In this paper we compare three different spectral estimation techniques for the classification of mental tasks. These techniques are the standard periodogram, the Welch periodogram and the Burg method, applied to electroencephalographic (EEG) signals. For each one of these methods we compute two parameters: the mean power and the root mean square (RMS), in various frequency bands. The classification of the mental tasks was conducted with a linear discriminate analysis. The Welch periodogram and the Burg method performed better than the standard periodogram. The use of the RMS allows better classification accuracy than the obtained with the power of EEG signals.
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http://dx.doi.org/10.1109/IEMBS.2008.4649366 | DOI Listing |
Psychol Trauma
January 2025
Research Centre for Stress Trauma and Related Conditions, School of Psychology, Queen's University Belfast.
Objective: Posttraumatic stress disorder (PTSD) and more complex posttraumatic symptomatology (i.e., dissociative PTSD [D-PTSD] and complex PTSD [CPTSD]) are differently described in the (5th ed.
View Article and Find Full Text PDFFront Aging Neurosci
January 2025
Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Purpose: Functional near-infrared spectroscopy (fNIRS) has shown feasibility in evaluating cognitive function and brain functional connectivity (FC). Therefore, this fNIRS study aimed to develop a screening method for subjective cognitive decline (SCD) and mild cognitive impairment (MCI) based on resting-state prefrontal FC and neuropsychological tests via machine learning.
Methods: Functional connectivity data measured by fNIRS were collected from 55 normal controls (NCs), 80 SCD individuals, and 111 MCI individuals.
BMC Microbiol
January 2025
Department of Neurology, Yongchuan Hospital of Chongqing Medical University, Chongqing, China.
Background: Depression is a common mental disorder accompanied by gut microbiota dysbiosis, which disturbs the metabolism of the host. While diurnal oscillation of the intestinal microbiota is involved in regulating host metabolism, the characteristics of the intestinal microbial circadian rhythm in depression remain unknown. Our aim was to investigate the microbial circadian oscillation signature and related metabolic pathways in a mouse model with depression-like behaviours.
View Article and Find Full Text PDFNat Commun
January 2025
Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology-Hellas, Heraklion, Crete, Greece.
Artificial neural networks (ANNs) are at the core of most Deep Learning (DL) algorithms that successfully tackle complex problems like image recognition, autonomous driving, and natural language processing. However, unlike biological brains who tackle similar problems in a very efficient manner, DL algorithms require a large number of trainable parameters, making them energy-intensive and prone to overfitting. Here, we show that a new ANN architecture that incorporates the structured connectivity and restricted sampling properties of biological dendrites counteracts these limitations.
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