A neuromimetic spiking neural network for simulating cortical circuits
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Abstract: In this paper, we present an hardware implementation of spiking neural networks based on analog integrated circuits.
Abstract—In this paper, we present an hardware implementation of spiking neural networks based on analog integrated circuits. These ICs compute in real-time ...
The implementation techniques provide an opportunity to construct large FPGA-based network models to investigate the effect of different neurophysiological ...
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Dec 7, 2011 · In this paper, we present the experimental measurements of our system which mimic the four most prominent biological cells: fast spiking, ...
Dec 7, 2011 · In this paper, we present the experimental measurements of our system which mimic the four most prominent biological cells: fast spiking, ...
Recurrent neural network (RNN) models trained to perform cognitive tasks are a useful computational tool for understanding how cortical circuits execute complex ...
Mar 1, 2023 · Here, we studied the emergent phenomenon of metastability in spiking neural network models that represent cortical local circuits.
Missing: neuromimetic | Show results with:neuromimetic
May 27, 2024 · In this paper, we present the experimental measurements of our system which mimic the four most prominent biological cells: fast spiking, ...
This paper describes an original neural simulation platform designed as a tool for computational neuroscience. The system, based on artificial electronic ...
Jul 24, 2017 · A neuromimetic spiking neural network for simulating cortical circuits. In Information Sciences and Systems. (CISS), 2011 45th Annual ...