Muhammad Samran Navid

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 signals 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.

Online detection and classification of movement kinetics

Over the past years brain-computer interface (BCI) technology has been proposed as a means for neurorehabilitation. To induce Hebbian-associated-like plasticity, the movement-related cortical potential (MRCP) can be detected from the continuous brain activity to trigger timely appropriate inflow of somatosensory feedback from electrical stimulation. The aim of this study was to detect the MRCP online from the continuous brain activity and decode two types of movements that were performed with different levels of force and speed (2x50 movements). 5 healthy subjects and 1 stroke patient performed/attempted to perform the movements. The system correctly detected and classified 65±3 % and 51 % of the movements for the healthy subjects and patient, respectively. The findings suggest that it is possible to detect movements and decode kinetic information online. This may have implications for stroke rehabilitation where task variability may be introduced to optimize the retention of relearned movements.

Chiropractic spinal manipulation alters TMS induced I-wave excitability and shortens the cortical silent period

The objective of this study was to construct peristimulus time histogram (PSTH) and peristimulus frequencygram (PSF) using single motor unit recordings to further characterize the previously documented immediate sensorimotor effects of spinal manipulation. Single pulse transcranial magnetic stimulation (TMS) via a double cone coil over the tibialis anterior (TA) motor area during weak isometric dorsiflexion of the foot was used on two different days in random order; pre/post spinal manipulation (in eighteen subjects) and pre/post a control (in twelve subjects) condition. TA electromyography (EMG) was recorded with surface and intramuscular fine wire electrodes. Three subjects also received sham double cone coil TMS pre and post a spinal manipulation intervention. From the averaged surface EMG data cortical silent periods (CSP) were constructed and analysed. Twenty-one single motor units were identified for the spinal manipulation intervention and twelve single motor units were identified for the control intervention. Following spinal manipulations there was a shortening of the silent period and an increase in the single unit I-wave amplitude. No changes were observed following the control condition. The results provide evidence that spinal manipulation reduces the TMS-induced cortical silent period and increases low threshold motoneurone excitability in the lower limb muscle. These finding may have important clinical implications as they provide support that spinal manipulation can be used to strengthen muscles. This could be followed up on populations that have reduced muscle strength, such as stroke victims.

Effect of subject training on a movement-related cortical potential-based brain-computer interface

Abstract Brain-computer interfaces (BCIs) have been developed for several purposes in communication, control, and rehabilitation. To use the BCI efficiently, the system must be technically tuned, and the user must learn to operate it. In this study, we investigated if the user could be trained to improve the performance of online detection of movement-related cortical potentials (MRCPs) associated with fast and slow movements. Seven healthy subjects participated in nine experiments over eight weeks while the ability of the online system to detect the movements was accessed. The movements were detected using template matching. No training effect was observed on the performance or MRCP morphology over the eight weeks. The system correctly detected ∼80% of the movements with ∼1.5 false positive detections/min. The findings suggest that the detection of MRCPs is stable from the first session and that several training sessions are not needed to obtain control of the BCI; this may have implication for the applicability of BCIs for movement detection.

Performance feedback assists practice driven plasticity

Motor skills are generally acquired by means of practice. This procedure comprised of acquiring particular task requirements by overruling intrinsic tendencies. The objectives of the present study were; to induce plasticity through bimanual finger tapping task; and to determine the influence of presence or absence of performance feedback on training. Behavioural data from 16 healthy subjects was recorded. They were randomly divided into two equal groups. First group performed bimanual finger tapping task according to 2∶1 mode with feedback (TF). Second group performed bimanual finger tapping task according to 2∶1 mode without feedback (TNF). All subjects performing Tapping task either with or without feedback improved their performance at the end of practice. However, TF performed better than TNF, F (1,14) = 22.378, p<0.01. The results illustrate that practice of 2∶1 task with feedback leads to augmented motor experience reflecting better practice driven plasticity.

Universal matched-filter template versus individualized template for single trial detection of movement intentions of different tasks

Brain-computer interfaces (BCIs) have been proposed for neurorehabilitation after stroke by inducing cortical plasticity. To transfer the technology from the controlled settings in the lab to the clinic several issues must be addressed. In this study, it was investigated how the performance was affected by using a universal task template to detect movement intentions associated with movements performed with two different levels of force and speed. The performance of the universal template was compared to an individualized template constructed for each task. Twelve healthy subjects performed four types of dorsi-flexions while continuous electroencephalography (EEG) was recorded from ten channels. The movement intentions were detected (~200–300 ms before the movement onset) from the continuous EEG using a matched-filter approach. The true positive rate was significantly higher (P = 0.001) when using the individualized template where 68–76 % of the movements were correctly detected on the contrary to 65–70 % when using the universal template. The number of false positive detections per 5 min was lower (P = 0.036) when using the universal template (~13) compared to the individualized template (~14). Despite the lower performance when using the universal detection template, the performance of the detector is in the range of what has been reported previously for inducing cortical plasticity.

A possible correlation between performance IQ, visuomotor adaptation ability and mu suppression.

BACKGROUND Psychometric, anatomical and functional brain studies suggest that individuals differ in the way that they perceive and analyze information and strategically control and execute movements. Inter-individual differences are also observed in neural correlates of specific and general cognitive ability. As a result, some individuals perceive and adapt to environmental conditions and perform motor activities better than others. The aim of this study was to identify a common factor that predicts adaptation of a reaching movement to a visual perturbation and suppression of movement-related brain activity (mu rhythms). RESULTS Twenty-eight participants participated in two different experiments designed to evaluate visuomotor adaptation and mu suppression ability. Performance intelligence quotient (IQ) was assessed using the revised Wechsler Adult Intelligence Scale. Performance IQ predicted adaptation index of visuomotor performance (r=0.43, p=0.02) and suppression of mu rhythms (r=-0.59; p<0.001). Participants with high performance IQ were faster at adapting to a visuomotor perturbation and better at suppressing mu activity than participants with low performance IQ. CONCLUSIONS We found a possible link between performance IQ and mu suppression, and performance IQ and the initial rate of adaptation. Individuals with high performance IQ were better in suppressing mu rhythms and were quicker at associating motor command and required movement than individuals with low performance IQ.