https://scholars.lib.ntu.edu.tw/handle/123456789/598965
標題: | Characteristics of brain connectivity during verbal fluency test: Convolutional neural network for functional near-infrared spectroscopy analysis | 作者: | Wang L.-M Huang Y.-H Chou P.-H Wang Y.-M Chen C.-M Sun C.-W. CHUNG-MING CHEN |
關鍵字: | Brain mapping;Convolution;Convolutional neural networks;Infrared devices;Machine learning;Near infrared spectroscopy;Brain connectivity;Convolutional neural network;Functional connectivity;Functional near infrared spectroscopy;High potential;Human brain;Human Connectome;Near-infrared spectroscopy analysis;Verbal fluencies;Verbal fluency test;Brain;brain;diagnostic imaging;human;near infrared spectroscopy;Humans;Neural Networks, Computer;Spectroscopy, Near-Infrared | 公開日期: | 2022 | 卷: | 15 | 期: | 1 | 來源出版物: | Journal of Biophotonics | 摘要: | Human connectome describes the complicated connection matrix of nervous system among human brain. It also possesses high potential of assisting doctors to monitor the brain injuries and recoveries in patients. In order to unravel the enigma of neuron connections and functions, previous research has strived to dig out the relations between neurons and brain regions. Verbal fluency test (VFT) is a general neuropsychological test, which has been used in functional connectivity investigations. In this study, we employed convolutional neural network (CNN) on a brain hemoglobin concentration changes (ΔHB) map obtained during VFT to investigate the connections of activated brain areas and different mental status. Our results show that feature of functional connectivity can be identified accurately with the employment of CNN on ΔHB mapping, which is beneficial to improve the understanding of brain functional connections. ? 2021 Wiley-VCH GmbH |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85117017011&doi=10.1002%2fjbio.202100180&partnerID=40&md5=801f480b3e9928ce658920bb294933b6 https://scholars.lib.ntu.edu.tw/handle/123456789/598965 |
ISSN: | 1864063X | DOI: | 10.1002/jbio.202100180 |
顯示於: | 醫學工程學研究所 |
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