  For the last several decades, emotion research has attempted to identify a
"biomarker" or consistent pattern of brain activity to characterize a single
category of emotion (e.g., fear) that will remain consistent across all
instances of that category, regardless of individual and context. In this
study, we investigated variation rather than consistency during emotional
experiences while people watched video clips chosen to evoke instances of
specific emotion categories. Specifically, we developed a sequential
probabilistic approach to model the temporal dynamics in a participant's brain
activity during video viewing. We characterized brain states during these clips
as distinct state occupancy periods between state transitions in blood oxygen
level dependent (BOLD) signal patterns. We found substantial variation in the
state occupancy probability distributions across individuals watching the same
video, supporting the hypothesis that when it comes to the brain correlates of
emotional experience, variation may indeed be the norm.
