Gray matter volume of functionally relevant primary motor cortex is causally related to learning a hand motor task.

Variability in brain structure is associated with the capacity for behavioral change. However, a causal link between specific brain areas and behavioral change (such as motor learning) has not been demonstrated. We hypothesized that greater gray matter volume of a primary motor cortex (M1) area active during a hand motor learning task is positively correlated with subsequent learning of the task, and that the disruption of this area blocks learning of the task. Healthy participants underwent structural MRI before learning a skilled hand motor task. Next, participants performed this learning task during fMRI to determine M1 areas functionally active during this task. This functional ROI was anatomically constrained with M1 boundaries to create a group-level "Active-M1" ROI used to measure gray matter volume in each participant. Greater gray matter volume in the left hemisphere Active-M1 ROI was related to greater motor learning in the corresponding right hand. When M1 hand area was disrupted with repetitive transcranial stimulation (rTMS), learning of the motor task was blocked, confirming its causal link to motor learning. Our combined imaging and rTMS approach revealed greater cortical volume in a task-relevant M1 area is causally related to learning of a hand motor task in healthy humans.

Performance in myoelectric pattern recognition improves with transcranial direct current stimulation.

Sensorimotor impairments, resulting from conditions like stroke and amputations, can profoundly impact an individual's functional abilities and overall quality of life. Assistive and rehabilitation devices such as prostheses, exo-skeletons, and serious gaming in virtual environments can help to restore some degree of function and alleviate pain after sensorimotor impairments. Myoelectric pattern recognition (MPR) has gained popularity in the past decades as it provides superior control over said devices, and therefore efforts to facilitate and improve performance in MPR can result in better rehabilitation outcomes. One possibility to enhance MPR is to employ transcranial direct current stimulation (tDCS) to facilitate motor learning. Twelve healthy able-bodied individuals participated in this crossover study to determine the effect of tDCS on MPR performance. Baseline training was followed by two sessions of either sham or anodal tDCS using the dominant and non-dominant arms. Assignments were randomized, and the MPR task consisted of 11 different hand/wrist movements, including rest or no movement. Surface electrodes were used to record EMG and the MPR open-source platform, BioPatRec, was used for decoding motor volition in real-time. The motion test was used to evaluate performance. We hypothesized that using anodal tDCS to increase the excitability of the primary motor cortex associated with non-dominant side in able-bodied individuals, will improve motor learning and thus MPR performance. Overall, we found that tDCS enhanced MPR performance, particularly in the non-dominant side. We were able to reject the null hypothesis and improvements in the motion test's completion rate during tDCS (28% change, p-value: 0.023) indicate its potential as an adjunctive tool to enhance MPR and motor learning. tDCS appears promising as a tool to enhance the learning phase of using assistive devices using MPR, such as myoelectric prostheses.

Localized and global representation of prior value, sensory evidence, and choice in male mouse cerebral cortex.

Adaptive behavior requires integrating prior knowledge of action outcomes and sensory evidence for making decisions while maintaining prior knowledge for future actions. As outcome- and sensory-based decisions are often tested separately, it is unclear how these processes are integrated in the brain. In a tone frequency discrimination task with two sound durations and asymmetric reward blocks, we found that neurons in the medial prefrontal cortex of male mice represented the additive combination of prior reward expectations and choices. The sensory inputs and choices were selectively decoded from the auditory cortex irrespective of reward priors and the secondary motor cortex, respectively, suggesting localized computations of task variables are required within single trials. In contrast, all the recorded regions represented prior values that needed to be maintained across trials. We propose localized and global computations of task variables in different time scales in the cerebral cortex.

Cerebral cortex activation and functional connectivity during low-load resistance training with blood flow restriction: An fNIRS study.

