Evolution of cerebral cortico-cortical communication during visuomotor adaptation to a cognitive-motor executive challenge

Abnormal structural covariance networks in young adults with recent cannabis use

BACKGROUND

Recent cannabis use (RCU) exerts adverse effects on the brain. However, the effect of RCU on structural covariance networks (SCNs) is still unclear. This retrospective cross-sectional study aimed to explore the effects of RCU on SCNs in young adults in terms of whole cerebral cortical thickness (CT) and cortical surface area (CSA).

METHODS

A total of 117 participants taking tetrahydrocannabinol (RCU group) and 896 participants not using cannabis (control group) were included in this study. All participants underwent MRI scanning following urinalysis screening, after which FreeSurfer 5.3 was used to calculate the CT and CSA, and SCNs matrices were constructed by Brain Connectivity Toolbox. Subsequently, the global and nodal network measures of the SCNs were computed based on these matrices. A nonparametric permutation test was used to investigate the group differences by Matlab.

RESULTS

Regarding global network measures of CT, young adults with RCU exhibited altered small-worldness (P = 0.020) and clustering coefficient (P = 0.031) compared to controls, whereas there were no significant group differences in terms of SCNs constructed with CSA. Additionally, SCNs based on CT and CSA displayed abnormal nodal degree, nodal efficiency, and nodal betweenness centrality in vital brain regions of the triple network, including the dorsolateral and ventrolateral prefrontal cortex, and anterior cingulate cortex.

CONCLUSION

The effects of RCU on brain structure in young adults can be detected by SCNs, in which structural abnormalities in the triple network are dominant, indicating that RCU can be detrimental to brain function.

Evaluating EEG neurofeedback in sport psychology: a systematic review of RCT studies for insights into mechanisms and performance improvement

Electroencephalographic Neurofeedback Training (EEG NFT) aims to improve sport performance by teaching athletes to control their mental states, leading to better cognitive, emotional, and physical outcomes. The psychomotor efficiency hypothesis suggests that optimizing brain function could enhance athletic ability, indicating the potential of EEG NFT. However, evidence for EEG-NFT's ability to alter critical brain activity patterns, such as sensorimotor rhythm and frontal midline theta-key for concentration and relaxation-is not fully established. Current research lacks standardized methods and comprehensive studies. This shortfall is due to inconsistent EEG target selection and insufficient focus on coherence in training. This review aims to provide empirical support for EEG target selection, conduct detailed control analyses, and examine the specificity of electrodes and frequencies to relation to the psychomotor efficiency hypothesis. Following the PRISMA method, 2,869 empirical studies were identified from PubMed, Science Direct, Web of Science, Embase, CNKI, and PsycINFO. Thirteen studies met the inclusion criteria: (i) proficient skill levels; (ii) use of EEG; (iii) neurofeedback training (NFT); (iv) motor performance metrics (reaction time, precision, dexterity, balance); (v) control group for NFT comparison; (vi) peer-reviewed English-language publication; and (vii) randomized controlled trial (RCT) design. Studies indicate that NFT can enhance sports performance, including improvements in shooting accuracy, golf putting, and overall motor skills, as supported by the psychomotor efficiency hypothesis. EEG NFT demonstrates potential in enhancing sports performance by optimizing performers' mental states and psychomotor efficiency. However, the current body of research is hampered by inconsistent methodologies and a lack of standardized EEG target selection. To strengthen the empirical evidence supporting EEG NFT, future studies need to focus on standardizing target selection, employing rigorous control analyses, and investigating underexplored EEG markers. These steps are vital to bolster the evidence for EEG NFT and enhance its effectiveness in boosting sport performance.

