We consider finite and infinite all-to-all coupled networks of identical theta neurons. Two types of synaptic interactions are investigated: instantaneous and delayed (via first-order synaptic processing). Extensive use is made of the Watanabe/Strogatz (WS) ansatz for reducing the dimension of networks of identical sinusoidally-coupled oscillators. As well as the degeneracy associated with the constants of motion of the WS ansatz, we also find continuous families of solutions for instantaneously coupled neurons, resulting from the reversibility of the reduced model and the form of the synaptic input. We also investigate a number of similar related models. We conclude that the dynamics of networks of all-to-all coupled identical neurons can be surprisingly complicated.
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http://dx.doi.org/10.1186/s13408-018-0059-7 | DOI Listing |
Pain Manag
January 2025
Department of Anesthesiology and Pain Medicine, University of Toronto, Toronto, ON, Canada.
Objectives: To systematically review and conduct a meta-analysis of studies on peripheral magnetic stimulation (PMS) for fibromyalgia (FM) treatment.
Methods: MEDLINE, EMBASE, CENTRAL, CINHAL, Web of Science, and ProQuest databases were searched from inception to July 2023 for studies in adult patients with FM treated with PMS. Studies using transcranial magnetic stimulation were excluded.
Data Brief
February 2025
Department of Computer Science, FEL, Czech Technical University in Prague, Technická 2, Prague 126 627, Czech Republic.
This data article introduces a new network dataset created to help understand how geographical location impacts the quality, type, and amount of incoming network attacks received by honeypots. The dataset consists of 12.4 million network flows collected from nine low-interaction honeypots in nine cities across the world for 65 days, from April 29th to July 1st, 2024.
View Article and Find Full Text PDFWhat we believe is a novel recurrent diffractive deep neural network (RD2NN) is proposed for image time division multiplexing and frequency division multiplexing. The RD2NN is formed by a diffractive deep neural network (D2NN) with its output connected backward to the input. Therefore, it enables the signals to be generated sequentially in the time domain.
View Article and Find Full Text PDFPediatr Neurol
January 2025
Division of Neurology, Department of Pediatrics, Nationwide Children's Hospital, Columbus, Ohio.
Background: Telestroke assessments are widely used to remotely assess adults with suspected stroke, although they have not been studied in children. SPOT, the Study of Performing the PedNIHSS Over Televideo, tested the feasibility of assessing the Pediatric National Institutes of Health Stroke Scale (PedNIHSS) by televideo in children.
Methods: Children aged 2 to 17 years with and without strokes were recruited and examined in the outpatient neurology clinic.
Lymphology
January 2025
Medical Biophysics Department, Medical Research Institute, Alexandria University, Alexandria, Egypt.
Lymphadenopathy is associated with lymph node abnormal size or consistency due to many causes. We employed the deep convolutional neural network ResNet-34 to detect and classify CT images from patients with abdominal lymphadenopathy and healthy controls. We created a single database containing 1400 source CT images for patients with abdominal lymphadenopathy (n = 700) and healthy controls (n = 700).
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