Fast calculation of short-term depressing synaptic conductances

Neural Computation

Volumn 11, Issue 6, 1999, Pages 1413-1426

  Giugliano, Michele ^a   Bove, Marco ^a   Grattarola, Massimo ^a  

^a Bioelectronics Neuroengineering Grp   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; COMPUTER SIMULATION; PHYSIOLOGY; SYNAPTIC TRANSMISSION; TIME;

ALGORITHMS; COMPUTER SIMULATION; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); SYNAPTIC TRANSMISSION; TIME FACTORS;

EID: 0033566452     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976699300016296     Document Type: Article

References (17)

1. Abbott, L. F., Varela, J. A., Sen, K., & Nelson, S. B. (1997). Synaptic depression and cortical gain control. Science, 275, 220-223.
2. Anderson, C. R., & Stevens, C. F. (1973). Voltage clamp analysis of acetylcholine-produced end-plate current fluctuations at frog neuromuscular junction. J. Physiol. (London), 235, 655-691.
3. Colquhoun, D., Jonas, P., & Sakmann, B. (1992). Action of brief pulses of glutamate on AMPA/KAINATE receptors in patches from different neurons of rate hippocampal slices. J. Physiol. (London), 458, 261-287.
4. Destexhe, A., Mainen, Z. F., & Sejnowski, T. J. (1994a). An efficient method for computing synaptic conductances based on a kinetic model of receptor binding. Neural Comp., 6, 14-18.
5. Destexhe, A., Mainen, Z. F., & Sejnowski, T. J. (1994b). Synaptic transmission and neuromodulation using a common kinetic formalism. J. Comp. Neurosci., 1, 195-230.
6. Hodgkin, A. L., & Huxley, A. F. (1952). A quantitative description of membrane current and its application to conduction and excitation of nerve. J. Physiol. (London), 117, 500-544.
7. Koch, C., & Segev, I. (eds.) (1989). Methods in neuronal modelling: from synapses to networks. Cambridge, MA: MIT Press.
8. Lytton, W. W. (1996). Optimizing synaptic conductance calculation for network simulations. Neural Comp., 8, 501-509.
9. Markram, H., & Tsodyks, M. (1996). Redistribution of synaptic efficacy between neocortical pyramidal neurons. Nature, 382, 807-810,
10. O'Donovan, M. J., & Rinzel, J. (1997). Synaptic depression: A dynamic regulator of synaptic communication with varied functional roles. Trend Neurosci., 20, 431-433.
11. Papoulis, A. (1991). Probability, random variables, and stochastic processes (3rd ed.). New York: McGraw-Hill.
12. Press, W. H., Teukolsky, S. A., Vetterling, W. T., & Flannery B. P. (1996). Numerical recipes in C: The art of scientific computing (2nd ed.). Cambridge: Cambridge University Press.
13. Srinivasan, R., & Chiel, H. J. (1993). Fast calculation of synaptic conductances. Neural Comp., 5, 200-204.
14. Stevens, C. F., & Tsujimoto, T. (1995). Estimates for the pool size of releasable quanta at a single central synapse and for the time required to refill the pool. Proc. Natl. Acad. Sci. USA, 92, 846-849.
15. Thomson, A. M., & Deuchars, J. (1994). Temporal and spatial properties of local circuits in neocortex. Trend Neurosci., 17, 119-126.
16. Tsodyks, M. V., & Markram, H. (1997). The neural code between neocortical pyramidal neurons depends on neurotransmitter release probability. Proc. Natl. Acad. Sci. USA, 94, 719-723.
17. Tsodyks, M., Pawelzik, K., & Markram, H. (1998). Neural networks with dynamic synapses. Neural Comp., 10, 821-835.