Hand differences in aiming task: A complementary spatial approach and analysis of dynamic brain networks with EEG

Left and right-hand exhibit differences in the execution of movements. Particularly, it has been shown that manual goal-directed aiming is more accurate with the right hand than with the left, which has been explained through the shorter time spent by the right hand in the feedback phase (FB). This explanation makes sense for the temporal aspects of the task; however, there is a lack of explanations for the spatial aspects. The present study hypothesizes that the right hand is more associated with the FB, while the left hand is more strongly associated with the pre-programming phase (PP). In addition, the present study aims to investigate differences between hands in functional brain connectivity (FBC). We hypothesize an increase in FBC of the right hand compared to the left hand. Twenty-two participants performed 20 trials of the goal-directed aiming task with both hands. Overall, the results confirm the study's hypotheses. Although the right hand stopped far from the target at the PP, it exhibited a lower final position error than the left hand. These findings imply that during the FB, the right hand compensates for the higher error observed in the PP, using the visual feedback to approach the target more closely than the left hand. Conversely, the left hand displayed a lower error at the PP than the right. Also, the right hand displayed greater FBC within and between brain hemispheres. This heightened connectivity in the right hand might be associated with inhibitory mechanisms between hemispheres.

A mental workload and biomechanical assessment during split-belt locomotor adaptation with and without optic flow

Adaptive human performance relies on the central nervous system to regulate the engagement of cognitive-motor resources as task demands vary. Despite numerous studies which employed a split-belt induced perturbation to examine biomechanical outcomes during locomotor adaptation, none concurrently examined the cerebral cortical dynamics to assess changes in mental workload. Additionally, while prior work suggests that optic flow provides critical information for walking regulation, a few studies have manipulated visual inputs during adaption to split-belt walking. This study aimed to examine the concurrent modulation of gait and Electroencephalography (EEG) cortical dynamics underlying mental workload during split-belt locomotor adaptation, with and without optic flow. Thirteen uninjured participants with minimal inherent walking asymmetries at baseline underwent adaptation, while temporal-spatial gait and EEG spectral metrics were recorded. The results revealed a reduction in step length and time asymmetry from early to late adaptation, accompanied by an elevated frontal and temporal theta power; the former being well corelated to biomechanical changes. While the absence of optic flow during adaptation did not affect temporal-spatial gait metrics, it led to an increase of theta and low-alpha power. Thus, as individuals adapt their locomotor patterns, the cognitive-motor resources underlying the encoding and consolidation processes of the procedural memory were recruited to acquire a new internal model of the perturbation. Also, when adaption occurs without optic flow, a further reduction of arousal is accompanied with an elevation of attentional engagement due to enhanced neurocognitive resources likely to maintain adaptive walking patterns.

Changes in Perceived Mental Load and Motor Performance during Practice-to-Learn and Practice-to-Maintain in Basketball

BACKGROUND

Attentional resource allocation during sports practice is associated with the players' perceived mental load. However, few ecological studies address this problem by considering the players' characteristics (e.g., practice experience, skill and cognition). Therefore, this study aimed to analyse the dose-response effect of two different types of practice, each with different learning objectives, on mental load and motor performance by using a linear mixed model analysis.

METHOD

Forty-four university students (age 20.36 ± 3.13 years) participated in this study. Two sessions were conducted, one based on a standard rules 1 × 1 basketball situation ("practice to maintain") and one with motor, temporal and spatial restrictions in 1 × 1 tasks ("practice to learn").

RESULTS

"Practice to learn" produced a higher perceived mental load (NASA-TLX scale) and a worse performance than "practice to maintain", but was moderated by experience and inhibition (p = 0.001). The same happens in the most demanding restriction (i.e., temporal, p < 0.0001).

CONCLUSION

The results showed that increasing the difficulty of 1 × 1 situations through restrictions harmed the player's performance and increased their perceived mental load. These effects were moderated by previous basketball experience and the player's inhibition capacity, so the difficulty adjustment should be based on the athletes themselves.

Quick balance skill improvement after short-term training with error amplification feedback for older adults

