David D. Vogel

Learn More
Mammalian memory is commonly "explained" in terms of long-term potentiation (LTP) of excitatory synapses. However, depotentiation of inhibitory pathways (disinhibition) is also a known phenomenon in the brain. Artificial neural networks which are offered as partial models of the cerebrum traditionally encode memory by the potentiation of excitatory(More)
I first describe a neural network model of associative memory in a small region of the brain. The model depends, unconventionally, on disinhibition of inhibitory links between excitatory neurons rather than long-term potentiation (LTP) of excitatory projections. The model may be shown to have advantages over traditional neural network models both in terms(More)
This paper provides an analysis of a new class of distributed memories known as R-nets. These networks are similar to Hebbian networks, but are relatively sparsly connected. R-nets use simple binary neurons and trained links between excitatory and inhibitory neurons. They use inhibition to prevent neurons not associated with a recalled pattern from firing.(More)
I first describe a neural network model of associative memory in a small region of the brain. The model depends, unconventionally, on disinhibition of inhibitory links between excitatory neurons rather than long-term potentiation of excitatory projections. The model may be shown to have advantages over traditional neural network models both in terms(More)
  • 1