Complexity of Resting Cortical Activity Predicts Neurophysiological Responses to Theta- Burst Stimulation but Fails to Generalize: A Rigorous Machine-Learning Approach
Ning, Matthew; Sun, Haoqi; Passera, Brice; Das, Duygu Bagci; Westover, Brandon; Pascual-Leone, Alvaro; Santarnecchi, Emiliano; +2 Authors
Ning, Matthew; Sun, Haoqi; Passera, Brice; Das, Duygu Bagci; Westover, Brandon; Pascual-Leone, Alvaro; Santarnecchi, Emiliano; Shafi, Mouhsin M; Ozdemir, Recep;
Complexity of Resting Cortical Activity Predicts Neurophysiological Responses to Theta- Burst Stimulation but Fails to Generalize: A Rigorous Machine-Learning Approach
Preprocessed files (resting-state EEG, motor-evoked potentials and TMS-EEG evoked potentials) for the manuscript of the same title: "Complexity of Resting Cortical Activity Predicts Neurophysiological Responses to Theta- Burst Stimulation but Fails to Generalize: A Rigorous Machine-Learning Approach," to be published on PLOS Computational Biology Journal (doi, coming soon). Uploaded as a single compressed file, which in turn, contains 574 files spanning two independent test-retest cohorts. De-identified in accordance with HIPAA/IRB. For feature store and labels, please refer to version 0.0.1 of this data repository.
- Beth Israel Deaconess Medical Center United States
- Massachusetts General Hospital United States
- Hebrew SeniorLife United States
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selected citations
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These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
Citations provided by BIP!popularityPopularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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