Movement related cortical potentials of cued versus self-initiated movements: double dissociated modulation by dorsal premotor cortex versus supplementary motor area rTMS

Connecting the dots: Sensory cueing enhances functional connectivity between pre-motor and supplementary motor areas in Parkinson's disease

People with Parkinson's disease often exhibit improvements in motor tasks when exposed to external sensory cues. While the effects of different types of sensory cues on motor functions in Parkinson's disease have been widely studied, the underlying neural mechanism of these effects and the potential of sensory cues to alter the motor cortical activity patterns and functional connectivity of cortical motor areas are still unclear. This study aims to compare changes in oxygenated haemoglobin, deoxygenated haemoglobin and correlations among different cortical regions of interest during wrist movement under different external stimulus conditions between people with Parkinson's disease and controls. Ten Parkinson's disease patients and 10 age- and sex-matched neurologically healthy individuals participated, performing repetitive wrist flexion and extension tasks under auditory and visual cues. Changes in oxygenated and deoxygenated haemoglobin in motor areas were measured using functional near-infrared spectroscopy, along with electromyograms from wrist muscles and wrist movement kinematics. The functional near-infrared spectroscopy data revealed significantly higher neural activity changes in the Parkinson's disease group's pre-motor area compared to controls (p = 0.006), and functional connectivity between the supplementary motor area and pre-motor area was also significantly higher in the Parkinson's disease group when external sensory cues were present (p = 0.016). These results indicate that external sensory cues' beneficial effects on motor tasks are linked to changes in the functional connectivity between motor areas responsible for planning and preparation of movements.

The Effect of Caffeine on Movement-Related Cortical Potential Morphology and Detection

Movement-related cortical potential (MRCP) is observed in EEG recordings prior to a voluntary movement. It has been used for e.g., quantifying motor learning and for brain-computer interfacing (BCIs). The MRCP amplitude is affected by various factors, but the effect of caffeine is underexplored. The aim of this study was to investigate if a cup of coffee with 85 mg caffeine modulated the MRCP amplitude and the classification of MRCPs versus idle activity, which estimates BCI performance. Twenty-six healthy participants performed 2 × 100 ankle dorsiflexion separated by a 10-min break before a cup of coffee was consumed, followed by another 100 movements. EEG was recorded during the movements and divided into epochs, which were averaged to extract three average MRCPs that were compared. Also, idle activity epochs were extracted. Features were extracted from the epochs and classified using random forest analysis. The MRCP amplitude did not change after consuming caffeine. There was a slight increase of two percentage points in the classification accuracy after consuming caffeine. In conclusion, a cup of coffee with 85 mg caffeine does not affect the MRCP amplitude, and improves MRCP-based BCI performance slightly. The findings suggest that drinking coffee is only a minor confounder in MRCP-related studies.

Effect of transcranial static magnetic stimulation over unilateral or bilateral motor association cortex on performance of simple and choice reaction time tasks

Background

Transcranial static magnetic stimulation (tSMS) is a non-invasive brain stimulation technique that place a strong neodymium magnet on scalp to reduce cortical excitability. We have recently developed a new tSMS device with three magnets placed close to each other (triple tSMS) and confirmed that this new device can produce a stronger and broader static magnetic field than the conventional single tSMS. The aim of the present study was to investigate the effect of the conventional single tSMS as well as triple tSMS over the unilateral or bilateral motor association cortex (MAC) on simple and choice reaction time (SRT and CRT) task performance.

Methods

There were two experiments: one involved the conventional tSMS, and the other involved the triple tSMS. In both experiments, right-handed healthy participants received each of the following stimulations for 20 min on different days: tSMS over the unilateral (left) MAC, tSMS over the bilateral MAC, and sham stimulation. The center of the stimulation device was set at the premotor cortex. The participants performed SRT and CRT tasks before, immediately after, and 15 min after the stimulation (Pre, Post 0, and Post 15). We evaluated RT, standard deviation (SD) of RT, and accuracy (error rate). Simulation was also performed to determine the spatial distribution of magnetic field induced by tSMS over the bilateral MAC.

Results

The spatial distribution of induced magnetic field was centered around the PMd for both tSMS systems, and the magnetic field reached multiple regions of the MAC as well as the sensorimotor cortices for triple tSMS. SD of CRT was significantly larger at Post 0 as compared to Pre when triple tSMS was applied to the bilateral MAC. No significant findings were noted for the other conditions or variables.

Discussion

We found that single tSMS over the unilateral or bilateral MAC did not affect performance of RT tasks, whereas triple tSMS over the bilateral MAC but not over the unilateral MAC increased variability of CRT. Our finding suggests that RT task performance can be modulated using triple tSMS.

Premotor cortex is hypoactive during sustained vowel production in individuals with Parkinson's disease and hypophonia

Introduction

Hypophonia is a common feature of Parkinson's disease (PD); however, the contribution of motor cortical activity to reduced phonatory scaling in PD is still not clear.

Methods

In this study, we employed a sustained vowel production task during functional magnetic resonance imaging to compare brain activity between individuals with PD and hypophonia and an older healthy control (OHC) group.

Results

When comparing vowel production versus rest, the PD group showed fewer regions with significant BOLD activity compared to OHCs. Within the motor cortices, both OHC and PD groups showed bilateral activation of the laryngeal/phonatory area (LPA) of the primary motor cortex as well as activation of the supplementary motor area. The OHC group also recruited additional activity in the bilateral trunk motor area and right dorsal premotor cortex (PMd). A voxel-wise comparison of PD and HC groups showed that activity in right PMd was significantly lower in the PD group compared to OHC (p < 0.001, uncorrected). Right PMd activity was positively correlated with maximum phonation time in the PD group and negatively correlated with perceptual severity ratings of loudness and pitch.

Discussion

Our findings suggest that hypoactivation of PMd may be associated with abnormal phonatory control in PD.

Enhancing Prediction of Forelimb Movement Trajectory through a Calibrating-Feedback Paradigm Incorporating RAT Primary Motor and Agranular Cortical Ensemble Activity in the Goal-Directed Reaching Task

Complete reaching movements involve target sensing, motor planning, and arm movement execution, and this process requires the integration and communication of various brain regions. Previously, reaching movements have been decoded successfully from the motor cortex (M1) and applied to prosthetic control. However, most studies attempted to decode neural activities from a single brain region, resulting in reduced decoding accuracy during visually guided reaching motions. To enhance the decoding accuracy of visually guided forelimb reaching movements, we propose a parallel computing neural network using both M1 and medial agranular cortex (AGm) neural activities of rats to predict forelimb-reaching movements. The proposed network decodes M1 neural activities into the primary components of the forelimb movement and decodes AGm neural activities into internal feedforward information to calibrate the forelimb movement in a goal-reaching movement. We demonstrate that using AGm neural activity to calibrate M1 predicted forelimb movement can improve decoding performance significantly compared to neural decoders without calibration. We also show that the M1 and AGm neural activities contribute to controlling forelimb movement during goal-reaching movements, and we report an increase in the power of the local field potential (LFP) in beta and gamma bands over AGm in response to a change in the target distance, which may involve sensorimotor transformation and communication between the visual cortex and AGm when preparing for an upcoming reaching movement. The proposed parallel computing neural network with the internal feedback model improves prediction accuracy for goal-reaching movements.

