Topic: salience network

Individuals with depression, psychosis and clinically high risk for psychosis face cognitive decline and show altered functional connectivity in resting-state networks. An unsupervised machine-learning method, sparse partial least squares analysis (SPLS) captures latent variables from clinical features and brain mechanisms, allowing the examination of relationships between functional connectivity and cognitive functions across disorders. This study aimed to explore relationships between functional connectivity, cognitive domains and study groups using SPLS. 990 participants with recent-onset p

Severe anxiety frequently co-occurs with core symptoms of autism spectrum disorders (ASD); however, the determinants are unexplored (Kerns et al., 2021). One of the most reliable anomalies reported in both ASD and anxiety disorder patients is an aberrant functional connectivity between the salience network and the default mode network (Uddin et al., 2015). Our data indicate that a specific inhibitory neuronal subpopulation plays a fundamental role in salience detection and in gating sensory stimuli to adaptively shape behavior. The aim of the project is to test whether failure in the encoding