Epstein Secrets

0,000 neurons each. Once one has committed oneself to looking at such groups, the next step is to ask how these groups are organized, which leads to Edelman's concept of "maps." A "map," in Edelman's terminology, is a connected set of groups with the property that when one of the inter-group connection

to Hebbian learning between assemblies has been pursued by Nobelist Gerald Edelman in his theory of neuronal group selection, or "Neural Darwinism." Edelman won a Nobel Prize for his work in immunology, which, like most modern immunology, was based on C. MacFarlane Burnet's theory of "clonal selection"

e our points about glocal knowledge representation in neural net type systems without discussing some aspects of learning in these systems. 13.5.1 Hebbian Learning The most common and plausible assumption about learning in the brain is that synaptic connec- tions between neurons are adapted via some variant of

50,000 neurons each. Once one has committed oneself to looking at such groups, the next step is to ask how these groups are organized, which leads to Edelman’s concept of “maps.” A “map,” in Edelman’s terminology, is a connected set of groups with the property that when one of the inter-group connections

similar transient assemblies when highly activated. The importance of repeated, slightly varied copies of the same subnetwork has been emphasized by Edelman [Ede93] among other neural theorists. 1 The larger an ensemble is, she suggests, the more vivid it is as a conscious experience; an hypothesis that

ake our points about glocal knowledge representation in neural net type systems without discussing some aspects of learning in these systems. 13.5.1 Hebbian Learning The most common and plausible assumption about learning in the brain is that synaptic connec- tions between neurons are adapted via some variant of

r-level behaviors like reasoning or subgoaling. • NOMAD (Neurally Organized Mobile Adaptive Device) automata and its successors [K EMI are based on Edelman's "Neural Darwinism" model of the brain, and feature large numbers of simulated neurons evolving by natural selection into configurations that carry

1 The Hopfield neural net model 256 13.4.2 Knowledge Representation via Cell Assemblies 257 13.5 Neural Foundations of Learning 258 13.5.1 Hebbian Learning 258 13.5.2 Virtual Synapses and Hebbian Learning Between Assemblies 258 13.5.3 Neural Darwinism 259 13.6 Glocal Memory 260 13.6.1 A Semi-Fo

er-level behaviors like reasoning or subgoaling. e NOMAD (Neurally Organized Mobile Adaptive Device) automata and its successors [KE06] are based on Edelman’s “Neural Darwinism” model of the brain, and feature large numbers of simulated neurons evolving by natural selection into configurations that carry

3.4.2 Knowledge Representation via Cell Assemblies .................2.05- 257 13.5 Neural Foundations of Learning ..........0 0.000 ee eee 258 13.5.1 Hebbian Learning............ 0.0.00 eee ete eee 258 13.5.2 Virtual Synapses and Hebbian Learning Between Assemblies .......... 258 35:38 Netital DArwitiiSitt +2; case