Estimating direction in brain-behavior interactions: Proactive and reactive brain states in driving

Abstract

Conventional neuroimaging analyses have ascribed function to particular brain regions, exploiting the power of the subtraction technique in fMRI and event-related potential analyses in EEG. Moving beyond this convention, many researchers have begun exploring network-based neurodynamics and coordination between brain regions as a function of behavioral parameters or environmental statistics; however, most approaches average evoked activity across the experimental session to study task-dependent networks. Here, we examined on-going oscillatory activity as measured with EEG and use a methodology to estimate directionality in brain-behavior interactions. After source reconstruction, activity within specific frequency bands (delta: 2-3Hz; theta: 4-7Hz; alpha: 8-12Hz; beta: 13-25Hz) in a priori regions of interest was linked to continuous behavioral measurements, and we used a predictive filtering scheme to estimate the asymmetry between brain-to-behavior and behavior-to-brain prediction using a variant of Granger causality. We applied this approach to a simulated driving task and examined directed relationships between brain activity and continuous driving performance (steering behavior or vehicle heading error). Our results indicated that two neuro-behavioral states may be explored with this methodology: a Proactive brain state that actively plans the response to the sensory information and is characterized by delta-beta activity, and a Reactive brain state that processes incoming information and reacts to environmental statistics primarily within the alpha band.

Automated EEG mega-analysis I: Spectral and amplitude characteristics across studies

“…Deviations from the nominal distribution may provide a more robust linkage between oscillatory activity, brain state, and task performance. A recent study, using one of the datasets included in this corpus (Garcia et al, 2017) employs a related approach by identifying fluctuations in the relationship between brain activity and behavior (i.e., proactive and reactive brain states) rather than direct correlations between power spectra and performance. These types of analyses, however, require a large, heterogeneous sample in order to establish baseline or nominal states that can generalize across tasks and individuals.…”

“…The ARL Baseline Driving Task was conducted at three different sites using an identical experimental apparatus that included a driving simulator with steering wheel and brake/foot pedals but no motion platform (Touryan et al, 2014) (Brooks et al, 2015) (Brooks and Kerick, 2015 (Garcia et al, 2017). The Baseline Driving Task included either 45 minutes of continuous driving or 60 minutes of driving organized into 10-minute blocks.…”

“…120 subjects were right-handed, 15 subjects were left-handed, 3 subjects were ambidextrous, and 17 subjects did not report handedness. Like the Baseline Driving Task, these experiments were conducted at three different sites using an identical experimental apparatus that included a driving simulator with steering wheel and brake/foot pedals but no motion platform (Touryan et al, 2014) (Brooks et al, 2015 (Brooks and Kerick, 2015) (Garcia et al, 2017). The ARL HRED site (Aberdeen MD) and the Teledyne site (Durham, NC) used BioSemi 64-channel headsets.…”

“…The ARL Lane-keeping with Speed Control Task, which is similar to the ARL Baseline Driving Task, consisted of 45 minutes of continuous driving in a driving simulator while maintaining the posted speed limit. The driving simulator included a steering wheel and brake/foot pedals but no motion platform (Touryan et al, 2014) (Brooks et al, 2015 (Brooks and Kerick, 2015) (Garcia et al, 2017). Subjects were instructed to maintain a constant specified speed and stay in the center of the lane while the vehicle underwent random lateral perturbations.…”

“…The ARL Lane-keeping with Traffic Complexity Task, which is similar to the ARL Baseline Driving Task, consisted of 45 minutes of continuous driving in a driving simulator with steering wheel and brake/foot pedals but no motion platform (Touryan et al, 2014) (Brooks et al, 2015 (Brooks and Kerick, 2015) (Garcia et al, 2017). The visual environment consisted of a long, straight highway with visual complexity derived from vehicle traffic, including oncoming traffic and traffic in the direction of travel (in the passing lane).…”