[Show abstract][Hide abstract] ABSTRACT: The amygdala plays a central role in processing facial affect, responding to diverse expressions and features shared between expressions. Although speculation exists regarding the nature of relationships between expression- and feature-specific amygdala reactivity this matter has not been fully explored. We used functional magnetic resonance imaging and principal component analysis (PCA) in a sample of 300 young adults, to investigate patterns related to expression- and feature-specific amygdala reactivity to faces displaying neutral, fearful, angry or surprised expressions. The PCA revealed a two-dimensional correlation structure that distinguished emotional categories. The first principal component separated neutral and surprised from fearful and angry expressions whereas the second principal component separated neutral and angry from fearful and surprised expressions. This two-dimensional correlation structure of amygdala reactivity may represent specific feature-based cues conserved across discrete expressions. To delineate which feature-based cues characterized this pattern, face stimuli were averaged and then subtracted according to their principal component loadings. The first principal component corresponded to displacement of the eyebrows whereas the second principal component corresponded to increased exposure of eye whites together with movement of the brow. Our results suggest a convergent representation of facial affect in the amygdala reflecting feature-based processing of discrete expressions.
Preview · Article · Jul 2013 · Social Cognitive and Affective Neuroscience
[Show abstract][Hide abstract] ABSTRACT: Impulsivity is a complex trait associated with a range of maladaptive behaviors, including many forms of psychopathology. Previous research has implicated multiple neural circuits and neurotransmitter systems in impulsive behavior, but the relationship between impulsivity and organization of whole-brain networks has not yet been explored. Using graph theory analyses, we characterized the relationship between impulsivity and the functional segregation ("modularity") of the whole-brain network architecture derived from resting-state functional magnetic resonance imaging (fMRI) data. These analyses revealed remarkable differences in network organization across the impulsivity spectrum. Specifically, in highly impulsive individuals, regulatory structures including medial and lateral regions of the prefrontal cortex were isolated from subcortical structures associated with appetitive drive, whereas these brain areas clustered together within the same module in less impulsive individuals. Further exploration of the modular organization of whole-brain networks revealed novel shifts in the functional connectivity between visual, sensorimotor, cortical, and subcortical structures across the impulsivity spectrum. The current findings highlight the utility of graph theory analyses of resting-state fMRI data in furthering our understanding of the neurobiological architecture of complex behaviors.