Research on autism has struggled to find a central theory underlying brain changes associated with autism spectrum disorder (ASD).
Now, a new study shows that individuals with the disorder exhibit different patterns of brain connectivity, when compared to typically developing individuals and that these patterns adjust as the individual ages.
“Our findings suggest that developmental stage must be taken into account to accurately build models that show how the brains of individuals with autism differ from neurotypical individuals. We believe that taking a developmental approach to examining brain connectivity in autism is critical for predicting response to treatment in young children with ASD.”
Our brain is composed of more than one trillion cells called neurons. They interact with one another to form complex signaling networks. Previous studies have identified patterns of both functional hypo- and hyper-connectivity of these signaling networks in individuals with ASD.
The study, titled “Developmental Changes in Large-Scale Network Connectivity in Autism,” attempts to explain these conflicting results, by indicating that the developmental stage of the individual plays a key role in the findings.
As the authors write in the paper:
We used data from the Autism Brain Imaging Data Exchange (ABIDE), a publicly available data set (Di Martino etal., 2014). Only data collected at the New York University Langone Medical Center were utilized to avoid cross-study methodological acquisition differences. To explore the effects of participant age on functional connectivity, we divided the data into three age groups of ASD and TD participants: young children under 11 years of age (n = 52), adolescents from 11–18 years of age (n = 56), and adults over 18 years of age (n = 36; Table1). Individuals with ASD had a clinical DSM-IV diagnosis of Autistic Disorder, Asperger’s syndrome, Pervasive Developmental Disorder Not-Otherwise Specified (PDD-NOS) while TD participants were required to have no Axis-I disorders based on the KSADS-PL questionnaire.
For Image processing:
Functional MRI data were preprocessed using FSL 5.06. The first three volumes of each data set were deleted. Preprocessing steps included motion correction, interleaved slice-timing correction, spatial smoothing (full width at half maximum = 5 mm), and high pass temporal filtering using a local fit of a straight line (Gaussian-weighted least-squares straight line fitting with sigma = 100 s). Images were then normalized to the Montreal Neurological Institute (MNI) 152 stereotactic space (2 mm) using the default settings in FSL’s FEAT toolbox by applying a linear transformation with 12 degrees of freedom.
Important Findings of the Study
* Children (7 to 11) with ASD, exhibit hyper-connectivity within large-scale brain networks, as well as decreased between-network connectivity, when compared to TD children.
* Adolescents (age 11 to 18) with ASD do not differ in within network connectivity, but have a decrease in between network connectivity, from TD adolescents.
* Adults (older than 18) with ASD show neither within, or between-network differences in functional connectivity compared with typical adults.
The findings suggest that alterations in the networks of the brain’s cortex may trigger the complex behavioral characteristics observed in individuals with ASD.
“This study helps us understand the functional organization of brain networks and how they change across the lifespan in autism,” said Jason S. Nomi, lead author of the study.
The authors conclude:
In sum, the current findings support adopting a developmental perspective to help reconcile the heterogeneous findings of functional hypo- and hyper-connectivity observed in the rsfMRI literature in ASD. These results demonstrating group differences specific to certain age cohorts highlight the utility of carefully considering developmental stage in studies of functional brain connectivity in ASD. We find that while children show atypical within and between-network functional relationships, adolescents exhibit fewer such differences and adults are indistinguishable from age-matched neurotypical peers on such measures. The fact that both within- and between-network differences diminish across the lifespan could offer an explanation for some of the improved function often found in adults with ASD compared to children with ASD. These results also highlight the importance of considering within- and between-network whole brain functional connections in conjunction with a developmental approach in order to better characterize brain connectivity in ASD.
The researchers are now working to explicitly characterize an important developmental transition in individuals with autism: the onset of puberty.