Transcranial magnetic stimulation to assess motor neurophysiology after acute stroke in the United States: Feasibility, lessons learned, and values for future research

Transcranial magnetic stimulation (TMS) has been widely applied in both basic and clinical neuroscience since its introduction in 1985 . .

Comparing a Novel Neuroanimation Experience to Conventional Therapy for High-Dose Intensive Upper-Limb Training in Subacute Stroke: The SMARTS2 Randomized Trial

BACKGROUND Evidence from animal studies suggests that greater reductions in poststroke motor impairment can be attained with significantly higher doses and intensities of therapy focused on movement quality. These studies also indicate a dose-timing interaction, with more pronounced effects if high-intensity therapy is delivered in the acute/subacute, rather than chronic, poststroke period. OBJECTIVE To compare 2 approaches of delivering high-intensity, high-dose upper-limb therapy in patients with subacute stroke: a novel exploratory neuroanimation therapy (NAT) and modified conventional occupational therapy (COT). METHODS A total of 24 patients were randomized to NAT or COT and underwent 30 sessions of 60 minutes time-on-task in addition to standard care. The primary outcome was the Fugl-Meyer Upper Extremity motor score (FM-UE). Secondary outcomes included Action Research Arm Test (ARAT), grip strength, Stroke Impact Scale hand domain, and upper-limb kinematics. Outcomes were assessed at baseline, and days 3, 90, and 180 posttraining. Both groups were compared to a matched historical cohort (HC), which received only 30 minutes of upper-limb therapy per day. RESULTS There were no significant between-group differences in FM-UE change or any of the secondary outcomes at any timepoint. Both high-dose groups showed greater recovery on the ARAT (7.3 ± 2.9 points; P = .011) but not the FM-UE (1.4 ± 2.6 points; P = .564) when compared with the HC. CONCLUSIONS Neuroanimation may offer a new, enjoyable, efficient, and scalable way to deliver high-dose and intensive upper-limb therapy

A comparison of walking and motor behaviors in children and adults during structured and unstructured practice

Thesis (M.S.O.T.) PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at [email protected]. Thank you.OBJECTIVE: We examined how gait behaviors in children and adults differed during a structured and during a minimally structured, practice walking task when temporal constraints were imposed. METHODS: Fifteen children between the ages of 5-7 and fifteen adults between the ages of 18-30 participated in an overground walking task: structured (i.e., on a defined path to specific paces) and minimally structured (i.e., freely around a room) interspersed with practice walking to the specific paces. At the beginning and end of the study, participants walked at their own pace on a 6-m long gait carpet. During the structured task, subjects walked on the same gait carpet to the beat of three different metronome paces (slow, normal, and fast). The distance and timing of participants’ steps were measured with the mechanized, pressure-sensitive gait carpet. During the minimally structured practice task, subjects walked freely around the room for two minutes to the same three metronome paces (slow, normal, and fast). All subject trials were videotaped and the two-minute minimally structured practice periods were analyzed using a video coding system. RESULTS: Compared to children, adults demonstrated a greater difference from their baseline walking in all gait parameters (i.e., velocity, cadence, step length, step time, swing time, stance time, single limb support time, and double limb support time) at the slow metronome pace (all ps<.01). However, at the slow pace, children had more difficulty keeping pace with the metronome compared to adults both before (p=.001) and after practice (p=.001). Furthermore, the magnitude of children’s errors in meeting the metronome pace was larger than that of adults at the normal (p=.007) and slow (p=.002) paces. During the two-minute minimally structured practice periods, children demonstrated more gait behaviors than adults however, only foot behaviors (i.e., leaping, cross stepping, walking backward, and toe-walking) reached initial significance when walking at the normal compared to the slow pace. Follow up comparisons did not reach significance for any of the gait behaviors for children or adults. CONCLUSION: We found that children and adults modified their gait patterns when given a temporal constraint in order to try to match the constraint. Children were more prone to maintain gait patterns that were similar to their baseline walking than adults and subsequently had more difficulty matching all of the metronome paces. In addition, children demonstrated a larger variety and frequency of gait behaviors than adults when able to structure their own walking during minimally structured practice tasks.2031-01-0

Nurturing diversity and inclusion in AI in Biomedicine through a virtual summer program for high school students.

Artificial Intelligence (AI) has the power to improve our lives through a wide variety of applications, many of which fall into the healthcare space; however, a lack of diversity is contributing to limitations in how broadly AI can help people. The UCSF AI4ALL program was established in 2019 to address this issue by targeting high school students from underrepresented backgrounds in AI, giving them a chance to learn about AI with a focus on biomedicine, and promoting diversity and inclusion. In 2020, the UCSF AI4ALL three-week program was held entirely online due to the COVID-19 pandemic. Thus, students participated virtually to gain experience with AI, interact with diverse role models in AI, and learn about advancing health through AI. Specifically, they attended lectures in coding and AI, received an in-depth research experience through hands-on projects exploring COVID-19, and engaged in mentoring and personal development sessions with faculty, researchers, industry professionals, and undergraduate and graduate students, many of whom were women and from underrepresented racial and ethnic backgrounds. At the conclusion of the program, the students presented the results of their research projects at the final symposium. Comparison of pre- and post-program survey responses from students demonstrated that after the program, significantly more students were familiar with how to work with data and to evaluate and apply machine learning algorithms. There were also nominally significant increases in the students' knowing people in AI from historically underrepresented groups, feeling confident in discussing AI, and being aware of careers in AI. We found that we were able to engage young students in AI via our online training program and nurture greater diversity in AI. This work can guide AI training programs aspiring to engage and educate students entirely online, and motivate people in AI to strive towards increasing diversity and inclusion in this field