Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding.
Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on emb...
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2015-11-01
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Online Access: | https://doi.org/10.1371/journal.pcbi.1004537 |
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doaj-e5d082addff04dfb8a2d3944dfc9170e2021-04-21T14:59:08ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582015-11-011111e100453710.1371/journal.pcbi.1004537Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding.Satohiro TajimaToru YanagawaNaotaka FujiiTaro ToyoizumiBrain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction, that permits a simultaneous characterization of complexity in local dynamics, directed interactions between brain areas, and how the complexity is produced by the interactions. We demonstrate this method in large-scale electrophysiological recordings from awake and anesthetized monkeys. The cross-embedding method captures structured interaction underlying cortex-wide dynamics that may be missed by conventional correlation-based analysis, demonstrating a critical role of time-series analysis in characterizing brain state. The method reveals a consciousness-related hierarchy of cortical areas, where dynamical complexity increases along with cross-area information flow. These findings demonstrate the advantages of the cross-embedding method in deciphering large-scale and heterogeneous neuronal systems, suggesting a crucial contribution by sensory-frontoparietal interactions to the emergence of complex brain dynamics during consciousness.https://doi.org/10.1371/journal.pcbi.1004537 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Satohiro Tajima Toru Yanagawa Naotaka Fujii Taro Toyoizumi |
spellingShingle |
Satohiro Tajima Toru Yanagawa Naotaka Fujii Taro Toyoizumi Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding. PLoS Computational Biology |
author_facet |
Satohiro Tajima Toru Yanagawa Naotaka Fujii Taro Toyoizumi |
author_sort |
Satohiro Tajima |
title |
Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding. |
title_short |
Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding. |
title_full |
Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding. |
title_fullStr |
Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding. |
title_full_unstemmed |
Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding. |
title_sort |
untangling brain-wide dynamics in consciousness by cross-embedding. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS Computational Biology |
issn |
1553-734X 1553-7358 |
publishDate |
2015-11-01 |
description |
Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction, that permits a simultaneous characterization of complexity in local dynamics, directed interactions between brain areas, and how the complexity is produced by the interactions. We demonstrate this method in large-scale electrophysiological recordings from awake and anesthetized monkeys. The cross-embedding method captures structured interaction underlying cortex-wide dynamics that may be missed by conventional correlation-based analysis, demonstrating a critical role of time-series analysis in characterizing brain state. The method reveals a consciousness-related hierarchy of cortical areas, where dynamical complexity increases along with cross-area information flow. These findings demonstrate the advantages of the cross-embedding method in deciphering large-scale and heterogeneous neuronal systems, suggesting a crucial contribution by sensory-frontoparietal interactions to the emergence of complex brain dynamics during consciousness. |
url |
https://doi.org/10.1371/journal.pcbi.1004537 |
work_keys_str_mv |
AT satohirotajima untanglingbrainwidedynamicsinconsciousnessbycrossembedding AT toruyanagawa untanglingbrainwidedynamicsinconsciousnessbycrossembedding AT naotakafujii untanglingbrainwidedynamicsinconsciousnessbycrossembedding AT tarotoyoizumi untanglingbrainwidedynamicsinconsciousnessbycrossembedding |
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1714668097299808256 |