Autism studies tend to focus on one part of the spectrum, often excluding those who also have other conditions such as anxiety, obsessive-compulsive disorder or intellectual disability. The result, some experts say, is piecemeal findings that don’t fit together to generate a whole picture.

A complex mathematical technique can improve the sensitivity of experiments that rely on brain imaging, allowing researchers to study how the brain responds to sequences of stimuli, according to a study published in the June issue of NeuroImage.

At 12 months of age, infant siblings of children with autism have a brain response to unfamiliar faces that is characteristic of typical children at a younger age, according to a study published 26 March in Brain Topography. This developmental delay could be used as an early biomarker for autism.

Diagnosing autism in children is difficult enough, but detecting the disorder in adults is even more complicated.

A delayed response to unexpected changes in sound frequency is a marker for language impairment and autism, according to a study published in March in Biological Psychiatry.

There does not appear to be a single genetic or environmental cause of autism, and given the heterogeneity of symptoms, coming up with a clear yes or no test for autism is challenging. Timothy Roberts argues that imaging and electrophysiology are key in the search for autism biomarkers.

It’s too soon to call it a diagnostic test for autism, but an algorithm that detects patterns in brain waves shows promise as one component of a screening battery for the disorder, say researchers familiar with the work.

Mice exposed to an epilepsy drug show several features of autism, including abnormal social interactions, repetitive behaviors and patterns of super-fast brain waves, called gamma oscillations, according to a study published 15 December in Biological Psychiatry.

Over the next five years, dozens of researchers funded by the $40 million ‘NIH Human Connectome Project’ will map the circuits of the human brain, tracing neural pathways and learning how different regions work together in synchrony.

An analysis of brain scans correctly distinguishes between people with autism and controls more than 90 percent of the time, according to a study published today in Autism Research.