A Neural Network Model of Tilt Aftereffects

Abstract

RF-LISSOM, a self-organising model of laterally connected orientation maps in the primary visual cortex, was used to study the psychological phenomenon known as the tilt aftereffect. The model allows observation of activation and connection patterns between large numbers of neurons simultaneously, making it possible to relate higher-level phenomena to low-level events, which is difficult to do experimentally. In RF-LISSOM, the same self-organising processes that are responsible for the development of the orientation map and its lateral connections are shown to result in tilt aftereffects over short time scales in the adult. The results give computational support for the idea that direct tilt aftereffects arise from adaptive lateral interactions between feature detectors, as has long been surmised. They also suggest that indirect effects could result from the conservation of synaptic resources during this process. The model thus provides a unified computational explanation of self-organisation and both direct and indirect tilt aftereffects in the primary visual cortex.