Machine learning streamlines neuroimaging data analysis
The method could boost reproducibility across brain imaging studies of autism.
Charting the structure and function of the brain’s many circuits may unravel autism’s mysteries.
The method could boost reproducibility across brain imaging studies of autism.
A researcher’s existential crisis led to a scientific breakthrough.
People’s brains have a larger network of inhibitory interneurons than mouse brains do, according to a new study. Changes to that network could contribute to autism or other conditions, says lead investigator Moritz Helmstaedter.
Regions of the brain’s fear center expand in autistic children and teenagers with anxiety, but not in their autistic or non-autistic peers without anxiety.
A theoretical neuroscientist, Kennedy uses a blend of computational modeling and real-world experiments to understand how brain activity shapes the behaviors of animals that model autism and other conditions.
The method, called Orgo-Seq, reveals that a deletion of genes on chromosome 16 increases the proportion of immature neurons and neural precursors in brain organoids derived from people with the mutation.
Deletion of the 22q11.2 chromosomal region alters the expression of numerous autism- and schizophrenia-linked genes, most of which are not contained within the deleted region, a new study suggests.
The expression levels of certain genes that track with brain activity are different in autistic people than in their non-autistic peers.
Long cast in supporting roles in the brain, astrocytes are now emerging as primary players in certain characteristics of autism and related conditions.
The growth differences vary between autistic boys and girls and are most apparent among children with prominent social difficulties.