Learning recurrent dynamics in spiking networks
Spiking activity of neurons engaged in learning and performing a task show complex spatiotemporal dynamics. While the output of recurrent network models can learn to perform various tasks, the possible range of recurrent dynamics that emerge after learning remains unknown. Here we show that modifyin...
Main Authors: | Christopher M Kim, Carson C Chow |
---|---|
Format: | Article |
Language: | English |
Published: |
eLife Sciences Publications Ltd
2018-09-01
|
Series: | eLife |
Subjects: | |
Online Access: | https://elifesciences.org/articles/37124 |
Similar Items
-
Identifying steady state in the network dynamics of spiking neural networks
by: Vivek Kurien George, et al.
Published: (2023-03-01) -
Volatile Memory Motifs: Minimal Spiking Neural Networks
by: Fabio Schittler Neves, et al.
Published: (2023-01-01) -
DTS-SNN: Spiking Neural Networks With Dynamic Time-Surfaces
by: Donghyung Yoo, et al.
Published: (2022-01-01) -
Equivalence of Additive and Multiplicative Coupling in Spiking Neural Networks
by: Georg Borner, et al.
Published: (2023-01-01) -
An All-MRR-Based Photonic Spiking Neural Network for Spike Sequence Learning
by: Yanan Han, et al.
Published: (2022-02-01)