ArticleScientific reports2026
Global neural oscillations underlie performance variability and attentional state fluctuations in humans.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
Fluctuations in attentional states, such as mind-wandering (MW), are associated with critical variability in task performance. While fMRI studies highlight the opposing roles of task-positive (e.g., dorsal attention network) and task-negative (e.g., default mode network) systems, the electrophysiological mechanisms underlying these dynamics remain poorly understood. Using intracranial electrocorticography in humans performing a sustained attention task, we identified global oscillatory dynamics linked to attentional shifts. MW was characterized by (1) reduced theta (θ) and alpha (α) power, (2) decreased aperiodic signal components, indicating a shift toward cortical inhibition, (3) enhanced phase synchronization across networks, and (4) strengthened θ phase-behavior correlations (ρ). These features support a non-network-specific framework in which low-frequency θ dynamics-captured by both θ power and ρ-are associated with attentional fluctuations, while aperiodic offset relates to attentional state indirectly through its association with ρ (structural equation modeling: power → state β = - 0.118, p = 0.002; ρ → state β = 0.246, p < 0.001; offset → ρ β = - 0.222, p < 0.001). Our study provides a unified neurophysiological framework for understanding how spontaneous neural activity can drive attentional fluctuations and performance variability, with implications for research on attention, learning, and neuropsychiatric disorders.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.