Regulation of arousal via online neurofeedback improves human performance in a demanding sensory-motor task
Abstract
Our state of arousal can significantly affect our ability to make optimal decisions, judgments, and actions in real-world dynamic environments. The Yerkes–Dodson law, which posits an inverse-U relationship between arousal and task performance, suggests that there is a state of arousal that is optimal for behavioral performance in a given task. Here we show that we can use online neurofeedback to shift an individual’s arousal from the right side of the Yerkes–Dodson curve to the left toward a state of improved performance. Specifically, we use a brain–computer interface (BCI) that uses information in the EEG to generate a neurofeedback signal that dynamically adjusts an individual’s arousal state when they are engaged in a boundary-avoidance task (BAT). The BAT is a demanding sensory-motor task paradigm that we implement as an aerial navigation task in virtual reality and which creates cognitive conditions that escalate arousal and quickly results in task failure (e.g., missing or crashing into the boundary). We demonstrate that task performance, measured as time and distance over which the subject can navigate before failure, is significantly increased when veridical neurofeedback is provided. Simultaneous measurements of pupil dilation and heart-rate variability show that the neurofeedback indeed reduces arousal. Our work demonstrates a BCI system that uses online neurofeedback to shift arousal state and increase task performance in accordance with the Yerkes–Dodson law.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 12, 2019
- Source ID
- 10.1073/pnas.1817207116
Entities
People
- Jennifer Cummings
- Josef Faller
- Paul Sajda
- Sameer Saproo
Organizations
- Army Research Office
- Columbia University
- Economic and Social Research Council
- National Science Foundation
- United States Army Research Laboratory