Balanced Excitation and Inhibition are Required for High-Capacity, Noise-Robust Neuronal Selectivity

3 May 2017

Papers citing "Balanced Excitation and Inhibition are Required for High-Capacity, Noise-Robust Neuronal Selectivity"

9 / 9 papers shown

Title
Brain-Model Evaluations Need the NeuroAI Turing Test Jenelle Feather Meenakshi Khosla N. Apurva Ratan Murty Aran Nayebi 158 6 0 22 Feb 2025
A theory of learning with constrained weight-distribution Weishun Zhong Ben Sorscher Daniel D. Lee H. Sompolinsky 43 2 0 14 Jun 2022
Emergent organization of receptive fields in networks of excitatory and inhibitory neurons Leon Lufkin Ashish Puri Ganlin Song Xinyi Zhong John D. Lafferty 47 1 0 26 May 2022
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? M. Farrell Blake Bordelon Shubhendu Trivedi Cengiz Pehlevan 64 5 0 14 Oct 2021
BackEISNN: A Deep Spiking Neural Network with Adaptive Self-Feedback and Balanced Excitatory-Inhibitory Neurons Dongcheng Zhao Yi Zeng Yang Li 75 43 0 27 May 2021
Optimal Learning with Excitatory and Inhibitory synapses Alessandro Ingrosso 49 5 0 25 May 2020
R-FORCE: Robust Learning for Random Recurrent Neural Networks Yang Zheng Eli Shlizerman OOD 41 5 0 25 Mar 2020
Training dynamically balanced excitatory-inhibitory networks Alessandro Ingrosso L. F. Abbott 50 39 0 29 Dec 2018
Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions Alekh Agarwal S. Negahban Martin J. Wainwright 250 433 0 23 Feb 2011