Despite accumulating evidence that blood flow restriction (BFR) training promotes muscle hypertrophy and strength gain, the underlying neurophysiological mechanisms have rarely been explored. The primary goal of this study is to investigate characteristics of cerebral cortex activity during BFR training under different pressure intensities. 24 males participated in 30% 1RM squat exercise, changes in oxygenated hemoglobin concentration (HbO) in the primary motor cortex (M1), pre-motor cortex (PMC), supplementary motor area (SMA), and dorsolateral prefrontal cortex (DLPFC), were measured by fNIRS. The results showed that HbO increased from 0 mmHg (non-BFR) to 250 mmHg but dropped sharply under 350 mmHg pressure intensity. In addition, HbO and functional connectivity were higher in M1 and PMC-SMA than in DLPFC. Moreover, the significant interaction effect between pressure intensity and ROI for HbO revealed that the regulation of cerebral cortex during BFR training was more pronounced in M1 and PMC-SMA than in DLPFC. In conclusion, low-load resistance training with BFR triggers acute responses in the cerebral cortex, and moderate pressure intensity achieves optimal neural benefits in enhancing cortical activation. M1 and PMC-SMA play crucial roles during BFR training through activation and functional connectivity regulation.

Long-lasting negativity in the left motoric brain structures during word memory inhibition in the Think/No-Think paradigm.

In this study, we investigated the electrical brain responses in a high-density EEG array (64 electrodes) elicited specifically by the word memory cue in the Think/No-Think paradigm in 46 participants. In a first step, we corroborated previous findings demonstrating sustained and reduced brain electrical frontal and parietal late potentials elicited by memory cues following the No-Think (NT) instructions as compared to the Think (T) instructions. The topographical analysis revealed that such reduction was significant 1000 ms after memory cue onset and that it was long-lasting for 1000 ms. In a second step, we estimated the underlying brain generators with a distributed method (swLORETA) which does not preconceive any localization in the gray matter. This method revealed that the cognitive process related to the inhibition of memory retrieval involved classical motoric cerebral structures with the left primary motor cortex (M1, BA4), thalamus, and premotor cortex (BA6). Also, the right frontal-polar cortex was involved in the T condition which we interpreted as an indication of its role in the maintaining of a cognitive set during remembering, by the selection of one cognitive mode of processing, Think, over the other, No-Think, across extended periods of time, as it might be necessary for the successful execution of the Think/No-Think task.

Video mirror feedback induces more extensive brain activation compared to the mirror box: an fNIRS study in healthy adults.

BACKGROUND: Mirror therapy (MT) has been shown to be effective for motor recovery of the upper limb after a stroke. The cerebral mechanisms of mirror therapy involve the precuneus, premotor cortex and primary motor cortex. Activation of the precuneus could be a marker of this effectiveness. MT has some limitations and video therapy (VT) tools are being developed to optimise MT. While the clinical superiority of these new tools remains to be demonstrated, comparing the cerebral mechanisms of these different modalities will provide a better understanding of the related neuroplasticity mechanisms. METHODS: Thirty-three right-handed healthy individuals were included in this study. Participants were equipped with a near-infrared spectroscopy headset covering the precuneus, the premotor cortex and the primary motor cortex of each hemisphere. Each participant performed 3 tasks: a MT task (right hand movement and left visual feedback), a VT task (left visual feedback only) and a control task (right hand movement only). Perception of illusion was rated for MT and VT by asking participants to rate the intensity using a visual analogue scale. The aim of this study was to compare brain activation during MT and VT. We also evaluated the correlation between the precuneus activation and the illusion quality of the visual mirrored feedback. RESULTS: We found a greater activation of the precuneus contralateral to the visual feedback during VT than during MT. We also showed that activation of primary motor cortex and premotor cortex contralateral to visual feedback was more extensive in VT than in MT. Illusion perception was not correlated with precuneus activation. CONCLUSION: VT led to greater activation of a parieto-frontal network than MT. This could result from a greater focus on visual feedback and a reduction in interhemispheric inhibition in VT because of the absence of an associated motor task. These results suggest that VT could promote neuroplasticity mechanisms in people with brain lesions more efficiently than MT. CLINICAL TRIAL REGISTRATION: NCT04738851.

A longitudinal electrophysiological and behavior dataset for PD rat in response to deep brain stimulation.

