Literature DB >> 30891353

Power spectrum of spontaneous cerebral homodynamic oscillation shows a distinct pattern in autism spectrum disorder.

Huiyi Cheng1, Jie Yu2, Lingyu Xu2,3, Jun Li1,4,5.   

Abstract

Spontaneous hemodynamic fluctuations recorded by functional near-infrared spectroscopy (fNIRS) from bilateral temporal lobes were analyzed on 25 children with autism spectrum disorder (ASD) and 22 typically developing (TD) children. By frequency domain analysis, a new characteristic was uncovered that the power spectrum of low frequency cerebral hemodynamic oscillation showed a distinct pattern in ASD. More specifically, at the frequency of 0.0200 Hz, the power of oxygenated hemoglobin was larger for TD than ASD, whereas in the band of 0.0267-0.0333 Hz, the power of deoxygenated hemoglobin was larger for ASD than TD. Using these new features and those identified previously together as feature variables for the support vector machine (SVM) classifier, accurate classification between ASD and TD was achieved with a sensitivity of 90.2%, specificity of 95.1% and accuracy of 92.7%.

Entities:  

Year:  2019        PMID: 30891353      PMCID: PMC6420268          DOI: 10.1364/BOE.10.001383

Source DB:  PubMed          Journal:  Biomed Opt Express        ISSN: 2156-7085            Impact factor:   3.732


  1 in total

1.  Prediction in Autism by Deep Learning Short-Time Spontaneous Hemodynamic Fluctuations.

Authors:  Lingyu Xu; Xiulin Geng; Xiaoyu He; Jun Li; Jie Yu
Journal:  Front Neurosci       Date:  2019-11-08       Impact factor: 4.677

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.