Functional connectivity of the human amygdala using resting state fMRI

Amy Krain Roy, Zarrar Shehzad, Daniel S. Margulies, A. M.Clare Kelly, Lucina Q. Uddin, Kristin Gotimer, Bharat B. Biswal, F. Xavier Castellanos, Michael P. Milham

Research output: Contribution to journalArticlepeer-review

627 Scopus citations

Abstract

The amygdala is composed of structurally and functionally distinct nuclei that contribute to the processing of emotion through interactions with other subcortical and cortical structures. While these circuits have been studied extensively in animals, human neuroimaging investigations of amygdala-based networks have typically considered the amygdala as a single structure, which likely masks contributions of individual amygdala subdivisions. The present study uses resting state functional magnetic resonance imaging (fMRI) to test whether distinct functional connectivity patterns, like those observed in animal studies, can be detected across three amygdala subdivisions: laterobasal, centromedial, and superficial. In a sample of 65 healthy adults, voxelwise regression analyses demonstrated positively-predicted ventral and negatively-predicted dorsal networks associated with the total amygdala, consistent with previous animal and human studies. Investigation of individual amygdala subdivisions revealed distinct differences in connectivity patterns within the amygdala and throughout the brain. Spontaneous activity in the laterobasal subdivision predicted activity in temporal and frontal regions, while activity in the centromedial nuclei predicted activity primarily in striatum. Activity in the superficial subdivision positively predicted activity throughout the limbic lobe. These findings suggest that resting state fMRI can be used to investigate human amygdala networks at a greater level of detail than previously appreciated, allowing for the further advancement of translational models.

Original languageEnglish (US)
Pages (from-to)614-626
Number of pages13
JournalNeuroImage
Volume45
Issue number2
DOIs
StatePublished - Apr 1 2009
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Neurology
  • Cognitive Neuroscience

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