Identifying Boys With Autism Spectrum Disorder Based on Whole-Brain Resting-State Interregional Functional Connections Using a Boruta-Based Support Vector Machine Approach.

An increasing number of resting-state functional magnetic resonance neuroimaging (R-fMRI) studies have used functional connections as discriminative features for machine learning to identify patients with brain diseases. However, it remains unclear which functional connections could serve as highly discriminative features to realize the classification of autism spectrum disorder (ASD). The aim of this study was to find ASD-related functional connectivity patterns and examine whether these patterns had the potential to provide neuroimaging-based information to clinically assist with the diagnosis of ASD by means of machine learning.

Altered dynamic functional connectivity of insular subregions could predict symptom severity of male patients with autism spectrum disorder.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by difficulties with social communication and restricted or repetitive patterns of behavior. This disorder was characterized by widespread abnormalities involving distributed brain networks. As one such key network node, the insular cortex has been regarded as a research focus of ASD neuropathology.

The acts of opening and closing the eyes are of importance for congenital blindness: Evidence from resting-state fMRI.

Volitional eye closure is observed only in conscious and awake humans, and is rare in animals. It is believed that eye closure can focus one's attention inward and facilitate activities such as meditation and mental imagery. Congenital blind individuals are also required to close their eyes for these activities.

Low SO2 emission from CFB co-firing MSW and bituminous.

Influence of co-firing rate on SO2 emission from co-firing municipal solid waste (MSW) and bituminous containing high amount of sulfur (1.79%) was studied in a 0.15 MWt circulating fluidized bed (CFB).