Top-down reconfiguration of SMA cortical connectivity during action preparation

The Bereitschaftspotential (BP), a scalp potential recorded in humans during action preparation, is characterized by a slow amplitude increase over fronto-central regions as action execution approaches. We recorded TMS evoked-potentials (TEP) stimulating the supplementary motor area (SMA) at different time-points during a Go/No-Go task to assess whether and how cortical excitability and connectivity of this region change as the BP increases. When approaching BP peak, left SMA reactivity resulted greater. Concurrently, its effective connectivity increased with the left occipital areas, while it decreased with the right inferior frontal gyrus, indicating a fast reconfiguration of cortical networks during the preparation of the forthcoming action. Functional connectivity patterns supported these findings, suggesting a critical role of frequency-specific inter-areal interactions in implementing top-down mechanisms in the sensorimotor system prior to action. These findings reveal that BP time-course reflects quantitative and qualitative changes in SMA communication patterns that shape mechanisms involved in motor readiness.

Design and Validation of a Low-Cost Mobile EEG-Based Brain-Computer Interface

Objective: We designed and validated a wireless, low-cost, easy-to-use, mobile, dry-electrode headset for scalp electroencephalography (EEG) recordings for closed-loop brain-computer (BCI) interface and internet-of-things (IoT) applications. Approach: The EEG-based BCI headset was designed from commercial off-the-shelf (COTS) components using a multi-pronged approach that balanced interoperability, cost, portability, usability, form factor, reliability, and closed-loop operation. Main Results: The adjustable headset was designed to accommodate 90% of the population. A patent-pending self-positioning dry electrode bracket allowed for vertical self-positioning while parting the user's hair to ensure contact of the electrode with the scalp. In the current prototype, five EEG electrodes were incorporated in the electrode bracket spanning the sensorimotor cortices bilaterally, and three skin sensors were included to measure eye movement and blinks. An inertial measurement unit (IMU) provides monitoring of head movements. The EEG amplifier operates with 24-bit resolution up to 500 Hz sampling frequency and can communicate with other devices using 802.11 b/g/n WiFi. It has high signal-to-noise ratio (SNR) and common-mode rejection ratio (CMRR) (121 dB and 110 dB, respectively) and low input noise. In closed-loop BCI mode, the system can operate at 40 Hz, including real-time adaptive noise cancellation and 512 MB of processor memory. It supports LabVIEW as a backend coding language and JavaScript (JS), Cascading Style Sheets (CSS), and HyperText Markup Language (HTML) as front-end coding languages and includes training and optimization of support vector machine (SVM) neural classifiers. Extensive bench testing supports the technical specifications and human-subject pilot testing of a closed-loop BCI application to support upper-limb rehabilitation and provides proof-of-concept validation for the device's use at both the clinic and at home. Significance: The usability, interoperability, portability, reliability, and programmability of the proposed wireless closed-loop BCI system provides a low-cost solution for BCI and neurorehabilitation research and IoT applications.

Readiness potential reflects the intention of sit-to-stand movement

The negative-going movement-related cortical potentials are associated with the preparation and execution of the voluntary movements. Thus far, the readiness potential (RP) for simple movements involving either the upper or lower body segments has been studied. We investigated the ability to decode the sit-to-stand movement's intention from the RP, which uses the upper and lower body segments. Therefore, we performed scalp electroencephalography in healthy volunteers. A gyro sensor was placed on the back to detect the movement of the upper body segment, and an electromyogram electrode was placed on the surface of the hamstrings and quadriceps to detect movement of the lower body segment. Our study revealed that a negative RP was evoked around 2 to 3 s before the onset of the upper body movement in the sit-to-stand movement in response to the start cue. The RP had a negative peak and a steeper negative slope from - 0.8 to - 0.001 s just before the onset of the upper body movement. Negative-going RPs reflect the intention of preparation/execution of the sit-to-stand movement. Therefore, we used the morphological component analysis method to extract the morphology of RPs from a single trial. This morphology of RPs is a promising aspect for limb neurotrophies or neurorehabilitation devices.

Predicting motor behavior: an efficient EEG signal processing pipeline to detect brain states with potential therapeutic relevance for VR-based neurorehabilitation

Virtual reality (VR)-based motor therapy is an emerging approach in neurorehabilitation. The combination of VR with electroencephalography (EEG) presents further opportunities to improve therapeutic efficacy by personalizing the paradigm. Specifically, the idea is to synchronize the choice and timing of stimuli in the perceived virtual world with fluctuating brain states relevant to motor behavior. Here, we present an open source EEG single-trial based classification pipeline that is designed to identify ongoing brain states predictive of the planning and execution of movements. 9 healthy volunteers each performed 1080 trials of a repetitive reaching task with an implicit two-alternative forced choice, i.e., use of the right or left hand, in response to the appearance of a visual target. The performance of the EEG decoding pipeline was assessed with respect to classification accuracy of right vs. left arm use, based on the EEG signal at the time of the stimulus. Different features, feature extraction methods, and classifiers were compared at different time windows; the number and location of informative EEG channels and the number of calibration trials needed were also quantified, as well as any benefits from individual-level optimization of pipeline parameters. This resulted in a set of recommended parameters that achieved an average 83.3% correct prediction on never-before-seen testing data, and a state-of-the-art 77.1% in a real-time simulation. Neurophysiological plausibility of the resulting classifiers was assessed by time-frequency and event-related potential analyses, as well as by Independent Component Analysis topographies and cortical source localization. We expect that this pipeline will facilitate the identification of relevant brain states as prospective therapeutic targets in closed-loop EEG-VR motor neurorehabilitation.

Decoding Hand Movement Types and Kinematic Information From Electroencephalogram

Brain-computer interfaces (BCIs) have achieved successful control of assistive devices, e.g. neuroprosthesis or robotic arm. Previous research based on hand movements Electroencephalogram (EEG) has shown limited success in precise and natural control. In this study, we explored the possibilities of decoding movement types and kinematic information for three reach-and-execute actions using movement-related cortical potentials (MRCPs). EEG signals were acquired from 12 healthy subjects during the execution of pinch, palmar and precision disk rotation actions that involved two levels of speeds and forces. In the case of discrimination between hand movement types under each of four different kinematics conditions, we obtained the average peak accuracies of 83.44% and 73.83% for the binary and 3-class classification, respectively. In the case of discrimination between different movement kinematics for each of three actions, the average peak accuracies of 82.9% and 58.2% could be achieved for the two and 4-class scenario. In both cases, peak decoding performance was significantly higher than the subject-specific chance level. We found that hand movement types all could be classified when these actions were executed at four different kinematic parameters. Meanwhile, for each of three hand movements, we decoded movement parameters successfully. Furthermore, the feasibility of decoding hand movements during hand retraction process was also demonstrated. These findings are of great importance for controlling neuroprosthesis or other rehabilitation devices in a fine and natural way, which would drastically increase the acceptance of motor impaired users.

