Neurophysiologic correlates of motor learning that can be monitored during neurorehabilitation interventions can facilitate the development of more effective learning methods. Previous studies have ...focused on the role of the beta band (14–30 Hz) because of its clear response during motor activity. However, it is difficult to discriminate between beta activity related to learning a movement and performing the movement. In this study, we analysed differences in the electroencephalography (EEG) power spectra of complex and simple explicit sequential motor tasks in healthy young subjects. The complex motor task (CMT) allowed EEG measurement related to motor learning. In contrast, the simple motor task (SMT) made it possible to control for EEG activity associated with performing the movement without significant motor learning. Source reconstruction of the EEG revealed task-related activity from 5 clusters covering both primary motor cortices (M1) and 3 clusters localised to different parts of the cingulate cortex (CC). We found no association between M1 beta power and learning, but the CMT produced stronger bilateral beta suppression compared to the SMT. However, there was a positive association between contralateral M1 theta (5–8 Hz) and alpha (8–12 Hz) power and motor learning, and theta and alpha power in the posterior mid-CC and posterior CC were positively associated with greater motor learning. These findings suggest that the theta and alpha bands are more related to motor learning than the beta band, which might merely relate to the level of perceived difficulty during learning.
Transcranial direct current stimulation (tDCS) has emerged as a non-invasive brain stimulation technique. Most studies show that anodal tDCS increases cortical excitability. However, this effect has ...been found to be highly variable.
To test the effect of anodal tDCS on cortical excitability and the interaction effect of two participant-specific factors that may explain individual differences in sensitivity to anodal tDCS: the Brain Derived Neurotrophic Factor Val66Met polymorphism (BDNF genotype) and the latency difference between anterior-posterior and lateromedial TMS pulses (APLM latency).
In 62 healthy participants, cortical excitability over the left motor cortex was measured before and after anodal tDCS at 2 mA for 20 min in a pre-registered, double-blind, randomized, placebo-controlled trial with repeated measures.
We did not find a main effect of anodal tDCS, nor an interaction effect of the participant-specific predictors. Moreover, further analyses did not provide evidence for the existence of responders and non-responders.
This study indicates that anodal tDCS at 2 mA for 20 min may not reliably affect cortical excitability.
•This study does not show an effect of 2 mA tDCS applied for 20 min on cortical excitability.•This study does not provide evidence for a subgroup of responders.•These results emphasize the need for large replication studies on the effect of tDCS.
Post-feedback frontal midline EEG activity has been found to correlate with error magnitude during motor adaptation. However, the role of this neuronal activity remains to be elucidated. It has been ...hypothesized that post-feedback frontal midline activity may represent a prediction error, which in turn may be directly related to the adaptation process or to an unspecific orienting response. To address these hypotheses, we replicated a previous visuomotor adaptation experiment with very small perturbations, likely to invoke implicit adaptation, in a new group of 60 participants and combined it with EEG recordings. We found error-related peaks in the frontal midline electrodes in the time domain. However, these were best understood as modulations of frontal midline theta activity (FMT, 4–8 Hz). Trial-level differences in FMT correlated with error magnitude. This correlation was robust even for very small errors as well as in the absence of imposed perturbations, indicating that FMT does not depend on explicit or strategic re-aiming. Within participants, trial-level differences in FMT were not related to between-trial error corrections. Between participants, individual differences in FMT-error-sensitivity did not predict differences in adaptation rate. Taken together, these results imply that FMT does not drive implicit motor adaptation. Finally, individual differences in FMT-error-sensitivity negatively correlate to motor execution noise. This suggests that FMT reflects saliency: larger execution noise means a larger standard deviation of errors so that a fixed error magnitude is less salient. In conclusion, this study suggests that frontal midline theta activity represents a saliency signal and does not directly drive motor adaptation.
