitous phenomenon in brain, remains poorly understood. Here, we implemented two models capable of presenting oscillatory behavior with different levels of abstraction: a phenomenological Stuart–Landau model and an exact mean-field model. The fit of these models informed by structural- to functional-weighted MRI signal (T1w/T2w) allowed us to explore the implication of the inclusion of heterogeneities for modeling resting-state fMRI recordings from healthy participants. We found that disease-specific regional functional heterogeneity imposed dynamical consequences within the oscillatory regime in fMRI recordings from neurodegeneration with specific impacts on brain atrophy/structure (Alzheimer’s patients). Overall, we found that models with oscillations perform better when structural and functional regional heterogeneities are considered, showing that phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.
Significant progress has been made in understanding the effects of regional heterogeneity on whole-brain dynamics. With imaging technologies, the number of high-resolution reference maps of brain structure and function has been increased, and whole-brain computational models have provided a suitable avenue to investigate the mechanisms supporting the relations between these maps and whole-brain dynamics. Here, we investigate the role of the heterogeneities when synchronous behavior is present in brain dynamics, which we could represent by models capable of oscillating in the presence of a Hopf bifurcation. We found that models with oscillations more faithfully reproduce empirical properties when structural and functional regional heterogeneities are considered, showing that both phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation. |
doi_str_mv | 10.1162/netn_a_00299 |
format | Article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_proquest_miscellaneous_2832844369</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_d706800f564043e2bebf8ca261a3b777</doaj_id><sourcerecordid>2832844369</sourcerecordid><originalsourceid>FETCH-LOGICAL-c568t-266eb5f2aeb1a0537229b395aed25d3b9131c9dd8fbe2dfc378506b0b8bb79903</originalsourceid><addsrcrecordid>eNptks1rFDEUwAdRbKm9eZYBLz04mo_J10mkaFsoeKk3ISSZN7tZZiZjkm1Z_3ozbq3bUggkvPzye-8lqaq3GH3EmJNPE-RJG40QUepFdUxaQRosGH55sD6qTlPaoMJgglErX1dHVFAlpODH1c-bNdR-nI3LdejrCCsfJjPUa8gQwwom8HlX-6m-W4cBGhtNWXe7yYzepSWey_k5QoLJwWIIyflhMLlo0pvqVW-GBKf380n149vXm_PL5vr7xdX5l-vGMS5zQzgHy3piwGKDGBWEKEsVM9AR1lGrMMVOdZ3sLZCud1RIhrhFVlorlEL0pLrae7tgNnqOfjRxp4Px-m8gxJU2MXs3gO4E4hKhnvEWtRSIBdtLZwjHhlohRHF93rvmrR2hczDlaIZH0sc7k1_rVbjVGFFMiGTFcHZviOHXFlLWo08OyqVMELZJE0mJbFvKVUHfP0E3YRvL_S-UVEzJUmehPuwpF0NKEfqHajDSyzfQh9-g4O8OO3iA_z36_xZHf5BwcdwKTzRtUQE1QYRqxJfx289PU5w9Y3i2mj-fItGV</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2889598564</pqid></control><display><type>article</type><title>The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations</title><source>DOAJ Directory of Open Access Journals</source><source>PubMed Central Open Access</source><source>EZB-FREE-00999 freely available EZB journals</source><source>ProQuest Central UK/Ireland</source><source>PubMed Central</source><source>ProQuest Central</source><creator>Perl, Yonatan Sanz ; Zamora-Lopez, Gorka ; Montbrió, Ernest ; Monge-Asensio, Martí ; Vohryzek, Jakub ; Fittipaldi, Sol ; Campo, Cecilia González ; Moguilner, Sebastián ; Ibañez, Agustín ; Tagliazucchi, Enzo ; Yeo, B. T. Thomas ; Kringelbach, Morten L. ; Deco, Gustavo</creator><creatorcontrib>Perl, Yonatan Sanz ; Zamora-Lopez, Gorka ; Montbrió, Ernest ; Monge-Asensio, Martí ; Vohryzek, Jakub ; Fittipaldi, Sol ; Campo, Cecilia González ; Moguilner, Sebastián ; Ibañez, Agustín ; Tagliazucchi, Enzo ; Yeo, B. T. Thomas ; Kringelbach, Morten L. ; Deco, Gustavo</creatorcontrib><description>Large variability exists across brain regions in health and disease, considering their cellular and molecular composition, connectivity, and function. Large-scale whole-brain models comprising coupled brain regions provide insights into the underlying dynamics