Back

Declarative Memory Through the Lens of Single-Trial Peaks in High-Frequency Power

Dede, A. J. O.; Cross, Z. R.; Gray, S. M.; Kelly, J. P.; Yin, Q.; Vahidi, P.; Asano, E.; Schuele, S. U.; Rosenow, J. M.; Wu, J. Y.; Lam, S. K.; Raskin, J. S.; Lin, J. J.; Kim-McManus, O.; Sattar, S.; Shaikhouni, A.; King-Stephens, D.; Weber, P. B.; Laxer, K. D.; Brunner, P.; Roland, J. L.; Saez, I.; Girgis, F.; Knight, R. T.; Ofen, N.; Johnson, E. L.

2025-01-02 neuroscience
10.1101/2025.01.02.631123 bioRxiv
Show abstract

Declarative memory depends on the coordination of local processing, indexed by high-frequency broadband (HFB) activity, with global network organization, indexed by theta oscillations. However, theta and HFB exhibit asynchronous timing, raising the question of how results of local processing are communicated throughout the network. Using intracranial EEG in patients performing a recognition memory task, we examined this coordination across the medial temporal lobe (MTL) and prefrontal cortex (PFC). HFB peak activity was earlier in the MTL than PFC. Anchoring analyses of theta phase clustering and connectivity to HFB peaks revealed strong phase clustering locked to HFB peaks in the PFC, as well as connectivity between the PFC and MTL that predicted individual memory performance. Graph analysis revealed specific connections amidst sparse network connectivity during memory success. This study demonstrates that transient brain states linked to internal physiological events support memory and refines our understanding of local and network-level process interactions. HighlightsO_LIMemory-linked theta activity is time-locked to internal brain events C_LIO_LINetwork connectivity changes dynamically during memory processing C_LIO_LISparse network connectivity supports successful memory C_LIO_LISpecific sequences of transient states may be critical for declarative memory C_LI

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.