Implicit Learning of a Finger Motor Sequence by Patients with Cerebral Palsy After Neurofeedback

The effects of neurofeedback training for children with cerebral palsy and co-occurring attention deficits: A pilot study

BACKGROUND

Limited research exists regarding the effectiveness of electroencephalogram (EEG) neurofeedback training for children with cerebral palsy (CP) and co-occurring attention deficits (ADs), despite the increasing prevalence of these dual conditions. This study aimed to fill this gap by examining the impact of neurofeedback training on the attention levels of children with CP and AD.

METHODS

Nineteen children with both CP and co-occurring ADs were randomly assigned to either a neurofeedback or control group. The neurofeedback group received 20 sessions of training, lasting approximately 1 h per day, twice a week. Theta/beta ratios of the quantitative electroencephalography (QEEG) recordings were measured pre-training and post-training in the resting state. The Continuous Performance Test (CPT), the Test of Visual Perceptual Skills-3rd Version (TVPS-3) and the Conners' Parent Rating Scale (CPRS) were measured at pre- and post-training.

RESULTS

The neurofeedback group showed both decreased theta/beta ratios compared with control group (p = 0.04) at post-training and a within-group improvement during training (p = 0.02). Additionally, the neurofeedback group had a trend of decreased omission rates of the CPT (p = 0.08) and the visual sequential memory and the visual closure subscores in the TVPS-3, compared with the control group (p = 0.02 and p = 0.01, respectively).

CONCLUSIONS

The results suggested that children with CP and co-occurring AD may benefit from neurofeedback training in their attention level. Further research is needed to explore long-term effects and expand its application in this population.

Determining optimal mobile neurofeedback methods for motor neurorehabilitation in children and adults with non-progressive neurological disorders: a scoping review

Background

Brain–computer interfaces (BCI), initially designed to bypass the peripheral motor system to externally control movement using brain signals, are additionally being utilized for motor rehabilitation in stroke and other neurological disorders. Also called neurofeedback training, multiple approaches have been developed to link motor-related cortical signals to assistive robotic or electrical stimulation devices during active motor training with variable, but mostly positive, functional outcomes reported. Our specific research question for this scoping review was: for persons with non-progressive neurological injuries who have the potential to improve voluntary motor control, which mobile BCI-based neurofeedback methods demonstrate or are associated with improved motor outcomes for Neurorehabilitation applications?

Methods

We searched PubMed, Web of Science, and Scopus databases with all steps from study selection to data extraction performed independently by at least 2 individuals. Search terms included: brain machine or computer interfaces, neurofeedback and motor; however, only studies requiring a motor attempt, versus motor imagery, were retained. Data extraction included participant characteristics, study design details and motor outcomes.

Results

From 5109 papers, 139 full texts were reviewed with 23 unique studies identified. All utilized EEG and, except for one, were on the stroke population. The most commonly reported functional outcomes were the Fugl-Meyer Assessment (FMA; n = 13) and the Action Research Arm Test (ARAT; n = 6) which were then utilized to assess effectiveness, evaluate design features, and correlate with training doses. Statistically and functionally significant pre-to post training changes were seen in FMA, but not ARAT. Results did not differ between robotic and electrical stimulation feedback paradigms. Notably, FMA outcomes were positively correlated with training dose.

Conclusion

This review on BCI-based neurofeedback training confirms previous findings of effectiveness in improving motor outcomes with some evidence of enhanced neuroplasticity in adults with stroke. Associative learning paradigms have emerged more recently which may be particularly feasible and effective methods for Neurorehabilitation. More clinical trials in pediatric and adult neurorehabilitation to refine methods and doses and to compare to other evidence-based training strategies are warranted.

Strengthening the GABAergic system through neurofeedback training suppresses implicit motor learning

Gamma-aminobutyric acid (GABA) activity within the primary motor cortex (M1) is essential for motor learning in cortical plasticity, and a recent study has suggested that real-time neurofeedback training (NFT) can self-regulate GABA activity. Therefore, this study aimed to investigate the effect of GABA activity strengthening via NFT on subsequent motor learning. Thirty-six healthy participants were randomly assigned to either an NFT group or control group, which received sham feedback. GABA activity was assessed for short intracortical inhibition (SICI) within the right M1 using paired-pulse transcranial magnetic stimulation. During the NFT intervention period, the participants tried to modulate the size of a circle, which was altered according to the degree of SICI in the NFT group. However, the size was altered independently of the degree of SICI in the control group. We measured the reaction time before, after (online learning), and 24 h after (offline learning) the finger-tapping task. Results showed the strengthening of GABA activity induced by the NFT intervention, and the suppression of the online but not the offline learning. These findings suggest that prior GABA activity modulation may affect online motor learning.