that shape complex patterns of spontaneous brain activity. In particular, biophysically grounded mean-field whole-brain models in the asynchronous regime were used to demonstrate the dynamical consequences of including regional variability. Nevertheless, the role of heterogeneities when brain dynamics are supported by synchronous oscillating state, which is a ubiquitous phenomenon in brain, remains poorly understood. Here, we implemented two models capable of presenting oscillatory behavior with different levels of abstraction: a phenomenological Stuart–Landau model and an exact mean-field model. The fit of these models informed by structural- to functional-weighted MRI signal (T1w/T2w) allowed us to explore the implication of the inclusion of heterogeneities for modeling resting-state fMRI recordings from healthy participants. We found that disease-specific regional functional heterogeneity imposed dynamical consequences within the oscillatory regime in fMRI recordings from neurodegeneration with specific impacts on brain atrophy/structure (Alzheimer’s patients). Overall, we found that models with oscillations perform better when structural and functional regional heterogeneities are considered, showing that phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.
Significant progress has been made in understanding the effects of regional heterogeneity on whole-brain dynamics. With imaging technologies, the number of high-resolution reference maps of brain structure and function has been increased, and whole-brain computational models have provided a suitable avenue to investigate the mechanisms supporting the relations between these maps and whole-brain dynamics. Here, we investigate the role of the heterogeneities when synchronous behavior is present in brain dynamics, which we could represent by models capable of oscillating in the presence of a Hopf bifurcation. We found that models with oscillations more faithfully reproduce empirical properties when structural and functional regional heterogeneities are considered, showing that both phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.</description><identifier>ISSN: 2472-1751</identifier><identifier>EISSN: 2472-1751</identifier><identifier>DOI: 10.1162/netn_a_00299</identifier><identifier>PMID: 37397876</identifier><language>eng</language><publisher>One Broadway, 12th Floor, Cambridge, Massachusetts 02142, USA: MIT Press</publisher><subject>Atrophy ; Brain ; Brain mapping ; Chemical composition ; Computational neuroscience ; Dynamics ; Exact mean-field model ; Functional anatomy ; Functional magnetic resonance imaging ; Heterogeneity ; Hopf bifurcation ; Magnetic resonance imaging ; Neural networks ; Neuroimaging ; Oscillations ; Regional heterogeneity ; Structure-function relationships ; Whole-brain model</subject><ispartof>Network neuroscience (Cambridge, Mass.), 2023-06, Vol.7 (2), p.632-660</ispartof><rights>2023 Massachusetts Institute of Technology.</rights><rights>2023. This work is published under https://creativecommons.org/licenses/by/4.0/legalcode (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2023 Massachusetts Institute of Technology 2023 Massachusetts Institute of Technology</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c568t-266eb5f2aeb1a0537229b395aed25d3b9131c9dd8fbe2dfc378506b0b8bb79903</citedby><cites>FETCH-LOGICAL-c568t-266eb5f2aeb1a0537229b395aed25d3b9131c9dd8fbe2dfc378506b0b8bb79903</cites><orcidid>0000-0002-1270-5564</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10312285/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2889598564?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,21388,27924,27925,33744,33745,43805,53791,53793,64385,64387,64389,72469</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37397876$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Perl, Yonatan Sanz</creatorcontrib><creatorcontrib>Zamora-Lopez, Gorka</creatorcontrib><creatorcontrib>Montbrió, Ernest</creatorcontrib><creatorcontrib>Monge-Asensio, Martí</creatorcontrib><creatorcontrib>Vohryzek, Jakub</creatorcontrib><creatorcontrib>Fittipaldi, Sol</creatorcontrib><creatorcontrib>Campo, Cecilia González</creatorcontrib><creatorcontrib>Moguilner, Sebastián</creatorcontrib><creatorcontrib>Ibañez, Agustín</creatorcontrib><creatorcontrib>Tagliazucchi, Enzo</creatorcontrib><creatorcontrib>Yeo, B. T. Thomas</creatorcontrib><creatorcontrib>Kringelbach, Morten L.