Here we presented an electrophysiological dataset collected from layer V of the primary motor cortex (M1) and the corresponding behavior dataset from normal and hemi-parkinson rats over 5 consecutive weeks. The electrophysiological dataset was constituted by the raw wideband signal, neuronal spikes, and local field potential (LFP) signal. The open-field test was done and recorded to evaluate the behavior variation of rats among the entire experimental cycle. We conducted technical validation of this dataset through sorting the spike data to form action potential waveforms and analyzing the spectral power of LFP data, then based on these findings a closed-loop DBS protocol was developed by the oscillation activity response of M1 LFP signal. Additionally, this protocol was applied to the hemi-parkinson rat for five consecutive days while simultaneously recording the electrophysiological data. This dataset is currently the only publicly available dataset that includes longitudinal closed-loop DBS recordings, which can be utilized to investigate variations of neuronal activity within the M1 following long-term closed-loop DBS, and explore additional reliable biomarkers.

The effects of verbal and spatial working memory on short- and long-latency sensorimotor circuits in the motor cortex.

Multiple sensorimotor loops converge in the motor cortex to create an adaptable system capable of context-specific sensorimotor control. Afferent inhibition provides a non-invasive tool to investigate the substrates by which procedural and cognitive control processes interact to shape motor corticospinal projections. Varying the transcranial magnetic stimulation properties during afferent inhibition can probe specific sensorimotor circuits that contribute to short- and long-latency periods of inhibition in response to the peripheral stimulation. The current study used short- (SAI) and long-latency (LAI) afferent inhibition to probe the influence of verbal and spatial working memory load on the specific sensorimotor circuits recruited by posterior-anterior (PA) and anterior-posterior (AP) TMS-induced current. Participants completed two sessions where SAI and LAI were assessed during the short-term maintenance of two- or six-item sets of letters (verbal) or stimulus locations (spatial). The only difference between the sessions was the direction of the induced current. PA SAI decreased as the verbal working memory load increased. In contrast, AP SAI was not modulated by verbal working memory load. Visuospatial working memory load did not affect PA or AP SAI. Neither PA LAI nor AP LAI were sensitive to verbal or spatial working memory load. The dissociation of short-latency PA and AP sensorimotor circuits and short- and long-latency PA sensorimotor circuits with increasing verbal working memory load support multiple convergent sensorimotor loops that provide distinct functional information to facilitate context-specific supraspinal control.

Oscillating latent dynamics in robot systems during walking and reaching.

Sensorimotor control of complex, dynamic systems such as humanoids or quadrupedal robots is notoriously difficult. While artificial systems traditionally employ hierarchical optimisation approaches or black-box policies, recent results in systems neuroscience suggest that complex behaviours such as locomotion and reaching are correlated with limit cycles in the primate motor cortex. A recent result suggests that, when applied to a learned latent space, oscillating patterns of activation can be used to control locomotion in a physical robot. While reminiscent of limit cycles observed in primate motor cortex, these dynamics are unsurprising given the cyclic nature of the robot's behaviour (walking). In this preliminary investigation, we consider how a similar approach extends to a less obviously cyclic behaviour (reaching). This has been explored in prior work using computational simulations. But simulations necessarily make simplifying assumptions that do not necessarily correspond to reality, so do not trivially transfer to real robot platforms. Our primary contribution is to demonstrate that we can infer and control real robot states in a learnt representation using oscillatory dynamics during reaching tasks. We further show that the learned latent representation encodes interpretable movements in the robot's workspace. Compared to robot locomotion, the dynamics that we observe for reaching are not fully cyclic, as they do not begin and end at the same position of latent space. However, they do begin to trace out the shape of a cycle, and, by construction, they are driven by the same underlying oscillatory mechanics.

Anodal transcranial direct current stimulation enhances response inhibition and attention allocation in fencers.

