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Updated: Feb 15, 2026

Analyzing Neural Activity and Connectivity Using Intracranial EEG Data with SPM Software
Published on: October 30, 2018
Signal Complexity of Human Intracranial EEG Tracks Successful Associative-Memory Formation across Individuals
Timothy C Sheehan1, Vishnu Sreekumar1, Sara K Inati2
1Surgical Neurology Branch and.
Abstract:
Memory performance is highly variable among individuals. Most studies examining human memory, however, have largely focused on the neural correlates of successful memory formation within individuals, rather than the differences among them. As such, what gives rise to this variability is poorly understood. Here, we examined intracranial EEG (iEEG) recordings captured from 43 participants (23 male) implanted with subdural electrodes for seizure monitoring as they performed a paired-associates verbal memory task. We identified three separate but related signatures of neural activity that tracked differences in successful memory formation across individuals. High-performing individuals consistently exhibited less broadband power, flatter power spectral density slopes, and greater complexity in their iEEG signals. Furthermore, within individuals across three separate time scales ranging from seconds to days, successful recall was positively associated with these same metrics. Our data therefore suggest that memory ability across individuals can be indexed by increased neural signal complexity.SIGNIFICANCE STATEMENT We show that participants whose intracranial EEG exhibits less low-frequency power, flatter power spectrums, and greater sample entropy overall are better able to memorize associations, and that the same metrics track fluctuations in memory performance across time within individuals. These metrics together signify greater neural signal complexity, which may index the brain's ability to flexibly engage with information and generate separable memory representations. Critically, the current set of results provides a unique window into the neural markers of individual differences in memory performance, which have hitherto been underexplored.
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