ArticleBiomedical optics express2019
Power spectrum of spontaneous cerebral homodynamic oscillation shows a distinct pattern in autism spectrum disorder.
Article in Biomedical optics express, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed.
- Depth-sensitive cerebral blood flow and low-frequency oscillations for consciousness assessment using time-domain diffuse correlation spectroscopy.Neurophotonics · 2026Article
- Detectability of hemodynamic oscillations in cerebral cortex through functional near-infrared spectroscopy: a simulation study.Neurophotonics · 2024Article
- Assessment of power spectral density of microvascular hemodynamics in skeletal muscles at very low and low-frequency via near-infrared diffuse optical spectroscopies.Biomedical optics express · 2023Article
- Non-Invasive Continuous Optical Monitoring of Cerebral Blood Flow after Traumatic Brain Injury in Mice Using Fiber Camera-Based Speckle Contrast Optical Spectroscopy.Brain sciences · 2023Article
- Correlation and predictive ability of sensory characteristics and social interaction in children with autism spectrum disorder.Frontiers in psychiatry · 2023Article
- Narrowband Resting-State fNIRS Functional Connectivity in Autism Spectrum Disorder.Frontiers in human neuroscience · 2021Article
- Prediction in Autism by Deep Learning Short-Time Spontaneous Hemodynamic Fluctuations.Frontiers in neuroscience · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
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%.
Identifiers
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Registered trials
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