This study investigated behavioral and cortical mechanisms for short-term postural training with error amplification (EA) feedback in the elderly. Thirty-six elderly subjects (65.7 ± 2.2 years) were grouped (control and EA, n = 18) for training in stabilometer balance under visual guidance. During the training session (8 training rounds of 60 s in Day 2), the EA group received visual feedback that magnified errors to twice the real size, whereas the control group received visual feedback that displayed real errors. Scalp EEG and kinematic data of the stabilometer plate and ankle joint were recorded in the pre-test (Day 1) and post-test (Day 3). The EA group (-46.5 ± 4.7%) exhibited greater post-training error reduction than that of the control group (-27.1 ± 4.0%)(p = 0.020), together with a greater decline in kinematic coupling between the stabilometer plate and ankle joint (EA: -26.6 ± 4.8%, control: 2.3 ± 8.6%, p = 0.023). In contrast to the control group, the EA group manifested greater reductions in mean phase-lag index (PLI) connectivity in the theta (4-7 Hz)(p = 0.011) and alpha (8-12 Hz) (p = 0.027) bands. Only the EA group showed post-training declines in the mean PLI in the theta and alpha bands. Minimal spanning tree analysis revealed that EA-based training led to increases in the diameter (p = 0.002) and average eccentricity (p = 0.004) of the theta band for enhanced performance monitoring and reduction in the leaf fraction (p = 0.030) of the alpha band for postural response with enhanced automaticity. In conclusion, short-term EA training optimizes balance skill, favoring multi-segment coordination for the elderly, which is linked to more sophisticated error monitoring with less attentive control over the stabilometer stance.

Archery under the (electroencephalography-)hood: Theta-lateralization as a marker for motor learning

An intrinsic characteristic of the motor system is the preference of one side of the body. Lateralization is found in motor behavior and in the structural and functional correlates of cortical motor networks. While genetic factors have been elucidated as mechanisms leading to such asymmetries, findings in motor learning and experience from clinical experience demonstrate considerable additional plasticity during the lifespan. If and how functional lateralization develops in short timeframes during training of motor skills involving both sides of the body is still largely unclear. In the present exploratory study, we investigate lateralization of theta-, alpha- and beta-band oscillations during training of an ecologically valid skill - archery. We relate lateralization shift to performance improvement and elucidate the underlying cortical areas. To this end, healthy participants without any previous experience in archery underwent intensive training with 100 shots on each of three days. 64-channel electroencephalography was recorded simultaneously during the individual shots. We found that a central-parietal theta lateralization shift to the left immediately before the shot was associated with performance improvement. Lateralization of alpha or beta did not yield a significant association. Importantly, areas of maximum activation were not identical with areas showing the strongest associations with performance improvement. These data suggest that learning a complex bimanual motor skill is associated with a shift of theta-band oscillations to the left in central-parietal areas. The relationship with performance improvement may reflect increased cortical efficiency of task-relevant processing.

Using EEG to study sensorimotor adaptation

Sensorimotor adaptation, or the capacity to flexibly adapt movements to changes in the body or the environment, is crucial to our ability to move efficiently in a dynamic world. The field of sensorimotor adaptation is replete with rigorous behavioural and computational methods, which support strong conceptual frameworks. An increasing number of studies have combined these methods with electroencephalography (EEG) to unveil insights into the neural mechanisms of adaptation. We review these studies: discussing EEG markers of adaptation in the frequency and the temporal domain, EEG predictors for successful adaptation and how EEG can be used to unmask latent processes resulting from adaptation, such as the modulation of spatial attention. With its high temporal resolution, EEG can be further exploited to deepen our understanding of sensorimotor adaptation.

Task Feedback Processing Differs Between Young and Older Adults in Visuomotor Rotation Learning Despite Similar Initial Adaptation and Savings

Ageing has been suggested to affect sensorimotor adaptation by impairing explicit strategy use. Here we recorded electrophysiological (EEG) responses during visuomotor rotation in both young (n = 24) and older adults (n = 25), to investigate the neural processes that underpin putative age-related effects on adaptation. We measured the feedback related negativity (FRN) and the P3 in response to task-feedback, as electrophysiological markers of task error processing and outcome evaluation. The two age groups adapted similarly and showed comparable after effects and savings when re-exposed to the same perturbation several days after the initial session. Older adults, however, had less distinct EEG responses (i.e., reduced FRN amplitudes) to negative and positive task feedback. The P3 did not differ between age groups. Both young and older adults also showed a sustained late positivity following task feedback. Measured at the frontal electrode Fz, this sustained activity was negatively associated with both the amount of voluntary disengagement of explicit strategy and savings. In conclusion, despite preserved task performance, we find clear differences in neural responses to errors in older people, which suggests that there is a fundamental decline in this aspect of sensorimotor brain function with age.