Intermittent Theta Burst Stimulation to the Primary Motor Cortex Reduces Cortical Inhibition: A TMS-EEG Study

Introduction: The aim of this study was to reveal the effects of intermittent theta burst stimulation (iTBS) in modulating cortical networks using transcranial magnetic stimulation and electroencephalography (TMS-EEG) recording. Methods: Eighteen young adults participated in our study and received iTBS to the primary motor cortex (M1), supplementary motor area, and the primary visual cortex in three separate sessions. A finger tapping task and ipsilateral single-pulse TMS-EEG recording for the M1 were administrated before and after iTBS in each session. The effects of iTBS in motor performance and TMS-evoked potentials (TEPs) were investigated. Results: The results showed that iTBS to the M1, but not supplementary motor area or the primary visual cortex, significantly reduced the N100 amplitude of M1 TEPs in bilateral hemispheres (p = 0.019), with a more prominent effect in the contralateral hemisphere than in the stimulated hemisphere. Moreover, only iTBS to the M1 decreased global mean field power (corrected ps < 0.05), interhemispheric signal propagation (t = 2.53, p = 0.030), and TMS-induced early α-band synchronization (p = 0.020). Conclusion: Our study confirmed the local and remote after-effects of iTBS in reducing cortical inhibition in the M1. TMS-induced oscillations after iTBS for changed cortical excitability in patients with various neurological and psychiatric conditions are worth further exploration.

Test Re-test Reliability of Dual-site TMS Measures of SMA-M1 Connectivity Differs Across Inter-stimulus Intervals in Younger and Older Adults

Dual-site transcranial magnetic stimulation (TMS) is a promising tool to measure supplementary motor area and primary motor cortex (SMA-M1) connectivity in younger and older adults, and could be used to understand the pathophysiology of movement disorders. However, test re-test reliability of dual-site TMS measures of SMA-M1 connectivity has not been established. We examined the reliability of SMA-M1 connectivity using dual-site TMS in two sessions in 30 younger and 30 older adults. For dual-site TMS, a conditioning pulse delivered to SMA (140% of active motor threshold) preceded a test pulse delivered to M1 (intensity that elicited MEPs of ~1 mV) by inter-stimulus intervals (ISI) of 6 ms, 7 ms, and 8 ms. Moderate intraclass correlation coefficients (ICC) were found for SMA-M1 connectivity at an ISI of 7 ms in younger (ICC: 0.69) and older adults (ICC: 0.68). Poor ICCs were found for SMA-M1 connectivity at ISIs of 6 ms and 8 ms in both age groups (ICC range: 0.01-0.40). We report evidence for stable measures of SMA-M1 connectivity at an ISI of 7 ms in both age groups. These findings are foundational for future research developing evidence-based interventions to strengthen SMA-M1 connectivity to improve bilateral motor control in older adults and populations with movement disorders.

Non-invasive brain stimulation to assess neurophysiologic underpinnings of lower limb motor impairment in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a neuroinflammatory disease resulting in axonal demyelination and an amalgamation of symptoms which commonly result in decreased quality of life due to mobility dysfunction and limited participation in meaningful activities.

NEW METHOD

The use of non-invasive brain stimulation (NIBS) techniques, specifically transcranial magnetic and transcranial direct current stimulation, have been essential in understanding the pathophysiological decrements related to disease progression, particularly with regard to motor impairments. Although the research in this area has primarily focused on the upper extremities, new interest has arisen in understanding the neurophysiological underpinnings of lower limb impairment. Therefore, the purpose of this review is to: first, provide an overview of common NIBS techniques used to explore sensorimotor neurophysiology; second, summarize lower limb neuromuscular and mobility impairments typically observed in PwMS; third, review the current knowledge regarding interactions between TMS-assessed neurophysiology and lower limb impairments in PwMS; and fourth, provide recommendations for future NIBS studies based on current gaps in the literature.

RESULTS

PwMS exhibit reduced excitability and increased inhibitory neurophysiologic function which has been related to disease severity and lower limb motor impairments. Comparison with existing methods: Moreover, promising results indicate that the use of repetitive stimulation and transcranial direct current stimulation may prime neural adaptability and prove useful as a therapeutic tool in ameliorating lower limb impairments.

CONCLUSIONS

While these studies are both informative and promising, additional studies are necessary to be conclusive. As such, studies assessing objective measures of lower limb impairments associated with neurophysiological adaptations need further evaluation.

Investigating the Intervention Parameters of Endogenous Paired Associative Stimulation (ePAS)

Advances in our understanding of neural plasticity have prompted the emergence of neuromodulatory interventions, which modulate corticomotor excitability (CME) and hold potential for accelerating stroke recovery. Endogenous paired associative stimulation (ePAS) involves the repeated pairing of a single pulse of peripheral electrical stimulation (PES) with endogenous movement-related cortical potentials (MRCPs), which are derived from electroencephalography. However, little is known about the optimal parameters for its delivery. A factorial design with repeated measures delivered four different versions of ePAS, in which PES intensities and movement type were manipulated. Linear mixed models were employed to assess interaction effects between PES intensity (suprathreshold (Hi) and motor threshold (Lo)) and movement type (Voluntary and Imagined) on CME. ePAS interventions significantly increased CME compared to control interventions, except in the case of Lo-Voluntary ePAS. There was an overall main effect for the Hi-Voluntary ePAS intervention immediately post-intervention (p = 0.002), with a sub-additive interaction effect at 30 min’ post-intervention (p = 0.042). Hi-Imagined and Lo-Imagined ePAS significantly increased CME for 30 min post-intervention (p = 0.038 and p = 0.043 respectively). The effects of the two PES intensities were not significantly different. CME was significantly greater after performing imagined movements, compared to voluntary movements, with motor threshold PES (Lo) 15 min post-intervention (p = 0.012). This study supports previous research investigating Lo-Imagined ePAS and extends those findings by illustrating that ePAS interventions that deliver suprathreshold intensities during voluntary or imagined movements (Hi-Voluntary and Hi-Imagined) also increase CME. Importantly, our findings indicate that stimulation intensity and movement type interact in ePAS interventions. Factorial designs are an efficient way to explore the effects of manipulating the parameters of neuromodulatory interventions. Further research is required to ensure that these parameters are appropriately refined to maximise intervention efficacy for people with stroke and to support translation into clinical practice.

