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Large-scale network dynamics underlying the first few hundred milliseconds after stimulus presentation: An investigation of visual recognition memory using iEEG
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SYSNO ASEP 0576548 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Large-scale network dynamics underlying the first few hundred milliseconds after stimulus presentation: An investigation of visual recognition memory using iEEG Author(s) Kopal, Jakub (UIVT-O) RID, ORCID, SAI
Hlinka, Jaroslav (UIVT-O) RID, SAI, ORCID
Despouy, E. (FR)
Valton, L. (FR)
Denuelle, M. (FR)
Sol, J.-Ch. (FR)
Curot, J. (FR)
Barbeau, E. J. (FR)Number of authors 8 Source Title Human Brain Mapping. - : Wiley - ISSN 1065-9471
Roč. 44, č. 17 (2023), s. 5795-5809Number of pages 15 s. Language eng - English Country US - United States Keywords connectivity ; dynamics ; intracranial EEG ; network ; recognition memory OECD category Neurosciences (including psychophysiology R&D Projects GA19-11753S GA ČR - Czech Science Foundation (CSF) Method of publishing Open access Institutional support UIVT-O - RVO:67985807 UT WOS 001064434300001 EID SCOPUS 85170521754 DOI https://doi.org/10.1002/hbm.26477 Annotation Recognition memory is the ability to recognize previously encountered objects. Even this relatively simple, yet extremely fast, ability requires the coordinated activity of large-scale brain networks. However, little is known about the sub-second dynamics of these networks. The majority of current studies into large-scale network dynamics is primarily based on imaging techniques suffering from either poor temporal or spatial resolution. We investigated the dynamics of large-scale functional brain networks underlying recognition memory at the millisecond scale. Specifically, we analyzed dynamic effective connectivity from intracranial electroencephalography while epileptic subjects (n = 18) performed a fast visual recognition memory task. Our data-driven investigation using Granger causality and the analysis of communities with the Louvain algorithm spotlighted a dynamic interplay of two large-scale networks associated with successful recognition. The first network involved the right visual ventral stream and bilateral frontal regions. It was characterized by early, predominantly bottom-up information flow peaking at 115 ms. It was followed by the involvement of another network with predominantly top-down connectivity peaking at 220 ms, mainly in the left anterior hemisphere. The transition between these two networks was associated with changes in network topology, evolving from a more segregated to a more integrated state. These results highlight that distinct large-scale brain networks involved in visual recognition memory unfold early and quickly, within the first 300 ms after stimulus onset. Our study extends the current understanding of the rapid network changes during rapid cognitive processes. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2024 Electronic address https://dx.doi.org/10.1002/hbm.26477
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