Mind and body: Psychophysiological profiles of instructional and motivational self-talk

Self-talk is a psychological skill that benefits motor performance by controlling and organizing performers' thoughts. While the behavioral effects of self-talk are clear, research on the mechanisms underpinning the effects of different modes of self-talk is sparse. To address this issue, we propose and test a psychophysiological model of the effects of self-talk on motor performance. Forty golf novices practiced a golf putting task while using either instructional or motivational self-talk preceding each putt. We measured performance (radial error), technique (club kinematics and muscle activity), cardiac activity (heart-rate and event-related heart-rate change), as well as electroencephalographic alpha power and connectivity in a randomized (group: instructional self-talk, motivational self-talk) experimental design. Instructional self-talk promoted superior technique and was associated with greater parietal alpha power and weaker connectivity between frontal and parietal electrodes and all other scalp sites, possibly indicative of increased top-down control of action. These findings provide initial evidence for an information-processing mechanism underlying the benefits of instructional self-talk. They also cast doubt on the validity of left-frontotemporal connectivity as a measure of verbal-analytic processing during motor tasks. Motivational self-talk led to increased heart-rate and reduced event-related heart rate variability, suggesting an effort-based mechanism to explain the benefits of motivational self-talk. Our study represents the most complete multi-measure investigation of self-talk to date. We hope that our psychophysiological model of self-talk will encourage researchers to move beyond the exclusive reliance on behavioral and self-report measures to discover the mechanisms underlying the benefits of self-talk for performance.

Cannabis-dependent adolescents show differences in global reward-associated network topology: A functional connectomics approach

Adolescence may be a period of increased vulnerability to the onset of drug misuse and addiction due to changes in developing brain networks that support cognitive and reward processing. Cannabis is a widely misused illicit drug in adolescence which can lead to dependence and alterations in reward-related neural functioning. Concerns exist that cannabis-related alterations in these reward networks in adolescence may sensitize behaviour towards all forms of reward that increase the risk of further drug use. Taking a functional connectomics approach, we compared an acutely abstinent adolescent cannabis-dependent (CAN) group with adolescent controls (CON) on global measures of network topology associated with anticipation on a monetary incentive delay task. In the presence of overall superior accuracy, the CAN group exhibited superior global connectivity (clustering coefficient, efficiency, characteristic path length) during monetary gain anticipation compared with the CON group. Additional analyses showed that the CAN group exhibited significantly greater connectivity strength during monetary gain anticipation across a subnetwork that included mesocorticolimbic nodes involving both interhemispheric and intrahemispheric connections. We discuss how these differences in reward-associated connectivity may allude to subtle functional alterations in network architecture in adolescent cannabis-dependence that could enhance the motivation for nondrug reward during acute abstinence.

Neurophysiological Correlates of Adaptation and Interference during Asymmetrical Bimanual Movements

In this study, we investigated brain dynamics during interference between hands during bimanual movements. Participants performed a bimanual center-out reaching task in which a visuomotor rotation was applied to the right hand while the left hand did not receive visual feedback of its movements. This manipulation resulted in interference from the adapting right hand to the kinesthetically guided left hand. Electroencephalography (EEG) recordings during the task showed that spectral power in the high and low beta frequency bands was elevated early in exposure, but decreased throughout learning. This may be representative of error-based updating of internal models of movement. Additionally, coherence, a measure of neural functional connectivity, was elevated both within and between hemispheres in the beta frequencies during the initial presentation of the visuomotor rotation, and then decreased throughout adaptation. This suggests that beta oscillatory neural activity may be marker for transmission of conflicting motor information between hemispheres, which manifests in interference between the hands during asymmetrical bimanual movements.

Motor learning and COMT Val158met polymorphism: Analyses of oculomotor behavior and corticocortical communication

Differences in motor learning can be partially explained by differences in genotype. The catechol-O-methyltransferase (COMT) Val158Met polymorphism regulates the dopamine (DA) availability in the prefrontal cortex modulating motor learning and performance. Given the differences in tonic and phasic DA transmission, this study aimed to investigate whether the greater cognitive flexibility associated with the Val allele would favor the learning of movement parametrization, while the greater cognitive stability associated with the Met allele favors the acquisition of the movement pattern. Furthermore, we investigated if the genotypic characteristics impact visual scanning of information related to parametrization and to the movement pattern, and the level of cortical connectivity associated with motor planning and control. Performance and learning of a sequential motor task were compared among three genotypes (Val/Val, Val/Met, and Met/Met), as well as their oculomotor behavior and level of cortical coherence. The findings show that the cognitive flexibility promoted by the Val allele is associated with a better parametrization. The search for information through visual scanning was specific to each genotype. Also, a greater cortical connectivity associated with the Val allele was found. The combined study of behavioral, electrophysiological and molecular levels of analysis showed that the cognitive stability and flexibility associated with the COMT alleles, influence specific aspects of motor learning.