Cortical mapping of mirror visual feedback training for unilateral upper extremity: A functional near-infrared spectroscopy study

INTRODUCTION

Mirror therapy has been shown to be effective in promoting hemiplegic arm recovery in patients with stroke or unilateral cerebral palsy. This study aimed to explore the cortical mapping associated with mirror therapy in a group of healthy adults by using functional near-infrared spectroscopy.

METHODS

Fifteen right-handed healthy adults were recruited by means of convenience sampling. A 2 × 2 factorial design was used: movement complexity with two levels-task-based (T) and movement-based (M), and visual direction with two levels-mirror visual feedback task (MT) and covered mirror with normal visual feedback task (NoT) as the control, constituting four conditions, namely TMT, MMT, TNoT, and MNoT. The regions of interest were the sensorimotor cortex (SMC), the supplementary motor area (SMA), the superior parietal cortex (SPL), and the precuneus in both the contralateral and ipsilateral hemispheres.

RESULTS

Our findings showed that in the ipsilateral hemisphere, MT induced a higher activation in the SMA and SPL than NoT. With regard to the activation of the ipsilateral SMC, only one channel was found showing superior effects of MT compared with NoT. In addition, MT can strengthen the functional connectivity between the SMC and SMA. In the contralateral hemisphere, both movement complexity and visual direction showed significant main effects in the SMC, while only movement complexity showed a significant main effect in the SMA and SPL. The precuneus of both sides was deactivated and showed no significant difference among the four conditions.

CONCLUSIONS

Our experiment implies that the modest activation of ipsilateral SMC during MT is likely to be associated with the enhanced activity of ipsilateral SMA and that the precuneus may not be an essential component of the MT-related neural network.

Towards an Embodied Signature of Improvisation Skills

Improvisation is not limited to the performing arts, but is extended to everyday life situations such as conversations and decision-making. Due to their ubiquitous nature, improvisation skills have received increasing attention from researchers over the last decade. A core challenge is to grasp the complex creative processes involved in improvisation performance. To date, many studies have attempted to provide insight on brain activity and perceptual experiences when perceiving a performance, especially in musical or artistic form. However, watching/listening a performance is quite different than acting in a performance or performing daily-life activities. In this Perspective, we discuss how researchers have often missed key points concerning the study of improvisation skills, especially by ignoring the central role of bodily experiences in their formation. Furthermore, we consider how the study of (neglected) motor component of improvisation performance can provide valuable insights into the underlying nature of creative processes involved in improvisation skills and their acquisition. Finally, we propose a roadmap for studying improvisation from the acquisition of kinematic data in an ecological context to analysis, including the consideration of the coalition of (individual, environmental and task) constraints in the emergence of improvised behaviors.

Automated Labeling of Movement- Related Cortical Potentials Using Segmented Regression

The movement-related cortical potential (MRCP) is a brain signal related to planning and execution of motor tasks. From an MRCP, three notable features can be identified: the early Bereitschaftspotential (BP1), the late Bereitschaftspotential (BP2), and the negative peak (PN). These features have been used in past studies to quantify neurophysiological changes in response to motor training. Currently, either manual labeling or a priori specification of time points is used to extract these features. The limitation of these methods is the inability to fully model the features. This paper proposes the segmented regression along with a local peak method for automated labeling of the features. The proposed method derives the onsets, amplitudes at onsets, and slopes of BP1 and BP2 along with time and amplitude of the PN in a typical average MRCP. To choose the most suitable regression technique a bounded segmented regression method, a change point method and multivariate adaptive regression splines were evaluated using the root-mean-square error on a dataset of 6000 simulated MRCPs. The best-performing regression technique combined with the local peak method was then applied to a smaller set of 123 simulated MRCPs. Error in onsets of BP1 and BP2 and time of PN were compared with the errors in manual labeling by an expert. The performance of the proposed method was also evaluated on an experimental dataset of MRCPs derived from electroencephalography (EEG) recorded across two sessions from 22 healthy participants during a lower limb task. The Bland-Altman plots were used to evaluate the absolute reliability of the proposed method. On experimental data, the proposed method was also compared with manual labeling by an expert. Bounded segmented regression produced the smallest error on the simulation data. For the experimental data, our proposed method did not exhibit statistically significant bias in any of the modeled features. Furthermore, its performance was comparable to manual labeling by experts. We conclude that the proposed method can be used to automatically obtain robust estimates for the MRCP features with known measurement error.

Does hypnotic susceptibility influence information processing speed and motor cortical preparatory activity?

Responsiveness to suggestions while hypnotized is termed hypnotic susceptibility. An association between reaction time and hypnotic susceptibility has been demonstrated, but whether distinct changes in brain activity accompany this relationship remains unclear. We investigated the effect of hypnotic susceptibility on the speed of information processing and motor cortical preparatory activity. Twenty-one "low" (Low_HS) and fifteen "high" (High_HS) hypnotically susceptible right-handed participants performed precued simple (SRT) and choice (CRT) reaction time key-press tasks under hypnotized and non-hypnotized conditions. Force and surface electromyography data were recorded from left and right index fingers. The contingent negative variation (CNV) was derived from electroencephalography data. Mean reaction time and premotor time was shorter in High_HS participants than Low_HS participants for both simple and choice reaction time tasks. High_HS participants in the hypnotized state performed fewer errors than High_HS participants in the non-hypnotized state and Low_HS participants in either state for the SRT task. High_HS participants made fewer errors overall than Low_HS participants for the CRT task. Mean C3/C4 CNV amplitude was larger in High_HS than in Low_HS participants. Furthermore, larger CNV amplitude was associated with shorter premotor time. Our findings indicate that shorter reaction time in the high hypnotically susceptible group is associated with a greater change in brain activity during motor preparation. One interpretation is that hypnotic susceptibility and neural mechanisms of arousal and selective attention are linked.

Altered resting-state functional connectivity of the putamen and internal globus pallidus is related to speech impairment in Parkinson's disease

INTRODUCTION

Speech impairment in Parkinson's disease (PD) is pervasive, with life-impacting consequences. Yet, little is known about how functional connections between the basal ganglia and cortex relate to PD speech impairment (PDSI). Whole-brain resting-state connectivity analyses of basal ganglia nuclei can expand the understanding of PDSI pathophysiology.

METHODS

Resting-state data from 89 right-handed subjects were downloaded from the Parkinson's Progression Markers Initiative database. Subjects included 12 older healthy controls ("OHC"), 42 PD patients without speech impairment ("PDN"), and 35 PD subjects with speech impairment ("PDSI"). Subjects were assigned to PDN and PDSI groups based on the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III speech item scores ("0" vs. "1-4"). Whole-brain functional connectivity was calculated for four basal ganglia seeds in each hemisphere: putamen, caudate, external globus pallidus (GPe), and internal globus pallidus (GPi). For each seed region, group-averaged connectivity maps were compared among OHC, PDN, and PDSI groups using a multivariate ANCOVA controlling for the effects of age and sex. Subsequent planned pairwise t-tests were performed to determine differences between the three groups using a voxel-wise threshold of p < 0.001 and cluster-extent threshold of 272 mm3 (FWE<0.05).

