IDENTIFYING THE CORRELATION BETWEEN ENCEPHALOGRAPHIC SIGNAL IRREGULARITY AND HEART RATE VARIABILITY TO DIFFERENTIATE INTERNALLY AND EXTERNALLY OPERATIVE ATTENTION

Abstract

This study identifies a correlation between low-frequency heart rate variability (LF-HRV) and encephalographic (EEG) complexity to differentiate internally operative attention (INT) and externally operative attention (EXT). Electrophysiological fluctuations in response to Posner’s spatial orienting paradigm were explored in 14 healthy volunteers who participated in 6 alternating sessions of attention tasks. HRV analysis was used to measure heart rate fluctuations, and approximate entropy (ApEn) was used to measure changes in the irregularity of EEG and HRV. Power spectral analysis of HRV revealed that there was found to be a significant difference between INT and EXT for HRV-low frequency (HRV-LF) and LH/HF ratio. ApEn for RR-interval time series increased for both attention tasks as compared to baseline and recovery session. The relationship between HRV-LF and EEG spectral power measured at F4 revealed significant negative correlation during ([Formula: see text], with [Formula: see text]) EXT than ([Formula: see text], with [Formula: see text]) INT. Furthermore, a significant positive correlation, yet of moderate strength was noted between HRV-LF and ApEn of EEG signal measured at POz ([Formula: see text], with [Formula: see text]) during EXT as compared to INT ([Formula: see text], with [Formula: see text]) and, a significant negative correlation was observed between ApEn of RR-interval and ApEn of EEG signal measured at POz ([Formula: see text], with [Formula: see text]) during EXT as compared to INT ([Formula: see text], with [Formula: see text]). Thus, it is evident that EXT leads to more irregularity in parietal regions of the brain than the INT. During EXT, the irregularity over the parietal region linked to increased sympathetic activity as compared to INT and corresponds to decreased heart rate. These results may benefit in designing robust human-computer interfaces and accelerated training paradigm to raise an athlete’s performance.