Susan Aliakbaryhosseinabadi

The effect of type of afferent feedback timed with motor imagery on the induction of cortical plasticity

A peripherally generated afferent volley that arrives at the peak negative (PN) phase during the movement related cortical potential (MRCP) induces significant plasticity at the cortical level in healthy individuals and chronic stroke patients. Transferring this type of associative brain-computer interface (BCI) intervention into the clinical setting requires that the proprioceptive input is comparable to the techniques implemented during the rehabilitation process. These consist mainly of functional electrical stimulation (FES) and passive movement induced by an actuated orthosis. In this study, we compared these two interventions (BCIFES and BCIpassive) where the afferent input was timed to arrive at the motor cortex during the PN of the MRCP. Twelve healthy participants attended two experimental sessions. They were asked to perform 30 dorsiflexion movements timed to a cue while continuous electroencephalographic (EEG) data were collected from FP1, Fz, FC1, FC2, C3, Cz, C4, CP1, CP2, and Pz, according to the standard international 10-20 system. MRCPs were extracted and the PN time calculated. Next, participants were asked to imagine the same movement 30 times while either FES (frequency: 20Hz, intensity: 8-35mAmp) or a passive ankle movement (amplitude and velocity matched to a normal gait cycle) was applied such that the first afferent inflow would coincide with the PN of the MRCP. The change in the output of the primary motor cortex (M1) was quantified by applying single transcranial magnetic stimuli to the area of M1 controlling the tibialis anterior (TA) muscle and measuring the motor evoked potential (MEP). Spinal changes were assessed pre and post by eliciting the TA stretch reflex. Both BCIFES and BCIpassive led to significant increases in the excitability of the cortical projections to TA (F(2,22)=4.44, p=0.024) without any concomitant changes at the spinal level. These effects were still present 30min after the cessation of both interventions. There was no significant main effect of intervention, F(1,11)=0.38, p=0.550, indicating that the changes in MEP occurred independently of the type of afferent inflow. An afferent volley generated from a passive movement or an electrical stimulus arrives at the somatosensory cortex at similar times. It is thus likely that the similar effects observed here are strictly due to the tight coupling in time between the afferent inflow and the PN of the MRCP. This provides further support to the associative nature of the proposed BCI system.

An Associative Brain-Computer-Interface for Acute Stroke Patients

An efficient innovative Brain-Computer-Interface system that empowers chronic stroke patients to control an artificial activation of their lower limb muscle through task specific motor intent has been tested in the past. In the current study it was applied to acute stroke patients. The system consists in detecting the movement-related cortical potential (MRCP) using scalp electrodes as the patient attempts to perform a dorsiflexion task. This is translated into the control command for an electrical stimulator to generate a stimulus to the nerve that innervates and thus activates the prime mover (tibialis anterior). This activation is precisely and individually timed such that the sensory signal arising from the stimulation reaches the motor cortex during its maximum activation due to the intention. The output of the motor cortical area representing the dorsiflexor muscles was significantly enhanced in all patients tested following a single session of 30 repetitions. All patients were able to perform the intervention with minimal training and very few repetitions, making this a feasible new efficient approach for restoration of motor function in stroke patients. Such few necessary applications of the protocol make it a unique approach in comparison to available techniques and paves the way for at home use devices.

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.

Robustness of movement detection techniques from motor execution: Single trial movement related cortical potential

Alterations in attention are known to modify excitability of underlying cortical structures and thus the activity recorded during non-invasive electroencephalography (EEG). Brain-Computer-Interface systems for neuromodulation are based on reliable detection of intended movements from continuous EEG signals, thereby generating real time feedback to induce neuroplasticity. We have shown in past studies that the movement related cortical potential (MRCP), a slow negative potential commencing 1-2 s prior to movement, can be reliably detected in real time within a single session and used to drive an external device that reproduces the intended movement. In the present study, our main objective was to characterize movement detection performance of two algorithms, when the subjects attention is altered. In nine healthy participants the auditory oddball paradigm was used to modulate attention. All subjects completed a set of movement executions prior to and following the oddball paradigm. The locality preserving projection followed by the linear discriminant analysis (LPP-LDA) and the matched-filter (MF) technique were applied offline for detection of movement. Results show that LPP-LDA significantly outperformed MF. The robustness of the LPP-LDA method was demonstrated by a higher true positive rate (TPR), lower false positive rate (FPR) and a shorter detection latency when attention levels were altered.

Detection of Movement Intention from Movement-Related Cortical Potentials with Different Paradigms

In this study, we compared the effects of two imagery paradigms typically used within the field of brain computer interfaces on the detection of movement intention from scalp electroencephalography (EEG). This issue is important in the rehabilitation area because of its direct relation with appropriately timed neurofeedback. Subjects were asked to imagine hand or foot movements using either a random or a non-random cue. Templates were constructed individually for each subject. Movement intent was detected according to the correlation between the movement related cortical potentials (MRCP) of single trials with the initial part of the template. The large Laplacian filter was used to increase the signal to noise ratio (SNR). For the random cue, the true positive rate (TPR) of detection of movement intention was 63.5±5.9% for foot movement and the corresponding detection latency was 202.8±129.5 ms before movement onset. For the non-random cue, foot movement intention was detected with TPR of 75.3±5.5% and latency of 291±169.3 ms. These results demonstrate that cue type, random or non-random, has a significant effect on the performance of MRCP-based movement intention detection algorithms.

