IEEE transactions on neural networks and learning systems
Apr 11, 2019
Memristors can be employed to mimic biological neural synapses or to describe electromagnetic induction effects. To exhibit the threshold effect of electromagnetic induction, this paper presents a threshold flux-controlled memristor and examines its ...
IEEE transactions on neural networks and learning systems
Apr 11, 2019
The pulse-coupled neural network (PCNN) model is a third-generation artificial neural network without training that uses the synchronous pulse bursts of neurons to process digital images, but the lack of in-depth theoretical research limits its exten...
IEEE transactions on neural networks and learning systems
Apr 11, 2019
We trained two spiking neural networks (SNNs), the cortical spiking network (CSN) and the cortical neuron-astrocyte network (CNAN), using a spike-based unsupervised method, on the MNIST and alpha-digit data sets and achieve an accuracy of 96.1% and 7...
Proceedings of the National Academy of Sciences of the United States of America
Apr 11, 2019
Calcium imaging records large-scale neuronal activity with cellular resolution in vivo. Automated, fast, and reliable active neuron segmentation is a critical step in the analysis workflow of utilizing neuronal signals in real-time behavioral studies...
Patch clamping is the gold standard measurement technique for cell-type characterization in vivo, but it has low throughput, is difficult to scale, and requires highly skilled operation. We developed an autonomous robot that can acquire multiple cons...
Neural networks : the official journal of the International Neural Network Society
Apr 8, 2019
The hippocampal theta rhythm (4-12 Hz) is one of the most important electrophysiological processes in the hippocampus, it participates in cognitive hippocampal functions, such as navigation in space, novelty detection, and declarative memory. We use ...
Neural networks : the official journal of the International Neural Network Society
Apr 8, 2019
Self-locking origami structures are characterized by their piecewise linear constitutive relations between force and deformation, which, in practice, are always completely opaque and unmeasurable: the number of piecewise segments, the positions of no...
Brains perform complex tasks using a fraction of the power that would be required to do the same on a conventional computer. New neuromorphic hardware systems are now becoming widely available that are intended to emulate the more power efficient, hi...
Neural networks : the official journal of the International Neural Network Society
Apr 1, 2019
The supervised learning methods for spiking neurons based on temporal encoding are important foundation for the development of spiking neural networks. During the learning process, the synaptic weights of a spiking neuron are adjusted to make the neu...
Computational intelligence and neuroscience
Apr 1, 2019
This paper proposes an artificial spiking neural network (SNN) sustaining the cognitive abstract process of spatial concept learning, embedded in virtual and real robots. Based on an operant conditioning procedure, the robots learn the relationship o...
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