Alpha down-regulation neurofeedback training effects on implicit motor learning and consolidation

OBJECTIVE

Implicit motor learning, which is a non-conscious form of learning characterized by motor performance improvement with practice, plays an essential role in various daily activities. Earlier study using neurofeedback training (NFT), a type of brain-computer interaction that enables the user to learn self-regulating his/her own brain activity, demonstrated that down-regulating alpha over primary motor cortex by NFT could immediately facilitate the implicit motor learning in a relatively simple motor task. However, detailed effects on EEG and implicit motor learning due to NFT especially in a more complex motor task are still unclear.

APPROACH

We designed a single-blind sham-controlled between-subject study to examine whether alpha down-regulation NFT could facilitate implicit motor learning and also its consolidation in a more difficult and motor predominant task. At left primary motor cortex (C3) in two days, the alpha NFT group received alpha down-regulation training through auditory feedback while the sham-control group received random beta NFT. At the end of NFT, all participants performed the continuous tracking task with their dominant (right) hand to evaluate the implicit motor learning immediately. Finally, the continuous tracking task was performed again on the next day to assess consolidation effects.

MAIN RESULTS

The alpha NFT group successfully decreased alpha amplitude during NFT, whereas the sham-control group maintained alpha at a relatively stable level. There was unfortunately no statistical evidence proving that the alpha NFT group significantly enhanced the implicit motor learning at the end of NFT and the consolidation on the next day compared to the sham-control group. Nevertheless, a significant correlation was found between the alpha change trend during NFT and the implicit motor learning for all participants, suggesting that faster alpha down-regulation was associated with better implicit motor learning.

SIGNIFICANCE

The findings suggested a close link between implicit motor learning and alpha change induced by NFT.

EEG coherence as a diagnostic tool to measure the initial stages of Parkinson Disease

Although Parkinson Disease was described a long time ago by James Parkinson and several biomarkers were used to predict the symptoms of PD, there is no accepted tool to distinguish the initial stages of this pathology. The present hypothesis discusses the Coherence Function, an Electroencephalography measure which could be used as a simple, and low-cost tool to describe the onset of cardinal signals of PD. Our hypothesis is based on three factors: beta frequency related to movement, motor action over particular cortical regions, and cortical coupling between cortical areas involved in the execution of voluntary movement. We believe that these factors support our hypothesis pointing out coherence function as an interesting measure to detect initial stages of PD.

Eyes-Closed Resting EEG Predicts the Learning of Alpha Down-Regulation in Neurofeedback Training

Neurofeedback training, which enables the trainee to learn self-control of the EEG activity of interest based on online feedback, has demonstrated benefits on cognitive and behavioral performance. Nevertheless, as a core mechanism of neurofeedback, learning of EEG regulation (i.e., EEG learning) has not been well understood. Moreover, a substantial number of non-learners who fail to achieve successful EEG learning have often been reported. This study investigated the EEG learning in alpha down-regulation neurofeedback, aiming to better understand the alpha learning and to early predict learner/non-learner. Twenty-nine participants received neurofeedback training to down-regulate alpha in two days, while eight of them were identified as non-learners who failed to reduce their alpha within sessions. Through a stepwise linear discriminant analysis, a prediction model was built based on participant's eyes-closed resting EEG activities in broad frequency bands including lower alpha, theta, sigma and beta 1 measured before training, which was validated in predicting learners/non-learners. The findings would assist in the early identification of the individuals who would not likely reduce their alpha during neurofeedback.

Enhancing health leadership performance using neurotherapy

The discovery of neuroplasticity means the brain can change, functionally, in response to the environment and to learning. While individuals can develop harmful patterns of brain activity in response to stressors, they can also learn to modify or control neurological conditions associated with specific behaviors. Neurotherapy is one way of changing brain functioning to modify troubling conditions which can impair leadership performance, through responding to feedback on their own brain activity, and enhancing optimal leadership functioning through learning to maximize such cognitive strengths as mental efficiency, focus, creativity, perseverance, and executive functioning. The present article outlines the application of the concept of optimal performance training to organizational leadership in a healthcare context, by describing approaches to neurotherapy and illustrating their application through a case study of a health leader learning to overcome the neurological and emotional sequelae of workplace stress and trauma.