Increased oscillatory activities in the beta frequency band (13-30 Hz) in the subthalamic nucleus (STN), and in particular prolonged episodes of increased synchrony in this frequency band, have been associated with motor symptoms such as bradykinesia and rigidity in Parkinson's disease (PD). Numerous studies have investigated sensorimotor cortical beta oscillations either as a control signal for Brain Computer Interfaces (BCI) or as target signal for neurofeedback training (NFB). However, it still remains unknown whether patients with PD can gain control of the pathological oscillations recorded from a subcortical site - the STN - with neurofeedback training. We tried to address this question in the current study. Specifically, we designed a simple basketball game, in which the position of a basketball changes based on the occurrence of events of temporally increased beta power quantified in real-time. Participants practised in the game to control the position of the basketball, which requires modulation of the beta oscillations recorded from STN local field potentials (LFPs). Our results suggest that it is possible to use neurofeedback training for PD patients to downregulate pathological beta oscillations in STN LFPs, and that this can lead to a reduction of beta oscillations in the cortical-STN motor network.
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http://dx.doi.org/10.1109/NER.2019.8717176 | DOI Listing |
BMC Geriatr
January 2025
Department of Electronic and Electrical Engineering, University of Liverpool, 9 Brownlow Hill, Liverpool, UK.
Background: Brain-computer interface (BCI) offers promising solutions to cognitive enhancement in older people. Despite the clear progress received, there is limited evidence of BCI implementation for rehabilitation. This systematic review addresses BCI applications and challenges in the standard practice of EEG-based neurofeedback (NF) training in healthy older people or older people with mild cognitive impairment (MCI).
View Article and Find Full Text PDFBackground: Reading impairments, a common consequence of stroke-induced aphasia, significantly hinder life participation, affecting both functional and leisure activities. Traditional post-stroke rehabilitation strategies often show limited generalization beyond trained materials, underscoring the need for novel interventions targeting the underlying neural mechanisms.
Method: This study investigates the feasibility and potential effectiveness of real-time functional magnetic resonance imaging (fMRI) neurofeedback (NFB) intervention for reading deficits associated with stroke and aphasia.
Behav Brain Res
January 2025
College of Electronic & Information Engineering, Hebei University, Baoding, China. Electronic address:
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with an unclear pathogenesis to date. Neurofeedback (NFB) had shown therapeutic effects in patients with ASD. In this study,we analyzed the brain functional networks of children with ASD and investigated the impact of NFB targeting the beta rhythm training on these networks.
View Article and Find Full Text PDFHum Brain Mapp
January 2025
The Mind Research Network/Lovelace Biomedical Research Institute, Albuquerque, New Mexico, USA.
Evaluation of mechanisms of action of EEG neurofeedback (EEG-nf) using simultaneous fMRI is highly desirable to ensure its effective application for clinical rehabilitation and therapy. Counterbalancing training runs with active neurofeedback and sham (neuro)feedback for each participant is a promising approach to demonstrate specificity of training effects to the active neurofeedback. We report the first study in which EEG-nf procedure is both evaluated using simultaneous fMRI and controlled via the counterbalanced active-sham study design.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Abu Dhabi Maritime Academy, Abu Dhabi P.O. Box 54477, United Arab Emirates.
Electroencephalography (EEG) has emerged as a pivotal tool in both research and clinical practice due to its non-invasive nature, cost-effectiveness, and ability to provide real-time monitoring of brain activity. Wearable EEG technology opens new avenues for consumer applications, such as mental health monitoring, neurofeedback training, and brain-computer interfaces. However, there is still much to verify and re-examine regarding the functionality of these devices and the quality of the signal they capture, particularly as the field evolves rapidly.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!