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Computational Modeling of Sensory Deficiencies in Autistic Children



One of the biggest challenges in neurodevelopmental disorders today is that they remain behaviorally diagnosed disorders. Despite the large amounts of data from the autistic brain and an abundance of experimental evidences for its pathophysiology, no measures robustly depict the observed differences between an autistic and a typically developing brain. Recently, we measured functional connectivity in the somatosensory cortex in typically developing and autistic children using magnetoencephalography (MEG) and found an imbalanced bimodal pattern in autism: long-range feedback and local connectivity are reduced while long-range feedforward connectivity is increased. The MEG data correlated strongly with behavioral measures of sensory processing and autism severity, and classified autism diagnosis blindly with 89% accuracy (Khan, Michmizos et al. 2015).

We introduced the notion of using a biophysically realistic computational model to explain the differences between the autistic and normal brain. The differences are captured by parameter modifications that support the hypothesis that feedforward and feedback pathways are imbalanced in autism (Michmizos et al. 2014; Khan, Michmizos et al. 2014). The simulation results open the door to further development of the model, allowing for testable predictions.

Click on the MedicalXPress link to read how brain connections can give clues to sensory problems in autism.


Relevant Publications

S. Khan, J.A. Hashmi, F. Mamashli, H.M.Bharadwaj, S. Ganesan, K.P. Michmizos, M. Kitzbichler, M. Zetino, K. Garel, M. Hämäläinen, T. Kenet, "Altered Onset Response Dynamics in Somatosensory Processing in Autism Spectrum Disorder," Frontiers in Neuroscience, section Child and Adolescent Psychiatry, 2016 [ link ]

S. Khan, K.P. Michmizos, M. Tommerdahl, S. Ganesan, M. Kitzbichler, M. Zetino, K. Garel, M. Herbert, M. Hämäläinen, T. Kenet, "Somatosensory cortex functional connectivity abnormalities in autism show opposite trends, depending on direction and spatial scale," Brain, 138(5):1394-409. doi: 10.1093/brain/awv043, 2015 [ link ]

S. Khan, J. Lefèvre, S. Baillet, K.P. Michmizos, S. Ganesan, M. Kitzbichler, M. Zetino, M. Hämäläinen, C. Papadelis, T. Kenet, "Encoding Cortical Dynamics in Sparse Features," Frontiers in Human Neuroscience, (9 pp.),2014 [ link ]

K.P. Michmizos, S. Khan, M. Hämäläinen, T. Kenet, "From spikes to MEG signals: A Computational Model Mimics Abnormalities in Cortical Feed-forward and Feed-back Connectivity in Autism Spectrum Disorders,"IEEE EMBC '14, Chicago, Illinois, 2014 [ link ]