A functional connectivity-based classification approach to autism spectrum disorder: only as good (or bad) as available diagnostic criteria
| Autor: | Patricia Shih, Christopher L. Keown, Ralph-Axel Müller |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
medicine.medical_specialty
Group membership medicine.diagnostic_test Resting state fMRI Functional connectivity Magnetic resonance imaging Audiology medicine.disease Developmental psychology Typically developing Neurology Autism spectrum disorder medicine Autism Neurology (clinical) Functional Connectivity MRI Psychology |
| Zdroj: | Future Neurology. 7:259-262 |
| ISSN: | 1748-6971 1479-6708 |
| DOI: | 10.2217/fnl.12.18 |
| Popis: | Evaluation of: Anderson JS, Nielsen JA, Froehlich AL et al. Functional connectivity magnetic resonance imaging classification of autism. Brain 134, 3742–3754 (2011). This study used functional connectivity detected from low-frequency fluctuations in functional MRI time series acquired during a resting state. Participants were adolescents and adults with autism spectrum disorder (ASD) and typically developing controls. Classification scores were used to predict group membership based on functional connectivity for a large number of regions of interest across the whole brain. Diagnostic prediction accuracy was approximately 75% overall. The results contribute to current knowledge of functional connectivity abnormalities in ASD, generally in support of underconnectivity theories. They are also promising with respect to the search for biomarkers of ASD that are needed to replace current behavior-based diagnostic criteria. While data from young children were not available for this study, findings appear to suggest that functional connectivity signatures may be more distinctively abnormal in children compared to adults with ASD. |
| Databáze: | OpenAIRE |
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