Detection of movement related cortical potentials from EEG using constrained ICA for brain-computer interface applications

The movement related cortical potential (MRCP), a slow cortical potential from the scalp electroencephalogram (EEG), has been used in real-time brain-computer-interface (BCI) systems designed for neurorehabilitation. Detecting MPCPs in real time with high accuracy and low latency is essential in these applications. In this study, we propose a new MRCP detection method based on constrained independent component analysis (cICA). The method was tested for MRCP detection during executed and imagined ankle dorsiflexion of 24 healthy participants, and compared with four commonly used spatial filters for MRCP detection in an offline experiment. The effect of cICA and the compared spatial filters on the morphology of the extracted MRCP was evaluated by two indices quantifying the signal-to-noise ratio and variability of the extracted MRCP. The performance of the filters for detection was then directly compared for accuracy and latency. The latency obtained with cICA (-34 ± 29 ms motor execution (ME) and 28 ± 16 ms for motor imagery (MI) dataset) was significantly smaller than with all other spatial filters. Moreover, cICA resulted in greater true positive rates (87.11 ± 11.73 for ME and 86.66 ± 6.96 for MI dataset) and lower false positive rates (20.69 ± 13.68 for ME and 19.31 ± 12.60 for MI dataset) compared to the other methods. These results confirm the superiority of cICA in MRCP detection with respect to previously proposed EEG filtering approaches

Influence of attention alternation on movement-related cortical potentials in healthy individuals and stroke patients.

OBJECTIVE: In this study, we analyzed the influence of artificially imposed attention variations using the auditory oddball paradigm on the cortical activity associated to motor preparation/execution. METHODS: EEG signals from Cz and its surrounding channels were recorded during three sets of ankle dorsiflexion movements. Each set was interspersed with either a complex or a simple auditory oddball task for healthy participants and a complex auditory oddball task for stroke patients. RESULTS: The amplitude of the movement-related cortical potentials (MRCPs) decreased with the complex oddball paradigm, while MRCP variability increased. Both oddball paradigms increased the detection latency significantly (p<0.05) and the complex paradigm decreased the true positive rate (TPR) (p=0.04). In patients, the negativity of the MRCP decreased while pre-phase variability increased, and the detection latency and accuracy deteriorated with attention diversion. CONCLUSION: Attention diversion has a significant influence on MRCP features and detection parameters, although these changes were counteracted by the application of the laplacian method. SIGNIFICANCE: Brain-computer interfaces for neuromodulation that use the MRCP as the control signal are robust to changes in attention. However, attention must be monitored since it plays a key role in plasticity induction. Here we demonstrate that this can be achieved using the single channel Cz

Classification of EEG signals to identify variations in attention during motor task execution

Background Brain-computer interface (BCI) systems in neuro-rehabilitation use brain signals to control external devices. User status such as attention affects BCI performance; thus detecting the user’s attention drift due to internal or external factors is essential for high detection accuracy. New method An auditory oddball task was applied to divert the users’ attention during a simple ankle dorsiflexion movement. Electroencephalogram signals were recorded from eighteen channels. Temporal and time-frequency features were projected to a lower dimension space and used to analyze the effect of two attention levels on motor tasks in each participant. Then, a global feature distribution was constructed with the projected time-frequency features of all participants from all channels and applied for attention classification during motor movement execution. Results Time-frequency features led to significantly better classification results with respect to the temporal features, particularly for electrodes located over the motor cortex. Motor cortex channels had a higher accuracy in comparison to other channels in the global discrimination of attention level. Comparing with existing methods Previous methods have used the attention to a task to drive external devices, such as the P300 speller. However, here we focus for the first time on the effect of attention drift while performing a motor task. Conclusions It is possible to explore user’s attention variation when performing motor tasks in synchronous BCI systems with time-frequency features. This is the first step towards an adaptive real-time BCI with an integrated function to reveal attention shifts from the motor task

Sensory Feedback in Interlimb Coordination: Contralateral Afferent Contribution to the Short-Latency Crossed Response during Human Walking.

A constant coordination between the left and right leg is required to maintain stability during human locomotion, especially in a variable environment. The neural mechanisms underlying this interlimb coordination are not yet known. In animals, interneurons located within the spinal cord allow direct communication between the two sides without the need for the involvement of higher centers. These may also exist in humans since sensory feedback elicited by tibial nerve stimulation on one side (ipsilateral) can affect the muscles activation in the opposite side (contralateral), provoking short-latency crossed responses (SLCRs). The current study investigated whether contralateral afferent feedback contributes to the mechanism controlling the SLCR in human gastrocnemius muscle. Surface electromyogram, kinematic and kinetic data were recorded from subjects during normal walking and hybrid walking (with the legs moving in opposite directions). An inverse dynamics model was applied to estimate the gastrocnemius muscle proprioceptors' firing rate. During normal walking, a significant correlation was observed between the magnitude of SLCRs and the estimated muscle spindle secondary afferent activity (P = 0.04). Moreover, estimated spindle secondary afferent and Golgi tendon organ activity were significantly different (P ≤ 0.01) when opposite responses have been observed, that is during normal (facilitation) and hybrid walking (inhibition) conditions. Contralateral sensory feedback, specifically spindle secondary afferents, likely plays a significant role in generating the SLCR. This observation has important implications for our understanding of what future research should be focusing on to optimize locomotor recovery in patient populations