Visual modelling.
The first purpose of this paper is to present a neural net model of the visual cortex of higher vertebrates based on the electrophysiological properties of the ganglion cells. This model takes Hebb's law [1] as the physiological learning rule for synaptic modification. The model consists of 85 x 85 neurons forming a layer similar to the cortex. The neurones are massively connected via weights that are typically adapted. We simulate several input patterns and show that the model reproduces the pattern recognition, contours pictures and moving perception.
Laboratoire MEDIMAT, Université Pierre et Marie Curie, Paris, France.
S
S
Bezerra
A
A
Caron
Y
Y
Cherruault
D000465:Algorithms; D000818:Animals; D008959:Models, Neurological; D009039:Motion Perception / Q000502:physiology; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D010786:Photoreceptor Cells / Q000502:physiology; D011323:Primates / Q000502:physiology; D012160:Retina / Q000502:physiology; D012165:Retinal Ganglion Cells / Q000502:physiology; D012984:Software; D014785:Vision, Ocular / Q000502:physiology*