ArticleScientific reports2019
The Relationship between Trial-by-Trial Variability and Oscillations of Cortical Population Activity.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- On variability in local field potentials.Communications biology · 2026Article
- A high-precision synchronization and centroid-based framework for single-trial decoding of perceived natural speech.Frontiers in computational neuroscience · 2026Article
- Neural variability reliably encodes interindividual differences in the perception of pain intensity.PLoS biology · 2025Article
- Perceptual Decision Efficiency Is Modifiable and Associated with Decreased Musculoskeletal Injury Risk Among Female College Soccer Players.Brain sciences · 2025Article
- Editorial: The new frontier in brain network physiology: from temporal dynamics to the principles of integration in physiological brain networks.Frontiers in computational neuroscience · 2023Article
- From Shorter to Longer Timescales: Converging Integrated Information Theory (IIT) with the Temporo-Spatial Theory of Consciousness (TTC).Entropy (Basel, Switzerland) · 2022Article
- Spatio-Temporally Efficient Coding Assigns Functions to Hierarchical Structures of the Visual System.Frontiers in computational neuroscience · 2022Article
- SEED-G: Simulated EEG Data Generator for Testing Connectivity Algorithms.Sensors (Basel, Switzerland) · 2021Article
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Authors and funding
5 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Neural activity fluctuates over time, creating considerable variability across trials. This trial-by-trial neural variability is dramatically reduced ("quenched") after the presentation of sensory stimuli. Likewise, the power of neural oscillations, primarily in the alpha-beta band, is also reduced after stimulus onset. Despite their similarity, these phenomena have so far been studied and discussed independently. We hypothesized that the two phenomena are tightly coupled in electrophysiological recordings of large cortical neural populations. To test this, we examined magnetoencephalography (MEG) recordings of healthy subjects viewing repeated presentations of a visual stimulus. The timing, amplitude, and spatial topography of variability-quenching and power-suppression were remarkably similar. Neural variability quenching was eliminated by excluding the alpha-beta band from the recordings, but not by excluding other frequency-bands. Moreover, individual magnitudes of alpha-beta band-power explained 86% of between-subject differences in variability quenching. An alternative mechanism that may generate variability quenching is increased phase alignment across trials. However, changes in inter-trial-phase-coherence (ITPC) exhibited distinct timing and no correlations with the magnitude of variability quenching in individual participants. These results reveal that neural variability quenching is tightly coupled with stimulus-induced changes in the power of alpha-beta band oscillations, associating two phenomena that have so far been studied in isolation.
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