RESULTS

In comparison with OHCs, both PDN and PDSI groups demonstrated significant differences in cortical connectivity with bilateral putamen, bilateral GPe, and right caudate. Compared to the PDN group, the PDSI subjects demonstrated significant differences in cortical connectivity with left putamen and left GPi. PDSI subjects had lower connectivity between the left putamen and left superior temporal gyrus compared to PDN. In addition, PDSI subjects had greater connectivity between left GPi and three cortical regions: left dorsal premotor/laryngeal motor cortex, left angular gyrus, and right angular gyrus.

CONCLUSIONS

The present findings suggest that speech impairment in PD is associated with altered cortical connectivity with left putamen and left GPi.

Suppression of somatosensory stimuli during motor planning may explain levels of balance and mobility after stroke

The ability to actively suppress, or gate, irrelevant sensory information is required for safe and efficient walking in sensory-rich environments. Both motor attention and motor planning alter somatosensory evoked potentials (SEPs) in healthy adults. This study's aim was to examine the effect of motor attention on processing of irrelevant somatosensory information during plantar flexion motor planning after stroke. Thirteen healthy older adults and 11 individuals with stroke participated. Irrelevant tibial nerve stimulation was delivered while SEPs were recorded over Cz, overlaying the leg portion of the sensorimotor cortex at the vertex of the head. Three conditions were tested in both legs: (1) Rest, (2) Attend To, and (3) Attend Away from the stimulated limb. In conditions 2 and 3, relevant vibration cued voluntary plantar flexion movements of the stimulated (Attend To) or non-stimulated (Attend Away) leg. SEP amplitudes were averaged during motor planning per condition. Individuals with stroke did not show attention-mediated gating of the N40 component associated with irrelevant somatosensory information during motor planning. It may be that dysfunction in pathways connecting to area 3b explains the lack of attention-mediated gating of the N40. Also, attention-mediated gating during motor planning explained significant and unique variance in a measure of community balance and mobility combined with response time. Thus, the ability to gate irrelevant somatosensory information appears important for stepping in both older adults and after stroke. Our data suggest that therapies that direct motor attention could positively impact walking after stroke.

Separation of trait and state in stuttering

Stuttering is a disorder in which the smooth flow of speech is interrupted. People who stutter show structural and functional abnormalities in the speech and motor system. It is unclear whether functional differences reflect general traits of the disorder or are specifically related to the dysfluent speech state. We used a hierarchical approach to separate state and trait effects within stuttering. We collected sparse-sampled functional MRI during two overt speech tasks (sentence reading and picture description) in 17 people who stutter and 16 fluent controls. Separate analyses identified indicators of: (1) general traits of people who stutter; (2) frequency of dysfluent speech states in subgroups of people who stutter; and (3) the differences between fluent and dysfluent states in people who stutter. We found that reduced activation of left auditory cortex, inferior frontal cortex bilaterally, and medial cerebellum were general traits that distinguished fluent speech in people who stutter from that of controls. The stuttering subgroup with higher frequency of dysfluent states during scanning (n = 9) had reduced activation in the right subcortical grey matter, left temporo-occipital cortex, the cingulate cortex, and medial parieto-occipital cortex relative to the subgroup who were more fluent (n = 8). Finally, during dysfluent states relative to fluent ones, there was greater activation of inferior frontal and premotor cortex extending into the frontal operculum, bilaterally. The above differences were seen across both tasks. Subcortical state effects differed according to the task. Overall, our data emphasise the independence of trait and state effects in stuttering.

Stimulating the Healthy Brain to Investigate Neural Correlates of Motor Preparation: A Systematic Review

Objective

Noninvasive brain stimulation techniques can be used to selectively increase or decrease the excitability of a cortical region, providing a unique opportunity to assess the causal contribution of that region to the process being assessed. The objective of this paper is to systematically examine studies investigating changes in reaction time induced by noninvasive brain stimulation in healthy participants during movement preparation.

Methods

A systematic review of the literature was performed in the PubMed, MEDLINE, EMBASE, PsycINFO, and Web of science databases. A combination of keywords related to motor preparation, associated behavioral outcomes, and noninvasive brain stimulation methods was used.

Results

Twenty-seven studies were included, and systematic data extraction and quality assessment were performed. Reaction time results were transformed in standardised mean difference and graphically pooled in forest plots depending on the targeted cortical area and the type of stimulation.

Conclusions

Despite methodological heterogeneity among studies, results support a functional implication of five cortical regions (dorsolateral prefrontal cortex, posterior parietal cortex, supplementary motor area, dorsal premotor cortex, and primary motor cortex), integrated into a frontoparietal network, in various components of motor preparation ranging from attentional to motor aspects.

Quantification of Movement-Related EEG Correlates Associated with Motor Training: A Study on Movement-Related Cortical Potentials and Sensorimotor Rhythms

The ability to learn motor tasks is important in both healthy and pathological conditions. Measurement tools commonly used to quantify the neurophysiological changes associated with motor training such as transcranial magnetic stimulation and functional magnetic resonance imaging pose some challenges, including safety concerns, utility, and cost. EEG offers an attractive alternative as a quantification tool. Different EEG phenomena, movement-related cortical potentials (MRCPs) and sensorimotor rhythms (event-related desynchronization—ERD, and event-related synchronization—ERS), have been shown to change with motor training, but conflicting results have been reported. The aim of this study was to investigate how the EEG correlates (MRCP and ERD/ERS) from the motor cortex are modulated by short (single session in 14 subjects) and long (six sessions in 18 subjects) motor training. Ninety palmar grasps were performed before and after 1 × 45 (or 6 × 45) min of motor training with the non-dominant hand (laparoscopic surgery simulation). Four channels of EEG were recorded continuously during the experiments. The MRCP and ERD/ERS from the alpha/mu and beta bands were calculated and compared before and after the training. An increase in the MRCP amplitude was observed after a single session of training, and a decrease was observed after six sessions. For the ERD/ERS analysis, a significant change was observed only after the single training session in the beta ERD. In conclusion, the MRCP and ERD change as a result of motor training, but they are subject to a marked intra- and inter-subject variability.

