Evidence map›Paper›PMID 30697149›Full record

ReviewFrontiers in cellular neuroscience2018

Cerebellum, Predictions and Errors.

Laurentiu S Popa, Timothy J Ebner

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in cellular neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
107citing papers in PubMed, 2 pooled it
10.5field-weighted citation impact, top 1% of its field
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

107 citing papers in PubMed, 2 syntheses or guidelines pooled it, 189 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Review
  6. Sensorimotor circuit connectivity as a candidate biomarker for responsiveness to sertraline in obsessive-compulsive disorder.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
    Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Neural subtypes in developmental stuttering.bioRxiv : the preprint server for biology · 2026
    Article
  16. Review
  17. Consensus Paper: Models of Cerebellar Functions.Cerebellum (London, England) · 2026
    Review
  18. Cerebellar Purkinje cell firing reduction contributes to aging-related declining motor coordination in mice.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  19. Article
  20. A brief history of dopamine prediction errors.Frontiers in computational neuroscience · 2026
    Review

47 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Laurentiu S PopaDepartment of Neuroscience, University of Minnesota, Minneapolis, MN, United States.
Timothy J EbnerDepartment of Neuroscience, University of Minnesota, Minneapolis, MN, United States.
University of Minnesota · US

Funding

ROLE OF THE CEREBELLUM IN VISUALLY GUIDED ARM MOVEMENTSR01NS018338 · NINDS · UNIVERSITY OF MINNESOTA TWIN CITIES · PI EBNER, TIMOTHY J · 1985 to 2020
$4.7M
NINDS NIH HHS R01 NS018338
6 · The paper itself

Abstract

Making predictions and validating the predictions against actual sensory information is thought to be one of the most fundamental functions of the nervous system. A growing body of evidence shows that the neural mechanisms controlling behavior, both in motor and non-motor domains, rely on prediction errors, the discrepancy between predicted and actual information. The cerebellum has been viewed as a key component of the motor system providing predictions about upcoming movements and receiving feedback about motor errors. Consequentially, studies of cerebellar function have focused on the motor domain with less consideration for the wider context in which movements are generated. However, motor learning experiments show that cognition makes important contributions to motor adaptation that involves the cerebellum. One of the more successful theoretical frameworks for understanding motor control and cerebellar function is the forward internal model which states that the cerebellum predicts the sensory consequences of the motor commands and is involved in computing sensory prediction errors by comparing the predictions to the sensory feedback. The forward internal model was applied and tested mainly for effector movements, raising the question whether cerebellar encoding of behavior reflects task performance measures associated with cognitive involvement. Electrophysiological studies based on pseudo-random tracking in monkeys show that the discharge of Purkinje cell, the sole output neurons of the cerebellar cortex, encodes predictive and feedback signals not only of the effector kinematics but also of task performance. The implications are that the cerebellum implements both effector and task performance forward models and the latter are consistent with the cognitive contributions observed during motor learning. The implications of these findings include insights into recent psychophysical observations on moving with reduced feedback and motor learning. The findings also support the cerebellum's place in hierarchical generative models that work in concert to refine predictions about behavior and the world. Therefore, cerebellar representations bridge motor and non-motor domains and provide a better understanding of cerebellar function within the functional architecture of the brain.

Indexed as

complex spikeforward internal modelgenerative modelkinematicsperformance errorPurkinje cellsensory prediction errorsimple spike

Identifiers

PMID30697149
PMCPMC6340992
OpenAlexW2903618123

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.