Motor Performance, Mental Workload and Self-Efficacy Dynamics during Learning of Reaching Movements throughout Multiple Practice Sessions

The human capability to learn new motor skills depends on the efficient engagement of cognitive-motor resources, as reflected by mental workload, and psychological mechanisms (e.g., self-efficacy). While numerous investigations have examined the relationship between motor behavior and mental workload or self-efficacy in a performance context, a fairly limited effort focused on the combined examination of these notions during learning. Thus, this study aimed to examine their concomitant dynamics during the learning of a novel reaching skill practiced throughout multiple sessions. Individuals had to learn to control a virtual robotic arm via a human-machine interface by using limited head motion throughout eight practice sessions while motor performance, mental workload, and self-efficacy were assessed. The results revealed that as individuals learned to control the robotic arm, performance improved at the fastest rate, followed by a more gradual reduction of mental workload and finally an increase in self-efficacy. These results suggest that once the performance improved, less cognitive-motor resources were recruited, leading to an attenuated mental workload. Considering that attention is a primary cognitive resource driving mental workload, it is suggested that during early learning, attentional resources are primarily allocated to address task demands and not enough are available to assess self-efficacy. However, as the performance becomes more automatic, a lower level of mental workload is attained driven by decreased recruitment of attentional resources. These available resources allow for a reliable assessment of self-efficacy resulting in a subsequent observable change. These results are also discussed in terms of the application to the training and design of assistive technologies.

Dynamic Office Environments Improve Brain Activity and Attentional Performance Mediated by Increased Motor Activity

Current research demonstrates beneficial effects of physical activity on brain functions and cognitive performance. To date, less is known on the effects of gross motor movements that do not fall into the category of sports-related aerobic or anaerobic exercise. In previous studies, we found beneficial effects of dynamic working environments, i.e., environments that encourage movements during cognitive task performance, on cognitive performance and corresponding brain activity. Aim of the present study was to examine the effects of working in a dynamic and a static office environment on attentional and vigilance performance, and on the corresponding electroencephalographic (EEG) brain oscillatory patterns. In a 2-week intervention study, participants worked either in a dynamic or a static office. In each intervention group, 12 subjects performed attentional and vigilance tasks. Spontaneous EEG was measured from 19 electrodes continuosly before, during, and immediately after each experimental condition at the first, and at the last intervention session. Results showed differences in EEG brain activity in the dynamic compared to the static office at the beginning as well as at the end of the intervention. EEG theta power increased in the vigilance task in anterior regions, alpha power in central and parietal regions in the dynamic compared to the static office. Further, increases in beta activity in the attention and vigilance task were shown in frontal and central regions in the dynamic office. Gamma power increased in the attention task in frontal and central regions. After 2 weeks, effects on brain activity increased in the attentional and vigilance task in the dynamic office. Increased theta and alpha oscillations were obtained in anterior areas with higher activity in the beta band in anterior and central areas in the dynamic compared to the static office. EEG oscillatory patterns indicate beneficial effects of dynamic office environments on attentional and vigilance performance that are mediated by increased motor activity. We discuss the obtained patterns of EEG oscillations in terms of the close interrelations between the attentional and the motor system.

