Evidence map›Paper›PMID 35074503›Full record

ArticleNeuroImage2022

Electrophysiological foundations of the human default-mode network revealed by intracranial-EEG recordings during resting-state and cognition.

Anup Das, Carlo de Los Angeles, Vinod Menon

Abstract read
In one paragraph

Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Trial
  2. Review
  3. Neural signatures of serial order access in verbal working memory.Cerebral cortex (New York, N.Y. : 1991) · 2026
    Article
  4. Temporal stability of functional network configurations and its relationship to cognition and psychopathology in early psychoses.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Article
  5. Quantum-inspired entanglement between collaborating brains during human memory encoding.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
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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

3 authors.

Anup DasDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305 USA. Electronic address: a1das@stanford.edu.
Carlo de Los AngelesDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305 USA.
Vinod MenonDepartment of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305 USA; Department of Neurology & Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94305 USA; Stanford Neurosciences Institute, Stanford University School of Medicine, Stanford, CA 94305 USA. Electronic address: menon@stanford.edu.

Funding

Integrative computational models of latent behavioral and neural constructs in children: a longitudinal developmental big-data approachR01MH121069 · NIMH · STANFORD UNIVERSITY · PI MENON, VINOD · 2019 to 2023
$3.9M
Methods for Dynamic Causal Interactions in Human Brain Function and DysfunctionR01NS086085 · NINDS · STANFORD UNIVERSITY · PI MENON, VINOD · 2014 to 2025
$3.9M
Computational modeling of dynamic causal brain circuits underlying cognitive dysfunction in Alzheimer's diseaseRF1NS086085 · NINDS · STANFORD UNIVERSITY · PI MENON, VINOD · 2021 to 2021
$2.0M
Novel Bayesian linear dynamical systems-based methods for discovering human brain circuit dynamics in health and diseaseR01EB022907 · NIBIB · STANFORD UNIVERSITY · PI MENON, VINOD · 2016 to 2018
$1.6M
NIBIB NIH HHS R01 EB022907NIMH NIH HHS R01 MH121069NINDS NIH HHS R01 NS086085NINDS NIH HHS RF1 NS086085
6 · The paper itself

Abstract

Investigations using noninvasive functional magnetic resonance imaging (fMRI) have provided significant insights into the unique functional organization and profound importance of the human default mode network (DMN), yet these methods are limited in their ability to resolve network dynamics across multiple timescales. Electrophysiological techniques are critical to address these challenges, yet few studies have explored the neurophysiological underpinnings of the DMN. Here we investigate the electrophysiological organization of the DMN in a common large-scale network framework consistent with prior fMRI studies. We used intracranial EEG (iEEG) recordings, and evaluated intra- and cross-network interactions during resting-state and its modulation during a cognitive task involving episodic memory formation. Our analysis revealed significantly greater intra-DMN phase iEEG synchronization in the slow-wave (< 4 Hz), while DMN interactions with other brain networks was higher in the beta (12-30 Hz) and gamma (30-80 Hz) bands. Crucially, slow-wave intra-DMN synchronization was observed in the task-free resting-state and during both verbal memory encoding and recall. Compared to resting-state, slow-wave intra-DMN phase synchronization was significantly higher during both memory encoding and recall. Slow-wave intra-DMN phase synchronization increased during successful memory retrieval, highlighting its behavioral relevance. Finally, analysis of nonlinear dynamic causal interactions revealed that the DMN is a causal outflow network during both memory encoding and recall. Our findings identify frequency specific neurophysiological signatures of the DMN which allow it to maintain stability and flexibility, intrinsically and during task-based cognition, provide novel insights into the electrophysiological foundations of the human DMN, and elucidate network mechanisms by which it supports cognition.

Indexed as

Default Mode NetworkElectrocorticographyBrainBrain MappingCognitionHumansMagnetic Resonance ImagingMental Recall

Identifiers

PMID35074503
PMCPMC8928656

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.