Evidence map›Paper›PMID 33357383›Full record

ArticleNeuron2021

The sensory representation of causally controlled objects.

Kelly B Clancy, Thomas D Mrsic-Flogel

Abstract read
In one paragraph

Article in Neuron, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Why is everyone talking about brain state?Trends in neurosciences · 2023
    Review
  5. Neural Plasticity in Sensorimotor Brain-Machine Interfaces.Annual review of biomedical engineering · 2023
    Review
  6. How far neuroscience is from understanding brains.Frontiers in systems neuroscience · 2023
    Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. 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.

Kelly B ClancyBiozentrum, University of Basel, 70 Klingelbergstrasse, 4056 Basel, Switzerland. Electronic address: k.clancy@ucl.ac.uk.
Thomas D Mrsic-FlogelBiozentrum, University of Basel, 70 Klingelbergstrasse, 4056 Basel, Switzerland. Electronic address: t.mrsic-flogel@ucl.ac.uk.

Funding

Wellcome TrustWellcome Trust 090843/E/09/Z
6 · The paper itself

Abstract

Intentional control over external objects is informed by our sensory experience of them. To study how causal relationships are learned and effected, we devised a brain machine interface (BMI) task using wide-field calcium signals. Mice learned to entrain activity patterns in arbitrary pairs of cortical regions to guide a visual cursor to a target location for reward. Brain areas that were normally correlated could be rapidly reconfigured to exert control over the cursor in a sensory-feedback-dependent manner. Higher visual cortex was more engaged when expert but not naive animals controlled the cursor. Individual neurons in higher visual cortex responded more strongly to the cursor when mice controlled it than when they passively viewed it, with the greatest response boosting as the cursor approached the target location. Thus, representations of causally controlled objects are sensitive to intention and proximity to the subject's goal, potentially strengthening sensory feedback to allow more fluent control.

Indexed as

Brain-Computer InterfacesRewardAnimalsExercise TestFeedback, SensoryFemaleMiceMice, Inbred C57BLMice, TransgenicPsychomotor PerformanceVisual Cortexbrain computer interfacebrain machine interfacecalcium imagingcausal controldecoderneuroprostheticsparietal cortexsensorimotor learningvisual cortexwidefield imaging

Identifiers

PMID33357383
PMCPMC7889580

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.