Evidence map›Paper›PMID 42781854›Full record

ArticleeLife2026

Real-time closed-loop feedback system for mouse mesoscale cortical signal and movement control.

Pankaj Kumar Gupta, Timothy H Murphy

Abstract read
In one paragraph

Article in eLife, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Pankaj Kumar GuptaDepartment of Psychiatry, University of British Columbia, Detwiller Pavilion, Vancouver, Canada.ORCID https://orcid.org/0000-0001-6814-2812
Timothy H MurphyDepartment of Psychiatry, University of British Columbia, Detwiller Pavilion, Vancouver, Canada.ORCID https://orcid.org/0000-0002-0093-4490

Funding

CIHR FDN-143209CIHR PJT-1800631Natural Sciences and Engineering Research Council of Canada GPIN-2022-03723
6 · The paper itself

Abstract

Increasingly, experiments designed to provide practical perturbations to circuits or behavior are required for hypothesis testing in various disciplines ranging from motor learning to recovery after injury. We present the implementation and efficacy of an open-source closed-loop neurofeedback (CLNF) and closed-loop movement feedback (CLMF) system. In CLNF, we measure mm-scale cortical mesoscale activity with GCaMP6s and provide graded auditory feedback (within ~63 ms) based on changes in dorsal-cortical activation within regions of interest (ROIs) and with a specified rule. Single or dual ROIs (ROI1, ROI2) on the dorsal cortical map were selected as targets. Both motor and sensory regions supported closed-loop training in male and female mice. Mice modulated activity in rule-specific target cortical ROIs to get increasing rewards over days (repeated-measures ANOVA [RM-ANOVA], p=2.83e-5) and adapted to changes in ROI rules (RM-ANOVA, p=8.3e-10, Table 4 for different rule changes). In CLMF, feedback (within ~67 ms) was based on tracking a specified body movement, and rewards were generated when the behavior reached a threshold. For movement training, the group that received graded auditory feedback performed significantly better (RM-ANOVA, p=9.6e-7) than a control group (RM-ANOVA, p=0.49) within 4 training days. Additionally, mice can learn a change in task rule from left forelimb to right forelimb within a day, after a brief performance drop on day 5. Offline analysis of neural data and behavioral tracking revealed changes in the overall distribution of Ca

Indexed as

Cerebral CortexNeurofeedbackAnimalsFeedback, SensoryFemaleMaleMiceMovementcalcium imagingclopyclosed-loopcomputational biologyGCaMP6smouseneurosciencereal-timesystems biologywidefield

Identifiers

PMID42781854
PMCPMC13609482

What OpenQuestion holds

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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.