Transcranial direct current stimulation (tDCS) over the contralateral primary motor cortex of the target muscle (conventional tDCS) has been described to enhance corticospinal excitability, as ...measured with transcranial magnetic stimulation. Recently, tDCS targeting the brain regions functionally connected to the contralateral primary motor cortex (motor network tDCS) was reported to enhance corticospinal excitability more than conventional tDCS. We compared the effects of motor network tDCS, 2 mA conventional tDCS, and sham tDCS on corticospinal excitability in 21 healthy participants in a randomized, single-blind within-subject study design. We applied tDCS for 12 min and measured corticospinal excitability with TMS before tDCS and at 0, 15, 30, 45, and 60 min after tDCS. Statistical analysis showed that neither motor network tDCS nor conventional tDCS significantly increased corticospinal excitability relative to sham stimulation. Furthermore, the results did not provide evidence for superiority of motor network tDCS over conventional tDCS. Motor network tDCS seems equally susceptible to the sources of intersubject and intrasubject variability previously observed in response to conventional tDCS.
Vestibular signals, which encode head movement in space as well as orientation relative to gravity, contribute to the ongoing muscle activity required to stand. The strength of this vestibular ...contribution changes with the presence and quality of sensory cues of balance. Here we investigate whether the vestibular drive for standing balance also depends on different sensory cues of gravity by examining vestibular-evoked muscle responses when independently varying load and gravity conditions. Standing subjects were braced by a backboard structure that limited whole-body sway to the sagittal plane while load and vestibular cues of gravity were manipulated by: (a) loading the body downward at 1.5 and 2 times body weight (i.e., load cues), and/or (b) exposing subjects to brief periods (20 s) of micro- (<0.05 g) and hyper-gravity (∼1.8 g) during parabolic flights (i.e., vestibular cues). A stochastic electrical vestibular stimulus (0-25 Hz) delivered during these tasks evoked a vestibular-error signal and corrective muscles responses that were used to assess the vestibular drive to standing balance. With additional load, the magnitude of the vestibular-evoked muscle responses progressively increased, however, when these responses were normalized by the ongoing muscle activity, they decreased and plateaued at 1.5 times body weight. This demonstrates that the increased muscle activity necessary to stand with additional load is accompanied a proportionally smaller increase in vestibular input. This reduction in the relative vestibular contribution to balance was also observed when we varied the vestibular cues of gravity, but only during an absence (<0.05 g) and not an excess (∼1.8 g) of gravity when compared to conditions with normal 1 g gravity signals and equivalent load signals. Despite these changes, vestibular-evoked responses were observed in all conditions, indicating that vestibular cues of balance contribute to upright standing even in the near absence of a vestibular signal of gravity (i.e., micro-gravity). Overall, these experiments provide evidence that both load and vestibular cues of gravity influence the vestibular signal processing for the control of standing balance.
Changes in transcranial magnetic stimulation motor map parameters can be used to quantify plasticity in the human motor cortex. The golden standard uses a counting analysis of motor evoked potentials ...(MEPs) acquired with a predefined grid. Recently, digital reconstruction methods have been proposed, allowing MEPs to be acquired with a faster pseudorandom procedure. However, the reliability of these reconstruction methods has never been compared to the golden standard.
To compare the absolute reliability of the reconstruction methods with the golden standard.
In 21 healthy subjects, both grid and pseudorandom acquisition were performed twice on the first day and once on the second day. The standard error of measurement was calculated for the counting analysis and the digital reconstructions.
The standard error of measurement was at least equal using digital reconstructions.
Pseudorandom acquisition and digital reconstruction can be used in intervention studies without sacrificing reliability.
Cerebellar transcranial direct current stimulation has been reported to enhance motor associative learning and motor adaptation, holding promise for clinical application in patients with movement ...disorders. However, behavioral benefits from cerebellar tDCS have been inconsistent.
Identifying determinants of treatment success is necessary. BDNF Val66Met is a candidate determinant, because the polymorphism is associated with motor skill learning and BDNF is thought to mediate tDCS effects.
