Mathematical Equivalence of Two Common Forms of Firing Rate Models of Neural Networks

DOI10.1162/NECO_A_00221zbMath1237.92015WikidataQ35613223 ScholiaQ35613223MaRDI QIDQ2885085

Kenneth D. Miller, Francesco Fumarola

Publication date: 21 May 2012

Published in: Neural Computation (Search for Journal in Brave)

Mathematics Subject Classification ID

Neural biology (92C20) Dynamical systems in biology (37N25) General theory for ordinary differential equations (34A99)

Related Items (5)

Codimension-2 parameter space structure of continuous-time recurrent neural networks ⋮ Dynamic branching in a neural network model for probabilistic prediction of sequences ⋮ Some joys and trials of mathematical neuroscience ⋮ Circuit Polarity Effect of Cortical Connectivity, Activity, and Memory ⋮ Integration of Additive Self-Motion Inputs in a General Bump Attractor Model

Cites Work

• Unnamed Item
• Mathematical foundations of neuroscience
• Minimal Models of Adapted Neuronal Response to In Vivo–Like Input Currents
• Parameter Space Structure of Continuous-Time Recurrent Neural Networks
• Spiking Neuron Models
• Rate Models for Conductance-Based Cortical Neuronal Networks

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