{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T10:30:36Z","timestamp":1793701836852,"version":"4.5.1"},"posted":{"date-parts":[[2025,11,26]]},"group-title":"Neuroscience","reference-count":77,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T00:00:00Z","timestamp":1764115200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,10,30]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>Episodic memory, the ability to rapidly learn and explicitly remember past events and experiences, plays a critical role in children\u2019s academic learning and knowledge acquisition. The formation of lasting memories relies on the brain\u2019s ability to dynamically organize its activity. How these neural configurations unfold moment-by-moment across encoding and offline phases remains poorly understood. To probe these dynamics, we applied a novel Bayesian Switching Dynamic Systems approach, a hidden Markov model with automatic state detection, to fMRI data from children performing scene encoding followed by an offline post-encoding rest. We identified four distinct brain states during encoding with unique activation modes between visual, medial temporal lobe, and frontoparietal and default mode network nodes. An \u201cactive-encoding\u201d state with integrated visual-hippocampal and frontoparietal activity dominated encoding and predicted individual memory performance, while an inactive state negatively predicted performance. State transition dynamics revealed that flexible shifts into the active-encoding state enhanced memory formation, whereas transitions toward inactive states impaired it, demonstrating that memory success depends on dynamic neural flexibility. Critically, encoding states spontaneously reemerged during post-encoding rest. A \u201cdefault-mode\u201d state characterized by enhanced default mode network activity showed sustained maintenance during rest and robustly predicted memory outcomes, an effect specific to post-encoding, not pre-encoding rest. These findings establish that episodic memory emerges from coordinated brain state sequences bridging online encoding with offline consolidation, providing a computational framework for how moment-to-moment neural dynamics support memory formation in children.<\/jats:p>\n                <jats:sec>\n                  <jats:title>Significance Statement<\/jats:title>\n                  <jats:p>How do children\u2019s brains form lasting memories? Using a novel computational approach, we reveal that memory formation depends on the brain\u2019s ability to rapidly shift between distinct coordination patterns, or \u201cbrain states.\u201d During learning, children who flexibly transition into an optimal brain state form stronger memory. Remarkably, these encoding states spontaneously reactivate during subsequent rest, and children who sustain specific default-mode network states longer show better memory retention. These findings demonstrate that successful memory emerges from dynamic neural flexibility across both active encoding and offline rest, offering a new computational framework for understanding memory formation in the developing brain.<\/jats:p>\n                <\/jats:sec>","DOI":"10.1101\/2025.11.25.690570","type":"posted-content","created":{"date-parts":[[2025,11,27]],"date-time":"2025-11-27T09:05:15Z","timestamp":1764234315000},"source":"Crossref","is-referenced-by-count":0,"title":["Dynamic brain states during encoding and their post-encoding reinstatement predict episodic memory in children"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4753-4328","authenticated-orcid":false,"given":"Yimeng","family":"Zeng","sequence":"first","affiliation":[{"name":"The State Key Laboratory of Cognitive Neuroscience and Learning & IDG\/McGovern Institute for Brain Research, Faculty of Psychology, Beijing Normal University, Beijing, China"},{"name":"School of Management, 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