Sex-specific neural circuits of emotion regulation in the centromedial amygdala.

Sex-related differences in emotion regulation (ER) in the frequency power distribution within the human amygdala, a brain region involved in emotion processing, have been reported. However, how sex differences in ER are manifested in the brain networks which are seeded on the amygdala subregions is unclear. The goal of this study was to investigate this issue from a brain network perspective.

Discriminating Bipolar Disorder From Major Depression Based on SVM-FoBa: Efficient Feature Selection With Multimodal Brain Imaging Data.

Discriminating between bipolar disorder (BD) and major depressive disorder (MDD) is a major clinical challenge due to the absence of known biomarkers; hence a better understanding of their pathophysiology and brain alterations is urgently needed. Given the complexity, feature selection is especially important in neuroimaging applications, however, feature dimension and model understanding present serious challenges. In this study, a novel feature selection approach based on linear support vector machine with a forward-backward search strategy (SVM-FoBa) was developed and applied to structural and resting-state functional magnetic resonance imaging data collected from 21 BD, 25 MDD and 23 healthy controls.

Variation of the default mode network with altered alertness levels induced by propofol.

Background: The default mode network (DMN) is closely associated with the maintenance of alertness and cognitive functions. This study aimed to observe the changes in DMN induced by increasing doses of propofol and progressively deepening sedation.

Methods: Twelve healthy subjects were selected; they received target-controlled infusion of propofol (1.

The neural correlates of risk propensity in males and females using resting-state fMRI.

Men are more risk prone than women, but the underlying basis remains unclear. To investigate this question, we developed a trait-like measure of risk propensity which we correlated with resting-state functional connectivity to identify sex differences. Specifically, we used short- and long-range functional connectivity densities to identify associated brain regions and examined their functional connectivities in resting-state functional magnetic resonance imaging (fMRI) data collected from a large sample of healthy young volunteers.