White Matter Microstructure Associations of Cognitive and Visuomotor Control in Children: A Sensory Processing Perspective

Objective: Recent evidence suggests that co-occurring deficits in cognitive control and visuomotor control are common to many neurodevelopmental disorders. Specifically, children with sensory processing dysfunction (SPD), a condition characterized by sensory hyper/hypo-sensitivity, show varying degrees of overlapping attention and visuomotor challenges. In this study, we assess associations between cognitive and visuomotor control abilities among children with and without SPD. In this same context, we also examined the common and unique diffusion tensor imaging (DTI) tracts that may support the overlap of cognitive control and visuomotor control. Method: We collected cognitive control and visuomotor control behavioral measures as well as DTI data in 37 children with SPD and 25 typically developing controls (TDCs). We constructed regressions to assess for associations between behavioral performance and mean fractional anisotropy (FA) in selected regions of interest (ROIs). Results: We observed an association between behavioral performance on cognitive control and visuomotor control. Further, our findings indicated that FA in the anterior limb of the internal capsule (ALIC), the anterior thalamic radiation (ATR), and the superior longitudinal fasciculus (SLF) are associated with both cognitive control and visuomotor control, while FA in the superior corona radiata (SCR) uniquely correlate with cognitive control performance and FA in the posterior limb of the internal capsule (PLIC) and the cerebral peduncle (CP) tract uniquely correlate with visuomotor control performance. Conclusions: These findings suggest that children who demonstrate lower cognitive control are also more likely to demonstrate lower visuomotor control, and vice-versa, regardless of clinical cohort assignment. The overlapping neural tracts, which correlate with both cognitive and visuomotor control suggest a possible common neural mechanism supporting both control-based processes.

Effect of Instrument Structure Alterations on Violin Performance

Extensive training with a musical instrument results in the automatization of the bodily operations needed to manipulate the instrument: the performer no longer has to consciously think about the instrument while playing. The ability of the performer to automate operations on the instrument is due to sensorimotor mechanisms that can predict changes in the state of the body and the instrument in response to motor commands. But how strong are these mechanisms? To what extent can we alter the structure of the instrument before they disappear? We performed an exploratory study to understand whether and how sensorimotor predictions survive instrument modification. We asked seven professional violinists to perform repertoire pieces and sight-reading exercises on four different violins: their own, a cheap violin, a small violin, and a violin whose strings had been put on in reverse order. We performed a series of quantitative investigations on performance intonation and duration, and on bowing gestures and errors. The analysis revealed that participants struggled adapting to the altered instruments, suggesting that prediction mechanisms are a function of instrument configuration. In particular, the analysis of bowing errors, intonation, and of performance duration suggested that the performance with the reverse violin was much less fluent and precise than the performer's own instrument; the performance with the small violin was also sub-standard though to a lesser extent. We also observed that violinists were differently affected by instrument modifications, suggesting that the capability to adapt to a new instrument is highly personal.

Evaluation on Directed Functional Brain Connectivity during the Expert Rifle Pre-shot Period

Experts require long-term and intense practice to acquire extraordinary motor skills that be known as the brain function regulator. However, the brain function network mechanism of rifle shooters is still unclear. The generalized orthogonalized partial directed coherence (gOPDC) algorithm and local efficiency significance analysis method (LESA) was applied to quantify the difference in directed functional networks between expert and novice rifle shooters during the pre-shot period. The more directed functional connections were observed in alpha and low-beta frequency bands as compared to other bands. Moreover, comparing with the novice's fluctuant connection, the values of connection (P3→C3) strength were increasing steadily in the experts during the pre-shot period. Fewer connections in left hemisphere networks were obtained in the experts than in the novices. The results validated the "neural efficiency" hypothesis in experts. Moreover, the strength of the functional connection (P3→C3) in the alpha and beta bands serves as a distinguishing feature between experts and novices.

Cannabis users exhibit increased cortical activation during resting state compared to non-users

