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| http://dx.doi.org/10.1016/j.jdcr.2020.08.004 | DOI Listing |
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A comparative study of wavelet families for schizophrenia detection.
Front Hum Neurosci
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Department of Electrical Engineering, Mathematics and Science, University of Gävle, Gävle, Sweden.
Schizophrenia (SZ) is a chronic mental disorder, affecting approximately 1% of the global population, it is believed to result from various environmental factors, with psychological factors potentially influencing its onset and progression. Discrete wavelet transform (DWT)-based approaches are effective in SZ detection. In this report, we aim to investigate the effect of wavelet and decomposition levels in SZ detection.
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Department of Nuclear Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China. Electronic address:
The brain is a highly complex and delicate system, and its internal neural processes are manifested as the interweaving and superposition of multi-frequency neural signals. However, traditional brain network studies are often limited to the whole frequency band or a specific frequency band, ignoring the potentially profound impact of the diversity of information within the frequency on the dynamics of brain networks. To comprehensively and deeply analyze this phenomenon, the present study is devoted to exploring the specific performance of brain networks at different frequencies.
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View Article and Find Full Text PDFEffects of pH on the differential absorbance spectra, d-d transition bands and structural properties of copper complexes with humic substances and model compounds.
Chemosphere
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Department of Civil and Environmental Engineering, University of Washington, Box 352700, Seattle, WA, 98195-2700, USA.
Interactions between metal cations, notably Cu(II), and humic substances (HS) affect their mobility, bioavailability, and toxicity. This necessitates a molecular-level determination of the nature of HS functional groups binding Cu(II) (Cu-HS) and effects of pH on them. This study investigates the pH effects on the spectroscopic and structural properties of the complexes of Cu(II) with HS and representative model compounds using differential absorbance spectroscopy (DAS), examination of the properties of the d-d transition band characteristic for Cu(II) ions, and quantum chemical (QC) calculations.
View Article and Find Full Text PDFResting-state EEG microstate features for Alzheimer's disease classification.
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School of Medical Technology and Engineering, Henan University of Science and Technology, Luoyang, China.
Resting-state electroencephalogram (EEG) microstate analysis resolves EEG signals into topographical maps representing discrete, sequential network activations. These maps can be used to identify patterns in EEGs that may be indicative of underlying neurological conditions. One such pattern is observed in EEGs of patients with Alzheimer's disease (AD), where a global microstate disorganization is evident.
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