A prominent hypothesis regarding the pathophysiology of autism is that an increase in the balance between neural excitation and inhibition results in an increase in neural responses. However, previous reports of population-level response magnitude in individuals with autism have been inconsistent. Critically, network interactions have not been considered in previous neuroimaging studies of excitation and inhibition imbalance in autism. In particular, a defining characteristic of cortical organization is its hierarchical and interactive structure; sensory and cognitive systems are comprised of networks where later stages inherit and build upon the processing of earlier input stages, and also influence and shape earlier stages by top-down modulation. Here we used the well established connections of the human visual system to examine response magnitudes in a higher-order motion processing region [middle temporal area (MT+)] and its primary input region (V1). Simple visual stimuli were presented to adult individuals with autism spectrum disorders (ASD; n = 24, mean age 23 years, 8 females) and neurotypical controls (n = 24, mean age 22, 8 females) during fMRI scanning. We discovered a strong dissociation of fMRI response magnitude between region MT+ and V1 in individuals with ASD: individuals with high MT+ responses had attenuated V1 responses. The magnitude of MT+ amplification and of V1 attenuation was associated with autism severity, appeared to result from amplified suppressive feedback from MT+ to V1, and was not present in neurotypical controls. Our results reveal the potential role of altered hierarchical network interactions in the pathophysiology of ASD.
Bibliographical noteFunding Information:
This work was supported by funding from the National Institutes of Health (R01 MH106520 to S.O.M.) and by the Israel Science Foundation (Grant 103/19 to T.K.). We thank Rachel Millin, Alex Kale, Anastasia Flevaris, Ly Nguyen, Heena Panjwani, Micah Pepper, and the University of Washington Diagnostic Imaging Center for help with recruitment, data collection, and/or data analysis.
Received Oct. 2, 2019; revised Jan. 11, 2020; accepted Jan. 22, 2020. Authorcontributions:T.K.,R.A.B.,andS.O.M.designedresearch;T.K.,M.-P.S.,andJ.G.performedresearch;T.K., M.-P.S., and S.O.M. analyzed data; T.K. wrote the paper. ThisworkwassupportedbyfundingfromtheNationalInstitutesofHealth(R01MH106520toS.O.M.)andbythe Israel Science Foundation (Grant 103/19 to T.K.). We thank Rachel Millin, Alex Kale, Anastasia Flevaris, Ly Nguyen, Heena Panjwani, Micah Pepper, and the University of Washington Diagnostic Imaging Center for help with recruitment, data collection, and/or data analysis. The authors declare no competing financial interests. Correspondence should be addressed to Tamar Kolodny at email@example.com. https://doi.org/10.1523/JNEUROSCI.2376-19.2020 Copyright © 2020 the authors
Copyright © 2020 the authors.
- E/I balance
- Visual cortex
PubMed: MeSH publication types
- Journal Article
- Research Support, N.I.H., Extramural
- Research Support, Non-U.S. Gov't