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Reading specific memories from human neurons before and after sleep
Preprint   Open access

Reading specific memories from human neurons before and after sleep

Yuanyi Ding, Soraya L. S. Dunn, John J. Sakon, Chenda Duan, Yipeng Zhang, Joel I. Berger, Ariane E. Rhone, Kirill V. Nourski, Hiroto Kawasaki, Matthew A. Howard, …
bioRxiv
Cold Spring Harbor Laboratory, 1.1
07/04/2025
DOI: 10.1101/2025.07.01.662486
PMCID: PMC12236671
PMID: 40631106
url
https://doi.org/10.1101/2025.07.01.662486View
Preprint (Author's original)This preprint has not been evaluated by subject experts through peer review. Preprints may undergo extensive changes and/or become peer-reviewed journal articles. Open Access

Abstract

The ability to retrieve a single episode encountered just once is a hallmark of human intelligence and episodic memory [1]. Yet, decoding a specific memory from neuronal activity in the human brain remains a formidable challenge. Here, we develop a transformer neural network model [2, 3] trained on neuronal spikes from intracranial microelectrodes recorded during a single viewing of an audiovisual episode. Combining spikes throughout the brain via cross-channel attention [4], capable of discovering neural patterns spread across brain regions and timescales, individual participant models predict memory retrieval of specific concepts such as persons or places. Brain regions differentially contribute to memory decoding before and after sleep. Models trained using only medial temporal lobe (MTL) spikes significantly decode concepts before but not after sleep, while models trained using only frontal cortex (FC) spikes decode concepts after but not before sleep. These findings suggest a system-wide distribution of information across neural populations that transforms over wake/sleep cycles [5]. Such decoding of internally generated memories suggests a path towards brain-computer interfaces to treat episodic memory disorders through enhancement or muting of specific memories.
Neuroscience

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