External activity and the freedom to recode

Neurocomputing

Volumn 69, Issue 10-12, 2006, Pages 1233-1237

  B Levy, William ^a   Wu, Xiangbao ^a  

^a UNIVERSITY OF VIRGINIA HEALTH SYSTEM   (United States)

Author keywords

Hippocampus; Learning; Transitive inference

Indexed keywords

COMPUTER SIMULATION; MATHEMATICAL MODELS; OPTIMIZATION; RANDOM PROCESSES;

EXTERNAL EXCITATION; HIPPOCAMPUS; OPTIMAL RANGE; RANDOMIZATION; TRANSITIVE INFERENCE;

LEARNING SYSTEMS;

ARTICLE; BRAIN FUNCTION; COMPUTER MODEL; COMPUTER SIMULATION; EXCITATION; HIPPOCAMPUS; LEARNING; PRIORITY JOURNAL; RANDOMIZATION; SYNAPTIC TRANSMISSION;

EID: 33748767192     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2005.12.083     Document Type: Article

References (21)

1. Alvarado M.C., and Rudy J.W. Some properties of configural learning: an investigation of the transverse-patterning problem. J. Exp. Psychol. 18 (1992) 145-153
2. August D.A., and B Levy W. Temporal sequence compression by an integrate-and-fire model of hippocampal area CA3. J. Comp. Neurosci. 6 (1999) 71-90
3. Dusek J.A., and Eichenbaum H. The hippocampus and memory for orderly stimulus relations. Proc. Natl. Acad. Sci. USA 94 (1997) 7109-7114
4. B Levy W. A computational approach to hippocampal function. In: Hawkins R.D., and Bower G.H. (Eds). Computational Models of Learning in Simple Neural Systems (1989), Academic Press, New York 243-305
5. B Levy W. A sequence predicting CA3 is a flexible associator that learns and uses context to solve hippocampal-like tasks. Hippocampus 6 (1996) 579-590
6. B Levy W., Hocking A.B., and Wu X.B. Interpreting hippocampal function as recoding and forecasting. Neural Networks 18 (2005) 1242-1264
7. B Levy W., and Sederberg P.B. A neural network model of hippocampally mediated trace conditioning. IEEE Int. Conf. Neural Networks (1997) I-372-I-376
8. B Levy W., and Steward O. Synapses as associative memory elements in the hippocampal formation. Brain Res. 175 (1979) 233-245
9. B Levy W., and Steward O. Temporal contiguity requirements for long-term associative potentiation/depression in the hippocampus. Neuroscience 8 (1983) 791-797
10. Lorente de Nó R. Studies of the structure of the cerebral cortex. II. Continuation of the study of the ammonic system,. J. Psychol. Neurol. 46 (1934) 113-177
11. Minai A.A., and B Levy W. Setting the activity level in sparse random networks. Neural Comput. 6 (1994) 85-99
12. K.E. Mitman, P.A. Laurent, W. B Levy, Defining in a minimal hippocampal CA3 model by matching time-span of associative synaptic modification and input pattern duration, Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2003, pp. 1631-1636.
13. Polyn S., Wu X.B., and B Levy W. Entorhinal/dentate excitation of CA3: a critical variable in hippocampal models. Neurocomputing 32-33 (2000) 493-499
14. Rodriguez P., and B Levy W. A model of hippocampal activity in trace conditioning: where's the trace? Behav. Neurosci. 115 (2001) 1224-1238
15. Shon A.P., Wu X.B., and B Levy W. Using computational simulations to discover optimal training paradigms. Neurocomputing 32-33 (2000) 995-1002
16. Shon A.P., Wu X.B., Sullivan D., and B Levy W. Initial state randomness improves sequence learning in a model hippocampal network. Phys. Rev. E 65 (2002) 031914-1-031914-15
17. Smith A.C., Wu X.B., and B Levy W. Controlling activity fluctuations in large, sparsely connected random networks. Network 11 (2000) 63-81
18. D.W. Sullivan, W. B Levy, Synaptic modification of interneuron afferents in a hippocampal CA3 model prevents activity oscillations, Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2003, pp. 1625-1630.
19. Sullivan D.W., and B Levy W. Quantal synaptic failures enhance performance in a minimal hippocampal model. Network 15 (2004) 45-67
20. Wu X.B., and B Levy W. Enhancing the performance of a hippocampal model by increasing variability early in learning. Neurocomputing 26-27 (1999) 601-607
21. X.B. Wu, W. B Levy, Decision functions that can support a hippocampal model, Neurocomputing, this issue, doi:10.1016/j.neucom.2005.12.084.