Shaping embodied neural networks for adaptive goal-directed behavior.

ABSTRACT: The acts of learning and memory are thought to emerge from the modifications of synaptic connections between neurons, as guided by sensory feedback during behavior. However, much is unknown about how such synaptic processes can sculpt and are sculpted by neuronal population dynamics and an interaction with the environment. Here, we embodied a simulated network, inspired by dissociated cortical neuronal cultures, with an artificial animal (an animat) through a sensory-motor loop consisting of structured stimuli, detailed activity metrics incorporating spatial information, and an adaptive training algorithm that takes advantage of spike timing dependent plasticity. By using our design, we demonstrated that the network was capable of learning associations between multiple sensory inputs and m

SUBMITTER: Chao ZC 

PROVIDER: S-EPMC2265558 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature