?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Presynaptic+lateral+inhibition+provides+a+better+architecture+for+self-organising+neural+networks&rft.creator=Spratling%2C+Michael&rft.subject=Neural+Nets&rft.subject=Neural+Modelling&rft.description=Unsupervised+learning+is+an+important+property+of+the+brain+and+of+many+artificial+neural+networks.+A+large+variety+of+unsupervised+learning+algorithms+have+been+proposed.+This+paper+takes+a+different+approach+in+considering+the+architecture+of+the+neural+network+rather+than+the+learning+algorithm.+It+is+shown+that+a+self-organising+neural+network+architecture+using+pre-synaptic+lateral+inhibition+enables+a+single+learning+algorithm+to+find+distributed%2C+local%2C+and+topological+representations+as+appropriate+to+the+structure+of+the+input+data+received.+It+is+argued+that+such+an+architecture+not+only+has+computational+advantages+but+is+a+better+model+of+cortical+self-organisation.&rft.date=1999&rft.type=Journal+(Paginated)&rft.type=PeerReviewed&rft.format=application%2Fpostscript&rft.identifier=http%3A%2F%2Fcogprints.org%2F1108%2F2%2Ffactopol.ps&rft.identifier=++Spratling%2C+Michael++(1999)+Presynaptic+lateral+inhibition+provides+a+better+architecture+for+self-organising+neural+networks.++%5BJournal+(Paginated)%5D+++++&rft.relation=http%3A%2F%2Fcogprints.org%2F1108%2F