Prismatic adaptation modulates oscillatory EEG correlates of motor preparation but not visual attention in healthy participants

Prismatic adaption (PA) has been proposed as a tool to induce neural plasticity and is used to help neglect rehabilitation. It leads to a recalibration of visuo-motor coordination during pointing as well as to after-effects on a number of sensorimotor and attention tasks, but whether these effects originate at a motor or attentional level remains a matter of debate. Our aim was to further characterise PA after-effects by using an approach that allows distinguishing between effects on attentional and motor processes. We recorded electroencephalography (EEG) in healthy human participants (9 females and 7 males) while performing a new double step, anticipatory attention/motor preparation paradigm before and after adaptation to rightward shifting prisms, with neutral lenses as a control. We then examined PA after-effects through changes in known oscillatory EEG signatures of spatial attention orienting and motor preparation in the alpha and beta frequency bands. Our results were twofold. First, we found PA to rightward shifting prisms to selectively affect EEG signatures of motor but not attentional processes. More specifically, PA modulated preparatory motor EEG activity over central electrodes in the right hemisphere, contralateral to the PA-induced, compensatory leftward shift in pointing movements. No effects were found on EEG signatures of spatial attention orienting over occipito-parietal sites. Second, we found the PA effect on preparatory motor EEG activity to dominate in the beta frequency band. We conclude that changes to intentional visuo-motor rather than attentional visuo-spatial processes underlie the PA after-effect of rightward deviating prisms in healthy participants

Proprioceptive feedback facilitates motor imagery-related operant learning of sensorimotor β-band modulation

Motor imagery (MI) activates the sensorimotor system independent of actual movements and might be facilitated by neurofeedback. Knowledge on the interaction between feedback modality and the involved frequency bands during MI-related brain self-regulation is still scarce. Previous studies compared the cortical activity during the MI task with concurrent feedback (MI with feedback condition) to cortical activity during the relaxation task where no feedback was provided (relaxation without feedback condition). The observed differences might, therefore, be related to either the task or the feedback. A proper comparison would necessitate studying a relaxation condition with feedback and a MI task condition without feedback as well. Right-handed healthy subjects performed two tasks, i.e., MI and relaxation, in alternating order. Each of the tasks (MI vs. relaxation) was studied with and without feedback. The respective event-driven oscillatory activity, i.e., sensorimotor desynchronization (during MI) or synchronization (during relaxation), was rewarded with contingent feedback. Importantly, feedback onset was delayed to study the task-related cortical activity in the absence of feedback provision during the delay period. The reward modality was alternated every 15 trials between proprioceptive and visual feedback. Proprioceptive input was superior to visual input to increase the range of task-related spectral perturbations in the α- and β-band, and was necessary to consistently achieve MI-related sensorimotor desynchronization (ERD) significantly below baseline. These effects occurred in task periods without feedback as well. The increased accuracy and duration of learned brain self-regulation achieved in the proprioceptive condition was specific to the β-band. MI-related operant learning of brain self-regulation is facilitated by proprioceptive feedback and mediated in the sensorimotor β-band

State-dependent modulation of cortico-spinal networks

Beta-band rhythm (13-30 Hz) is a dominant oscillatory activity in the sensorimotor system. Numerous studies reported on links between motor performance and the cortical and cortico-spinal beta rhythm. However, these studies report divergent beta-band frequencies and are, additionally, based on differently performed motor-tasks (e.g., motor imagination, muscle contraction, reach, grasp, and attention). This diversity blurs the role of beta in the sensorimotor system. It consequently challenges the development of beta-band activity-dependent stimulation protocols in the sensorimotor system. In this vein, we studied the functional role of beta-band cortico-cortical and cortico-spinal networks during a motor learning task. We studied how the contribution of cortical and spinal beta changes in the course of learning, and how this modulation is affected by afferent feedback to the sensorimotor system. We furthermore researched the relationship to motor performance. Consider that we made our study in the absence of any residual movement to allow our findings to be translated into rehabilitation programs for severely affected stroke patients. This thesis, at first, investigates evoked responses after transcranial magnetic stimulation (TMS). This revealed two different beta-band networks, i.e., in the low and high beta-band reflecting cortical and cortico-spinal activity. We, then, used a broader frequency range in the beta-band to trigger passive opening of the hand (peripheral feedback) or cortical stimulation (cortical feedback). While a unilateral hemispheric increase in cortico-spinal synchronization was observed in the group with peripheral feedback, a bilateral hemispheric increase in cortico-cortical and cortico-spinal synchronization was observed for the group with cortical feedback. An improvement in motor performance was found in the peripheral group only. Additionally, an enhancement in the directed cortico-spinal synchronization from cortex to periphery was observed for the peripheral group. Similar neurophysiological and behavioral changes were observed for stroke patients receiving peripheral feedback. The results 6 suggest two different mechanisms for beta-band activity-dependent protocols depending on the feedback modality. While the peripheral feedback appears to increase the synchronization among neural groups, cortical stimulation appears to recruit dormant neurons and to extend the involved motor network. These findings may provide insights regarding the mechanism behind novel activity-dependent protocols. It also highlights the importance of afferent feedback for motor restoration in beta-band activity-dependent rehabilitation programs

