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Marine Vernet, Shahid Bashir, Edwin Robertson, Alvaro Pascual-Leone; Motor cortical and distributed network modulation during visuo-motor learning: A TMS-EEG study. Journal of Vision 2011;11(11):936. https://doi.org/10.1167/11.11.936.
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© ARVO (1962-2015); The Authors (2016-present)
Prior studies have shown changes in motor cortical outputs associated with implicit and explicit motor learning. This study aims to evaluate changes in local cortical reactivity and distributed neural network dynamics in the course of motor sequence learning. We record electroencephalographic (EEG) responses to single-pulse transcranial magnetic stimulation (TMS) at baseline and serially while participants perform 4 blocks of a serial reaction time task (SRTT). On each trial, upon the appearance of a visual cue at one of four possible positions, participants have to press an appropriate key. Random trials are compared with trials repeating a sequence of 12 items. TMS is applied over M1 in the time window between motor response and onset of the following visual cue. TMS is also applied between SRTT blocks. Motor-evoked potentials (MEPs) of the first dorsal interosseous are recorded. Decrease of reaction times for sequence trials, compared to random trials, is indicative of sequence learning. During practice, explicit knowledge of the sequence might develop. This can be reflected by changes in responses to TMS, specific to the learning state, during the task performance and during following periods of rest. Preliminary results shows that MEPs recorded after each block, compared to baseline MEPs, reflect changes in cortical reactivity associated with learning. Moreover, playing a sequence of random trials, compared to rest, modifies local reactivity. Finally, responding to a sequence that is getting familiar, compared to performing random trials, also modifies brain responses in remote areas. Distinct phases of learning are associated with different changes in local motor cortical reactivity and distributed neural network modulation. These preliminary data highlight the importance of capturing brain local and distributed network activity in order to fully understand the neural substrates of visuo-motor learning. This is possible with the integration of TMS and EEG during SRTT.
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