Background: The aim of this study is to investigate the acute effects of anodal transcranial direct current stimulation (tDCS) on reaction time, response inhibition and attention in fencers. Methods: Sixteen professional female fencers were recruited, and subjected to anodal tDCS and sham stimulation in the primary motor area (M1) one week apart in a randomized, crossover, single-blind design. A two-factor analysis of variance with repeated measures was used to analyze the effects of stimulation conditions (anodal stimulation, sham stimulation) and time (pre-stimulation, post-stimulation) on reaction time, response inhibition, and attention in fencers. Results: The study found a significant improvement in response inhibition and attention allocation from pre-stimulation to post-stimulation following anodal tDCS but not after sham stimulation. There was no statistically significant improvement in reaction time and selective attention. Conclusions: A single session of anodal tDCS could improve response inhibition, attention allocation in female fencers. This shows that tDCS has potential to improve aspects of an athlete's cognitive performance, although we do not know if such improvements would transfer to improved performance in competition. However, more studies involving all genders, large samples, and different sports groups are needed in the future to further validate the effect of tDCS in improving the cognitive performance of athletes.

Cholecystokinin facilitates motor skill learning by modulating neuroplasticity in the motor cortex.

Cholecystokinin (CCK) is an essential modulator for neuroplasticity in sensory and emotional domains. Here, we investigated the role of CCK in motor learning using a single pellet reaching task in mice. Mice with a knockout of Cck gene (Cck-/-) or blockade of CCK-B receptor (CCKBR) showed defective motor learning ability; the success rate of retrieving reward remained at the baseline level compared to the wildtype mice with significantly increased success rate. We observed no long-term potentiation upon high-frequency stimulation in the motor cortex of Cck-/- mice, indicating a possible association between motor learning deficiency and neuroplasticity in the motor cortex. In vivo calcium imaging demonstrated that the deficiency of CCK signaling disrupted the refinement of population neuronal activity in the motor cortex during motor skill training. Anatomical tracing revealed direct projections from CCK-expressing neurons in the rhinal cortex to the motor cortex. Inactivation of the CCK neurons in the rhinal cortex that project to the motor cortex bilaterally using chemogenetic methods significantly suppressed motor learning, and intraperitoneal application of CCK4, a tetrapeptide CCK agonist, rescued the motor learning deficits of Cck-/- mice. In summary, our results suggest that CCK, which could be provided from the rhinal cortex, may surpport motor skill learning by modulating neuroplasticity in the motor cortex.

De novo motor learning creates structure in neural activity that shapes adaptation.

Animals can quickly adapt learned movements to external perturbations, and their existing motor repertoire likely influences their ease of adaptation. Long-term learning causes lasting changes in neural connectivity, which shapes the activity patterns that can be produced during adaptation. Here, we examined how a neural population's existing activity patterns, acquired through de novo learning, affect subsequent adaptation by modeling motor cortical neural population dynamics with recurrent neural networks. We trained networks on different motor repertoires comprising varying numbers of movements, which they acquired following various learning experiences. Networks with multiple movements had more constrained and robust dynamics, which were associated with more defined neural 'structure'-organization in the available population activity patterns. This structure facilitated adaptation, but only when the changes imposed by the perturbation were congruent with the organization of the inputs and the structure in neural activity acquired during de novo learning. These results highlight trade-offs in skill acquisition and demonstrate how different learning experiences can shape the geometrical properties of neural population activity and subsequent adaptation.

Dynamical and individualised approach of transcranial ultrasound neuromodulation effects in non-human primates.

Low-frequency transcranial ultrasound stimulation (TUS) allows to alter brain functioning with a high spatial resolution and to reach deep targets. However, the time-course of TUS effects remains largely unknown. We applied TUS on three brain targets for three different monkeys: the anterior medial prefrontal cortex, the supplementary motor area and the perigenual anterior cingulate cortex. For each, one resting-state fMRI was acquired between 30 and 150 min after TUS as well as one without stimulation (control). We captured seed-based brain connectivity changes dynamically and on an individual basis. We also assessed between individuals and between targets homogeneity and brain features that predicted TUS changes. We found that TUS prompts heterogenous functional connectivity alterations yet retain certain consistent changes; we identified 6 time-courses of changes including transient and long duration alterations; with a notable degree of accuracy we found that brain alterations could partially be predicted. Altogether, our results highlight that TUS induces heterogeneous functional connectivity alterations. On a more technical point, we also emphasize the need to consider brain changes over-time rather than just observed during a snapshot; to consider inter-individual variability since changes could be highly different from one individual to another.

