A Method for Using Neurofeedback to Guide Mental Imagery for Improving Motor Skill

Mental imagery (MI) is gaining attention as a strategy towards endogenous brain stimulation for improving motor skill. Neurofeedback (NF) is commonly used to guide MI in order to activate the relevant brain networks. The current study investigates an individualized EEG-based method for NF through broad consideration of interactions between different brain networks. We selected the change in brain functional connectivity (FC) as an objective neurophysiological measure of change in motor skill during a longitudinal physical training (PT) program. Digital tracing tasks were developed for skill training and the spatial error in tracing was used to gauge the change in skill. We used partial least squares algorithms to find the most robust contributing networks towards correlation between the resting state FC and the acquired motor skill. We used the network with the largest margin for increasing FC as the candidate for NF training while experimenting with MI during a neurofeedback training program. The participant was informed of the changes in instantaneous FC through real-time audio feedback to help guide the MI. We showed over 20% reduction in tracing error through neurofeedback training alone, without any additional PT. We also showed retention of improvement in skill for several days after the completion of neurofeedback training. Our proposed methodology shows promise for a highly individualized approach towards improvement in motor skill. Given that EEG is an accessible health and wellness technology, such a method could provide a practical complementary option towards personalized therapeutic strategies to improve motor function.ISSN:1534-4320ISSN:1558-021

An MRI-Based Semiquantitative Index for the Evaluation of Brain Atrophy and Lesions in Alzheimer's Disease, Mild Cognitive Impairment and Normal Aging

Background: This study investigates how T1-weighted MRI can be used to evaluate brain anatomical changes. We investigated these changes in Alzheimer\u2019s disease (AD) and normal aging. Methods: A semiquantitative brain atrophy and lesion index (BALI) was constructed by adapting existing visual rating scales and validated in 3 datasets. Results: The T1- and T2-weighted-imaging-based scores were highly correlated. They were both closely associated with age and with cognitive test scores. Conclusion: The T1-based BALI helps describe brain structural variability in AD, mild cognitive impairment and normal aging.Peer reviewed: YesNRC publication: Ye

An MRI brain atrophy and lesion index to assess the progression of structural changes in Alzheimer's disease, mild cognitive impairment, and normal aging: a follow-up study

Background: A brain atrophy and lesion index (BALI) based on high-field magnetic resonance imaging (MRI) has recently been validated to evaluate structural changes in the aging brain. The present study investigated the two-year progression of brain structural deficits in people with Alzheimer's disease (AD) and mild cognitive impairment (MCI), and in healthy control older adults (HC) using the BALI rating. Methods: T1-weighted high-resolution anatomical imaging data using 3 Tesla MRI at baseline (AD = 39, MCI = 82, HC = 58) and at 24-months were obtained from the Alzheimer's disease Neuroimaging Initiative database. Lesions in various brain structures, including the infratentorial and basal ganglia areas, and the periventricular and deep white matter and global atrophy, were evaluated and combined into the BALI scale. Results: Mean progression of brain deficits over two years was evident in all diagnostic groups (p < 0.001) and was statistically greater in MCI-AD converters than in the non-converters (p = 0.044). An increase in the BALI score was significantly associated with cognitive test scores (p = 0.008 for the Mini-Mental State Examination MMSE and p = 0.013 for the Alzheimer's Disease Assessment Scale-Cognitive Subscale ADAS-cog) in a model that adjusted for age, sex, and education. Conclusion: The BALI rating quantified the progression of brain deficits over two years, which is associated with cognitive decline. BALI ratings may be used to help summarize AD-associated structural variations.Peer reviewed: YesNRC publication: Ye