Showing 371 to 380 of 1319 articles
Clear Filters
Computers in biology and medicine
Oct 4, 2022
Recent studies have demonstrated the superiority of deep learning in medical image analysis, especially in cell instance segmentation, a fundamental step for many biological studies. However, the excellent performance of the neural networks requires ...
IEEE transactions on pattern analysis and machine intelligence
Oct 4, 2022
Spiking neural networks (SNNs) have shown clear advantages over traditional artificial neural networks (ANNs) for low latency and high computational efficiency, due to their event-driven nature and sparse communication. However, the training of deep ...
Nature communications
Oct 2, 2022
Learning is a fundamental component of creating intelligent machines. Biological intelligence orchestrates synaptic and neuronal learning at multiple time scales to self-organize populations of neurons for solving complex tasks. Inspired by this, we ...
Computational intelligence and neuroscience
Sep 29, 2022
This paper investigates the bifurcation issue of fractional-order four-neuron recurrent neural network with multiple delays. First, the stability and Hopf bifurcation of the system are studied by analyzing the associated characteristic equations. It ...
Journal of mathematical biology
Sep 27, 2022
The activity generated by an ensemble of neurons is affected by various noise sources. It is a well-recognised challenge to understand the effects of noise on the stability of such networks. We demonstrate that the patterns of activity generated by n...
The Journal of physiology
Sep 25, 2022
Due to the staggering complexity of the brain and its neural circuitry, neuroscientists rely on the analysis of mathematical models to elucidate its function. From Hodgkin and Huxley's detailed description of the action potential in 1952 to today, ne...
Sensors (Basel, Switzerland)
Sep 24, 2022
Neuromorphic hardware, the new generation of non-von Neumann computing system, implements spiking neurons and synapses to spiking neural network (SNN)-based applications. The energy-efficient property makes the neuromorphic hardware suitable for powe...
Nature communications
Sep 24, 2022
Computational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes, e.g., perceptrons, with decision-making capabilities and flexible weighted links. Analogously to their r...
Molecules (Basel, Switzerland)
Sep 23, 2022
The classification of biological neuron types and networks poses challenges to the full understanding of the human brain's organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal morpholog...
IEEE transactions on cybernetics
Sep 19, 2022
Most existing studies on computational modeling of neural plasticity have focused on synaptic plasticity. However, regulation of the internal weights in the reservoir based on synaptic plasticity often results in unstable learning dynamics. In this a...