</creatorcontrib><creatorcontrib>Deco, Gustavo</creatorcontrib><title>The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations</title><title>Network neuroscience (Cambridge, Mass.)</title><addtitle>Netw Neurosci</addtitle><description>Large variability exists across brain regions in health and disease, considering their cellular and molecular composition, connectivity, and function. Large-scale whole-brain models comprising coupled brain regions provide insights into the underlying dynamics that shape complex patterns of spontaneous brain activity. In particular, biophysically grounded mean-field whole-brain models in the asynchronous regime were used to demonstrate the dynamical consequences of including regional variability. Nevertheless, the role of heterogeneities when brain dynamics are supported by synchronous oscillating state, which is a ubiquitous phenomenon in brain, remains poorly understood. Here, we implemented two models capable of presenting oscillatory behavior with different levels of abstraction: a phenomenological Stuart–Landau model and an exact mean-field model. The fit of these models informed by structural- to functional-weighted MRI signal (T1w/T2w) allowed us to explore the implication of the inclusion of heterogeneities for modeling resting-state fMRI recordings from healthy participants. We found that disease-specific regional functional heterogeneity imposed dynamical consequences within the oscillatory regime in fMRI recordings from neurodegeneration with specific impacts on brain atrophy/structure (Alzheimer’s patients). Overall, we found that models with oscillations perform better when structural and functional regional heterogeneities are considered, showing that phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.
Significant progress has been made in understanding the effects of regional heterogeneity on whole-brain dynamics. With imaging technologies, the number of high-resolution reference maps of brain structure and function has been increased, and whole-brain computational models have provided a suitable avenue to investigate the mechanisms supporting the relations between these maps and whole-brain dynamics. Here, we investigate the role of the heterogeneities when synchronous behavior is present in brain dynamics, which we could represent by models capable of oscillating in the presence of a Hopf bifurcation. We found that models with oscillations more faithfully reproduce empirical properties when structural and functional regional heterogeneities are considered, showing that both phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.</description><subject>Atrophy</subject><subject>Brain</subject><subject>Brain mapping</subject><subject>Chemical composition</subject><subject>Computational neuroscience</subject><subject>Dynamics</subject><subject>Exact mean-field model</subject><subject>Functional anatomy</subject><subject>Functional magnetic resonance imaging</subject><subject>Heterogeneity</subject><subject>Hopf bifurcation</subject><subject>Magnetic resonance imaging</subject><subject>Neural networks</subject><subject>Neuroimaging</subject><subject>Oscillations</subject><subject>Regional heterogeneity</subject><subject>Structure-function relationships</subject><subject>Whole-brain model</subject><issn>2472-1751</issn><issn>2472-1751</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>DOA</sourceid><recordid>eNptks1rFDEUwAdRbKm9eZYBLz04mo_J10mkaFsoeKk3ISSZN7tZZiZjkm1Z_3ozbq3bUggkvPzye-8lqaq3GH3EmJNPE-RJG40QUepFdUxaQRosGH55sD6qTlPaoMJgglErX1dHVFAlpODH1c-bNdR-nI3LdejrCCsfJjPUa8gQwwom8HlX-6m-W4cBGhtNWXe7yYzepSWey_k5QoLJwWIIyflhMLlo0pvqVW-GBKf380n149vXm_PL5vr7xdX5l-vGMS5zQzgHy3piwGKDGBWEKEsVM9AR1lGrMMVOdZ3sLZCud1RIhrhFVlorlEL0pLrae7tgNnqOfjRxp4Px-m8gxJU2MXs3gO4E4hKhnvEWtRSIBdtLZwjHhlohRHF93rvmrR2hczDlaIZH0sc7k1_rVbjVGFFMiGTFcHZviOHXFlLWo08OyqVMELZJE0mJbFvKVUHfP0E3YRvL_S-UVEzJUmehPuwpF0NKEfqHajDSyzfQh9-g4O8OO3iA_z36_xZHf5BwcdwKTzRtUQE1QYRqxJfx289PU5w9Y3i2mj-fItGV</recordid><startdate>20230630</startdate><enddate>20230630</enddate><creator>Perl, Yonatan