A preliminary neural model for movement direction recognition based on biologically plausible plasticity rules

Abstract

In this work we implement a neural architecture for recognizing the direction of movement using neural properties that are consistent with biological findings like intrinsic plasticity and synaptic metaplasticity. The network architecture has two memory layers and two competitive layers. This un-supervised neural network is able to identify the direction of movement of an object, being a promising network for object tracking, hand-written and speech recognition. © Springer-Verlag Berlin Heidelberg 2007.