Studies have shown altered task-based brain functioning as a result of cannabis use. To date, however, whether similar alterations in baseline resting state and functional organization of neural activity are observable in cannabis users remains unknown. We characterized global resting state cortical activations and functional connectivity via electroencephalography (EEG) in cannabis users and related these activations to measures of cannabis use. Resting state EEG in the eyes closed condition was collected from age- and sex-matched cannabis users (N = 17; 6 females; mean age = 30.9 ± 7.4 years) and non-using controls (N = 21; 9 females; mean age = 33.1 ± 11.6 years). Power spectral density and spectral coherence were computed to determine differences in cortical activations and connectivity between the two groups in the delta (1-4Hz), theta (4-7 Hz), alpha (8-12 Hz), beta (13-30 Hz), and gamma (31-50 Hz) frequency bands. Cannabis users exhibited decreased delta and increased theta, beta, and gamma power compared to controls, suggesting increased cortical activation in resting state and a disinhibition of inhibitory functions that may interrupt cognitive processes. Cannabis users also exhibited increased interhemispheric and intrahemispheric coherence relative to controls, reduced mean network degree, and increased clustering coefficient in specific regions and frequencies. This increased cortical activity may indicate a loss of neural refinement and efficiency that may indicate a "noisy" brain. Lastly, measures related to cannabis use were correlated with spectral power and functional connectivity measures, indicating that specific electrophysiological signals are associated with cannabis use. These results suggest that there are differences in cortical activity and connectivity between cannabis users and non-using controls in the resting state that may be related to putative cognitive impairments and can inform effectiveness of intervention programs.

Visuomotor coordination and cortical connectivity of modular motor learning

The ability to transfer sensorimotor skill components to new actions and the capacity to use skill components from whole actions are characteristic of the adaptability of the human sensorimotor system. However, behavioral evidence suggests complex limitations for transfer after combined or modular learning of motor adaptations. Also, to date, only behavioral analysis of the consequences of the modular learning has been reported, with little understanding of the sensorimotor mechanisms of control and the interaction between cortical areas. We programmed a video game with distorted kinematic and dynamic features to test the ability to combine sensorimotor skill components learned modularly (composition) and the capacity to use separate sensorimotor skill components learned in combination (decomposition). We examined motor performance, eye-hand coordination, and EEG connectivity. When tested for integrated learning, we found that combined practice initially performed better than separated practice, but differences disappeared after integrated practice. Separate learning promotes fewer anticipatory control mechanisms (depending more on feedback control), evidenced in a lower gaze leading behavior and in higher connectivity between visual and premotor domains, in comparison with the combined practice. The sensorimotor system can acquire motor modules in a separated or integrated manner. However, the system appears to require integrated practice to coordinate the adaptations with the skill learning and the networks involved in the integrated behavior. This integration seems to be related to the acquisition of anticipatory mechanism of control and with the decrement of feedback control.

Does practicing a skill with the expectation of teaching alter motor preparatory cortical dynamics?

Recent evidence suggests practicing a motor skill with the expectation of teaching it enhances learning by increasing information processing during motor preparation. However, the specific motor preparatory processes remain unknown. The present study sought to address this shortcoming by employing EEG to assess participants' motor preparatory processes while they completed a golf putting pretest, and then practiced putting with the expectation of (a) teaching another participant how to putt the next day (teach group, n = 30), or (b) being tested on their putting the next day (test group, n = 30). Participants' EEG during the 3-s prior to and 1-s after initiating putter movement was analyzed. All participants completed posttests 1 day after the practice session. The teach group exhibited better posttest performance (superior learning) relative to the test group, but no group differences in motor preparatory processing (EEG) emerged. However, participants in both groups exhibited linear decreases in both theta power at frontal midline and upper-alpha power over motor areas during putt initiation. These results suggest a decrease in working memory and action monitoring (frontal midline theta), and an increase in motor programming (motor upper-alpha) during putt initiation. Further, participants in both groups exhibited increased frontal midline theta from pretest to practice, but decreases in both upper motor-alpha and upper-alpha coherence between left/right temporal and motor planning regions. These results suggest participants utilized working memory and action monitoring to a greater extent during practice relative to pretest, while refining their motor programming and verbal-analytic/visuospatial involvement in motor programming.

Changes in motor performance and mental workload during practice of reaching movements: a team dynamics perspective

Few investigations have examined mental workload during motor practice or learning in a context of team dynamics. This study examines the underlying cognitive-motor processes of motor practice by assessing the changes in motor performance and mental workload during practice of reaching movements. Individuals moved a robotic arm to reach targets as fast and as straight as possible while satisfying the task requirement of avoiding a collision between the end-effector and the workspace limits. Individuals practiced the task either alone (HA group) or with a synthetic teammate (HRT group), which regulated the effector velocity to help satisfy the task requirements. The findings revealed that the performance of both groups improved similarly throughout practice. However, when compared to the individuals of the HA group, those in the HRT group (1) had a lower risk of collisions, (2) exhibited higher performance consistency, and (3) revealed a higher level of mental workload while generally perceiving the robotic teammate as interfering with their performance. As the synthetic teammate changed the effector velocity in specific regions near the workspace boundaries, individuals may have been constrained to learn a piecewise visuomotor map. This piecewise map made the task more challenging, which increased mental workload and perception of the synthetic teammate as a burden. The examination of both motor performance and mental workload revealed a combination of both adaptive and maladaptive team dynamics. This work is a first step to examine the human cognitive-motor processes underlying motor practice in a context of team dynamics and contributes to inform human-robot applications.

Spectral Entropy Can Predict Changes of Working Memory Performance Reduced by Short-Time Training in the Delayed-Match-to-Sample Task

Spectral entropy, which was generated by applying the Shannon entropy concept to the power distribution of the Fourier-transformed electroencephalograph (EEG), was utilized to measure the uniformity of power spectral density underlying EEG when subjects performed the working memory tasks twice, i.e., before and after training. According to Signed Residual Time (SRT) scores based on response speed and accuracy trade-off, 20 subjects were divided into two groups, namely high-performance and low-performance groups, to undertake working memory (WM) tasks. We found that spectral entropy derived from the retention period of WM on channel FC4 exhibited a high correlation with SRT scores. To this end, spectral entropy was used in support vector machine classifier with linear kernel to differentiate these two groups. Receiver operating characteristics analysis and leave-one out cross-validation (LOOCV) demonstrated that the averaged classification accuracy (CA) was 90.0 and 92.5% for intra-session and inter-session, respectively, indicating that spectral entropy could be used to distinguish these two different WM performance groups successfully. Furthermore, the support vector regression prediction model with radial basis function kernel and the root-mean-square error of prediction revealed that spectral entropy could be utilized to predict SRT scores on individual WM performance. After testing the changes in SRT scores and spectral entropy for each subject by short-time training, we found that 16 in 20 subjects’ SRT scores were clearly promoted after training and 15 in 20 subjects’ SRT scores showed consistent changes with spectral entropy before and after training. The findings revealed that spectral entropy could be a promising indicator to predict individual’s WM changes by training and further provide a novel application about WM for brain–computer interfaces.

Multiple Kernel Based Region Importance Learning for Neural Classification of Gait States from EEG Signals

With the development of Brain Machine Interface (BMI) systems, people with motor disabilities are able to control external devices to help them restore movement abilities. Longitudinal validation of these systems is critical not only to assess long-term performance reliability but also to investigate adaptations in electrocortical patterns due to learning to use the BMI system. In this paper, we decode the patterns of user's intended gait states (e.g., stop, walk, turn left, and turn right) from scalp electroencephalography (EEG) signals and simultaneously learn the relative importance of different brain areas by using the multiple kernel learning (MKL) algorithm. The region of importance (ROI) is identified during training the MKL for classification. The efficacy of the proposed method is validated by classifying different movement intentions from two subjects—an able-bodied and a spinal cord injury (SCI) subject. The preliminary results demonstrate that frontal and fronto-central regions are the most important regions for the tested subjects performing gait movements, which is consistent with the brain regions hypothesized to be involved in the control of lower-limb movements. However, we observed some regional changes comparing the able-bodied and the SCI subject. Moreover, in the longitudinal experiments, our findings exhibit the cortical plasticity triggered by the BMI use, as the classification accuracy and the weights for important regions—in sensor space—generally increased, as the user learned to control the exoskeleton for movement over multiple sessions.

Cognitive motor deficits in cannabis users

Cannabis use affects cortico-striatal networks that are essential for producing movement. In this review, we summarize the literature on motor system dysfunction in cannabis users and provide a rationale for why motor learning should be considered an important area in cannabis research. A majority of studies have addressed cognitive impairments in cannabis users and some have focused on driving performance, motor impulsivity, and motor inhibition. Our review of the literature has found that cannabis use is associated with motor performance impairments; however, there is a gap in the literature regarding impairments in motor learning. The involvement of the cortico-striatal network in both cannabis addiction and movement also suggests potential avenues for treatment and rehabilitation via the motor system.