Sanz</creator><creator>Zamora-Lopez, Gorka</creator><creator>Montbrió, Ernest</creator><creator>Monge-Asensio, Martí</creator><creator>Vohryzek, Jakub</creator><creator>Fittipaldi, Sol</creator><creator>Campo, Cecilia González</creator><creator>Moguilner, Sebastián</creator><creator>Ibañez, Agustín</creator><creator>Tagliazucchi, Enzo</creator><creator>Yeo, B. T. Thomas</creator><creator>Kringelbach, Morten L.</creator><creator>Deco, Gustavo</creator><general>MIT Press</general><general>MIT Press Journals, The</general><general>The MIT Press</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>LK8</scope><scope>M7P</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-1270-5564</orcidid></search><sort><creationdate>20230630</creationdate><title>The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations</title><author>Perl, Yonatan Sanz ; Zamora-Lopez, Gorka ; Montbrió, Ernest ; Monge-Asensio, Martí ; Vohryzek, Jakub ; Fittipaldi, Sol ; Campo, Cecilia González ; Moguilner, Sebastián ; Ibañez, Agustín ; Tagliazucchi, Enzo ; Yeo, B. T. Thomas ; Kringelbach, Morten L. ; Deco, Gustavo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c568t-266eb5f2aeb1a0537229b395aed25d3b9131c9dd8fbe2dfc378506b0b8bb79903</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Atrophy</topic><topic>Brain</topic><topic>Brain mapping</topic><topic>Chemical composition</topic><topic>Computational neuroscience</topic><topic>Dynamics</topic><topic>Exact mean-field model</topic><topic>Functional anatomy</topic><topic>Functional magnetic resonance imaging</topic><topic>Heterogeneity</topic><topic>Hopf bifurcation</topic><topic>Magnetic resonance imaging</topic><topic>Neural networks</topic><topic>Neuroimaging</topic><topic>Oscillations</topic><topic>Regional heterogeneity</topic><topic>Structure-function relationships</topic><topic>Whole-brain model</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Perl, Yonatan Sanz</creatorcontrib><creatorcontrib>Zamora-Lopez, Gorka</creatorcontrib><creatorcontrib>Montbrió, Ernest</creatorcontrib><creatorcontrib>Monge-Asensio, Martí</creatorcontrib><creatorcontrib>Vohryzek, Jakub</creatorcontrib><creatorcontrib>Fittipaldi, Sol</creatorcontrib><creatorcontrib>Campo, Cecilia González</creatorcontrib><creatorcontrib>Moguilner, Sebastián</creatorcontrib><creatorcontrib>Ibañez, Agustín</creatorcontrib><creatorcontrib>Tagliazucchi, Enzo</creatorcontrib><creatorcontrib>Yeo, B. T. Thomas</creatorcontrib><creatorcontrib>Kringelbach, Morten L.</creatorcontrib><creatorcontrib>Deco, Gustavo</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Biological Science Collection</collection><collection>Biological Science Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Network neuroscience (Cambridge, Mass.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Perl, Yonatan Sanz</au><au>Zamora-Lopez, Gorka</au><au>Montbrió, Ernest</au><au>Monge-Asensio, Martí</au><au>Vohryzek, Jakub</au><au>Fittipaldi, Sol</au><au>Campo, Cecilia González</au><au>Moguilner, Sebastián</au><au>Ibañez, Agustín</au><au>Tagliazucchi, Enzo</au><au>Yeo, B. T. Thomas</au><au>Kringelbach, Morten L.</au><au>Deco, Gustavo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations</atitle><jtitle>Network neuroscience (Cambridge, Mass.)