Evidence map›Paper›PMID 41523210›Full record

ArticleImaging neuroscience (Cambridge, Mass.)

Neural correlates of kinematic features of passive finger movement revealed by univariate and multivariate fMRI analyses.

Gustavo S P Pamplona, James Sulzer, Ewa Beldzik, Olivier Lambercy, Silvio Ionta, Roger Gassert, Jarrod Lewis-Peacock

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Article in Imaging neuroscience (Cambridge, Mass.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Gustavo S P PamplonaSensoriMotorLab, Jules-Gonin Eye Hospital/Fondation Asile des Aveugles, Department of Ophthalmology/University of Lausanne, Lausanne, Switzerland.ORCID https://orcid.org/0000-0002-0278-203X
James SulzerDepartment of Physical Medicine and Rehabilitation, Case Western Reserve University, Cleveland, OH, United States.
Ewa BeldzikResearch Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, United States.
Olivier LambercyRehabilitation Engineering Laboratory (RELab), Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Silvio IontaSensoriMotorLab, Jules-Gonin Eye Hospital/Fondation Asile des Aveugles, Department of Ophthalmology/University of Lausanne, Lausanne, Switzerland.
Roger GassertRehabilitation Engineering Laboratory (RELab), Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland.
Jarrod Lewis-PeacockDepartment of Psychology, University of Texas at Austin, Austin, TX, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Finger movements are associated with a relatively large neural representation. Passive finger movement-externally generated movement without voluntary muscle activity-is a robust approach to investigate the neural representation of kinesthesia and proprioception. While some studies have characterized the neural correlates of passive finger movement, they have relied solely on mass univariate analysis, potentially limiting sensitivity. Additionally, limited consideration has been given to stimulus duration, a factor closely tied to kinematic features such as amplitude and velocity, which more recent modeling approaches account for explicitly. Here, we reanalyzed previously published data using both univariate and multivariate analyses to examine how kinesthesia is represented in the brain in neurotypical subjects across two experiments. Systematic passive stimulation of the fingers was provided using an MR-compatible robot while functional magnetic resonance imaging data were recorded. Our analyses were conducted separately for amplitude, velocity, and direction and adjusted for stimulus duration, thereby controlling for this factor whether or not neural activation scaled with it. We provide a detailed mapping of brain areas related to these kinematic features, including sensorimotor, subcortical, and cerebellar regions. In general, multivariate pattern analysis was more sensitive than the univariate approach in identifying brain regions associated with passive finger movement. Our univariate results showed that activity in sensorimotor and subcortical areas was higher for larger amplitudes and slower velocities, which contrasted with the original study's findings, likely due to our treatment of stimulus duration as a parametric modulator. A novel result was that sensorimotor areas showed higher activation for extension compared to flexion of passive finger movement. Across kinematic features, a larger neural representation was observed for amplitude and direction than for velocity, suggesting that kinesthesia and proprioception may rely more strongly on displacement than on movement. Whereas univariate analyses are limited in addressing heterogeneity across voxels, our multivariate analyses revealed that a broader set of brain regions carried condition-related information about passive movement, based on distributed voxel activity patterns. Together, these findings extend current knowledge on how the brain represents physical kinematic features of finger movements.

Indexed as

fingerfMRIkinematic featuresMVPApassive movementunivariate analysis

Identifiers

PMID41523210
PMCPMC12779755

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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.