MAR 20, 2014 10:00 AM PDT

Impairments of brain network connectivity in autism

Presented At Neuroscience
  • Director of the Brain Development Imaging Lab, Professor of Psychology, San Diego State University
      Dr. Ralph-Axel Mueller is Professor of Psychology at San Diego State University (San Diego, CA). He received his Ph.D. from the Johann-Wolfgang-Goethe University of Frankfurt (Germany) and received postdoctoral training with Dr. Harry Chugani at Childrens Hospital of Michigan. Over the past twenty years, Dr. Mueller has applied functional and anatomical imaging techniques to the study of brain development in typical children and adolescents, as well as those with developmental disorders. While his early work focused on the implementation of positron emission tomography in children with epilepsy and tumors in preparation for neurosurgery and on the investigation of lesion-induced neuroplasticity, work in the past 15 years has been dedicated to magnetic resonance imaging in autism. His group was among the first to use functional MRI and subsequently functional connectivity MRI in the study of brain network abnormalities in autism spectrum disorders. More recently, work in his laboratory has expanded to include other imaging techniques, such as diffusion tensor imaging (for the study of anatomical connectivity), as well as anatomical brain volumetrics and magnetic resonance spectroscopy. Dr. Mueller laboratory ( has been continuously funded by grants from the National Institutes of Health (NINDS, NIDCD, NIMH) and other agencies since 2001.


    With a rising prevalence recently exceeding 1%, autism spectrum disorder (ASD) has become a pressing public health issue. Crucial hurdles on the way to targeted treatments are (i) the reliance on behavioral diagnostic criteria for disorder known to be neurological in nature, and (ii) the lack of knowledge about biologically defined subtypes that may be linked to identifiable sets of genetic (and environmental) risk factors. Despite a plethora of neuroscientific findings, fully sensitive and specific brain biomarkers have not been identified. However, there are strong indications from genetics, postmortem literature, and neuroimaging supporting the investigation of brain network connectivity as a promising source of the needed biomarkers. Functional connectivity MRI (fcMRI) has been one widely applied method, but with a recently grown awareness of methodological issues, the initial model of general underconnectivity has to be revised in favor of concepts such as impaired network integration and differentiation in ASD. Anatomical connectivity has been primarily studied with diffusion tensor imaging (DTI), with findings supporting atypical age-related changes in tract maturation and organization as well as widespread white matter compromise in adolescents and adults with ASD. Multimodal imaging approaches will be crucial for a more comprehensive understanding of network abnormalities in ASD, but findings from fcMRI and DTI reflect different parameters of connectivity and do not always coincide. The mandate of hypothesis-driven investigation may create as much harm as good in the specific case of ASD research, as data-mining techniques (such as machine learning diagnostic classification) may be uniquely suited to uncover complex patterns of biomarkers.

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