Evidence map›Paper›PMID 41931518›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Cerebellar contributions to action and cognition: Prediction, timescale, and continuity.

Jonathan S Tsay, Richard B Ivry

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jonathan S TsayDepartment of Psychology, Carnegie Mellon University, Pittsburgh, PA 15213.ORCID 0000-0002-3992-9023
Richard B IvryDepartment of Psychology, University of California, Berkeley, CA 94720.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The cerebellum is implicated in nearly every domain of human cognition, yet our understanding of how this subcortical structure contributes to cognition remains elusive. Efforts on this front have tended to fall into one of two camps. On one side are those who seek to identify a universal cerebellar transform, a single algorithm that can be applied across domains as diverse as sensorimotor learning, social cognition, and decision-making. On the other side are those who focus on functional specializations tailored for different task domains. In this perspective, we propose an integrated approach, one that recognizes functional specialization across different cerebellar subregions, but also builds on common constraints that help define the conditions that engage the cerebellum. Drawing on recurring principles from the cerebellum's well-established role in motor control, we identify three core constraints: 1) Prediction-the cerebellum performs anticipatory, simulation-based computations; 2) Timescale-the cerebellum generates predictions limited to short intervals; and 3) Continuity-the cerebellum facilitates the manipulation of mental representations in a continuous, but not discrete manner. Together, these constraints define the boundary conditions underlying how the cerebellum supports cognition, and, just as importantly, specify the types of computations that should not depend on the cerebellum.

Indexed as

CerebellumCognitionAnimalsDecision MakingHumansLearningModels, Neurologicalactioncerebellumcognitionlearningsubcortex

Identifiers

PMID41931518
PMCPMC13079976

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.