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Found 6 papers, 2 papers with code
Structure of activity in multiregion recurrent neural networks
To characterize this interaction, we develop a dynamical mean-field theory to analyze such networks in the limit where each region contains infinitely many neurons, with cross-region currents as key order parameters.
Theory of coupled neuronal-synaptic dynamics
In chaotic states with strong Hebbian plasticity, a stable fixed point of neuronal dynamics is destabilized by synaptic dynamics, allowing any neuronal state to be stored as a stable fixed point by halting the plasticity.
Dimension of activity in random neural networks
Neural networks are high-dimensional nonlinear dynamical systems that process information through the coordinated activity of many connected units.
Credit Assignment Through Broadcasting a Global Error Vector
We prove that these weight updates are matched in sign to the gradient, enabling accurate credit assignment.
Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis
Linear dimensionality reduction methods are commonly used to extract low-dimensional structure from high-dimensional data.
Spiking Linear Dynamical Systems on Neuromorphic Hardware for Low-Power Brain-Machine Interfaces
Neuromorphic architectures achieve low-power operation by using many simple spiking neurons in lieu of traditional hardware.
