Heng Chen1, Xujun Duan1, Feng Liu1, Fengmei Lu1, Xujing Ma1, Youxue Zhang1, Lucina Q Uddin2, Huafu Chen3. 1. Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, PR China. 2. Department of Psychology, University of Miami, Coral Gables, United States. 3. Key laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology and Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 610054, PR China. Electronic address: chenhf@uestc.edu.cn.
Abstract
BACKGROUND: Resting-state functional magnetic resonance imaging studies examining low frequency fluctuations (0.01-0.08 Hz) have revealed atypical whole brain functional connectivity patterns in adolescents with autism spectrum disorder (ASD), and these atypical patterns can be used to discriminate individuals with ASD from controls. However, at present it is unknown whether functional connectivity at specific frequency bands can be used to discriminate individuals with ASD from controls, and whether relationships with symptom severity are stronger in specific frequency bands. METHODS: We selected 240 adolescent subjects (12-18 years old, 112 with autism spectrum disorder (101/11, males/females) and 128 healthy controls (104/24, males/females)) from 6 separate international sites in the Autism Brain Imaging Data Exchange database. Whole brain functional connectivity networks were constructed in the Slow-5 (0.01-0.027 Hz) and Slow-4 (0.027-0.073 Hz) frequency bands, which were then used as classification features. RESULTS: An accuracy of 79.17% (p<0.001) was obtained using support vector machine. Most of the discriminative features were concentrated on the Slow-4 band. In the Slow-4 band, atypical connections between the default mode network, fronto-parietal network and cingulo-opercular network were detected. A significant correlation was found between social and communication deficits as measured by the ADOS in individuals with ASD and the classification scores based on connectivity between the default mode network and the cingulo-opercular network. Connections of the thalamus were of the highest classification weight in the Slow-4 band. CONCLUSIONS: Our findings provide preliminary evidence for frequency-specific whole brain functional connectivity indices that may eventually be used to aid detection of ASD.
BACKGROUND: Resting-state functional magnetic resonance imaging studies examining low frequency fluctuations (0.01-0.08 Hz) have revealed atypical whole brain functional connectivity patterns in adolescents with autism spectrum disorder (ASD), and these atypical patterns can be used to discriminate individuals with ASD from controls. However, at present it is unknown whether functional connectivity at specific frequency bands can be used to discriminate individuals with ASD from controls, and whether relationships with symptom severity are stronger in specific frequency bands. METHODS: We selected 240 adolescent subjects (12-18 years old, 112 with autism spectrum disorder (101/11, males/females) and 128 healthy controls (104/24, males/females)) from 6 separate international sites in the Autism Brain Imaging Data Exchange database. Whole brain functional connectivity networks were constructed in the Slow-5 (0.01-0.027 Hz) and Slow-4 (0.027-0.073 Hz) frequency bands, which were then used as classification features. RESULTS: An accuracy of 79.17% (p<0.001) was obtained using support vector machine. Most of the discriminative features were concentrated on the Slow-4 band. In the Slow-4 band, atypical connections between the default mode network, fronto-parietal network and cingulo-opercular network were detected. A significant correlation was found between social and communication deficits as measured by the ADOS in individuals with ASD and the classification scores based on connectivity between the default mode network and the cingulo-opercular network. Connections of the thalamus were of the highest classification weight in the Slow-4 band. CONCLUSIONS: Our findings provide preliminary evidence for frequency-specific whole brain functional connectivity indices that may eventually be used to aid detection of ASD.
Authors: Ashley N Nielsen; Deanna J Greene; Caterina Gratton; Nico U F Dosenbach; Steven E Petersen; Bradley L Schlaggar Journal: Cereb Cortex Date: 2019-06-01 Impact factor: 5.357
Authors: Pradyumna Lanka; D Rangaprakash; Michael N Dretsch; Jeffrey S Katz; Thomas S Denney; Gopikrishna Deshpande Journal: Brain Imaging Behav Date: 2020-12 Impact factor: 3.978