ArticleThe Journal of neuroscience : the official journal of the Society for Neuroscience2017
Learning Predictive Statistics: Strategies and Brain Mechanisms.
Article in The Journal of neuroscience : the official journal of the Society for Neuroscience, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 19 papers.
What it found
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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.
Structure Learning Training and Cognitive Flexibility
Investigating Cognitive Flexibility Training
Who cites it
19 citing papers in PubMed.
- Hippocampal representations of temporal structure increase in scale and symmetry across development.bioRxiv : the preprint server for biology · 2026Article
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- Contributions of Basal Ganglia Circuits to Perception, Attention, and Consciousness.Journal of cognitive neuroscience · 2024Review
- Response times are affected by mispredictions in a stochastic game.Scientific reports · 2024Article
- Incidental learning of predictive temporal context within cortical representations of visual shape.Imaging neuroscience (Cambridge, Mass.) · 2024Article
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- Study protocol: How does cognitive flexibility relate to other executive functions and learning in healthy young adults?PloS one · 2023Article
- Flexible structure learning under uncertainty.Frontiers in neuroscience · 2023Article
- Computational and neural mechanisms of statistical pain learning.Nature communications · 2022Article
- A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High-Quality Data: Development and Usability Study.Journal of medical Internet research · 2022Article
- Resolving visual motion through perceptual gaps.Trends in cognitive sciences · 2021Review
- Retrieving the structure of probabilistic sequences of auditory stimuli from EEG data.Scientific reports · 2021Article
- Content-based Dissociation of Hippocampal Involvement in Prediction.Journal of cognitive neuroscience · 2020Article
- fMRI reveals language-specific predictive coding during naturalistic sentence comprehension.Neuropsychologia · 2020Article
- Multimodal imaging of brain connectivity reveals predictors of individual decision strategy in statistical learning.Nature human behaviour · 2019Article
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- Specific patterns of brain alterations underlie distinct clinical profiles in Huntington's disease.NeuroImage. Clinical · 2019Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations. Here, we test the brain mechanisms that mediate our ability to adapt to the environment's statistics and predict upcoming events. By combining behavioral training and multisession fMRI in human participants (male and female), we track the corticostriatal mechanisms that mediate learning of temporal sequences as they change in structure complexity. We show that learning of predictive structures relates to individual decision strategy; that is, selecting the most probable outcome in a given context (maximizing) versus matching the exact sequence statistics. These strategies engage distinct human brain regions: maximizing engages dorsolateral prefrontal, cingulate, sensory-motor regions, and basal ganglia (dorsal caudate, putamen), whereas matching engages occipitotemporal regions (including the hippocampus) and basal ganglia (ventral caudate). Our findings provide evidence for distinct corticostriatal mechanisms that facilitate our ability to extract behaviorally relevant statistics to make predictions.
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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.