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Voltage gated sodium channels (VGSCs) are required for action potential initiation and propagation in mammalian neurons. As with other ion channel families, VGSC density varies between neurons. Importantly, sodium current (I) density variability is reduced in pyramidal neurons of Scn1b null mice. Scn1b encodes the VGSC β1/ β1B subunits, which regulate channel expression, trafficking, and voltage dependent properties. Here, we investigate how variable I density in cortical layer 6 and subicular pyramidal neurons affects spike patterning and network synchronization. Constitutive or inducible Scn1b deletion enhances spike timing correlations between pyramidal neurons in response to fluctuating stimuli and impairs spike-triggered average current pattern diversity while preserving spike reliability. Inhibiting I with a low concentration of tetrodotoxin similarly alters patterning without impairing reliability, with modest effects on firing rate. Computational modeling shows that broad I density ranges confer a similarly broad spectrum of spike patterning in response to fluctuating synaptic conductances. Network coupling of neurons with high I density variability displaces the coupling requirements for synchronization and broadens the dynamic range of activity when varying synaptic strength and network topology. Our results show that I heterogeneity between neurons potently regulates spike pattern diversity and network synchronization, expanding VGSC roles in the nervous system.
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http://dx.doi.org/10.1038/s41598-023-36036-0 | DOI Listing |
PLoS One
September 2025
Electrical Engineering Department, Faculty of Engineering, Minia University, Minia, Egypt.
With the increasing demand for wind energy in the electric power generation industry, optimizing robust and efficient control strategies is essential for a wind energy conversion system (WECS). In this regard, this study proposes a novel hybrid control strategy for wind power systems directly coupled to a permanent-magnet synchronous generator (PMSG). The contribution of this work is to propose a control strategy design based on a combination of the nonlinear Backstepping approach for system stabilization according to Lyapunov theory and the application of artificial neural network to maximize energy harvesting regardless of wind speed fluctuations.
View Article and Find Full Text PDFIEEE Trans Neural Netw Learn Syst
September 2025
In multiagent systems, learning optimal behavior policies for individual agents remains a challenging yet crucial task. While recent research has made strides in this area, the issue of when agents should maintain consistent behaviors with one another is still not adequately addressed. This article proposes a novel approach to enable agents to autonomously decide whether their behaviors should align with those of their peers by leveraging intrinsic rewards to optimize their policies.
View Article and Find Full Text PDFChaos
September 2025
Instituto de Física, Universidade Federal de Alagoas, Maceió, Alagoas 57072-970, Brazil.
Neuronal heterogeneity, characterized by a multitude of spiking neuronal patterns, is a widespread phenomenon throughout the nervous system. In particular, the brain exhibits strong variability among inhibitory neurons. Despite the huge neuronal heterogeneity across brain regions, which in principle could decrease synchronization due to differences in intrinsic neuronal properties, cortical areas coherently oscillate during various cognitive tasks.
View Article and Find Full Text PDFFront Neural Circuits
September 2025
Faculty of Science and Engineering, Waseda University, Shinjuku, Tokyo, Japan.
Neuronal networks in animal brains are considered to realize specific filter functions through the precise configuration of synaptic weights, which are autonomously regulated without external supervision. In this study, we employ a single Hodgkin-Huxley-type neuron with autapses as a minimum model to computationally investigate how spike-timing-dependent plasticity (STDP) adjusts synaptic weights through recurrent feedback. The results show that the weights undergo oscillatory potentiation or depression with respect to autaptic delay and high-frequency stimulation.
View Article and Find Full Text PDFMed Phys
September 2025
Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China.
Background: Four-dimensional magnetic resonance imaging (4D-MRI) holds great promise for precise abdominal radiotherapy guidance. However, current 4D-MRI methods are limited by an inherent trade-off between spatial and temporal resolutions, resulting in compromised image quality characterized by low spatial resolution and significant motion artifacts, hindering clinical implementation. Despite recent advancements, existing methods inadequately exploit redundant frame information and struggle to restore structural details from highly undersampled acquisitions.
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