New Study Finds Stable Individual Brain Connectivity Patterns but No Clear Autism Group Differences
A new study finds that individual brain connectivity patterns are stable and unique but do not reliably differentiate autism spectrum disorder from controls, highlighting challenges in neuroimaging biomarkers for autism.
New Dynamic Brain Graph Model Enhances Identification of Brain Disorders
A new dynamic brain graph model incorporating modular network structure improves classification accuracy for autism and depression using resting-state fMRI data.
Study Compares Synolitic Graphs and Traditional Methods for Autism Classification Using Resting-State fMRI
A new study compared synolitic graphs with traditional connectivity methods for classifying autism from resting-state fMRI data, finding conventional approaches more accurate.
Low-Frequency rTMS Shows Promise for Improving Brain Activity and Symptoms in Preschool Children with Autism
A new study finds that low-frequency rTMS over the left dorsolateral prefrontal cortex may improve brain activity and reduce core symptoms in preschool children with autism spectrum disorder.
Study Finds Preserved Neural Timescale Hierarchy in Autism with Subtle Individual Variations Linked to Sensory Traits
A new study shows that the hierarchical organization of brain activity timing is largely preserved in autism spectrum disorder, with subtle individual differences linked to sensory traits.
Hidden Markov Models Reveal Distinct Brain Network Dynamics in Autism Spectrum Disorder
A meta-analysis reveals that Hidden Markov Models applied to resting-state fMRI capture distinctive brain network dynamics in autism, highlighting reduced integrative network engagement and increased sensory activation.