Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy
Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective meth...
Gespeichert in:
Veröffentlicht in: | arXiv.org 2018-09 |
---|---|
Hauptverfasser: | , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | |
---|---|
container_issue | |
container_start_page | |
container_title | arXiv.org |
container_volume | |
creator | Reddy, Pranav G Betzel, Richard F Khambhati, Ankit N Shah, Preya Kini, Lohith Litt, Brian Lucas, Thomas H Davis, Kathryn A Bassett, Danielle S |
description | Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention. |
format | Article |
fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2102640957</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2102640957</sourcerecordid><originalsourceid>FETCH-proquest_journals_21026409573</originalsourceid><addsrcrecordid>eNqNjrEKwjAURYMgWLT_EHAupElrdVVbnVzUuYSaQmrNi3kJ0r83gx_gdOFwONwZSbgQebYtOF-QFHFgjPFNxctSJOR-UkZ53VFpHvSiggNppIeX7uRIr8FacJ724GgTTOc1mIj3TmoTZf8B96THycioI42stnpUFqcVmfdyRJX-dknWTX07nDPr4B0U-naA4GILW57HMwXblZX4z_oC3ztA_Q</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2102640957</pqid></control><display><type>article</type><title>Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy</title><source>Free E- Journals</source><creator>Reddy, Pranav G ; Betzel, Richard F ; Khambhati, Ankit N ; Shah, Preya ; Kini, Lohith ; Litt, Brian ; Lucas, Thomas H ; Davis, Kathryn A ; Bassett, Danielle S</creator><creatorcontrib>Reddy, Pranav G ; Betzel, Richard F ; Khambhati, Ankit N ; Shah, Preya ; Kini, Lohith ; Litt, Brian ; Lucas, Thomas H ; Davis, Kathryn A ; Bassett, Danielle S</creatorcontrib><description>Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Attention Deficit Hyperactivity Disorder ; Brain ; Dynamics ; Epilepsy ; Mathematical models ; Medical imaging ; Neurological diseases ; Neurology ; Pathology ; Patients ; Predictions ; Refractory materials ; Seizures</subject><ispartof>arXiv.org, 2018-09</ispartof><rights>2018. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>780,784</link.rule.ids></links><search><creatorcontrib>Reddy, Pranav G</creatorcontrib><creatorcontrib>Betzel, Richard F</creatorcontrib><creatorcontrib>Khambhati, Ankit N</creatorcontrib><creatorcontrib>Shah, Preya</creatorcontrib><creatorcontrib>Kini, Lohith</creatorcontrib><creatorcontrib>Litt, Brian</creatorcontrib><creatorcontrib>Lucas, Thomas H</creatorcontrib><creatorcontrib>Davis, Kathryn A</creatorcontrib><creatorcontrib>Bassett, Danielle S</creatorcontrib><title>Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy</title><title>arXiv.org</title><description>Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention.</description><subject>Attention Deficit Hyperactivity Disorder</subject><subject>Brain</subject><subject>Dynamics</subject><subject>Epilepsy</subject><subject>Mathematical models</subject><subject>Medical imaging</subject><subject>Neurological diseases</subject><subject>Neurology</subject><subject>Pathology</subject><subject>Patients</subject><subject>Predictions</subject><subject>Refractory materials</subject><subject>Seizures</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqNjrEKwjAURYMgWLT_EHAupElrdVVbnVzUuYSaQmrNi3kJ0r83gx_gdOFwONwZSbgQebYtOF-QFHFgjPFNxctSJOR-UkZ53VFpHvSiggNppIeX7uRIr8FacJ724GgTTOc1mIj3TmoTZf8B96THycioI42stnpUFqcVmfdyRJX-dknWTX07nDPr4B0U-naA4GILW57HMwXblZX4z_oC3ztA_Q</recordid><startdate>20180911</startdate><enddate>20180911</enddate><creator>Reddy, Pranav G</creator><creator>Betzel, Richard F</creator><creator>Khambhati, Ankit N</creator><creator>Shah, Preya</creator><creator>Kini, Lohith</creator><creator>Litt, Brian</creator><creator>Lucas, Thomas H</creator><creator>Davis, Kathryn A</creator><creator>Bassett, Danielle S</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20180911</creationdate><title>Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy</title><author>Reddy, Pranav G ; Betzel, Richard F ; Khambhati, Ankit N ; Shah, Preya ; Kini, Lohith ; Litt, Brian ; Lucas, Thomas H ; Davis, Kathryn A ; Bassett, Danielle S</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_21026409573</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Attention Deficit Hyperactivity Disorder</topic><topic>Brain</topic><topic>Dynamics</topic><topic>Epilepsy</topic><topic>Mathematical models</topic><topic>Medical imaging</topic><topic>Neurological diseases</topic><topic>Neurology</topic><topic>Pathology</topic><topic>Patients</topic><topic>Predictions</topic><topic>Refractory materials</topic><topic>Seizures</topic><toplevel>online_resources</toplevel><creatorcontrib>Reddy, Pranav G</creatorcontrib><creatorcontrib>Betzel, Richard F</creatorcontrib><creatorcontrib>Khambhati, Ankit N</creatorcontrib><creatorcontrib>Shah, Preya</creatorcontrib><creatorcontrib>Kini, Lohith</creatorcontrib><creatorcontrib>Litt, Brian</creatorcontrib><creatorcontrib>Lucas, Thomas H</creatorcontrib><creatorcontrib>Davis, Kathryn A</creatorcontrib><creatorcontrib>Bassett, Danielle S</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</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>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Reddy, Pranav G</au><au>Betzel, Richard F</au><au>Khambhati, Ankit N</au><au>Shah, Preya</au><au>Kini, Lohith</au><au>Litt, Brian</au><au>Lucas, Thomas H</au><au>Davis, Kathryn A</au><au>Bassett, Danielle S</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy</atitle><jtitle>arXiv.org</jtitle><date>2018-09-11</date><risdate>2018</risdate><eissn>2331-8422</eissn><abstract>Focal epilepsy is a devastating neurological disorder that affects an overwhelming number of patients worldwide, many of whom prove resistant to medication. The efficacy of current innovative technologies for the treatment of these patients has been stalled by the lack of accurate and effective methods to fuse multimodal neuroimaging data to map anatomical targets driving seizure dynamics. Here we propose a parsimonious model that explains how large-scale anatomical networks and shared genetic constraints shape inter-regional communication in focal epilepsy. In extensive ECoG recordings acquired from a group of patients with medically refractory focal-onset epilepsy, we find that ictal and preictal functional brain network dynamics can be accurately predicted from features of brain anatomy and geometry, patterns of white matter connectivity, and constraints complicit in patterns of gene coexpression, all of which are conserved across healthy adult populations. Moreover, we uncover evidence that markers of non-conserved architecture, potentially driven by idiosyncratic pathology of single subjects, are most prevalent in high frequency ictal dynamics and low frequency preictal dynamics. Finally, we find that ictal dynamics are better predicted by white matter features and more poorly predicted by geometry and genetic constraints than preictal dynamics, suggesting that the functional brain network dynamics manifest in seizures rely on - and may directly propagate along - underlying white matter structure that is largely conserved across humans. Broadly, our work offers insights into the generic architectural principles of the human brain that impact seizure dynamics, and could be extended to further our understanding, models, and predictions of subject-level pathology and response to intervention.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | EISSN: 2331-8422 |
ispartof | arXiv.org, 2018-09 |
issn | 2331-8422 |
language | eng |
recordid | cdi_proquest_journals_2102640957 |
source | Free E- Journals |
subjects | Attention Deficit Hyperactivity Disorder Brain Dynamics Epilepsy Mathematical models Medical imaging Neurological diseases Neurology Pathology Patients Predictions Refractory materials Seizures |
title | Genetic and Neuroanatomical Support for Functional Brain Network Dynamics in Epilepsy |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T15%3A35%3A57IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Genetic%20and%20Neuroanatomical%20Support%20for%20Functional%20Brain%20Network%20Dynamics%20in%20Epilepsy&rft.jtitle=arXiv.org&rft.au=Reddy,%20Pranav%20G&rft.date=2018-09-11&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2102640957%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2102640957&rft_id=info:pmid/&rfr_iscdi=true |