11 citations · 20 across the 4 of their papers we have counts for
7 papers
Biologically Plausible Variational Policy Gradient with Spiking Recurrent Winner-Take-All Networks
Zhile Yang, Shangqi Guo, Ying Fang +1
One stream of reinforcement learning research is exploring biologically plausible models and algorithms to simulate biological intelligence and fit neuromorphic hardware. Among the…
Towards the Next Generation of Retinal Neuroprosthesis: Visual Computation with Spikes
Zhaofei Yu, Jian K. Liu, Shanshan Jia +4
Neuroprosthesis, as one type of precision medicine device, is aiming for manipulating neuronal signals of the brain in a closed-loop fashion, together with receiving stimulus from…
Coding Capacity of Purkinje Cells with Different Schemes of Morphological Reduction
Lingling An, Yuanhong Tang, Quan Wang +4
The brain as a neuronal system has very complex structure with large diversity of neuronal types. The most basic complexity is seen from the structure of neuronal morphology, which…
Reconstruction of Natural Visual Scenes from Neural Spikes with Deep Neural Networks
Yichen Zhang, Shanshan Jia, Yajing Zheng +5
Neural coding is one of the central questions in systems neuroscience for understanding how the brain processes stimulus from the environment, moreover, it is also a cornerstone fo…
Probabilistic Inference of Binary Markov Random Fields in Spiking Neural Networks through Mean-field Approximation
Yajing Zheng, Shanshan Jia, Zhaofei Yu +3
Recent studies have suggested that the cognitive process of the human brain is realized as probabilistic inference and can be further modeled by probabilistic graphical models like…
Revealing Fine Structures of the Retinal Receptive Field by Deep Learning Networks
Qi Yan, Yajing Zheng, Shanshan Jia +6
Deep convolutional neural networks (CNNs) have demonstrated impressive performance on many visual tasks. Recently, they became useful models for the visual system in neuroscience.…