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Abstract Stroke is a leading cause of adult disability worldwide, with approximately 101 million survivors globally. Over 60% of these individuals live with from long-term, often lifelong, movement impairments that significantly hinder their ability to perform essential daily activities and maintain independence. Post-stroke movement disabilities are highly associated with structural and functional changes in motor descending pathways, particularly the corticospinal tract and other indirect motor pathways via the brainstem. For decades, neuroengineers have been working to quantitively evaluate the post-stroke changes of motor descending pathways, aiming to establish a precision prognosis and tailoring treatments to post-stroke motor impairment. However, a clear and practicable technique has not yet been established as a breakthrough to change the standard of care for current clinical practice. In this review, we outline recent progress in neuroimaging, neuromodulation, and electrophysiological approaches for assessing structural and functional changes of motor descending pathways in stroke. We also discuss their limitations and challenges, arguing the need of artificial intelligence and large multi-modal data registry for a groundbreaking advance to this important topic. 

Research Problem: K-12 school systems are racing to implement Computer Science (CS) education within classrooms across the United States. Prior research on education reform movements suggests that without rigorous research, combined with careful technical support for implementation, we should expect wide variation across districts in how they choose to implement computer science education as well as extreme inequality in which districts provide equitable opportunities to learn CS, with the most underserved students fairing the worst (Ahn & Quarles, 2016; Bryk, Gomez, Grunow, & LeMahieu, 2015; Carlson, Borman, & Robinson, 2011; Gordon and Heck, 2019). It stands to reason that these same challenges are at play in the CS subfield of cybersecurity. Research Question: In what ways does the JROTC-CS experience impact the cognitive (e.g. knowledge and skills) and non-cognitive factors (e.g. social and emotional behaviors) of cadets in high school? Methodology: We used a qualitative study using a semi-structured interview protocol with JROTC cadets attending the schools involved in the intervention (n=17). The interview protocol focused on the types of cognitive and non-cognitive impacts the cadets experienced when participating in CS and Cybersecurity learning experiences. Data Collection: We conducted interviews with 17 cadets and coded the transcripts using a priori codes. Findings: Sixteen of the students reported an increase in their knowledge and skills through self-reported grades and self-perceived knowledge gained through the CS and cybersecurity experiences. While all of the students indicated that the courses and extracurricular activities were beneficial and interesting, only two of the students indicated they wanted to have a career in the computer science or cybersecurity field. However, the findings indicated a lack of school personnel support, specifically at the guidance counselor level. Finally, all of the students reported a strong sense of belonging in their CS and cybersecurity experiences leading to increased peer collaboration and support. Implications: Based on other evidence collected during the intervention, the intervention had multiple successes in expanding equitable experiences for cadets in the schools involved in the study. Guidance counselors and other personnel who are in a position to influence the future career choices of cadets may need more professional development; however, more research is needed to understand the ways in which they currently influence cadets. 

ObjectiveThis quasi-experimental study examined the effect of repetitive finger stimulation on brain activation in eight stroke and seven control subjects, measured by quantitative electroencephalogram. MethodsWe applied 5 mins of 2-Hz repetitive bilateral index finger transcutaneous electrical nerve stimulation and compared differences pre– and post–transcutaneous electrical nerve stimulation using quantitative electroencephalogram metrics delta/alpha ratio and delta-theta/alpha-beta ratio. ResultsBetween-group differences before and after stimulation were significantly different in the delta/alpha ratio (z= −2.88,P= 0.0040) and the delta-theta/alpha-beta ratio variables (z= −3.90 withP< 0.0001). Significant decrease in the delta/alpha ratio and delta-theta/alpha-beta ratio variables after the transcutaneous electrical nerve stimulation was detected only in the stroke group (delta/alpha ratio diff = 3.87,P= 0.0211) (delta-theta/alpha-beta ratio diff = 1.19,P= 0.0074). ConclusionsThe decrease in quantitative electroencephalogram metrics in the stroke group may indicate improved brain activity after transcutaneous electrical nerve stimulation. This finding may pave the way for a future novel therapy based on transcutaneous electrical nerve stimulation and quantitative electroencephalogram measures to improve brain recovery after stroke. 

High-definition transcranial direct current stimulation (HD-tDCS) is a promising approach for stroke rehabilitation, which may induce functional changes in the cortical sensorimotor areas to facilitate movement recovery. However, it lacks an objective measure that can indicate the effect of HD-tDCS on alteration of brain activity. Quantitative electroencephalography (qEEG) has shown promising results as an indicator of post-stroke functional recovery. Therefore, this study aims to determine whether qEEG metrics could serve as quantitative measures to assess alteration in brain activity induced by HD-tDCS. Resting state EEG was collected from stroke participants before and after (1) anodal HD-tDCS of the lesioned hemisphere, (2) cathodal stimulation of the non-lesioned hemisphere, and (3) sham. The average power spectrum was calculated using the Fast Fourier Transform for frequency bands alpha, beta, delta, and theta. In addition, delta-alpha ratio (DAR), Delta-alpha-beta-theta ratio (DTABR), and directional brain symmetry index (BSI) were also evaluated. We found that both anodal and cathodal stimulation significantly decreased the DAR and BSI over various frequency bands, which are associated with reduced motor impairments and improved nerve conduction velocity from the brain to muscles. This result indicates that qEEG metrics DAR and BSI could be quantitative indicators to assess alteration of brain activity induced by HD-tDCS in stroke rehabilitation. This would allow future development of EEG-based neurofeedback system to guide and evaluate the effect of HD-tDCS on improving movement-related brain function in stroke.