</jtitle><addtitle>Netw Neurosci</addtitle><date>2023-06-30</date><risdate>2023</risdate><volume>7</volume><issue>2</issue><spage>632</spage><epage>660</epage><pages>632-660</pages><issn>2472-1751</issn><eissn>2472-1751</eissn><abstract>Large variability exists across brain regions in health and disease, considering their cellular and molecular composition, connectivity, and function. Large-scale whole-brain models comprising coupled brain regions provide insights into the underlying dynamics that shape complex patterns of spontaneous brain activity. In particular, biophysically grounded mean-field whole-brain models in the asynchronous regime were used to demonstrate the dynamical consequences of including regional variability. Nevertheless, the role of heterogeneities when brain dynamics are supported by synchronous oscillating state, which is a ubiquitous phenomenon in brain, remains poorly understood. Here, we implemented two models capable of presenting oscillatory behavior with different levels of abstraction: a phenomenological Stuart–Landau model and an exact mean-field model. The fit of these models informed by structural- to functional-weighted MRI signal (T1w/T2w) allowed us to explore the implication of the inclusion of heterogeneities for modeling resting-state fMRI recordings from healthy participants. We found that disease-specific regional functional heterogeneity imposed dynamical consequences within the oscillatory regime in fMRI recordings from neurodegeneration with specific impacts on brain atrophy/structure (Alzheimer’s patients). Overall, we found that models with oscillations perform better when structural and functional regional heterogeneities are considered, showing that phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.
Significant progress has been made in understanding the effects of regional heterogeneity on whole-brain dynamics. With imaging technologies, the number of high-resolution reference maps of brain structure and function has been increased, and whole-brain computational models have provided a suitable avenue to investigate the mechanisms supporting the relations between these maps and whole-brain dynamics. Here, we investigate the role of the heterogeneities when synchronous behavior is present in brain dynamics, which we could represent by models capable of oscillating in the presence of a Hopf bifurcation. We found that models with oscillations more faithfully reproduce empirical properties when structural and functional regional heterogeneities are considered, showing that both phenomenological and biophysical models behave similarly at the brink of the Hopf bifurcation.</abstract><cop>One Broadway, 12th Floor, Cambridge, Massachusetts 02142, USA</cop><pub>MIT Press</pub><pmid>37397876</pmid><doi>10.1162/netn_a_00299</doi><tpages>29</tpages><orcidid>https://orcid.org/0000-0002-1270-5564</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 2472-1751 |
ispartof | Network neuroscience (Cambridge, Mass.), 2023-06, Vol.7 (2), p.632-660 |
issn | 2472-1751 2472-1751 |
language | eng |
recordid | cdi_proquest_miscellaneous_2832844369 |
source | DOAJ Directory of Open Access Journals; PubMed Central Open Access; EZB-FREE-00999 freely available EZB journals; ProQuest Central UK/Ireland; PubMed Central; ProQuest Central |
subjects | Atrophy Brain Brain mapping Chemical composition Computational neuroscience Dynamics Exact mean-field model Functional anatomy Functional magnetic resonance imaging Heterogeneity Hopf bifurcation Magnetic resonance imaging Neural networks Neuroimaging Oscillations Regional heterogeneity Structure-function relationships Whole-brain model |
title | The impact of regional heterogeneity in whole-brain dynamics in the presence of oscillations |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-20T12%3A29%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20impact%20of%20regional%20heterogeneity%20in%20whole-brain%20dynamics%20in%20the%20presence%20of%20oscillations&rft.jtitle=Network%20neuroscience%20(Cambridge,%20Mass.)&rft.au=Perl,%20Yonatan%20Sanz&rft.date=2023-06-30&rft.volume=7&rft.issue=2&rft.spage=632&rft.epage=660&rft.pages=632-660&rft.issn=2472-1751&rft.eissn=2472-1751&rft_id=info:doi/10.1162/netn_a_00299&rft_dat=%3Cproquest_pubme%3E2832844369%3C/proquest_pubme%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2889598564&rft_id=info:pmid/37397876&rft_doaj_id=oai_doaj_org_article_d706800f564043e2bebf8ca261a3b777&rfr_iscdi=true |