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Phase Consistency Dynamics of Memory Encoding.

  • Published In: Journal of Neuroscience, 2025, v. 45, n. 35. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Colyer, Ryan A.; Kahana, Michael J. 3 of 3

Abstract

Human and animal studies implicate theta and alpha oscillations in memory function. We tested whether theta, alpha, and beta phase consistency predicts memory encoding dynamics in neurosurgical patients performing delayed free recall tasks with either unrelated (N = 188: 99 male, 89 female) or categorized words (N = 157: 88 male, 69 female). We observed widespread post-stimulus phase consistency (3-21 Hz) and, crucially, identified distinct frequency-specific patterns predictive of successful encoding. Specifically, increased early list item recall was significantly correlated across subjects with increased theta (3-7 Hz) phase consistency. Subsequent recall analyses, controlling for serial position, revealed distinct frequency signatures for successfully encoded items: theta (3-6 Hz) and alpha (9-14 Hz) for unrelated lists, and theta (3-6 Hz) and beta (14-19 Hz) for categorized lists. Regional analyses for unrelated lists highlighted the lateral temporal cortex for theta effects and the prefrontal cortex for both theta and alpha consistency. These findings provide novel evidence for the frequency-specific presence of increased phase consistency during episodic encoding, revealing its sensitivity to both item context and temporal position within a learning sequence. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Neuroscience. 2025/08, Vol. 45, Issue 35, p1
  • Document Type:Article
  • Subject Area:Psychology
  • Publication Date:2025
  • ISSN:0270-6474
  • DOI:10.1523/JNEUROSCI.2077-24.2025
  • Accession Number:187686622
  • Copyright Statement:Copyright of Journal of Neuroscience is the property of Society for Neuroscience and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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