Cognitive Dynamics Estimation: A whole-brain spatial regression paradigm for extracting the temporal dynamics of cognitive processes

Abstract

Abstract Functional MRI (fMRI) has been instrumental to understanding how cognitive processes are spatially mapped in the brain, yielding insights into brain region and function. Here we propose a different approach to fMRI analysis, called Cognitive Dynamics Estimation (CDE), that models how cognitive processes occur over time. Conventional analysis regresses cognitive events across time to estimate voxel activity. CDE transposes this regression and uses spatial maps of cognitive processes from meta-analysis as regressors, estimating their activity over time. We show that CDE successfully estimates cognitive processing activity while demonstrating advantages over the conventional brain mapping paradigm. CDE can chart the time series of virtually any cognitive process without the need for experimental event logs that assume their onset and offset. It also alleviates the problem of multicollinearity in conventional analysis, dissociating temporally correlated processes across time. Evaluating CDE models showed its estimated time series captured the trial-by-trial fluctuation of intensity and timing of cognitive processes, including predicting participants’ task ability. As an addition to our fMRI analytic toolkit, these results suggest the potential for CDE to elucidate underexplored cognitive phenomena in the temporal domain.