TY - JOUR
T1 - Explaining Individual Differences in Motor Behavior by Intrinsic Functional Connectivity and Corticospinal Excitability
AU - Herszage, Jasmine
AU - Dayan, Eran
AU - Sharon, Haggai
AU - Censor, Nitzan
N1 - Publisher Copyright:
© Copyright © 2020 Herszage, Dayan, Sharon and Censor.
PY - 2020/2/5
Y1 - 2020/2/5
N2 - Motor performance varies substantially between individuals. This variance is rooted in individuals’ innate motor abilities, and should thus have a neural signature underlying these differences in behavior. Could these individual differences be detectable with neural measurements acquired at rest? Here, we tested the hypothesis that motor performance can be predicted by resting motor-system functional connectivity and motor-evoked-potentials (MEPs) induced by non-invasive brain stimulation. Twenty healthy right handed subjects performed structural and resting-state fMRI scans. On a separate day, MEPs were measured using transcranial magnetic stimulation (TMS) over the contrateral primary motor cortex (M1). At the end of the session, participants performed a finger-tapping task using their left non-dominant hand. Resting-state functional connectivity between the contralateral M1 and the supplementary motor area (SMA) predicted motor task performance, indicating that individuals with stronger resting M1-SMA functional connectivity exhibit better motor performance. This prediction was neither improved nor reduced by the addition of corticospinal excitability to the model. These results confirm that motor behavior can be predicted from neural measurements acquired prior to task performance, primarily relying on resting functional connectivity rather than corticospinal excitability. The ability to predict motor performance from resting neural markers, provides an opportunity to identify the extent of successful rehabilitation following neurological damage.
AB - Motor performance varies substantially between individuals. This variance is rooted in individuals’ innate motor abilities, and should thus have a neural signature underlying these differences in behavior. Could these individual differences be detectable with neural measurements acquired at rest? Here, we tested the hypothesis that motor performance can be predicted by resting motor-system functional connectivity and motor-evoked-potentials (MEPs) induced by non-invasive brain stimulation. Twenty healthy right handed subjects performed structural and resting-state fMRI scans. On a separate day, MEPs were measured using transcranial magnetic stimulation (TMS) over the contrateral primary motor cortex (M1). At the end of the session, participants performed a finger-tapping task using their left non-dominant hand. Resting-state functional connectivity between the contralateral M1 and the supplementary motor area (SMA) predicted motor task performance, indicating that individuals with stronger resting M1-SMA functional connectivity exhibit better motor performance. This prediction was neither improved nor reduced by the addition of corticospinal excitability to the model. These results confirm that motor behavior can be predicted from neural measurements acquired prior to task performance, primarily relying on resting functional connectivity rather than corticospinal excitability. The ability to predict motor performance from resting neural markers, provides an opportunity to identify the extent of successful rehabilitation following neurological damage.
KW - excitability
KW - functional connectivity
KW - individual differences
KW - motor skill
KW - motor-evoked-potentials
KW - transcranial magnetic stimulation
UR - http://www.scopus.com/inward/record.url?scp=85079797008&partnerID=8YFLogxK
U2 - 10.3389/fnins.2020.00076
DO - 10.3389/fnins.2020.00076
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C2 - 32116520
AN - SCOPUS:85079797008
SN - 1662-4548
VL - 14
JO - Frontiers in Neuroscience
JF - Frontiers in Neuroscience
M1 - 76
ER -