Regulation of arousal via online neurofeedback improves human performance in a demanding sensory-motor task

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Edited by Richard M. Shiffrin, Indiana University, Bloomington, IN, and approved February 19, 2019 (received for review October 6, 2018)

vol. 116 no. 13 6482-6490

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^aDepartment of Biomedical Engineering, Columbia University, New York, NY 10027;
^bData Science Institute, Columbia University, New York, NY 10027

Edited by Richard M. Shiffrin, Indiana University, Bloomington, IN, and approved February 19, 2019 (received for review October 6, 2018)

↵¹To whom correspondence may be addressed. Email: josef.faller{at}gmail.com or psajda{at}columbia.edu.

Author contributions: J.F., S.S., and P.S. designed research; J.F. and J.C. performed research; J.F. contributed new reagents/analytic tools; J.F. analyzed data; and J.F. and P.S. wrote the paper.
Conflict of interest statement: P.S. is a co-founder of Neuromatters LLC, a company which develops and applies brain computer interface technology for assessment of media and stimuli. None of this work was funded by Neuromatters or used Neuromatters resources. None of what is described in the paper is licensed to Neuromatters or any other company, nor is it being submitted as a patent filing.
This article is a PNAS Direct Submission.
Data deposition: All data needed to reproduce the findings in this paper are publicly available via IEEE DataPort (dx.doi.org/10.21227/rn3e-bp31).
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1817207116/-/DCSupplemental.