Long-latency interhemispheric interactions between motor-related areas and the primary motor cortex: a dual site TMS study

The primary motor cortex (M1) is highly influenced by premotor/motor areas both within and across hemispheres. Dual site transcranial magnetic stimulation (dsTMS) has revealed interhemispheric interactions mainly at early latencies. Here, we used dsTMS to systematically investigate long-latency causal interactions between right-hemisphere motor areas and the left M1 (lM1). We stimulated lM1 using a suprathreshold test stimulus (TS) to elicit motor-evoked potentials (MEPs) in the right hand. Either a suprathreshold or a subthreshold conditioning stimulus (CS) was applied over the right M1 (rM1), the right ventral premotor cortex (rPMv), the right dorsal premotor cortex (rPMd) or the supplementary motor area (SMA) prior to the TS at various CS-TS inter-stimulus intervals (ISIs: 40–150 ms). The CS strongly affected lM1 excitability depending on ISI, CS site and intensity. Inhibitory effects were observed independently of CS intensity when conditioning PMv, rM1 and SMA at a 40-ms ISI, with larger effects after PMv conditioning. Inhibition was observed with suprathreshold PMv and rM1 conditioning at a 150-ms ISI, while site-specific, intensity-dependent facilitation was detected at an 80-ms ISI. Thus, long-latency interhemispheric interactions, likely reflecting indirect cortico-cortical/cortico-subcortical pathways, cannot be reduced to nonspecific activation across motor structures. Instead, they reflect intensity-dependent, connection- and time-specific mechanisms.

Elucidating the neural circuitry underlying planning of internally-guided voluntary action

In an attempt to elucidate the neural circuitry of planning of internally guided voluntary action, Ariani et al. (2015) used a delayed-movement design and multivariate pattern analysis of functional MRI data and found areas decoding internally elicited action plans, stimulus-elicited action plans, and both types of plans. In interpreting their results in the context of a heuristic decision model of voluntary action, encompassing "what" action to perform, "when" to perform it, and "whether" to perform it at all, we highlight at least some neural dissociation of these components. More to that, we note that the exact neural circuitry of each component might vary depending on the performed action type, and finally, we underscore the importance of understanding the temporal specifics of such circuitries to further elucidate how they are involved and interact during voluntary action planning.

A Review of Techniques for Detection of Movement Intention Using Movement-Related Cortical Potentials

The movement-related cortical potential (MRCP) is a low-frequency negative shift in the electroencephalography (EEG) recording that takes place about 2 seconds prior to voluntary movement production. MRCP replicates the cortical processes employed in planning and preparation of movement. In this study, we recapitulate the features such as signal's acquisition, processing, and enhancement and different electrode montages used for EEG data recoding from different studies that used MRCPs to predict the upcoming real or imaginary movement. An authentic identification of human movement intention, accompanying the knowledge of the limb engaged in the performance and its direction of movement, has a potential implication in the control of external devices. This information could be helpful in development of a proficient patient-driven rehabilitation tool based on brain-computer interfaces (BCIs). Such a BCI paradigm with shorter response time appears more natural to the amputees and can also induce plasticity in brain. Along with different training schedules, this can lead to restoration of motor control in stroke patients.

Induction of Long-term Depression-like Plasticity by Pairings of Motor Imagination and Peripheral Electrical Stimulation

Long-term depression (LTD) and long-term potentiation (LTP)-like plasticity are models of synaptic plasticity which have been associated with memory and learning. The induction of LTD and LTP-like plasticity, using different stimulation protocols, has been proposed as a means of addressing abnormalities in cortical excitability associated with conditions such as focal hand dystonia and stroke. The aim of this study was to investigate whether the excitability of the cortical projections to the tibialis anterior (TA) muscle could be decreased when dorsiflexion of the ankle joint was imagined and paired with peripheral electrical stimulation (ES) of the nerve supplying the antagonist soleus muscle. The effect of stimulus timing was evaluated by comparing paired stimulation timed to reach the cortex before, at and after the onset of imagined movement. Fourteen healthy subjects participated in six experimental sessions held on non-consecutive days. The timing of stimulation delivery was determined offline based on the contingent negative variation (CNV) of electroencephalography brain data obtained during imagined dorsiflexion. Afferent stimulation was provided via a single pulse ES to the peripheral nerve paired, based on the CNV, with motor imagination of ankle dorsiflexion. A significant decrease (P = 0.001) in the excitability of the cortical projection of TA was observed when the afferent volley from the ES of the tibial nerve (TN) reached the cortex at the onset of motor imagination based on the CNV. When TN stimulation was delivered before (P = 0.62), or after (P = 0.23) imagined movement onset there was no significant effect. Nor was a significant effect found when ES of the TN was applied independent of imagined movement (P = 0.45). Therefore, the excitability of the cortical projection to a muscle can be inhibited when ES of the nerve supplying the antagonist muscle is precisely paired with the onset of imagined movement.

Analyzing EEG signals to detect unexpected obstacles during walking

Background

When an unexpected perturbation in the environment occurs, the subsequent alertness state may cause a brain activation responding to that perturbation which can be detected and employed by a Brain-Computer Interface (BCI). In this work, the possibility of detecting a sudden obstacle appearance analyzing electroencephalographic (EEG) signals is assessed. For this purpose, different features of EEG signals are evaluated during the appearance of sudden obstacles while a subject is walking on a treadmill. The future goal is to use this procedure to detect any obstacle appearance during walking when the user is wearing a lower limb exoskeleton in order to generate an emergency stop command for the exoskeleton. This would enhance the user-exoskeleton interaction, improving the safety mechanisms of current exoskeletons.

Methods

In order to detect the change in the brain activity when an obstacle suddenly appears, different features of EEG signals are evaluated using the recordings of five healthy subjects. Since the change in the brain activity occurs in the time domain, the features evaluated are: common spatial patterns, average power, slope, and the coefficients of a polynomial fit. A Linear Discriminant Analysis-based classifier is used to differentiate between two conditions: the appearance or not of an obstacle. The evaluation of the performance to detect the obstacles is made in terms of accuracy, true positive (TP) and false positive (FP) rates.

Results

From the offline analysis, the best performance is achieved when the slope or the polynomial coefficients are used as features, with average detection accuracy rates of 74.0 and 79.5 %, respectively. These results are consistent with the pseudo-online results, where a complete EEG recording is segmented into windows of 500 ms and overlapped 400 ms, and a decision about the obstacle appearance is made for each window. The results of the best subject were 11 out of 14 obstacles detected with a rate of 9.09 FPs/min, and 10 out of 14 obstacles detected with a rate of 6.34 FPs/min using slope and polynomial coefficients features, respectively.

Conclusions

An EEG-based BCI can be developed to detect the appearance of unexpected obstacles. The average accuracy achieved is 79.5 % of success rate with a low number of false detections. Thus, the online performance of the BCI would be suitable for commanding in a safely way a lower limb exoskeleton during walking.

