Background: Cortical reorganization occurs in the adult central nervous system, especially during motor skill acquisition. This plasticity contributes to various forms of human behavior including skill learning and memory formation, consolidation, reconsolidation and short- and long-term retention. It is very important to understand the role of these different behavioral processes and of the mechanisms underlying these various forms of human plasticity during skill acquisition to improve skill learning and memory in healthy adults. Findings this year: Over the past year, we have advanced several research initiatives aimed at characterizing intra- and inter-individual variability in responses to non-invasive brain stimulation. The rationale for this work is that a more nuanced understanding of these sources of variability is crucial for the development of personalized neuromodulatory protocols using non-invasive brain stimulation into effective therapies for neurorehabilitation in individual patients. While the link between the local primary motor cortex structure motor function has been well documented, motor function is known to result from a network of interconnected brain regions over large areas of the brain. The relationship between the features characterizing these distributed structural brain networks and motor function remains poorly understood. Here, we examined whether distributed patterns of brain structure, extending beyond the primary motor cortex can predict inter-individual variance in corticospinal excitability and intracortical inhibition, two clinically well described features of motor function. We acquired high-resolution structural MRI scans, motor evoked potentials (MEPs, a measure of corticospinal excitability) elicited by single-pulse transcranial magnetic stimulation (TMS) and short-interval intracortical inhibition (SICI) in 25 healthy volunteers. We used support vector machine (SVM) pattern classification to identify distributed multi-voxel gray-matter areas, which distinguished subjects who had lower and higher MEPs and SICIs, respectively. The results of this machine learning-based approach revealed that low or high MEP and SICI classification could be predicted based on a widely distributed, largely non-overlapping pattern of voxels in frontal, parietal, temporal, occipital, and cerebellar regions. Thus, distributed structural brain network features play a significant role in inter-individual variability of TMS effects. A second project compared the effects of different types of non-invasive brain stimulation (NIBS) on motor skill learning in healthy adults. A anodal transcranial direct current stimulation (tDCS), paired associative stimulation (PAS25), and intermittent theta burst stimulation (iTBS), along with a sham tDCS control condition were applied in a between-subject design. A total of 28 participants were randomly assigned to different groups and trained on a motor skill learning task. Online, offline and retention components of motor learning were calculated. The effects of NIBS on corticospinal excitability was also evaluated. We did not find consistent effects across the non-invasive brain stimulation types on motor learning or cortical excitability. The preliminary results observed in this small sample size, which require replication with larger samples, are consistent with previous reports of small and variable effect sizes of these interventions on motor learning between individuals and techniques. A third project conducted in collaboration with Dr. Julien Doyon at the McGill University investigated reconsolidation of long-term motor memories in healthy humans. Previous animal work showed that consolidated memories return to labile states when reactivated and that restabilization through reconsolidation processes is necessary for these memories to persist over the long time periods (i.e. years). This is supported by the finding that application of pharmacological agents following memory reactivation that block protein synthesis within the hippocampus results in failure to sustain the same memories over time. In humans, the hypothesis that memory reactivation paired with a competitive task can interfere with memory restabilitation has been proposed. Here, new skill learning was performed to interfere with the restabilization of an existing motor memory acquired through training on a finger tapping sequence task. When the interfering task was introduced immediately following memory reactivation, offline learning (i.e. continued performance gains that normally occur following the end of the training period) is extinguished. In summary, these results support the idea that instead of reactivation-induced plasticity resulting in reconsolidation of existing memories, memories are maintained within a competitive structure in which new information acquired during interfering experiences is integrated into existing memories through biological consolidation processes.
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