98 research outputs found

    Advancing functional connectivity research from association to causation

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    Cognition and behavior emerge from brain network interactions, such that investigating causal interactions should be central to the study of brain function. Approaches that characterize statistical associations among neural time series-functional connectivity (FC) methods-are likely a good starting point for estimating brain network interactions. Yet only a subset of FC methods ('effective connectivity') is explicitly designed to infer causal interactions from statistical associations. Here we incorporate best practices from diverse areas of FC research to illustrate how FC methods can be refined to improve inferences about neural mechanisms, with properties of causal neural interactions as a common ontology to facilitate cumulative progress across FC approaches. We further demonstrate how the most common FC measures (correlation and coherence) reduce the set of likely causal models, facilitating causal inferences despite major limitations. Alternative FC measures are suggested to immediately start improving causal inferences beyond these common FC measures

    Neurophysiology

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    Contains research objectives and summary of research on ten research projects.National Institutes of Health (Grant 5 R01 EY01149-02)National Institutes of Health (Grant 1 T01 EY00090-01)Bell Telephone Laboratories, Inc. (Grant)National Institutes of Health (Grant 5 TO1 GM00778-19)National Institutes of Health (Grant 5 TO1 GM01555-08

    Relationship Between Peer Assessment During Medical School, Dean’s Letter Rankings, and Ratings by Internship Directors

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    BACKGROUND: It is not known to what extent the dean’s letter (medical student performance evaluation [MSPE]) reflects peer-assessed work habits (WH) skills and/or interpersonal attributes (IA) of students. OBJECTIVE: To compare peer ratings of WH and IA of second- and third-year medical students with later MSPE rankings and ratings by internship program directors. DESIGN AND PARTICIPANTS: Participants were 281 medical students from the classes of 2004, 2005, and 2006 at a private medical school in the northeastern United States, who had participated in peer assessment exercises in the second and third years of medical school. For students from the class of 2004, we also compared peer assessment data against later evaluations obtained from internship program directors. RESULTS: Peer-assessed WH were predictive of later MSPE groups in both the second (F = 44.90, P < .001) and third years (F = 29.54, P < .001) of medical school. Interpersonal attributes were not related to MSPE rankings in either year. MSPE rankings for a majority of students were predictable from peer-assessed WH scores. Internship directors’ ratings were significantly related to second- and third-year peer-assessed WH scores (r = .32 [P = .15] and r = .43 [P = .004]), respectively, but not to peer-assessed IA. CONCLUSIONS: Peer assessment of WH, as early as the second year of medical school, can predict later MSPE rankings and internship performance. Although peer-assessed IA can be measured reliably, they are unrelated to either outcome

    Brainhack: a collaborative workshop for the open neuroscience community

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    International audienceBrainhack events offer a novel workshop format with participant-generated content that caters to the rapidly growing open neuroscience community. Including components from hackathons and unconferences, as well as parallel educational sessions, Brainhack fosters novel collaborations around the interests of its attendees. Here we provide an overview of its structure, past events, and example projects. Additionally, we outline current innovations such as regional events and post-conference publications. Through introducing Brainhack to the wider neuroscience community, we hope to provide a unique conference format that promotes the features of collaborative, open science
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