Higher surface folding of the human premotor cortex is associated with better long-term learning capability.

The capacity to learn enabled the human species to adapt to various challenging environmental conditions and pass important achievements on to the next generation. A growing body of research suggests links between neocortical folding properties and numerous aspects of human behavior, but their impact on enhanced human learning capacity remains unexplored. Here we leverage three training cohorts to demonstrate that higher levels of premotor cortical folding reliably predict individual long-term learning gains in a challenging new motor task, above and beyond initial performance differences. Individual folding-related predisposition to motor learning was found to be independent of cortical thickness and intracortical microstructure, but dependent on larger cortical surface area in premotor regions. We further show that learning-relevant features of cortical folding occurred in close spatial proximity to practice-induced structural brain plasticity. Our results suggest a link between neocortical surface folding and human behavioral adaptability.

Information flow between motor cortex and striatum reverses during skill learning.

The coordination of neural activity across brain areas during a specific behavior is often interpreted as neural communication involved in controlling the behavior. However, whether information relevant to the behavior is actually transferred between areas is often untested. Here, we used information-theoretic tools to quantify how motor cortex and striatum encode and exchange behaviorally relevant information about specific reach-to-grasp movement features during skill learning in rats. We found a temporal shift in the encoding of behaviorally relevant information during skill learning, as well as a reversal in the primary direction of behaviorally relevant information flow, from cortex-to-striatum during naive movements to striatum-to-cortex during skilled movements. Standard analytical methods that quantify the evolution of overall neural activity during learning-such as changes in neural signal amplitude or the overall exchange of information between areas-failed to capture these behaviorally relevant information dynamics. Using these standard methods, we instead found a consistent coactivation of overall neural signals during movement production and a bidirectional increase in overall information propagation between areas during learning. Our results show that skill learning is achieved through a transformation in how behaviorally relevant information is routed across cortical and subcortical brain areas and that isolating the components of neural activity relevant to and informative about behavior is critical to uncover directional interactions within a coactive and coordinated network.

Differential Modulation of Local Field Potentials in the Primary and Premotor Cortices during Ipsilateral and Contralateral Reach to Grasp in Macaque Monkeys.

Hand movements are associated with modulations of neuronal activity across several interconnected cortical areas, including the primary motor cortex (M1) and the dorsal and ventral premotor cortices (PMd and PMv). Local field potentials (LFPs) provide a link between neuronal discharges and synaptic inputs. Our current understanding of how LFPs vary in M1, PMd, and PMv during contralateral and ipsilateral movements is incomplete. To help reveal unique features in the pattern of modulations, we simultaneously recorded LFPs in these areas in two macaque monkeys performing reach and grasp movements with either the right or left hand. The greatest effector-dependent differences were seen in M1, at low (≤13 Hz) and γ frequencies. In premotor areas, differences related to hand use were only present in low frequencies. PMv exhibited the greatest increase in low frequencies during instruction cues and the smallest effector-dependent modulation during movement execution. In PMd, δ oscillations were greater during contralateral reach and grasp, and ß activity increased during contralateral grasp. In contrast, ß oscillations decreased in M1 and PMv. These results suggest that while M1 primarily exhibits effector-specific LFP activity, premotor areas compute more effector-independent aspects of the task requirements, particularly during movement preparation for PMv and production for PMd. The generation of precise hand movements likely relies on the combination of complementary information contained in the unique pattern of neural modulations contained in each cortical area. Accordingly, integrating LFPs from premotor areas and M1 could enhance the performance and robustness of brain-machine interfaces.

Effects of transcranial direct current stimulation and sensorimotor training in anterior cruciate ligament patients: a sham-controlled pilot study.