Oscillatory Control over Representational States in Working Memory

In the visual world, attention is guided by perceptual goals activated in visual working memory (VWM). However, planning multiple-task sequences also requires VWM to store representations for future goals. These future goals need to be prevented from interfering with the current perceptual task. Recent findings have implicated neural oscillations as a control mechanism serving the implementation and switching of different states of prioritization of VWM representations. We review recent evidence that posterior alpha-band oscillations underlie the flexible activation and deactivation of VWM representations and that frontal delta-to-theta-band oscillations play a role in the executive control of this process. That is, frontal delta-to-theta appears to orchestrate posterior alpha through long-range oscillatory networks to flexibly set up and change VWM states during multitask sequences

Attention shapes our expectations and perceptions: The neural mechanisms of top-down attention during adulthood and development

Top-down attention is the focusing of attention at one\u27s will through knowledge regarding a current task. There is evidence that top-down attention involves the modulation of sensory cortices by higher order regions. However, the mechanisms of top-down attention across sensory modalities, its influence on early sensory inputs, as well as interactions with motivational systems remain unclear. We performed the following set of electrophysiological experiments in typically developed adults and adolescents to examine these areas. 1) The supramodal attentional theory holds that parietally-based attentional mechanisms are shared across sensory modalities. We tested the supramodal theory by examining if lateralized parieto-occipital alpha-band activity, an established metric of top-down spatial attention, was observed in an audiospatial and visuospatial task. In support of the supramodal theory, we observed similar anticipatory alpha-band processes across auditory and visual tasks, but we also found an interaction of supramodal and sensory-specific attentional control processes. 2) There is evidence that top-down attention influences information immediately upon its arrival to sensory cortices, although there is debate in this area. In the current work, volitionally-driven top-down attention was engaged toward one of several overlapping surfaces in an illusion, in which the perceived brightness of the attended surface was enhanced. We observed the attentional enhancement of early visual evoked potentials, indicating that top-down attention shapes the earliest activations in visual cortices. 3) It is well known that motivation impacts attention, but the neural bases of these interactions remain unclear. We examined how level of interest in stimuli influenced top-down spatial attention mechanisms in typically-developing adolescents. Motivation enhanced established attentional processes during the anticipation of high vs. low interest stimuli, but also independently influenced frontal and parieto-occipital activations. These findings provide potential implications to inform clinical measures to improve impaired attentional processes in clinical populations (e.g. individuals with autism spectrum disorders). In sum, these studies revealed the powerful influence of top-down attentional control and its interacting systems on neural activations through several stages of anticipatory and post-stimulus processing during development and adulthood

EEG During Motor Tasks in Stroke: The Effects of Remote Ischemic Conditioning and Fatigue on Brain Activity

This dissertation aimed to use electroencephalography (EEG) to identify the effects of fatigue and remote ischemic conditioning on brain activity. Lesions due to stroke directly or indirectly affect regions of the brain and the descending corticospinal pathways. Cortical reorganization and alternate descending neural pathways are used during recovery from stroke as compensation mechanisms for motor deficits. These mechanisms exacerbate the deficits by worsening the ability to terminate muscle activity, individuate muscles for fine motor control and minimize abnormal muscle synergy and coactivation patterns to conserve resources during movement. Even though imaging and muscle activation studies have documented the existence and impact of cortical reorganization and the use of alternate descending pathways, temporal changes in cortical activation during long motor tasks are not well understood. We expect that potential changes in cerebrovascular function and physiology of brain metabolism after stroke might impact the ability of the brain to produce extended activity. We used EEG for its high temporal resolution compared to other imaging modalities to document temporal changes in brain activity when people with stroke performed various motor tasks. We first documented the changes in activation during and at the end of a simple cued finger tap task between people with stroke and controls. We then pushed the neuromuscular system to its limits using a fatiguing contraction of the wrist to visualize changes in brain activation patterns after extended muscle contraction. Lastly, we tested a neurorehabilitation therapy protocol, remote ischemic conditioning (RIC), that has shown functional improvements in people with stroke to determine if cortical activation is changed during a complex, multijoint visuomotor task. The results show that cortical activation in people with stroke is divergent from controls. People with stroke continue brain activation at the end of a simple task but cannot increase activation at the end of a fatiguing task. RIC, however, increases activation during a multijoint elbow/shoulder task. This research has improved our understanding of brain activation during a simple task and in response to fatigue in people with stroke. The knowledge of cortical changes due to RIC demonstrates the therapy’s ability to “prime” the brain for neurorehabilitation, which might lead to better therapeutic outcomes post-rehabilitation in people with stroke

Sensor Approach for Brain Pathophysiology of Freezing of Gait in Parkinson\u27s Disease Patients

