Large-scale functional coupling and computational modelling reveal frontotemporal hotspots in distributed network connectivity during working memory recognition, encoding, and retrieval
Wuyang Zhang, Haoru Zhang, Yuantao Deng, Xinran Deng, Yuchao Ji, Genbo Wang, Chen YaoiD, Yue WangiD, Yingchao YuiD, Yiting Liu, Yuanwu Zhu, Wenbo Wang, Lanhui Huang, Sixian Li, Yue Yuan, Junfan CheniD, Aoqing Luo, Yaochu Jin, J S CheniD, Yuchen Xiao
Abstract
Working memory depends on coordinated activity across distributed brain networks, but how these interactions support recognition, encoding, and retrieval remains unclear. Here, we analyzed intracranial local field potentials from 1,652 sites in 36 epilepsy patients performing a naturalistic card-matching task. Phase-amplitude and phase-phase coupling revealed widespread condition-dependent interactions, with frontal and temporal regions emerging as recurrent network hubs. Event-related analyses showed reproducible within-trial coupling dynamics across participants. Directed phase transfer entropy further identified frequency-specific information flow, including frontal regions acting as a theta-band source and an alpha-band sink. Finally, a time-delay-embedded hidden Markov model identified task-locked latent states with condition-dependent occupancy trajectories and distinct coherence profiles. Together, these results suggest that working memory is implemented through dynamic, directionally organized large-scale networks, in which frontotemporal hubs coordinate flexible transitions among distributed neural states rather than operating in isolation.
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