Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/154884
Title: Diagnostic classification of autism using resting-state fMRI data improves with full correlation functional brain connectivity compared to partial correlation
Authors: Agastinose Ronicko, Jac Fredo
Thomas, John
Thangavel, Prasanth
Koneru, Vineetha
Langs, Georg
Dauwels, Justin
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Agastinose Ronicko, J. F., Thomas, J., Thangavel, P., Koneru, V., Langs, G. & Dauwels, J. (2020). Diagnostic classification of autism using resting-state fMRI data improves with full correlation functional brain connectivity compared to partial correlation. Journal of Neuroscience Methods, 345, 108884-. https://dx.doi.org/10.1016/j.jneumeth.2020.108884
Journal: Journal of Neuroscience Methods
Abstract: Autism Spectrum Disorder (ASD) is a neurodevelopmental disability with altered connectivity in brain networks.
URI: https://hdl.handle.net/10356/154884
ISSN: 0165-0270
DOI: 10.1016/j.jneumeth.2020.108884
Rights: © 2020 Elsevier B.V. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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