Validation of a diffusion imaging biomarker of autism

  • Awarded: 2014
  • Award Type: Pilot
  • Award #: 307098

The proposed research takes advantage of the resources available at the University of Oxford in the U.K. to validate a new noninvasive magnetic resonance imaging (MRI) biomarker of autism using postmortem imaging. This has enormous potential for subsequent development as a tool for early detection, diagnosis, monitoring and assessment of individuals with autism. Steven Chance and his colleagues seek to better understand the cause of autism by investigating the neuroanatomical basis of the condition. Accurate diagnosis in life is difficult because the detailed changes in the cerebral cortex cannot be seen in brain imaging of living people.

Recent observations found that the vertical cellular circuits, called minicolumns, which constitute the fundamental structural organization throughout the cerebral cortex, are altered in autism1. Disturbed development of the brain’s detailed structure forms one of the key theories of the neuropathology of autism. This microscopic columnar architecture correlates with cognitive ability and has been proposed as the neural basis of symptoms, as well as the neural basis of enhanced capacities such as fine touch discrimination. It has also been implicated in the beneficial effects of interventions such as transcranial magnetic stimulation as a way of improving function by increasing the inhibition of over-excitable minicolumns in autism2.

Chance and his group aim to develop a noninvasive brain imaging marker of this microscopic structure by proving that it may be detected and quantified in MRI scans of postmortem tissue, with the potential for future application in living people. If validated, such a measure would aid early diagnosis and provide a harmless method to monitor ongoing changes across the lifespan, including changes in response to therapies. The detection of change in primary sensory brain regions holds implications for simple, sensory, diagnostic tests, and could ultimately improve individual care by more effectively targeting therapies.



  1. Casanova M.F. et al. Neuroscientist 9, 496-507 (2003) PubMed
  2. Sokhadze E.M. et al. J. Autism Dev. Disord. 39, 619-634 (2009) PubMed
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