ArticleFrontiers in neuroinformatics2020
Classification of Schizophrenia by Functional Connectivity Strength Using Functional Near Infrared Spectroscopy.
Article in Frontiers in neuroinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The most fundamental and popular literature on functional near-infrared spectroscopy: a bibliometric analysis of the top 100 most cited articles.Frontiers in neurology · 2024Pooled it
- Cortical activation and functional connectivity during dual-task walking under different cognitive loads: an fNIRS study.Frontiers in human neuroscience · 2026Article
- Sensory integration deficits in Parkinson's disease with freezing of gait: cortical network dynamics and paradoxical dopaminergic modulation.Journal of neurology · 2025Article
- An alternating breathing pattern significantly affects the brain functional connectivity and mood states.Frontiers in human neuroscience · 2025Article
- Functional near-infrared spectroscopy as a diagnostic aid for stable schizophrenia.Frontiers in psychiatry · 2025Article
- The impact of interactive motor-cognitive dual tasking on brain activation, functional connectivity, and behavioral performance in healthy adults: an fNIRS study.Frontiers in human neuroscience · 2025Article
- Degeneracy and disordered brain networks in psychiatric patients using multivariate structural covariance analyzes.Frontiers in psychiatry · 2023Article
- Differentiating people with schizophrenia from healthy controls in a developing Country: An evaluation of portable functional near infrared spectroscopy (fNIRS) as an adjunct diagnostic tool.Frontiers in psychiatry · 2023Article
- Increased both cortical activation and functional connectivity after transcranial direct current stimulation in patients with post-stroke: A functional near-infrared spectroscopy study.Frontiers in psychiatry · 2022Article
- Optimizing functional near-infrared spectroscopy (fNIRS) channels for schizophrenic identification during a verbal fluency task using metaheuristic algorithms.Frontiers in psychiatry · 2022Article
- Altered Interhemispheric Functional Connectivity Associated With Early Verbal Fluency Decline After Deep Brain Stimulation in Parkinson's Disease.Frontiers in aging neuroscience · 2022Article
- fNIRS-derived neurocognitive ratio as a biomarker for neuropsychiatric diseases.Neurophotonics · 2021Article
- Deep Neural Network to Differentiate Brain Activity Between Patients With First-Episode Schizophrenia and Healthy Individuals: A Multi-Channel Near Infrared Spectroscopy Study.Frontiers in psychiatry · 2021Article
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Functional near-infrared spectroscopy (fNIRS) has been widely employed in the objective diagnosis of patients with schizophrenia during a verbal fluency task (VFT). Most of the available methods depended on the time-domain features extracted from the data of single or multiple channels. The present study proposed an alternative method based on the functional connectivity strength (FCS) derived from an individual channel. The data measured 100 patients with schizophrenia and 100 healthy controls, who were used to train the classifiers and to evaluate their performance. Different classifiers were evaluated, and support machine vector achieved the best performance. In order to reduce the dimensional complexity of the feature domain, principal component analysis (PCA) was applied. The classification results by using an individual channel, a combination of several channels, and 52 ensemble channels with and without the dimensional reduced technique were compared. It provided a new approach to identify schizophrenia, improving the objective diagnosis of this mental disorder. FCS from three channels on the medial prefrontal and left ventrolateral prefrontal cortices rendered accuracy as high as 84.67%, sensitivity at 92.00%, and specificity at 70%. The neurophysiological significance of the change at these regions was consistence with the major syndromes of schizophrenia.
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