Influence of dual-tasking with different levels of attention diversion on characteristics of the movement-related cortical potential

Dual tasking is defined as performing two tasks concurrently and has been shown to have a significant effect on attention directed to the performance of the main task. In this study, an attention diversion task with two different levels was administered while participants had to complete a cue-based motor task consisting of foot dorsiflexion. An auditory oddball task with two levels of complexity was implemented to divert the users attention. Electroencephalographic (EEG) recordings were made from nine single channels. Event-related potentials (ERPs) confirmed that the oddball task of counting a sequence of two tones decreased the auditory P300 amplitude more than the oddball task of counting one target tone among three different tones. Pre-movement features quantified from the movement-related cortical potential (MRCP) were changed significantly between single and dual-task conditions in motor and fronto-central channels. There was a significant delay in movement detection for the case of single tone counting in two motor channels only (237.1-247.4ms). For the task of sequence counting, motor cortex and frontal channels showed a significant delay in MRCP detection (232.1-250.5ms). This study investigated the effect of attention diversion in dual-task conditions by analysing both ERPs and MRCPs in single channels. The higher attention diversion lead to a significant reduction in specific MRCP features of the motor task. These results suggest that attention division in dual-tasking situations plays an important role in movement execution and detection. This has important implications in designing real-time brain-computer interface systems.

Effect of Attention Variation in Stroke Patients: Analysis of Single Trial Movement-Related Cortical Potentials

We have previously developed a Brain-computer interface (BCI) for neuromodulation based on movement related cortical potentials (MRCP). Since successful induction of plasticity is dependent on the attention of the user, the aim of this study was to analyze the changes in MRCPs during imposed attentional shifts in patients. We recorded EEG signals from Cz and its surrounding channels in seven chronic stroke patients, who were asked to attempt ankle dorsiflexion in two subsets of 30 repetitions. Each subset was separated from the other by an auditory oddball task comprised of three tones. Patients were asked to detect the target tone by pressing a button. Nine temporal features were extracted from single trial MRCPs and compared between the two subsets of dorsiflexion that were interspersed by the oddball task. The amplitude of the MRCP negativity, pre-movement slopes, pre-movement variability and movement detection latency and accuracy changed significantly when attention was diverted from the main task of dorsiflexion. This has significant implications for BCIs designed to induce plasticity since detection failure will result in inappropriate device control.

The changing brain: bidirectional learning between algorithm and user

In 2013–2014 we have advanced our MRCP-based BCI by demonstrating: (1) the ability to detect movement intent during dynamic tasks; (2) better detection accuracy than conventional approaches by implementing the locality preserving projection (LPP) approach; (3) the ability to use a single channel for accurate detection; and (4) enhanced neuroplasticity by driving a robotic device in an online mode. To realize our final goal of an at home system, we have characterized alterations during single session use in our extracted signal when the user is undergoing complex learning or experiencing significant attentional shifts—all seriously affecting the detection of user intent. Learning enhances the variability of MRCP at specific recording sites while attention shifts result in a more global increase in signal variability. With the results presented, we are working towards an adaptive brain–computer interface where bidirectional learning (either user or algorithm) is possible.

Brain state-dependent peripheral nerve stimulation for plasticity induction in stroke patients

Artificial activation of peripheral afferent fibers, with the resulting sensory feedback timed to arrive at the peak negativity of the movement-related cortical potential, induces significant increases in the excitability of cortical projections to the target muscle in healthy individuals and chronic stroke patients. In the currently ongoing study, we applied this associative brain-computer interface paradigm to sub-acute stroke patients. Compared to a sham group, where the peripheral electrical stimulation intensity was below the activation threshold of the sensory afferents, the associative intervention group displayed substantial increases in corticospinal excitability to the target muscle (tibialis anterior).

Brain-State Dependent Peripheral Nerve Stimulation for Plasticity Induction Targeting Upper-Limb

Brain-computer interfaces have increasingly found applications within the rehabilitation of lost motor function in stroke patients. Most studies have targeted upper limb muscles and used sensorimotor rhythms as the control signal. In a series of studies, we have introduced an associative BCI modeled on known theories of memory and learning that implements the movement related cortical potential (MRCP) as a way to control an external device that provides afferent generated feedback to the user’s brain at the time of the peak negative phase of the MRCP. In its application to lower limb muscles it demonstrates significant plasticity induction that requires no user training. In the current study, we tested if this associative BCI is effective when targeting upper limb muscles. Further, we explored if there is a difference when the MRCP is generated as part of a simple (wrist extension) versus a complex (reach and grasp) movement.