Emerging tools and techniques that may advance autism research.
The machine-learning approach could help identify how brain structure differs between autistic and non-autistic infants, the researchers say.
The catalog of rare copy number variants tied to autism and other conditions could help researchers identify which genes account for the mutations’ effects.
The new tool may help researchers reconstruct the sequence of biological events that underlie development.
The method could boost reproducibility across brain imaging studies of autism.
By breaking rodent vocalizations into parts, TrackUSF distinguishes rats with mutations in the SHANK3 gene from their wildtype counterparts.
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.
The catalog could help researchers understand the effects of autism-linked DNA variants that fall outside genes.
The DNA specific to mitochondria is difficult to access, but new methods place its secrets within reach.
Researchers updated the tool’s scoring system to better align with the experiences of autistic people.
The ‘projectome’ charts axonal pathways between individual cells in the prefrontal cortex, a brain region implicated in autism.
By coupling the tool — called SLEAP — with optogenetics, researchers can determine the neural circuits underlying social behaviors.
