ArticleFrontiers in neuroscience2022
Rethinking statistical learning as a continuous dynamic stochastic process, from the motor systems perspective.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Statistical learning re-shapes the center-surround inhibition of the visuo-spatial attentional focus.Scientific reports · 2025Article
- The time is ripe for the renaissance of autism treatments: evidence from clinical practitioners.Frontiers in integrative neuroscience · 2023Article
- Dynamic Interrogation of Stochastic Transcriptome Trajectories Using Disease Associated Genes Reveals Distinct Origins of Neurological and Psychiatric Disorders.Frontiers in neuroscience · 2022Article
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2 authors.
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Abstract
The brain integrates streams of sensory input and builds accurate predictions, while arriving at stable percepts under disparate time scales. This stochastic process bears different unfolding dynamics for different people, yet statistical learning (SL) currently averages out, as noise, individual fluctuations in data streams registered from the brain as the person learns. We here adopt a new analytical approach that instead of averaging out fluctuations in continuous electroencephalographic (EEG)-based data streams, takes these gross data as the important signals. Our new approach reassesses how individuals dynamically learn predictive information in stable and unstable environments. We find neural correlates for two types of learners in a visuomotor task: narrow-variance learners, who retain explicit knowledge of the regularity embedded in the stimuli. They seem to use an
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