Evidence map›Paper›PMID 25769277›Full record

ArticleJournal of neuroscience methods2015

An automated behavioral box to assess forelimb function in rats.

Chelsea C Wong, Dhakshin S Ramanathan, Tanuj Gulati, Seok Joon Won, Karunesh Ganguly

Open access · greenAbstract read
In one paragraph

Article in Journal of neuroscience methods, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
2.8field-weighted citation impact, top 10% 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

31 citing papers in PubMed, 55 citations in OpenAlex.

  1. A paradigm for skilled forelimb reaching by head-restrained mice.bioRxiv : the preprint server for biology · 2026
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  4. Coupling of Slow Oscillations in the Prefrontal and Motor Cortex Predicts Onset of Spindle Trains and Persistent Memory Reactivations.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024
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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

5 authors at 2 institutions in 1 country.

Chelsea C WongNeurology & Rehabilitation Service, San Francisco VA Medical Center, San Francisco, CA, United States; Department of Neurology, University of California, San Francisco, CA, United States.
Dhakshin S RamanathanNeurology & Rehabilitation Service, San Francisco VA Medical Center, San Francisco, CA, United States; Psychiatry Service, San Francisco VA Medical Center, San Francisco, CA, United States; Department of Psychiatry, University of California, San Francisco, CA, United States.
Tanuj GulatiNeurology & Rehabilitation Service, San Francisco VA Medical Center, San Francisco, CA, United States; Department of Neurology, University of California, San Francisco, CA, United States.
Seok Joon WonNeurology & Rehabilitation Service, San Francisco VA Medical Center, San Francisco, CA, United States; Department of Neurology, University of California, San Francisco, CA, United States.
Karunesh GangulyNeurology & Rehabilitation Service, San Francisco VA Medical Center, San Francisco, CA, United States; Department of Neurology, University of California, San Francisco, CA, United States. Electronic address: karunesh.ganguly@ucsf.edu.
San Francisco VA Medical Center · USUniversity of California, San Francisco · US

Funding

TRAINING THE NEXT GENERATION OF MENTAL HEALTH RESEARCHERSR25MH060482 · NIMH · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DANIEL H MATHALON, Susan M. Voglmaier · 2000 to 2026
$5.2M
NIMH NIH HHS R25 MH060482
6 · The paper itself

Abstract

backgroundRodent forelimb reaching behaviors are commonly assessed using a single-pellet reach-to-grasp task. While the task is widely recognized as a very sensitive measure of distal limb function, it is also known to be very labor-intensive, both for initial training and the daily assessment of function. NEW

methodUsing components developed by open-source electronics platforms, we have designed and tested a low-cost automated behavioral box to measure forelimb function in rats. Our apparatus, made primarily of acrylic, was equipped with multiple sensors to control the duration and difficulty of the task, detect reach outcomes, and dispense pellets. Our control software, developed in MATLAB, was also used to control a camera in order to capture and process video during reaches. Importantly, such processing could monitor task performance in near real-time.

resultsWe further demonstrate that the automated apparatus can be used to expedite skill acquisition, thereby increasing throughput as well as facilitating studies of early versus late motor learning. The setup is also readily compatible with chronic electrophysiological monitoring. COMPARISON WITH EXISTING

methodsCompared to a previous version of this task, our setup provides a more efficient method to train and test rodents for studies of motor learning and recovery of function after stroke. The unbiased delivery of behavioral cues and outcomes also facilitates electrophysiological studies.

conclusionsIn summary, our automated behavioral box will allow high-throughput and efficient monitoring of rat forelimb function in both healthy and injured animals.

Indexed as

Pattern Recognition, AutomatedAnalysis of VarianceAnimalsBehavior, AnimalConditioning, OperantFeeding BehaviorForelimbMaleMotor CortexPsychomotor PerformanceRatsRats, Long-EvansElectrophysiologyMotor learningReach

Identifiers

PMID25769277
PMCPMC5472046
OpenAlexW1993925695

What OpenQuestion holds

Textmetadata
LicenceTDM
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.