Author

Michael A. Motes

The University of Texas at DallasORCID 0000-0001-6635-6948Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Assay:electronic health records· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

Bambi DeLaRosaiD· 2 shared Jeffrey S. SpenceiD· 2 shared John HartiD· 2 shared Michael A. KrautiD· 2 shared Sven VannesteiD· 2 shared Wing Ting ToiD· 2 shared

Activity by Year

2020-2020 · peak 2/yr

Co-Author Collaboration Network

6 top collaborators · 15 mutual co-author links

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2 shared papersNeuroscience

Bambi DeLaRosaORCID

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2 papers

Recent·Most cited

NeurosciencebioRxivPreprintOct 27, 2020

THE INFLUENCE OF PRE-SUPPLEMENTARY MOTOR AREA TARGETED HIGH-DEFINITION TRANSCRANIAL DIRECT CURRENT STIMULATION ON INHIBITORY CONTROL

Bambi DeLaRosa, Jeffrey S. Spence, Michael A. Motes…·Michael A. Kraut

This study investigates the effect of HD-tDCS on preSMA to improve inhibitory control, finding that both anodal and cathodal stimulation enhanced performance compared to sham.

2 citations

humanelectronic health records

𝕏 PostBluesky

NeuroscienceBrain and BehaviorPeer-reviewedOct 19, 2020

Identification of selection and inhibition components in a go/nogo task from EEG spectra using a machine learning model

Bambi DeLaRosa, Jeffrey S. Spence, Michael A. Motes…·John Hart

The paper uses a machine learning model to identify EEG features distinguishing Go and NoGo conditions in a task, achieving 92% accuracy and localizing brain regions involved in selection and inhibition.

23 citations

electronic health recordsmachine learning (classical)

𝕏 PostBluesky