The 'default network' is a network of brain regions that are active when the brain is at wakeful rest and deactivated when the individual engages in goal-directed tasks. Atypical activity and weak interconnections in this network may be a common feature in autism spectrum disorders, as well as in attention deficit hyperactivity disorder, which often co-occurs with autism. This observation highlights an emerging storyline in the study and understanding of these two disorders.
Joel Nigg and his team at Oregon Health and Science University are trying to identify the brain anatomy underlying network dysfunctions in people with one or both disorders. The researchers predict that under-connectivity in the default network characterizes both disorders, whereas the under-development of two additional control networks may differentiate the two disorders. For their study, the researchers plan to use resting-state functional magnetic resonance imaging to measure spontaneous brain activity while subjects are at rest. This technique allows for an easily applied, non-invasive mapping of brain networks, which is appropriate for investigating the development of neuropsychiatric disorders in children, particularly children with autism.
Their research is also concerned with the diversity of autism spectrum disorders. It seems likely that multiple disease mechanisms exist across the spectrum, which do not map cleanly on to clinical features. That is, even children with a similar clinical presentation may have distinct neurobiology or a distinct configuration of poorly connected brain circuits. To examine this possibility, the researchers plan to apply an analysis method called 'graph theoretical community detection algorithms' to the resting-state fMRI data in an effort to identify 'communities' of autism patients with distinct underlying neuropathology. This would be the first application of this approach to autism and, if successful, the project will open new avenues for characterizing specific brain networks and specific sets of children with autism.