Aug 2026· Brain Structure and Function· Vol 231· 0 citations· 104 references
Medicine
Abstract
The recollection of complex events is multidimensional. Recent work has gathered evidence for varying degrees of functional specialization for different memory dimensions across the main cortical networks involved in cued recollection. However, how functional brain network topology reorganizes to support the retrieval of different types of information remains largely unexplored. Here, we applied graph theoretical analysis to task-related fMRI functional connectivity data from 22 participants engaged in cued recollection of specific details from naturalistic movie scenes. A beta series correlation approach was used to identify the pattern of whole-brain regional co-activation for cued recollection in general, and separately for each memory dimension of interest (object and character details, spatial layouts, temporal sequences, and verbal dialogues). Subsequently, using graph theory, we investigated the association between indices of brain network topology and cued recollection performance, as well as differences in functional brain network architecture across memory dimensions at the multiscale level. Successful recollection was associated with higher global efficiency and lower modularity at the whole-network level, as well as with lower system segregation within the Frontoparietal control network. Crucially, retrieval conditions placing greater demands on relational integration (i.e., temporal order judgments), compared to those emphasizing single-item details, were associated with more integration in the Default Mode network and increased degree centrality, efficiency, and reduced path length in the right hippocampus. Together, these findings reinforce the idea that successful retrieval requires system integration, especially when accessing complex relational representations like temporal sequences.
An approach to construct dynamic large-scale brain networks from trial-wise activation maps in the Natural Scenes Dataset is developed and a previously unrecognized network-level representational mechanism that supports recognition memory is uncovered, refining current models of distributed information coding in the hu...
Jin-Tao Sheng, Jun-Le Li, Xiang-Li Zeng et al.· Proceedings of the National...· 0 citations
Visual recognition memory depends on coordinated interactions across distributed medial temporal, prefrontal, and limbic networks, yet the sub-second large-scale network dynamics distinguishing successful from unsuccessful recognition remain poorly understood. Here we used intracranial EEG recordings from seven patient...
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The neural mechanisms underlying the brain's representation of event gist remain poorly understood. In this study, we investigate the neural architecture and computational principles governing the hierarchical representation of event gist in the human brain. Using an integrative approach that combines natural language...
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Why are some individuals able to recollect past events and imagine future events more richly than others? Here we examine how structural connectivity within a ‘core network’ supporting mnemonic cognition, substantially overlapping with the canonical default network, underpins inter-individual variation in autobiographi...
Lucie S. Reed, E. Messaritaki, Craig Hedge et al.· bioRxiv· 0 citations
The neural mechanisms underlying spontaneous perceptual switches during bistable perception, particularly the dynamic interplay between large-scale brain networks, remain incompletely understood. Here, using functional magnetic resonance imaging (fMRI) in six participants and a bistable kinetic depth effect (KDE) stimu...
A. Ponzi, Katsunori Miyahara, Keisuke Suzuki· bioRxiv· 0 citations
The human brain operates through large-scale networks whose subcortical components are critical for consciousness, emotion, and cognition. While cortical network connectivity has been mapped with increasing precision, subcortical network mapping has lagged far behind due to two fundamental barriers: the overlapping and...
Jian Li, A. Atalay, Mark D. Olchanyi et al.· Proceedings of the National...· 0 citations
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