A Neural Network Model of Visual Tilt Aftereffects

RF-LISSOM, a self-organizing model of laterally connected orientation maps in the primary visual cortex, was used to study the psychological phenomenon known as the tilt aftereffect. The same self-organizing processes that are responsible for the long-term development of the map and its lateral connections are shown to result in tilt aftereffects over short time scales in
the adult. The model allows observing large numbers of neurons and connections simultaneously, making it possible to relate higher-level phenomena to low-level events, which is difficult to do experimentally. 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-organization and both direct and indirect tilt aftereffects in the primary visual cortex.