We undertook two cerebellar tDCS studies in subjects genotyped for BDNF Val66Met. Subjects performed an eyeblink conditioning task and received sham, anodal or cathodal tDCS (N = 117, between-subjects design) or a vestibulo-ocular reflex adaptation task and received sham and anodal tDCS (N = 51 subjects, within-subjects design). Performance was quantified as a learning parameter from 0 to 100%. We investigated (1) the distribution of the learning parameter with mixture modeling presented as the mean (M), standard deviation (S) and proportion (P) of the groups, and (2) the role of BDNF Val66Met and cerebellar tDCS using linear regression presented as the regression coefficients (B) and odds ratios (OR) with equally-tailed intervals (ETIs).
For the eyeblink conditioning task, we found distinct groups of learners (MLearner = 67.2%; SLearner = 14.7%; PLearner = 61.6%) and non-learners (MNon-learner = 14.2%; SNon-learner = 8.0%; PNon-learner = 38.4%). Carriers of the BDNF Val66Met polymorphism were more likely to be learners (OR = 2.7 1.2 6.2). Within the group of learners, anodal tDCS supported eyeblink conditioning in BDNF Val66Met non-carriers (B = 11.9% 95%ETI = 0.8 23.0%), but not in carriers (B = 1.0% 95%ETI = -10.2 12.1%). For the vestibulo-ocular reflex adaptation task, we found no effect of BDNF Val66Met (B = −2.0% 95%ETI = -8.7 4.7%) or anodal tDCS in either carriers (B = 3.4% 95%ETI = -3.2 9.5%) or non-carriers (B = 0.6% 95%ETI = -3.4 4.8%). Finally, we performed additional saccade and visuomotor adaptation experiments (N = 72) to investigate the general role of BDNF Val66Met in cerebellum-dependent learning and found no difference between carriers and non-carriers for both saccade (B = 1.0% 95%ETI = -8.6 10.6%) and visuomotor adaptation (B = 2.7% 95%ETI = -2.5 7.9%).
The specific role for BDNF Val66Met in eyeblink conditioning, but not vestibulo-ocular reflex adaptation, saccade adaptation or visuomotor adaptation could be related to dominance of the role of simple spike suppression of cerebellar Purkinje cells with a high baseline firing frequency in eyeblink conditioning. Susceptibility of non-carriers to anodal tDCS in eyeblink conditioning might be explained by a relatively larger effect of tDCS-induced subthreshold depolarization in this group, which might increase the spontaneous firing frequency up to the level of that of the carriers.
•BDNF Val66Met is associated with faster eyeblink conditioning.•Cerebellar tDCS and BDNF Val66Met interact in eyeblink conditioning.•Interaction between tDCS and BDNF points to a common effect on simple spike firing.•Inconsistency in cerebellar tDCS literature is partially explained by BDNF Val66Met.
Individual variations in motor adaptation rate were recently shown to correlate with movement variability or "motor noise" in a forcefield adaptation task. However, this finding could not be ...replicated in a meta-analysis of adaptation experiments. Possibly, this inconsistency stems from noise being composed of distinct components that relate to adaptation rate in different ways. Indeed, previous modeling and electrophysiological studies have suggested that motor noise can be factored into planning noise, originating from the brain, and execution noise, stemming from the periphery. Were the motor system optimally tuned to these noise sources, planning noise would correlate positively with adaptation rate, and execution noise would correlate negatively with adaptation rate, a phenomenon familiar in Kalman filters. To test this prediction, we performed a visuomotor adaptation experiment in 69 subjects. Using a novel Bayesian fitting procedure, we succeeded in applying the well-established state-space model of adaptation to individual data. We found that adaptation rate correlates positively with planning noise (
= 0.44; 95% HDI = 0.27 0.59) and negatively with execution noise (
= -0.39; 95% HDI = -0.50 -0.30). In addition, the steady-state Kalman gain calculated from planning and execution noise correlated positively with adaptation rate (
= 0.54; 95% HDI = 0.38 0.66). These results suggest that motor adaptation is tuned to approximate optimal learning, consistent with the "optimal control" framework that has been used to explain motor control. Since motor adaptation is thought to be a largely cerebellar process, the results further suggest the sensitivity of the cerebellum to both planning noise and execution noise.
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