Aims: Near-infrared spectroscopy has the potential for aiding the diagnosis of major depressive disorder. The purpose of this study was to systematically review the evidence from observational studies regarding the use of near-infrared spectroscopy in patients with major depressive disorder and to identify the characteristic pattern of prefrontal lobe activity in major depressive disorder.Methods: MEDLINE, PubMed, Cochrane Library and Web of Science databases were searched in December 2013. All case-control studies were included. The quality of evidence was examined using the Newcastle-Ottawa Quality Assessment Scale. The primary outcome measures were the mean oxygenated and deoxygenated hemoglobin alterations of the cerebral cortex during cognitive activation periods. The standard mean difference for the overall pooled effects across the included studies was estimated using random or fixed effect models. The primary outcome measures were included in the meta-analysis.Results: Fourteen studies met the inclusion criteria. Six studies (n = 692 participants) were included in the analysis of the mean oxygenated hemoglobin alterations; the pooled mean standardized difference was −0.74 (95% confidence interval, −0.97 to −0.52), indicating that patients with major depressive disorder were associated with attenuated increase in oxygenated hemoglobin during cognitive activation in the prefrontal regions compared to healthy controls. Five studies (n = 668 participants) were included in the analysis of mean deoxygenated-hemoglobin changes; the pooled standardized mean difference was 0.18 (95% confidence interval, −0.20 to 0.56).Conclusions: Using near-infrared spectroscopy measurements, we observed that compared to healthy subjects, patients with major depressive disorder had significantly lower prefrontal activation during cognitive tasks.

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BackgroundSchizophrenia is a kind of serious mental illness. Due to the lack of an objective physiological data supporting and a unified data analysis method, doctors can only rely on the subjective experience of the data to distinguish normal people and patients, which easily lead to misdiagnosis. In recent years, functional Near-Infrared Spectroscopy (fNIRS) has been widely used in clinical diagnosis, it can get the hemoglobin concentration through the variation of optical intensity.MethodsFirstly, the prefrontal brain networks were constructed based on oxy-Hb signals from 52-channel fNIRS data of schizophrenia and healthy controls. Then, Complex Brain Network Analysis (CBNA) was used to extract features from the prefrontal brain networks. Finally, a classier based on Support Vector Machine (SVM) is designed and trained to discriminate schizophrenia from healthy controls. We recruited a sample which contains 34 healthy controls and 42 schizophrenia patients to do the one-back memory task. The hemoglobin response was measured in the prefrontal cortex during the task using a 52-channel fNIRS system.ResultsThe experimental results indicate that the proposed method can achieve a satisfactory classification with the accuracy of 85.5%, 92.8% for schizophrenia samples and 76.5% for healthy controls. Also, our results suggested that fNIRS has the potential capacity to be an effective objective biomarker for the diagnosis of schizophrenia.ConclusionsOur results suggested that, using the appropriate classification method, fNIRS has the potential capacity to be an effective objective biomarker for the diagnosis of schizophrenia.

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