BACKGROUND: Studies showed changes in the central nervous system in patients who sustained an anterior cruciate ligament tear. There is a lack of evidence regarding the effectiveness of transcranial direct-current stimulation in such patients. METHODS: A sham-controlled randomised study. One group of patients (n = 6) underwent 6 weeks of sensorimotor training after an anterior cruciate ligament tear during transcranial direct-current stimulation. The stimulation consisted of 20 minutes (3 sessions/week; 2 weeks) of 2 mA anodal transcranial direct-current stimulation over the primary motor and premotor cortex. The second group (n = 6) received sham stimulation with 6 weeks of sensorimotor training. Centre of pressure deviations in the medio-lateral and anterior-posterior direction and centre of pressure velocity were measured. RESULTS: The results demonstrated a significant effect of sensorimotor training on the centre of pressure in medio-lateral and anterior-posterior direction (p=0.025) (p=0.03) in the leg in which an anterior cruciate ligament tear occurred. The type of training did not affect the results. Post-hoc tests showed no significant effect of training in the subgroups (p≥0.115). CONCLUSION: Sensorimotor training led to a decrease in sway of the centre of pressure in patients who sustained an anterior cruciate ligament tear, but the addition of anodal transcranial direct-current stimulation placed over the primary motor cortex did not potentiate the adaptive responses of the sensorimotor training.

Motor, somatosensory, and executive cortical areas elicit monosynaptic and polysynaptic neuronal activity in the auditory midbrain.

We recently reported that the central nucleus of the inferior colliculus (the auditory midbrain) is innervated by glutamatergic pyramidal cells originating not only in auditory cortex (AC), but also in multiple 'non-auditory' regions of the cerebral cortex. Here, in anaesthetised rats, we used optogenetics and electrical stimulation, combined with recording in the inferior colliculus to determine the functional influence of these descending connections. Specifically, we determined the extent of monosynaptic excitation and the influence of these descending connections on spontaneous activity in the inferior colliculus. A retrograde virus encoding both green fluorescent protein (GFP) and channelrhodopsin (ChR2) injected into the central nucleus of the inferior colliculus (ICc) resulted in GFP expression in discrete groups of cells in multiple areas of the cerebral cortex. Light stimulation of AC and primary motor cortex (M1) caused local activation of cortical neurones and increased the firing rate of neurones in ICc indicating a direct excitatory input from AC and M1 to ICc with a restricted distribution. In naïve animals, electrical stimulation at multiple different sites within M1, secondary motor, somatosensory, and prefrontal cortices increased firing rate in ICc. However, it was notable that stimulation at some adjacent sites failed to influence firing at the recording site in ICc. Responses in ICc comprised singular spikes of constant shape and size which occurred with a short, and fixed latency (∼ 5 ms) consistent with monosynaptic excitation of individual ICc units. Increasing the stimulus current decreased the latency of these spikes, suggesting more rapid depolarization of cortical neurones, and increased the number of (usually adjacent) channels on which a monosynaptic spike was seen, suggesting recruitment of increasing numbers of cortical neurons. Electrical stimulation of cortical regions also evoked longer latency, longer duration increases in firing activity, comprising multiple units with spikes occurring with significant temporal jitter, consistent with polysynaptic excitation. Increasing the stimulus current increased the number of spikes in these polysynaptic responses and increased the number of channels on which the responses were observed, although the magnitude of the responses always diminished away from the most activated channels. Together our findings indicate descending connections from motor, somatosensory and executive cortical regions directly activate small numbers of ICc neurones and that this in turn leads to extensive polysynaptic activation of local circuits within the ICc.

Human local field potentials in motor and non-motor brain areas encode upcoming movement direction.

Limb movement direction can be inferred from local field potentials in motor cortex during movement execution. Yet, it remains unclear to what extent intended hand movements can be predicted from brain activity recorded during movement planning. Here, we set out to probe the directional-tuning of oscillatory features during motor planning and execution, using a machine learning framework on multi-site local field potentials (LFPs) in humans. We recorded intracranial EEG data from implanted epilepsy patients as they performed a four-direction delayed center-out motor task. Fronto-parietal LFP low-frequency power predicted hand-movement direction during planning while execution was largely mediated by higher frequency power and low-frequency phase in motor areas. By contrast, Phase-Amplitude Coupling showed uniform modulations across directions. Finally, multivariate classification led to an increase in overall decoding accuracy (>80%). The novel insights revealed here extend our understanding of the role of neural oscillations in encoding motor plans.