bioRxivNeurosciencePreprint
Declarative Memory Through the Lens of Single-Trial Peaks in High-Frequency Power
Adam J. O. DedeiD, Zachariah R. CrossiD, Samantha M. GrayiD, Joseph P. KellyiD, Qin YiniD, Parisa VahidiiD, Eishi AsanoiD, Stephan SchueleiD, Joshua M. RosenowiD, Joyce Y. WuiD, Sandi Karen LamiD, Jeffrey Steven RaskiniD, Jack J. LiniD, Olivia Kim McManusiD, Shifteh SattariD, Ammar ShaikhouniiD, David King‐StephensiD, Peter B. WeberiD, Kenneth D. LaxeriD, Peter BrunneriD, Jarod L. RolandiD, Ignacio SáeziD, Fady GirgisiD, Robert Thomas KnightiD, Noa OfeniD, Elizabeth L. JohnsoniD
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
- organism: human
- assay: electronic health records
- research focus: cell-cell communication
- approach: statistical model
- Citations
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