Motor cortex activation during visuomotor transformations: evoked potentials during overt and imagined movements.

Despite the prevalence of visuomotor transformations in our motor skills, their mechanisms remain incompletely understood, especially when imagery actions are considered such as mentally picking up a cup or pressing a button. Here, we used a stimulus-response task to directly compare the visuomotor transformation underlying overt and imagined button presses. Electroencephalographic activity was recorded while participants responded to highlights of the target button while ignoring the second, non-target button. Movement-related potentials (MRPs) and event-related desynchronization occurred for both overt movements and motor imagery (MI), with responses present even for non-target stimuli. Consistent with the activity accumulation model where visual stimuli are evaluated and transformed into the eventual motor response, the timing of MRPs matched the response time on individual trials. Activity-accumulation patterns were observed for MI, as well. Yet, unlike overt movements, MI-related MRPs were not lateralized, which appears to be a neural marker for the distinction between generating a mental image and transforming it into an overt action. Top-down response strategies governing this hemispheric specificity should be accounted for in future research on MI, including basic studies and medical practice.

Event-Related Desynchronization Induced by Tactile Imagery: an EEG Study.

It is well known that both hand movements and mental representations of movement lead to event-related desynchronization (ERD) of the electroencephalogram (EEG) recorded over the corresponding cortical motor areas. However, the relationship between ERD in somatosensory cortical areas and mental representations of tactile sensations is not well understood. In this study, we employed EEG recordings in healthy humans to compare the effects of real and imagined vibrotactile stimulation of the right hand. Both real and imagined sensations produced contralateral ERD patterns, particularly in the µ-band and most significantly in the C3 region. Building on these results and the previous literature, we discuss the role of tactile imagery as part of the complex body image and the potential for using EEG patterns induced by tactile imagery as control signals in brain-computer interfaces (BCIs). Combining this approach with motor imagery (MI) could improve the performance of BCIs intended for rehabilitation of sensorimotor function after stroke and neural trauma.

Peripheral nerve stimulation enables somatosensory feedback while suppressing phantom limb pain in transradial amputees.

To simultaneously treat phantom limb pain (PLP) and restore somatic sensations using peripheral nerve stimulation (PNS), two bilateral transradial amputees were implanted with stimulating electrodes in the proximity of the medial, ulnar and radial nerves. Application of PNS evoked tactile and proprioceptive sensations in the phantom hand. Both patients learned to determine the shape of invisible objects by scanning a computer tablet with a stylus while receiving feedback based on PNS or transcutaneous electrical nerve stimulation (TENS). Оne patient learned to use PNS as feedback from the prosthetic hand that grasped objects of different sizes. PNS abolished PLP completely in one patient and reduced it by 40-70% in the other. We suggest incorporating PNS and/or TENS in active tasks to reduce PLP and restore sensations in amputees.

Mental Strategies in a P300-BCI: Visuomotor Transformation Is an Option.

Currently, P300-BCIs are mostly used for spelling tasks, where the number of commands is equal to the number of stimuli that evoke event-related potentials (ERPs). Increasing this number slows down the BCI operation because each stimulus has to be presented several times for better classification. Furthermore, P300 spellers typically do not utilize potentially useful imagery-based approaches, such as the motor imagery successfully practiced in motor rehabilitation. Here, we tested a P300-BCI with a motor-imagery component. In this BCI, the number of commands was increased by adding mental strategies instead of increasing the number of targets. Our BCI had only two stimuli and four commands. The subjects either counted target appearances mentally or imagined hand movements toward the targets. In this design, the motor-imagery paradigm enacted a visuomotor transformation known to engage cortical and subcortical networks participating in motor control. The operation of these networks suffers in neurological conditions such as stroke, so we view this BCI as a potential tool for the rehabilitation of patients. As an initial step toward the development of this clinical method, sixteen healthy participants were tested. Consistent with our expectation that mental strategies would result in distinct EEG activities, ERPs were different depending on whether subjects counted stimuli or imagined movements. These differences were especially clear in the late ERP components localized in the frontal and centro-parietal regions. We conclude that (1) the P300 paradigm is suitable for enacting visuomotor transformations and (2) P300-based BCIs with multiple mental strategies could be used in applications where the number of possible outputs needs to be increased while keeping the number of targets constant. As such, our approach adds to both the development of versatile BCIs and clinical approaches to rehabilitation.

Cortical and autonomic responses during staged Taoist meditation: Two distinct meditation strategies.

Meditation is a consciousness state associated with specific physiological and neural correlates. Numerous investigations of these correlates reported controversial results which prevented a consistent depiction of the underlying neurophysiological processes. Here we investigated the dynamics of multiple neurophysiological indicators during a staged meditation session. We measured the physiological changes at rest and during the guided Taoist meditation in experienced meditators and naive subjects. We recorded EEG, respiration, galvanic skin response, and photoplethysmography. All subjects followed the same instructions split into 16 stages. In the experienced meditators group we identified two subgroups with different physiological markers dynamics. One subgroup showed several signs of general relaxation evident from the changes in heart rate variability, respiratory rate, and EEG rhythmic activity. The other subgroup exhibited mind concentration patterns primarily noticeable in the EEG recordings while no autonomic responses occurred. The duration and type of previous meditation experience or any baseline indicators we measured did not explain the segregation of the meditators into these two groups. These results suggest that two distinct meditation strategies could be used by experienced meditators, which partly explains the inconsistent results reported in the earlier studies evaluating meditation effects. Our findings are also relevant to the development of the high-end biofeedback systems.

Short-delay neurofeedback facilitates training of the parietal alpha rhythm.

