Year: 2001
Type: conference-paper
Abstract: The brain must be capable of achieving extraordinarily precise sub-millisecond timing with imprecise neural hardware.We discuss how this might be possible using synfire chains (Abeles, 1991) and present a synfire chain learning algorithm for a sparsely-distributed network of spiking neurons (Sougné, 1999).Surprisingly, we show that this learning is not subject to catastrophic interference, a problem that plagues many standard connectionist networks.We show that the forgetting of synfire chains in this type of network closely resembles the classic forgetting pattern described by Barnes & Underwood (1959).
Authors: Jacques Sougné, Robert M. French
Institution: University of Liège
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W1541092645