Brain network for small-scale features in active touch.

Saeed Babadi, Roger Gassert, Vincent Hayward, Marco Piccirelli, Spyros Kollias, Theodore E Milner

Abstract read

In one paragraph

Article in Neuroimage. Reports, 2022. 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.

Network-oriented neurorehabilitation after stroke: a paradigmatic approach.Journal of neuroengineering and rehabilitation · 2026
Review

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.

Saeed BabadiDepartment of Kinesiology and Physical Education, McGill University, Montreal, QC H2W 1S4, Canada.

Roger GassertRehabilitation Engineering Laboratory, D-HEST, ETH Zürich, Zurich, Switzerland.

Vincent HaywardInstitut des Systèmes Intelligents et de Robotique, Sorbonne Université, 75005, Paris, France.

Marco PiccirelliClinic of Neuroradiology, University Hospital Zurich, Zurich, Switzerland.

Spyros KolliasClinic of Neuroradiology, University Hospital Zurich, Zurich, Switzerland.

Theodore E MilnerDepartment of Kinesiology and Physical Education, McGill University, Montreal, QC H2W 1S4, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An important tactile function is the active detection of small-scale features, such as edges or asperities, which depends on fine hand motor control. Using a resting-state fMRI paradigm, we sought to identify the functional connectivity of the brain network engaged in mapping tactile inputs to and from regions engaged in motor preparation and planning during active touch. Human participants actively located small-scale tactile features that were rendered by a computer-controlled tactile display. To induce rapid perceptual learning, the contrast between the target and the surround was reduced whenever a criterion level of success was achieved, thereby raising the task difficulty. Multiple cortical and subcortical neural connections within a parietal-cerebellar-frontal network were identified by correlating behavioral performance with changes in functional connectivity. These cortical areas reflected perceptual, cognitive, and attention-based processes required to detect and use small-scale tactile features for hand dexterity.

Indexed as

fMRIFunctional connectivityPerceptual learningResting-state networkSomatosensory

Identifiers

PMID40567573

DOI10.1016/j.ynirp.2022.100123

PMCPMC12172874

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LicenceCC BY-NC-ND

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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.