Evidence map›Paper›PMID 36327142›Full record

ArticleThe Journal of physiology2023

Mechanisms of Hebbian-like plasticity in the ventral premotor - primary motor network.

Andrea Casarotto, Elisa Dolfini, Pasquale Cardellicchio, Luciano Fadiga, Alessandro D'Ausilio, Giacomo Koch

Open access · greenAbstract read
In one paragraph

Article in The Journal of physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
2.3field-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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Andrea CasarottoIIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy.ORCID 0000-0002-2927-2486
Elisa DolfiniIIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy.
Pasquale CardellicchioIIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy.
Luciano FadigaIIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy.
Alessandro D'AusilioIIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy.
Giacomo KochIIT@UniFe Center for Translational Neurophysiology, Istituto Italiano di Tecnologia, Ferrara, Italy.
University of Ferrara · ITItalian Institute of Technology · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The functional connection between ventral premotor cortex (PMv) and primary motor cortex (M1) is critical for the organization of goal-directed actions. Repeated activation of this connection by means of cortico-cortical paired associative stimulation (cc-PAS), a transcranial magnetic stimulation (TMS) protocol, may induce Hebbian-like plasticity. However, the physiological modifications produced by Hebbian-like plasticity in the PMv-M1 network are poorly understood. To fill this gap, we investigated the effects of cc-PAS on PMv-M1 circuits. We hypothesized that specific interactions would occur with I

Indexed as

Evoked Potentials, MotorMotor CortexElectromyographyLong-Term PotentiationNeuronal PlasticityTranscranial Magnetic Stimulationcortico-cortical paired associative stimulationHebbian-like plasticityI-wavesLTP-like and LTD-like after-effectprimary motor cortexventral premotor cortex

Identifiers

PMID36327142
PMCPMC10100355
OpenAlexW4308053557

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.