ReviewNeuroscience and biobehavioral reviews2020
How does the brain learn environmental structure? Ten core principles for understanding the neurocognitive mechanisms of statistical learning.
Review in Neuroscience and biobehavioral reviews, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 1 of them a synthesis that pooled it.
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Who cites it
112 citing papers in PubMed, 1 synthesis or guideline pooled it.
- What neurological diseases tell us about procedural perceptual-motor learning? A systematic review of the literature.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2023Pooled it
- The specific nature of the statistical learning deficit in developmental dyslexia: Impaired temporal and spared spatial learning abilities.Psychonomic bulletin & review · 2026Article
- Coupling between statistical learning and interference suppression.Psychological research · 2026Article
- Longitudinal evidence for decreasing statistical learning abilities across childhood.Nature communications · 2026Article
- Re-Evaluating the Role of Statistical Learning: Domain-General Predictors of Language in Typical and Atypical Development.Cognitive science · 2026Article
- Learning and Using Different Task Rule Updating Strategies Require Extensive Practice.Cognitive science · 2026Article
- Spontaneous emergence of context-dependent statistical learning in humans and neural networks.iScience · 2026Article
- Obsessive-compulsive tendencies shift the balance between competitive neurocognitive functions.iScience · 2026Article
- When attention matters: Domain-specific disruption of explicit but not implicit memory in statistical learning.Memory & cognition · 2026Article
- Neural correlates of learning speed reveal developmental differences in memory.Developmental cognitive neuroscience · 2026Article
- Modality-general sensitivity of pupil responses to regularity violations.Cognitive, affective & behavioral neuroscience · 2026Article
- Unsupervised nonmotor learning in the human cerebellum.bioRxiv : the preprint server for biology · 2026Article
- Second-Language Learning Facilitates Non-Adjacent Dependency Learning: Effects Moderated by Specific Language.Cognitive science · 2026Article
- Repetitions trigger illusory awareness in implicit statistical learning.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Exploring the spiking neural autoencoder: from hyperexcitability to noise-driven compensation.Frontiers in systems neuroscience · 2026Article
- Procedural or declarative deficit in adults with developmental dyslexia? A study of Artificial grammar learning.PloS one · 2026Article
- A preliminary study of implicit statistical learning in non-clinical young adults exposed to early adversity.Frontiers in psychiatry · 2026Article
- Hemispheric disparity theory: a dual-system framework for consciousness.Frontiers in psychology · 2026Article
- The Effects of Cognitive Fatigue and Articulatory Suppression on Statistical Language Learning Depend on the Strength of Cognitive Resources.Cognitive science · 2026Article
- Neural entrainment to visual rules in infant and adult brain.Scientific reports · 2025Article
52 more citing papers are in PubMed but not listed here.
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Abstract
Despite a growing body of research devoted to the study of how humans encode environmental patterns, there is still no clear consensus about the nature of the neurocognitive mechanisms underpinning statistical learning nor what factors constrain or promote its emergence across individuals, species, and learning situations. Based on a review of research examining the roles of input modality and domain, input structure and complexity, attention, neuroanatomical bases, ontogeny, and phylogeny, ten core principles are proposed. Specifically, there exist two sets of neurocognitive mechanisms underlying statistical learning. First, a "suite" of associative-based, automatic, modality-specific learning mechanisms are mediated by the general principle of cortical plasticity, which results in improved processing and perceptual facilitation of encountered stimuli. Second, an attention-dependent system, mediated by the prefrontal cortex and related attentional and working memory networks, can modulate or gate learning and is necessary in order to learn nonadjacent dependencies and to integrate global patterns across time. This theoretical framework helps clarify conflicting research findings and provides the basis for future empirical and theoretical endeavors.
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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.