Decoding a temporal population code

Neural Computation

Volumn 16, Issue 10, 2004, Pages 2079-2100

  Knüsel, Philipp ^a   Wyss, Reto ^a   König, Peter ^a   Verschure, Paul F M J ^a  

^a Institute of Neuroinformatics Zurich   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIAL; ANIMAL; ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; CLASSIFICATION; COMPARATIVE STUDY; CYTOLOGY; HUMAN; NERVE CELL; NERVE CELL INHIBITION; NERVE TRACT; PHOTOSTIMULATION; PHYSIOLOGY; SYNAPSE; SYNAPTIC TRANSMISSION; VISUAL CORTEX;

ACTION POTENTIALS; ANIMALS; HUMANS; MODELS, NEUROLOGICAL; NEURAL INHIBITION; NEURAL NETWORKS (COMPUTER); NEURAL PATHWAYS; NEURONS; PHOTIC STIMULATION; SYNAPSES; SYNAPTIC TRANSMISSION; VISUAL CORTEX;

EID: 4344588320     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/0899766041732459     Document Type: Article

References (19)

1. Auer, P., Burgsteiner, H., & Maass, W. (2001). The p-delta learning rule for parallel perceptions. Manuscript submitted for publication.
2. Buonomano, D. (2000). Decoding temporal information: A model based on short-term synaptic plasticity. Journal of Neuroscience, 20(3), 1129-1141.
3. Buonomano, D., & Merzenich, M. (1995). Temporal information transformed into a spatial code by a neural network with realistic properties. Science, 267, 1028-1030.
4. Heinbockel, T., Christensen, T., & Hildebrand, J. (1999). Temporal tuning of odor responses in pheromone-responsive projection neurons in the brain of the sphinx moth manduca sexta. Journal of Comparative Neurology, 409(1), 1-12.
5. Kirkpatrick, S., Gelatt, C., & Vecchi, M. (1983). Optimization by simulated annealing. Science, 220, 671-680.
6. Kolen, J., & Kremer, S. (Eds.). (2001). A field guide to dynamical recurrent networks. New York: IEEE Press.
7. König, P., Engel, A., Rolfsema, P., & Singer, W. (1995). How precise is neuronal synchronization. Neural Computation, 7, 469-485.
8. Legenstein, R. A., Markram, H., & Maass, W. (2003). Input prediction and autonomous movement analysis in recurrent circuits of spiking neurons. Reviews in the Neurosciences, 14(1-2), 5-19.
9. Maass, W., & Markram, H. (2003). Temporal integration in recurrent microcircuits. In M. Arbib (Ed.), The handbook of brain theory and neural networks (2nd ed., pp. 1159-1163). Cambridge, MA: MIT Press.
10. Maass, W., Natschläger, T., & Markram, H. (2002). Real-time computing without stable states: A new framework for neural computation based on perturbations. Neural Computation, 14(11), 2531-2560.
11. Maass, W., Natschläger, T., & Markram, H. (2003). A model for real-time computation in generic neural microcircuits. In S. Becker, S. Thrun, & K. Obermayer (Eds.), Advances in neural information processing systems, 15 (pp. 213-220). Cambridge, MA: MIT Press.
12. Markram, H., Wang, Y., & Tsodyks, M. (1998). Differential signaling via the same axon of neocortical pyramidal neurons. Proceedings of the National Academy of Sciences, USA, 95, 5323-5328.
13. Mozer, M. (1994). Neural net architectures for temporal sequence processing. In A. Weigend & N. Gershenfeld (Eds.), Time series prediction: Forecasting the future and understanding the past (pp. 243-264). