Matches in SemOpenAlex for { <https://semopenalex.org/work/W2889437488> ?p ?o ?g. }
- W2889437488 abstract "Complex thought and behavior arise through dynamic recruitment of large-scale brain networks. The signatures of this process may be observable in electrophysiological data; yet robust modeling of rapidly changing functional network structure on rapid cognitive timescales remains a considerable challenge. Here, we present one potential solution using Hidden Markov Models (HMMs), which are able to identify brain states characterized by engaging distinct functional networks that reoccur over time. We show how the HMM can be inferred on continuous, parcellated source-space Magnetoencephalography (MEG) task data in an unsupervised manner, without any knowledge of the task timings. We apply this to a freely available MEG dataset in which participants completed a face perception task, and reveal task-dependent HMM states that represent whole-brain dynamic networks transiently bursting at millisecond time scales as cognition unfolds. The analysis pipeline demonstrates a general way in which the HMM can be used to do a statistically valid whole-brain, group-level task analysis on MEG task data, which could be readily adapted to a wide range of task-based studies." @default.
- W2889437488 created "2018-09-07" @default.
- W2889437488 creator A5014616472 @default.
- W2889437488 creator A5048405025 @default.
- W2889437488 creator A5051947577 @default.
- W2889437488 creator A5059314195 @default.
- W2889437488 creator A5088377480 @default.
- W2889437488 creator A5090284787 @default.
- W2889437488 date "2018-08-28" @default.
- W2889437488 modified "2023-10-17" @default.
- W2889437488 title "Task-Evoked Dynamic Network Analysis Through Hidden Markov Modeling" @default.
- W2889437488 cites W1951380151 @default.
- W2889437488 cites W1967125431 @default.
- W2889437488 cites W1974554864 @default.
- W2889437488 cites W1993938052 @default.
- W2889437488 cites W2012423033 @default.
- W2889437488 cites W2017288758 @default.
- W2889437488 cites W2021285908 @default.
- W2889437488 cites W2033881971 @default.
- W2889437488 cites W2040737547 @default.
- W2889437488 cites W2060108923 @default.
- W2889437488 cites W206280282 @default.
- W2889437488 cites W2083110905 @default.
- W2889437488 cites W2103152221 @default.
- W2889437488 cites W2105594594 @default.
- W2889437488 cites W2114863284 @default.
- W2889437488 cites W2122418437 @default.
- W2889437488 cites W2126693856 @default.
- W2889437488 cites W2138790588 @default.
- W2889437488 cites W2141224535 @default.
- W2889437488 cites W2146141169 @default.
- W2889437488 cites W2148261180 @default.
- W2889437488 cites W2153667747 @default.
- W2889437488 cites W2175184313 @default.
- W2889437488 cites W2418779657 @default.
- W2889437488 cites W2499800833 @default.
- W2889437488 cites W2520939316 @default.
- W2889437488 cites W2537240939 @default.
- W2889437488 cites W2599888381 @default.
- W2889437488 cites W2625709425 @default.
- W2889437488 cites W2724344943 @default.
- W2889437488 cites W2737349650 @default.
- W2889437488 cites W2764285534 @default.
- W2889437488 cites W2765216222 @default.
- W2889437488 cites W2767814366 @default.
- W2889437488 cites W2777412843 @default.
- W2889437488 cites W2889437488 @default.
- W2889437488 cites W2950721622 @default.
- W2889437488 cites W2953012587 @default.
- W2889437488 cites W3101590534 @default.
- W2889437488 cites W4247122376 @default.
- W2889437488 cites W84782489 @default.
- W2889437488 doi "https://doi.org/10.3389/fnins.2018.00603" @default.
- W2889437488 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6121015" @default.
- W2889437488 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30210284" @default.
- W2889437488 hasPublicationYear "2018" @default.
- W2889437488 type Work @default.
- W2889437488 sameAs 2889437488 @default.
- W2889437488 citedByCount "115" @default.
- W2889437488 countsByYear W28894374882018 @default.
- W2889437488 countsByYear W28894374882019 @default.
- W2889437488 countsByYear W28894374882020 @default.
- W2889437488 countsByYear W28894374882021 @default.
- W2889437488 countsByYear W28894374882022 @default.
- W2889437488 countsByYear W28894374882023 @default.
- W2889437488 crossrefType "journal-article" @default.
- W2889437488 hasAuthorship W2889437488A5014616472 @default.
- W2889437488 hasAuthorship W2889437488A5048405025 @default.
- W2889437488 hasAuthorship W2889437488A5051947577 @default.
- W2889437488 hasAuthorship W2889437488A5059314195 @default.
- W2889437488 hasAuthorship W2889437488A5088377480 @default.
- W2889437488 hasAuthorship W2889437488A5090284787 @default.
- W2889437488 hasBestOaLocation W28894374881 @default.
- W2889437488 hasConcept C153180895 @default.
- W2889437488 hasConcept C154945302 @default.
- W2889437488 hasConcept C15744967 @default.
- W2889437488 hasConcept C162324750 @default.
- W2889437488 hasConcept C169760540 @default.
- W2889437488 hasConcept C169900460 @default.
- W2889437488 hasConcept C187736073 @default.
- W2889437488 hasConcept C23224414 @default.
- W2889437488 hasConcept C2779226451 @default.
- W2889437488 hasConcept C2780451532 @default.
- W2889437488 hasConcept C2781312939 @default.
- W2889437488 hasConcept C28490314 @default.
- W2889437488 hasConcept C41008148 @default.
- W2889437488 hasConcept C522805319 @default.
- W2889437488 hasConcept C556910895 @default.
- W2889437488 hasConcept C58693492 @default.
- W2889437488 hasConceptScore W2889437488C153180895 @default.
- W2889437488 hasConceptScore W2889437488C154945302 @default.
- W2889437488 hasConceptScore W2889437488C15744967 @default.
- W2889437488 hasConceptScore W2889437488C162324750 @default.
- W2889437488 hasConceptScore W2889437488C169760540 @default.
- W2889437488 hasConceptScore W2889437488C169900460 @default.
- W2889437488 hasConceptScore W2889437488C187736073 @default.
- W2889437488 hasConceptScore W2889437488C23224414 @default.
- W2889437488 hasConceptScore W2889437488C2779226451 @default.
- W2889437488 hasConceptScore W2889437488C2780451532 @default.
- W2889437488 hasConceptScore W2889437488C2781312939 @default.