Brain connectivity in Autistic individuals

Every brain is unique, and this is even more so with Autistic individuals. One of the challenges when investigating the Autistic brain is the variability from person-to-person, meaning that traditional approaches using a limited number of participants (i.e 20 individuals) produce very unreliable results. To address this issues, research centres from around the world have combined existing data to create the Autism Brain Imaging Data Exchange (ABIDE), allowing scientists to investigate 1000’s of participants brain structure and connectivity in an effort to generate more reliable and individualised biomarkers of the Autistic brain.


  • Di Martino, A., O’Connor, D., Chen, B., Alaerts, K., Anderson, J. S., Assaf, M., Balsters, J.H., et al. (2017). Enhancing studies of the connectome in autism using the autism brain imaging data exchange II. Scientific Data, 4, 170010.
  • Balsters, J., Mantini, D., & Wenderoth, N. (2017). Connectivity-based parcellation reveals distinct cortico-striatal connectivity fingerprints in Autism Spectrum Disorder. Neuroimage.
  • Balsters, J., Mantini, D., Apps, M. A. J., Eickhoff, S. B., & Wenderoth, N. (2016). Connectivity-based parcellation increases network detection sensitivity in resting state fMRI: An investigation into the cingulate cortex in autism. NeuroImage: Clinical, 11, 494–507.
  • Kassraian Fard, P., Matthis, C., Balsters, J., Maathuis, M. H., & Wenderoth, N. (2016). Promises, Pitfalls, and Basic Guidelines for Applying Machine Learning Classifiers to Psychiatric Imaging Data, with Autism as an Example. Frontiers in Psychiatry, 7(8), 329.
  • Delmonte, S., Gallagher, L., O’Hanlon, E., McGrath, J., & Balsters, J. (2013). Functional and structural connectivity of frontostriatal circuitry in Autism Spectrum Disorder. Frontiers in Human Neuroscience, 7, 430.