Simulating prosopagnosia through a lesion of lateral connections in a feed-forward neural network.
We show that particular features of prosopagnosic impairment can be simulated by a connectionist model trained with an unsupervised learning procedure. In particular we describe a Kohonen's neural network which is able to correctly recognize and categorize a series of digitized pictures of faces when learning is characterized by certain parameter values, but which shows a prosopagnosic behavior when lateral connections are lesioned. We discuss the relationship between this result and some neurophysiological hypotheses about prosopagnosia.
Pessa
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Department of Psychology, University of Roma La Sapienza, Italy.
Bandinelli
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PL
Penna
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MP
D003198:Computer Simulation; D005145:Face; D005260:Female; D006801:Humans; D008297:Male; D008959:Models, Neurological; D016571:Neural Networks, Computer; D010364:Pattern Recognition, Visual / Q000502:physiology; D010781:Photography; D020238:Prosopagnosia / Q000503:physiopathology*