A computational framework for optimal control of a self-adjustive neural system with activity-dependent and homeostatic plasticity.
Jiyoung KangJinseok EoDong Myeong LeeHae-Jeong ParkPublished in: NeuroImage (2021)
Keyphrases
- computational framework
- optimal control
- control problems
- computational model
- dynamic programming
- biologically plausible
- biologically inspired
- feedback control
- spike trains
- learning rules
- class of nonlinear systems
- control strategy
- infinite horizon
- neural network
- risk sensitive
- optimal control problems
- network architecture
- tensor voting
- reinforcement learning
- control law
- brownian motion
- lyapunov function
- linear quadratic
- synaptic plasticity
- control method
- feed forward