Quantitative study of attractor neural network retrieving at low spike rates: I. Substrate - spikes, rates and neuronal gain

Network: Computation in Neural Systems

Volumn 2, Issue 3, 1991, Pages 259-273

  Amit, Daniel J ^a   Tsodyks, M V ^a  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 36149028967     PISSN: 0954898X     EISSN: None     Source Type: Journal    
DOI: 10.1088/0954-898X_2_3_003     Document Type: Article

References (25)

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3. Attractor neural networks with biological probe neurons
4. Associative memory neural networks with low temporal spiking rates
5. Low firing rates: an effective Hamiltonian for excitatory neurons
6. Oscillations and low firing rates in associative memory neural networks
7. Substantiation of the ‘point approximation’ for describing the total electrical activity of the brain with the use of a simulation model
8. Neurons with graded response have collective computational properties like those of two-state neurons
9. Absolute stability of globa1 pattern formation and parallel memory storage by competitive neural networks
10. Graded-response neurons and information encodings in autoassociative memories
11. Excitatory and inhibitory interactions in localized populatons of model neurons
12. Realistic synaptic inputs for model neural networks
13. Metastable and unstable states in the brain
14. Analysis of the activity of single neurons in stochastic settings
15. Quantitative study of attractor neural networks retrieving at low spike rates II Low rate retrieval in symmetric networks
16. The enhanced storage capacity in neural networks with low activity level
17. Associative memory with high information content
18. Model neurons From Hodgkin-Huxley to Hopfield
19. A quantitative description of membrane current and its application to conductance and excitation in nerve
20. Comparative electrophysiology of pyramidal and sparsely spiny stellate neurons of the neocortex