Parkinson\u27s Disease (PD) affects over 1% of the population over 60 years of age and is expected to reach 1 million in the USA by the year 2020, growing by 60 thousand each year. It is well understood that PD is characterized by dopaminergic loss, leading to decreased executive function causing motor symptoms such as tremors, bradykinesia, dyskinesia, and freezing of gait (FoG) as well as non-motor symptoms such as loss of smell, depression, and sleep abnormalities. A PD diagnosis is difficult to make since there is no worldwide approved test and difficult to manage since its manifestations are widely heterogeneous among subjects. Thus, understanding the patient subsets and the neural biomarkers that set them apart will lead to improved personalized care. To explore the physiological alternations caused by PD on neurological pathways and their effect on motor control, it is necessary to detect the neural activity and its dissociation with healthy physiological function. To this effect, this study presents a custom ultra-wearable sensor solution, consisting of electroencephalograph, electromyograph, ground reaction force, and symptom measurement sensors for the exploration of neural biomarkers during active gait paradigms. Additionally, this study employed novel de-noising techniques for dealing with the motion artifacts associated with active gait EEG recordings and compared time-frequency features between a group of PD with FoG and a group of age-matched controls and found significant differences between several EEG frequency bands during start and end of normal walking (with a p\u3c0.05)

Competing at the Cybathlon championship for people with disabilities: Long-term motor imagery brain-computer interface training of a cybathlete who has tetraplegia

BACKGROUND: The brain–computer interface (BCI) race at the Cybathlon championship, for people with disabilities, challenges teams (BCI researchers, developers and pilots with spinal cord injury) to control an avatar on a virtual racetrack without movement. Here we describe the training regime and results of the Ulster University BCI Team pilot who has tetraplegia and was trained to use an electroencephalography (EEG)-based BCI intermittently over 10 years, to compete in three Cybathlon events. METHODS: A multi-class, multiple binary classifier framework was used to decode three kinesthetically imagined movements (motor imagery of left arm, right arm, and feet), and relaxed state. Three game paradigms were used for training i.e., NeuroSensi, Triad, and Cybathlon Race: BrainDriver. An evaluation of the pilot’s performance is presented for two Cybathlon competition training periods—spanning 20 sessions over 5 weeks prior to the 2019 competition, and 25 sessions over 5 weeks in the run up to the 2020 competition. RESULTS: Having participated in BCI training in 2009 and competed in Cybathlon 2016, the experienced pilot achieved high two-class accuracy on all class pairs when training began in 2019 (decoding accuracy > 90%, resulting in efficient NeuroSensi and Triad game control). The BrainDriver performance (i.e., Cybathlon race completion time) improved significantly during the training period, leading up to the competition day, ranging from 274–156 s (255 ± 24 s to 191 ± 14 s mean ± std), over 17 days (10 sessions) in 2019, and from 230–168 s (214 ± 14 s to 181 ± 4 s), over 18 days (13 sessions) in 2020. However, on both competition occasions, towards the race date, the performance deteriorated significantly. CONCLUSIONS: The training regime and framework applied were highly effective in achieving competitive race completion times. The BCI framework did not cope with significant deviation in electroencephalography (EEG) observed in the sessions occurring shortly before and during the race day. Changes in cognitive state as a result of stress, arousal level, and fatigue, associated with the competition challenge and performance pressure, were likely contributing factors to the non-stationary effects that resulted in the BCI and pilot achieving suboptimal performance on race day. Trial registration not registered SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12984-022-01073-9

Learning and adaptation in brain machine interfaces

Balancing subject learning and decoder adaptation is central to increasing brain machine interface (BMI) performance. We addressed these complementary aspects in two studies: (1) a learning study, in which mice modulated “beta” band activity to control a 1D auditory cursor, and (2) an adaptive decoding study, in which a simple recurrent artificial neural network (RNN) decoded intended saccade targets of monkeys. In the learning study, three mice successfully increased beta band power following trial initiations, and specifically increased beta burst durations from 157 ms to 182 ms, likely contributing to performance. Though the task did not explicitly require specific movements, all three mice appeared to modulate beta activity via active motor control and had consistent vibrissal motor cortex multiunit activity and local field potential relationships with contralateral whisker pad electromyograms. The increased burst durations may therefore by a direct result of increased motor activity. These findings suggest that only a subset of beta rhythm phenomenology can be volitionally modulated (e.g. the tonic “hold” beta), therefore limiting the possible set of successful beta neuromodulation strategies. In the adaptive decoding study, RNNs decoded delay period activity in oculomotor and working memory regions while monkeys performed a delayed saccade task. Adaptive decoding sessions began with brain-controlled trials using pre-trained RNN models, in contrast to static decoding sessions in which 300-500 initial eye-controlled training trials were performed. Closed loop RNN decoding performance was lower than predicted by offline simulations. More consistent delay period activity and saccade paths across trials were associated with higher decoding performance. Despite the advantage of consistency, one monkey’s delay period activity patterns changed over the first week of adaptive decoding, and the other monkey’s saccades were more erratic during adaptive decoding than during static decoding sessions. It is possible that the altered session paradigm eliminating eye-controlled training trials led to either frustration or exploratory learning, causing the neural and behavioral changes. Considering neural control and decoder adaptation of BMIs in these studies, future work should improve the “two-learner” subject-decoder system by better modeling the interaction between underlying brain states (and possibly their modulation) and the neural signatures representing desired outcomes