Long-term training-dependent representation of individual finger movements in the primary motor cortex
| Autor: | Kenji Ogawa, Kaoru Mitsui, Shuhei Nishida, Fumihito Imai |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Adult
Male medicine.medical_specialty Cognitive Neuroscience Motor Activity Audiology Somatosensory system computer.software_genre Representational similarity analysis 050105 experimental psychology Fingers Young Adult 03 medical and health sciences Finger movement 0302 clinical medicine Voxel medicine Humans 0501 psychology and cognitive sciences Brain Mapping medicine.diagnostic_test 05 social sciences Motor Cortex Magnetic Resonance Imaging Term (time) Neurology Practice Psychological Multivariate Analysis Female Sensorimotor Cortex Primary motor cortex Motor learning Psychology Functional magnetic resonance imaging computer Psychomotor Performance 030217 neurology & neurosurgery |
| Zdroj: | NeuroImage. 202:116051 |
| ISSN: | 1053-8119 |
| DOI: | 10.1016/j.neuroimage.2019.116051 |
| Popis: | We investigated the effects of long-term training on the neural representation of individual finger movements in the primary sensorimotor cortex. One group of participants (trained group) included subjects trained in playing the piano (mean years of experience = 17.9; range = 9–26; n = 20). The other group of participants (novice group) had no prior experience (n = 20). All participants performed finger-tapping movements using either of the four digits of the hand (index, middle, ring, and little fingers). Functional magnetic resonance imaging (fMRI) was used to analyze the spatial activation patterns elicited by individual finger movements. Subsequently, we tried to classify the finger that was being moved using a multi-voxel pattern analysis (MVPA). Our results showed significantly higher-than-chance classification accuracies in both primary motor cortex (M1) and somatosensory cortex (S1) contralateral to the hand. We also found significantly lower classification accuracies for both hands in the trained group compared with the novice group in M1, without significant differences in the average signal changes and the number of activated voxels for individual fingers or overlap between digits. Representational similarity analysis (RSA) also demonstrated the differences in similarity patterns of activations between the trained and novice groups in M1. Our results indicate the modulation of neural representations of individual finger movements of M1 due to long-term training. |
| Databáze: | OpenAIRE |
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