Repetitive transcranial magnetic stimulation over the supplementary motor area modifies breathing pattern in response to inspiratory loading in normal humans

In awake humans, breathing depends on automatic brainstem pattern generators. It is also heavily influenced by cortical networks. For example, functional magnetic resonance imaging and electroencephalographic data show that the supplementary motor area becomes active when breathing is made difficult by inspiratory mechanical loads like resistances or threshold valves, which is associated with perceived respiratory discomfort. We hypothesized that manipulating the excitability of the supplementary motor area with repetitive transcranial magnetic stimulation would modify the breathing pattern response to an experimental inspiratory load and possibly respiratory discomfort. Seven subjects (three men, age 25 ± 4) were studied. Breathing pattern and respiratory discomfort during inspiratory loading were described before and after conditioning the supplementary motor area with repetitive stimulation, using an excitatory paradigm (5 Hz stimulation), an inhibitory paradigm, or sham stimulation. No significant change in breathing pattern during loading was observed after sham conditioning. Excitatory conditioning shortened inspiratory time (p = 0.001), decreased tidal volume (p = 0.016), and decreased ventilation (p = 0.003), as corroborated by an increased end-tidal expired carbon dioxide (p = 0.013). Inhibitory conditioning did not affect ventilation, but lengthened expiratory time (p = 0.031). Respiratory discomfort was mild under baseline conditions, and unchanged after conditioning of the supplementary motor area. This is the first study to show that repetitive transcranial magnetic stimulation conditioning of the cerebral cortex can alter breathing pattern. A 5 Hz conditioning protocol, known to enhance corticophrenic excitability, can reduce the amount of hyperventilation induced by inspiratory threshold loading. Further studies are needed to determine whether and under what circumstances rTMS can have an effect on dyspnoea.

Comparison of spatial filters and features for the detection and classification of movement-related cortical potentials in healthy individuals and stroke patients

OBJECTIVE

The possibility of detecting movement-related cortical potentials (MRCPs) at the single trial level has been explored for closing the motor control loop with brain-computer interfaces (BCIs) for neurorehabilitation. A distinct feature of MRCPs is that the movement kinetic information is encoded in the brain potential prior to the onset of the movement, which makes it possible to timely drive external devices to provide sensory feedback according to the efferent activity from the brain. The aim of this study was to compare methods for the detection (different spatial filters) and classification (features extracted from various domains) of MRCPs from continuous electroencephalography recordings from executed and imagined movements from healthy subjects (n = 24) and attempted movements from stroke patients (n = 6) to optimize the performance of MRCP-based BCIs for neurorehabilitation.

APPROACH

The MRCPs from four cue-based tasks were detected with a template matching approach and a set of spatial filters, and classified with a linear support vector machine using the combination of temporal, spectral, time-scale, or entropy-based features.

MAIN RESULTS

The best spatial filter (large Laplacian spatial filter (LLSF)) resulted in a true positive rate of 82 ± 9%, 78 ± 12% and 72 ± 9% (with detections occurring ∼ 200 ms before the onset of the movement) for executed, imagined and attempted movements (stroke patients). The best feature combination (temporal and spectral) led to pairwise classification of 73 ± 9%, 64 ± 10% and 80 ± 12%. When the detection was combined with classification, 60 ± 10%, 49 ± 10% and 58 ± 10% of the movements were both correctly detected and classified for executed, imagined and attempted movements. A similar performance for detection and classification was obtained with optimized spatial filtering.

SIGNIFICANCE

A simple setup with an LLSF is useful for detecting cued movements while the combination of features from the time and frequency domain can optimize the decoding of kinetic information from MRCPs; this may be used in neuromodulatory BCIs.

Electrode fusion for the prediction of self-initiated fine movements from single-trial readiness potentials

Current human-machine interfaces (HMIs) for users with severe disabilities often have difficulty distinguishing between intentional and inadvertent activations. Pre-movement neuro-cortical activity may aid in this elusive discrimination task but has not been exploited in HMIs. This work investigates the utility of the readiness potential (RP), a slow negative cortical potential preceding voluntary movement, for detecting the intention of self-initiated fine movements prior to their motoric realization. We recorded electroencephalography from the frontal, central, parietal and occipital lobes of 10 participants using a self-initiated switch activation protocol. Eye movement artifacts were removed by regression and the RP was detected on a single-trial basis, in a narrow frequency range (0.1-1 Hz). Common average reference was applied prior to windowed-averaging for feature extraction. Electrodes were selected according to a separability measure based on Fisher projection. Our findings demonstrate that feature fusion from an optimal number of electrodes achieves a statistically significant lower classification error than the best single classifier. Finally, voluntary fine movement intention was detected on a single-trial basis at above-chance levels approximately 396 ms before physical switch activation. These findings encourage the development of rapid-response, intention-aware HMIs for individuals with severe disabilities who struggle with executing voluntary fine motor movements.

Comparison of effects of transcranial magnetic stimulation on primary motor cortex and supplementary motor area in motor skill learning (randomized, cross over study)

Motor skills require quick visuomotor reaction time, fast movement time, and accurate performance. Primary motor cortex (M1) and supplementary motor area (SMA) are closely related in learning motor skills. Also, it is well known that high frequency repeated transcranial magnetic stimulation (rTMS) on these sites has a facilitating effect. The aim of this study was to compare the effects of high frequency rTMS activation of these two brain sites on learning of motor skills. Twenty three normal volunteers participated. Subjects were randomly stimulated on either brain area, SMA or M1. The motor task required the learning of sequential finger movements, explicitly or implicitly. It consisted of pressing the keyboard sequentially with their right hand on seeing 7 digits on the monitor explicitly, and then tapping the 7 digits by memorization, implicitly. Subjects were instructed to hit the keyboard as fast and accurately as possible. Using Musical Instrument Digital Interface (MIDI), the keyboard pressing task was measured before and after high frequency rTMS for motor performance, which was measured by response time (RT), movement time, and accuracy (AC). A week later, the same task was repeated by cross-over study design. At this time, rTMS was applied on the other brain area. Two-way ANOVA was used to assess the carry over time effect and stimulation sites (M1 and SMA), as factors. Results indicated that no carry-over effect was observed. The AC and RT were not different between the two stimulating sites (M1 and SMA). But movement time was significantly decreased after rTMS on both SMA and M1. The amount of shortened movement time after rTMS on SMA was significantly increased as compared to the movement time after rTMS on M1 (p < 0.05), especially for implicit learning of motor tasks. The coefficient of variation was lower in implicit trial than in explicit trial. In conclusion, this finding indicated an important role of SMA compared to M1, in implicit motor learning.

