Effects of resting heart rate variability on performance in the P300 brain-computer interface

ObjectiveBrain computer interfaces (BCI) can serve as a communication system for people with severe impairment in speech and motor function due to neurodegenerative disease or injury. Reasons for inter-individual differences in capability of BCI usage are not yet fully understood. Paradigms making use of the P300 event-related potential are widely used. Success in a P300 based BCI requires the capability to focus attention and inhibit interference by distracting irrelevant stimuli. Such inhibitory control has been closely linked to peripheral physiological parameters, such as heart rate variability (HRV). The present study investigated the association between resting HRV and performance in the P300-BCI.MethodsHeart rate was recorded from 34 healthy participants under resting conditions, and subsequently a P300-BCI task was performed.ResultsFrequency domain measures of HRV were significantly associated with BCI-performance, in that higher vagal activation was related to better BCI-performance.ConclusionsResting HRV accounted for almost 26% of the variance of BCI performance and may, therefore, serve as a predictor for the capacity to control a P300 oddball based BCI.SignificanceThis is the first study to demonstrate resting vagal-cardiac activation to predict capability of P300-BCI usage.

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► HRV was identified as predictor of Brain-Computer-Interface (BCI) performance.
► HRV at rest is a proxy for assessing prefrontal executive functions used for BCI.
► These findings may allow for rapid identification of BCI performance capability.