For the analysis of the airflow velocity and oesophageal pressure signals of anaesthetized spontaneously breathing small animals (rats and guinea pigs), a signal processing program package was developed for a multiprocessor system (Electronic Measuring Gears Co., Budapest). 4-10 respiratory cycles were analysed in a signal series and the arithmetic mean value was used to increase the accuracy of the method. Since standardization of the respiratory parameters of small animals has not yet been specified, the normalization of volume values per 100 cm2 body surface is proposed.
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Chaos
January 2025
Beijing Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.
Generally, epilepsy is considered as abnormally enhanced neuronal excitability and synchronization. So far, previous studies on the synchronization of epileptic brain networks mainly focused on the synchronization strength, but the synchronization stability has not yet been explored as deserved. In this paper, we propose a novel idea to construct a hypergraph brain network (HGBN) based on phase synchronization.
View Article and Find Full Text PDFPsychophysiology
January 2025
Department of Psychology, Ben-Gurion University of the Negev, Beer Sheva, Israel.
Cognitive control deficits and increased intra-subject variability have been well established as core characteristics of attention deficit hyperactivity disorder (ADHD), and there is a growing interest in their expression at the neural level. We aimed to study neural variability in ADHD, as reflected in theta inter-trial phase coherence (ITC) during error processing, a process that involves cognitive control. We examined both traditional event-related potential (ERP) measures of error processing (i.
View Article and Find Full Text PDFHeliyon
July 2024
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China.
Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive neuroimaging technique widely utilized in the research of Autism Spectrum Disorder (ASD), providing preliminary insights into the potential biological mechanisms underlying ASD. Deep learning techniques have demonstrated significant potential in the analysis of rs-fMRI. However, accurately distinguishing between healthy control group and ASD has been a longstanding challenge.
View Article and Find Full Text PDFIn this Letter, we propose a high-performance optimized detection scheme based on a neural network (NN) in a receiver digital signal processing (DSP) for bandwidth-limited intensity modulation and direct detection (IM/DD) transmission systems. The NN-based optimized detection scheme consists of two components, an NN-based lookup table (NN-LUT) and an NN-based log-maximum estimation with a fixed number of surviving state (NN-MAP) decoder. The NN-LUT provides more accurate and sufficient information (PI) to the decoder than the conventional filter-form PI without increasing computational complexity.
View Article and Find Full Text PDFA parallel Hilbert transform arctangent phase demodulation (PHT-ATAN) method based on overlapping computation is proposed for phase demodulation of laser heterodyne Doppler vibrometers. The method suppresses the end point effects by utilizing overlapping computation and data concatenation and accelerates phase demodulation through parallel processing. Simulation and experimental results demonstrate that when the algorithm's parallelism is ≥4, the computation speed of this method increases by over 100% compared to traditional methods, while maintaining the signal-to-noise ratio and accuracy of the phase demodulation results.
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