Evidence map›Paper›PMID 40235588›Full record

ArticleiScience2025

Hippocampal and cortical high-frequency oscillations orchestrate human semantic networks during word list memory.

Akash Mishra, Serdar Akkol, Elizabeth Espinal, Noah Markowitz, Gelana Tostaeva, Elisabeth Freund, Ashesh D Mehta, Stephan Bickel

Abstract read
In one paragraph

Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Hippocampal Ripples during Offline Periods Predict Human Motor Sequence Learning.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Akash MishraNorthwell, New Hyde Park, NY, USA.
Serdar AkkolNorthwell, New Hyde Park, NY, USA.
Elizabeth EspinalNorthwell, New Hyde Park, NY, USA.
Noah MarkowitzNorthwell, New Hyde Park, NY, USA.
Gelana TostaevaNorthwell, New Hyde Park, NY, USA.
Elisabeth FreundNorthwell, New Hyde Park, NY, USA.
Ashesh D MehtaNorthwell, New Hyde Park, NY, USA.
Stephan BickelNorthwell, New Hyde Park, NY, USA.

Funding

Determining neural dynamics of human memory using invasive recordings and closed-loop electrical brain stimulationF30MH139332 · NIMH · HOFSTRA UNIVERSITY · PI Akash Mishra · 2024 to 2026
$85k
NIMH NIH HHS F30 MH139332
6 · The paper itself

Abstract

Episodic memory requires the precise coordination between the hippocampus and distributed cortical regions. This may be facilitated by bursts of brain activity called high-frequency oscillations (HFOs). We hypothesized that HFOs activate specific networks during memory retrieval and aimed to describe the electrophysiological properties of HFO-associated activity. To study this, we recorded intracranial electroencephalography while human participants performed a list learning task. Hippocampal HFOs (hHFOs) increased during encoding and retrieval, and these increases correlated with memory performance. During retrieval, hHFOs demonstrated activation of semantic processing regions that were previously active during encoding. This consisted of broadband high-frequency activity (HFA) and cortical HFOs. HFOs in the anterior temporal lobe, a major semantic hub, co-occurred with hHFOs, particularly during retrieval. These coincident HFOs were associated with greater cortical HFA and cortical theta bursts. Hence, HFOs may support synchronization of activity across distributed nodes of the hippocampal-cortical memory network.

Indexed as

Cognitive neuroscienceLinguistics

Identifiers

PMID40235588
PMCPMC11999489

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.