Objective.Feedback latency was shown to be a critical parameter in a range of applications that imply learning. The therapeutic effects of neurofeedback (NFB) remain controversial. We hypothesized that often encountered unreliable results of NFB intervention could be associated with large feedback latency values that are often uncontrolled and may preclude the efficient learning.Approach.We engaged our subjects into a parietal alpha power unpregulating paradigm facilitated by visual NFB based on the individually extracted envelope of the alpha-rhythm at P4 electrode. NFB was displayed either as soon as electroencephalographic (EEG) envelope was processed, or with an extra 250 or 500 ms delay. The feedback training consisted of 15 two-minute long blocks interleaved with 15 s pauses. We have also recorded 2 min long baselines immediately before and after the training.Main results.The time course of NFB-induced changes in the alpha rhythm power clearly depended on NFB latency, as shown with the adaptive Neyman test. NFB had a strong effect on the alpha-spindle incidence rate, but not on their duration or amplitude. The sustained changes in alpha activity measured after the completion of NFB training were negatively correlated to latency, with the maximum change for the shortest tested latency and no change for the longest.Significance.Here we for the first time show that visual NFB of parietal EEG alpha-activity is efficient only when delivered to human subjects at short latency, which guarantees that NFB arrives when an alpha spindle is still ongoing. Such a considerable effect of NFB latency on the alpha-activity temporal structure could explain some of the previous inconsistent results, where latency was neither controlled nor documented. Clinical practitioners and manufacturers of NFB equipment should add latency to their specifications while enabling latency monitoring and supporting short-latency operations.

Digital filters for low-latency quantification of brain rhythms in real time.

OBJECTIVE: The rapidly developing paradigm of closed-loop neuroscience has extensively employed brain rhythms as the signal forming real-time neurofeedback, triggering brain stimulation, or governing stimulus selection. However, the efficacy of brain rhythm contingent paradigms suffers from significant delays related to the process of extraction of oscillatory parameters from broad-band neural signals with conventional methods. To this end, real-time algorithms are needed that would shorten the delay while maintaining an acceptable speed-accuracy trade-off. APPROACH: Here we evaluated a family of techniques based on the application of the least-squares complex-valued filter (LSCF) design to real-time quantification of brain rhythms. These techniques allow for explicit optimization of the speed-accuracy trade-off when quantifying oscillatory patterns. We used EEG data collected from 10 human participants to systematically compare LSCF approach to the other commonly used algorithms. Each method being evaluated was optimized by scanning through the grid of its hyperparameters using independent data samples. MAIN RESULTS: When applied to the task of estimating oscillatory envelope and phase, the LSCF techniques outperformed in speed and accuracy both conventional Fourier transform and rectification based methods as well as more advanced techniques such as those that exploit autoregressive extrapolation of narrow-band filtered signals. When operating at zero latency, the weighted LSCF approach yielded 75% accuracy when detecting alpha-activity episodes, as defined by the amplitude crossing of the 95th-percentile threshold. SIGNIFICANCE: The LSCF approaches are easily applicable to low-delay quantification of brain rhythms. As such, these methods are useful in a variety of neurofeedback, brain-computer-interface and other experimental paradigms that require rapid monitoring of brain rhythms.

Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist).

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

Subcortical neuronal ensembles: an analysis of motor task association, tremor, oscillations, and synchrony in human patients.

Deep brain stimulation (DBS) has expanded as an effective treatment for motor disorders, providing a valuable opportunity for intraoperative recording of the spiking activity of subcortical neurons. The properties of these neurons and their potential utility in neuroprosthetic applications are not completely understood. During DBS surgeries in 25 human patients with either essential tremor or Parkinson's disease, we acutely recorded the single-unit activity of 274 ventral intermediate/ventral oralis posterior motor thalamus (Vim/Vop) neurons and 123 subthalamic nucleus (STN) neurons. These subcortical neuronal ensembles (up to 23 neurons sampled simultaneously) were recorded while the patients performed a target-tracking motor task using a cursor controlled by a haptic glove. We observed that modulations in firing rate of a substantial number of neurons in both Vim/Vop and STN represented target onset, movement onset/direction, and hand tremor. Neurons in both areas exhibited rhythmic oscillations and pairwise synchrony. Notably, all tremor-associated neurons exhibited synchrony within the ensemble. The data further indicate that oscillatory (likely pathological) neurons and behaviorally tuned neurons are not distinct but rather form overlapping sets. Whereas previous studies have reported a linear relationship between power spectra of neuronal oscillations and hand tremor, we report a nonlinear relationship suggestive of complex encoding schemes. Even in the presence of this pathological activity, linear models were able to extract motor parameters from ensemble discharges. Based on these findings, we propose that chronic multielectrode recordings from Vim/Vop and STN could prove useful for further studying, monitoring, and even treating motor disorders.

Brain-machine interfaces: past, present and future.

Since the original demonstration that electrical activity generated by ensembles of cortical neurons can be employed directly to control a robotic manipulator, research on brain-machine interfaces (BMIs) has experienced an impressive growth. Today BMIs designed for both experimental and clinical studies can translate raw neuronal signals into motor commands that reproduce arm reaching and hand grasping movements in artificial actuators. Clearly, these developments hold promise for the restoration of limb mobility in paralyzed subjects. However, as we review here, before this goal can be reached several bottlenecks have to be passed. These include designing a fully implantable biocompatible recording device, further developing real-time computational algorithms, introducing a method for providing the brain with sensory feedback from the actuators, and designing and building artificial prostheses that can be controlled directly by brain-derived signals. By reaching these milestones, future BMIs will be able to drive and control revolutionary prostheses that feel and act like the human arm.