Journal ArticleDOI
Neural networks with nonlinear synapses and a static noise
TLDR
The theory of neural networks is extended to include a static noise as well as nonlinear updating of synapses by learning, which may modify the energy surface and lead to interesting new computational capabilities in an unsaturated network.Abstract:
The theory of neural networks is extended to include a static noise as well as nonlinear updating of synapses by learning. The noise appears either in the form of spin-glass interactions, which are independent of the learning process, or as a random decaying of synapses. In an unsaturated network, the nonlinear learning algorithms may modify the energy surface and lead to interesting new computational capabilities. Close to saturation, they act as an additional source of a static noise. The effect of the noise on memory storage is calculated.read more
Citations
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Journal ArticleDOI
The Hebbian paradigm reintegrated: Local reverberations as internal representations
TL;DR: Cognitive and neurophysiological predictions are made, many following directly from the language used to describe the activity in the experimental delay period, others from the details of how the model captures the properties of the internal representations.
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Synaptic mechanisms of pattern completion in the hippocampal CA3 network
TL;DR: Real-size modeling indicated that CA3 networks with sparse connectivity, disynaptic motifs, and single-contact connections robustly generated pattern completion, and macro- and microconnectivity contribute to efficient memory storage and retrieval in hippocampal networks.
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Synaptic pruning in development: a computational account
TL;DR: It is shown that memory performance is maximized if synapses are first overgrown and then pruned following optimal minimal-value deletion, which leads to interesting insights concerning childhood amnesia.
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Neuronal regulation: a mechanism for synaptic pruning during brain maturation
TL;DR: It is proved that neuronal regulation implements near-optimal synaptic modification and maintains the performance of a network undergoing massive synaptic pruning, supporting the possibility that neural regulation complements the action of Hebbian synaptic changes in the self-organization of the developing brain.
Journal ArticleDOI
Notions of associative memory and sparse coding
TL;DR: This paper summarizes associative memory models and sparse representation of memory in these models and discusses the biological plausibility of the discussed associative memories and sparse coding.