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Traveling waves shape neural population dynamics enabling predictions and internal model updating
Preprint   Open access

Traveling waves shape neural population dynamics enabling predictions and internal model updating

S Mohanta, D M Cleveland, M Afrasiabi, A E Rhone, U Górska, M Cooper Borkenhagen, R D Sanders, M Boly, K V Nourski and Y B Saalmann
bioRxiv : the preprint server for biology
Cold Spring Harbor laboratory
01/10/2024
DOI: 10.1101/2024.01.09.574848
PMCID: PMC10802392
PMID: 38260606
url
https://doi.org/10.1101/2024.01.09.574848View
Preprint (Author's original)This preprint has not been evaluated by subject experts through peer review. Preprints may undergo extensive changes and/or become peer-reviewed journal articles. Open Access

Abstract

The brain generates predictions based on statistical regularities in our environment. However, it is unclear how predictions are optimized through iterative interactions with the environment. Because traveling waves (TWs) propagate across the cortex shaping neural excitability, they can carry information to serve predictive processing. Using human intracranial recordings, we show that anterior-to-posterior alpha TWs correlated with prediction strength. Learning about priors altered neural state space trajectories, and how much it altered correlated with trial-by-trial prediction strength. Learning involved mismatches between predictions and sensory evidence triggering alpha-phase resets in lateral temporal cortex, accompanied by stronger alpha phase-high gamma amplitude coupling and high-gamma power. The mismatch initiated posterior-to-anterior alpha TWs and change in the subsequent trial's state space trajectory, facilitating model updating. Our findings suggest a vital role of alpha TWs carrying both predictions to sensory cortex and mismatch signals to frontal cortex for trial-by-trial fine-tuning of predictive models.

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