There is a critical clinical need for quantitative objective measures that can be used to assess and treat individuals with mood disorders. Dr. Mower Provost’s research addresses this need by investigating computational methodologies to differentiate emotion perception (EP) patterns of healthy controls (HC) and individuals with Major Depressive Disorder (MDD) or Bipolar Disorder (BP). MDD and BP are common mood disorders characterized by transitions between euthymia (absence of mania/depression) and depression or mania in BP and between euthymia and depression in MDD. Both MDD and BP carry a significant personal and societal burden and are associated with significant cognitive abnormalities including cognitive distortions, impulse control deficits, and the focus of this proposed study, disturbances in EP.
For example, individuals in a depressed state may display more negative biases when interpreting facial and vocal cues compared with HCs, misidentifying neutral faces as angry or sad. However, it is not yet understood how individuals integrate and interpret audio-visual cues to arrive at specific EP. The proposed experiments address this open question, probing the link between mood state, audio-visual cues and EP using novel computational techniques.
“The results from this study will not only increase our understanding of this complex relationship, but will have important implications for developing therapies to correct any distortions in EP and provide an additional measure of severity for mood disorders,” says Mower Provost.