Effects of dopaminergic treatment on functional cortico-cortical connectivity in Parkinson's disease

Interactions between dorsal premotor cortex (PMd) and primary motor cortex (M1) and interhemispheric inhibition (IHI) between M1 are impaired in Parkinson's disease (PD). We used dual-site transcranial magnetic stimulation to compare effects of first-time levodopa application with chronic dopaminergic therapy on these interactions in PD. Twelve untreated PD patients were studied before and after their first-ever intake of levodopa. The effects of chronic dopaminergic medication were evaluated in 11 patients who had received regular dopaminergic medication for approximately 3 years. Nine of these patients were also measured after overnight withdrawal of medication. For IHI, conditioning stimuli (CS) were applied to left M1 followed by test stimuli (TS) over right M1 and vice versa in separate blocks at interstimulus intervals (ISI) of 6-10 ms. Next, CS were applied to left PMd at subthreshold intensity followed by TS over left M1 at ISIs of 4 and 6 ms. Results were compared to 17 age- and gender-matched controls. In de novo PD patients, levodopa reduced left-to-right IHI, but did not alter PMd-M1 connectivity. In contrast, inhibitory PMd-M1 connectivity was present in early disease patients under chronic dopaminergic stimulation, but not in de novo PD patients at low stimulus intensities at an ISI of 4 ms. First-time exposure to levodopa exerts different effects on cortico-cortical pathways than chronic dopaminergic stimulation in PD, suggesting a change in the responsiveness of cortico-cortical circuits during the course of PD.

Attention Allocation and Task Representation during Joint Action Planning

We investigated whether people take into account an interaction partner's attentional focus and whether they represent in advance their partner's part of the task when planning to engage in a synchronous joint action. The experiment involved two participants planning and performing joint actions (i.e., synchronously lifting and clinking glasses), unimanual individual actions (i.e., lifting and moving a glass as if clinking with another person), and bimanual individual actions. EEG was recorded from one of the participants. We employed a choice reaction paradigm where a visual cue indicated the type of action to be planned, followed 1.5 sec later by a visual go stimulus, prompting the participants to act. We studied attention allocation processes by examining two lateralized EEG components, namely the anterior directing attention negativity and the late directing attention positivity. Action planning processes were examined using the late contingent negative variation and the movement-related potential. The results show that early stages of joint action planning involve dividing attention between locations in space relevant for one's own part of the joint action and locations relevant for one's partner's part of the joint action. At later stages of joint action planning, participants represented in advance their partner's upcoming action in addition to their own action, although not at an effector-specific level. Our study provides electrophysiological evidence supporting the operation of attention sharing processes and predictive self/other action representation during the planning phase of a synchronous joint task.

TMS reveals a direct influence of spinal projections from human SMAp on precise force production

The corticospinal (CS) system plays an important role in fine motor control, especially in precision grip tasks. Although the primary motor cortex (M1) is the main source of the CS projections, other projections have been found, especially from the supplementary motor area proper (SMAp). To study the characteristics of these CS projections from SMAp, we compared muscle responses of an intrinsic hand muscle (FDI) evoked by stimulation of human M1 and SMAp during an isometric static low-force control task. Subjects were instructed to maintain a small cursor on a target force curve by applying a pressure with their right precision grip on a force sensor. Neuronavigated transcranial magnetic stimulation was used to stimulate either left M1 or left SMAp with equal induced electric field values at the defined cortical targets. The results show that the SMAp stimulation evokes reproducible muscle responses with similar latencies and amplitudes as M1 stimulation, and with a clear and significant shorter silent period. These results suggest that (i) CS projections from human SMAp are as rapid and efficient as those from M1, (ii) CS projections from SMAp are directly involved in control of the excitability of spinal motoneurons and (iii) SMAp has a different intracortical inhibitory circuitry. We conclude that human SMAp and M1 both have direct influence on force production during fine manual motor tasks.

Lateralized alpha-band cortical networks regulate volitional modulation of beta-band sensorimotor oscillations

Sensorimotor rhythms (SMRs) are oscillatory brain activities in the α- and β-bands across the sensorimotor regions of the brain. Each frequency band has its own specific function. The α-band oscillations are closely related to intrinsic cortical networks, whereas oscillations in the β-band are relevant for the information transfer between the cortex and periphery, as well as for visual and proprioceptive feedback. This study aimed to investigate the interaction between these two frequency bands, under the premise that the regional modulation of β-band power is linked to a cortical network in the α-band. We therefore designed a procedure to maximize the modulation of β-band activity over the sensorimotor cortex by combining kinesthetic motor-imagery with closed-loop haptic feedback. The cortical network activity during this procedure was estimated via the phase slope index in electroencephalographic recordings. Analysis of effective connectivity within the α-band network revealed an information flow between the precentral (premotor and primary motor), postcentral (primary somatosensory) and parietal cortical areas. The range of β-modulation was connected to a reduction of an ipsilateral sensorimotor and parietal α-network and, consequently, to a lateralization of this network to the contralateral side. These results showed that regional sensorimotor oscillatory activity in the β-band was regulated by cortical coupling of distant areas in the α-band.

Single pulse TMS differentially modulates reward behavior

Greater knowledge of cortical brain regions in reward processing may set the stage for using transcranial magnetic stimulation (TMS) as a treatment in patients with avolition, apathy or other drive-related symptoms. This study examined the effects of single pulse (sp) TMS to two reward circuit targets on drive in healthy subjects. Fifteen healthy subjects performed the monetary incentive delay task (MID) while receiving fMRI-guided spTMS to either inferior parietal lobe (IPL) or supplemental motor area (SMA). The study demonstrated decreasing reaction times (RT) for increasing reward. It also showed significant differences in RT modulation for TMS pulses to the IPL versus the SMA. TMS pulses during the delay period produced significantly more RT slowing when targeting the IPL than those to the SMA. This RT slowing carried over into subsequent trials without TMS stimulation, with significantly slower RTs in sessions that had targeted the IPL compared to those targeting SMA. The results of this study suggest that both SMA and IPL are involved in reward processing, with opposite effects on RT in response to TMS stimulation. TMS to these target cortical regions may be useful in modulating reward circuit deficits in psychiatric populations.

Detection and classification of movement-related cortical potentials associated with task force and speed

OBJECTIVE

In this study, the objective was to detect movement intentions and extract different levels of force and speed of the intended movement from scalp electroencephalography (EEG). We then estimated the performance of the closed loop system.

APPROACH

Cued movements were detected from continuous EEG recordings using a template of the initial phase of the movement-related cortical potential in 12 healthy subjects. The temporal features, extracted from the movement intention, were classified with an optimized support vector machine. The system performance was evaluated when combining detection with classification.

MAIN RESULTS

The system detected 81% of the movements and correctly classified 75 ± 9% and 80 ± 10% of these at the point of detection when varying the force and speed, respectively. When the detector was combined with the classifier, the system detected and correctly classified 64 ± 13% and 67 ± 13% of these movements. The system detected and incorrectly classified 21 ± 7% and 16 ± 9% of the movements. The movements were detected 317 ± 73 ms before the movement onset.

SIGNIFICANCE

The results indicate that it is possible to detect movement intentions with limited latencies, and extract and classify different levels of force and speed, which may be combined with assistive technologies for patient-driven neurorehabilitation.