  Conventional neuroimaging analyses have revealed the computational
specificity of localized 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 and use a methodology
to estimate directionality in brain-behavior interactions. After source
reconstruction, activity within specific frequency bands 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. We applied this approach to a simulated
driving task and examine directed relationships between brain activity and
continuous driving behavior (steering or heading error). Our results indicated
that two neuro-behavioral states emerge in this naturalistic environment: a
Proactive brain state that actively plans the response to the sensory
information, and a Reactive brain state that processes incoming information and
reacts to environmental statistics.
