{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T04:29:52Z","timestamp":1791433792336,"version":"4.3.3"},"reference-count":35,"publisher":"SPIE-Intl Soc Optical Eng","issue":"02","license":[{"start":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T00:00:00Z","timestamp":1620950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neurophoton."],"published-print":{"date-parts":[[2021,5,14]]},"abstract":"<jats:p>Significance: There is an emerging need for convenient and continuous bedside monitoring of full-term newborns with hypoxic-ischemic brain damage (HIBD) to determine whether early intervention is required. Functional near-infrared spectroscopy (fNIRS)-based resting-state brain network analysis, which could provide an effective evaluation method, remains to be extensively studied.\nAim: Our study aims to verify the feasibility of fNIRS-based resting-state brain networks for evaluating brain function in infants with HIBD to provide a new and effective means for clinical research in neonatal HIBD.\nApproach: Thirteen neonates with HIBD were scanned using fNIRS in the resting state. The brain network properties were explored to attempt to extract effective features as recognition indicators.\nResults: Compared with healthy controls, newborns with HIBD showed decreased brain functional connectivity. Specifically, there were severe losses of long-range functional connectivity of the contralateral parietal-temporal lobe, contralateral parietal-frontal lobe, and contralateral parietal lobe. The node degree showed a widespread decrease in the left frontal middle gyrus, left superior frontal gyrus dorsal, and right central posterior gyrus. However, newborns with HIBD showed a significantly higher local network efficiency (*p\u2009\u2009&lt;\u2009\u20090.05). Subsequently, network indicators based on small-worldness, local efficiency, modularity, and normalized clustering coefficient were extracted for HIBD identification with the accuracy observed as 79.17%.\nConclusions: Our findings indicate that fNIRS-based resting-state brain network analysis could support early HIBD diagnosis.<\/jats:p>","DOI":"10.1117\/1.nph.8.2.025007","type":"journal-article","created":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T00:36:41Z","timestamp":1620952601000},"page":"1-17","source":"Crossref","is-referenced-by-count":25,"title":["Resting-state brain networks in neonatal hypoxic-ischemic brain damage: a functional near-infrared spectroscopy study"],"prefix":"10.1117","volume":"8","author":[{"given":"Shen","family":"Zhang","sequence":"first","affiliation":[{"name":"Beihang Univ."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3770-586X","authenticated-orcid":false,"given":"Cheng","family":"Peng","sequence":"additional","affiliation":[{"name":"Peking Univ. 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