Abstract

Functional outcomes (e.g., subjective percepts, emotions, memory retrievals, decisions, etc...) are partly determined by external stimuli and/or cues. But they may also be strongly influenced by (trial-by-trial) uncontrolled variations in brain responses to incoming information. In turn, this variability provides information regarding how stimuli and/or cues are processed by the brain to shape behavioral responses. This can be exploited by brain-behavior mediation analysis to make specific claims regarding the contribution of brain regions to functionally-relevant input-output transformations. In this work, we address four challenges of this type of approach, when applied in the context of mass-univariate fMRI data analysis: (i) we quantify the specificity and sensitivity profiles of different variants of mediation statistical tests, (ii) we evaluate their robustness to hemo-dynamic and other confounds, (iii) we identify the sorts of brain mediators that one can expect to detect, and (iv) we disclose possible interpretational issues and address them using complementary information-theoretic approaches. En passant, we propose a computationally efficient algorithmic implementation of the approach that is amenable to whole-brain exploratory analysis. We also demonstrate the strengths and weaknesses of brain-behavior mediation analysis in the context of an fMRI study of decision under risk. Finally, we discuss the limitations and possible extensions of the approach.