Supplementary materials for: A solution to the learning dilemma for recurrent networks of spiking neurons Supplementary Figures Supplementary Tables Supplementary Notes 1 Eligibility traces Results中的“Mathematical basis for e-prop”一节中介绍了资格迹。在这里,我们提供有关资格迹的更多信息。首先,我们讨论作为...
We illustrate key features of an analog, VLSI (aVLSI) chip implementing a network composed of 32 integrate-and-fire (IF) neurons with firing rate adaptation (AHP current), endowed with both a recurrent synaptic connectivity and AER-based connectivity with external, AER-compliant devices. Synaptic...
当前的预测误差将反馈到LSNN和对帧进行预处理的脉冲CNN。(c) 使用基于奖励的e-prop学习后,对LSNN进行样本试验。从上到下:随机动作的概率,未来奖励的预测,随机突触的学习动态(任意单位),240个样本LIF神经元中10个和160个样本ALIF神经元中10个的脉冲活动以及位于上方脉冲栅格底部的两个样本神经元的膜电位。(d) 受...
Recurrently connected networks of spiking neurons underlie the astounding information processing capabilities of the brain. Yet in spite of extensive research, how they can learn through synaptic plasticity to carry out complex network computations
Here, we show that probabilistic planning can be implemented and learned by recurrent networks of spiking neurons such that the generated spike sequences realize mental plans. Recently, it was shown that recurrent spiking networks can implement Bayesian filtering and are able to learn a generative ...
Recurrently connected networks of spiking neurons underlie the astounding information processing capabilities of the brain. Yet in spite of extensive research, how they can learn through synaptic plasticity to carry out complex network computationsremains unclear. We argue that two pieces of this puzzle ...
Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons. The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic f... Buesing,Lars,Bill,... - 《Plos...
论文学习:Sampling-based Bayesian inference in recurrent circuits of stochastic spiking neurons 用户问题 what is the meain points of this paper? chatGPT 这篇文章的主要内容如下: 研究背景: 皮层神经元表现出大的尖峰变异性,且呈现近似泊松分布。 皮层电路中存在大量的递归连接,这两种特性如何结合支持感觉表征...
In recent years, spiking neural networks (SNNs), which originated from the theoretical basis of neuroscience, have attracted neuromorphic computing and brain‐like computing due to their advantages, such as neural dynamics and coding mechanism, which are similar to biological neurons. SNNs have become...
Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons. The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic f... Buesing,Lars,Bill,... - 《Plos...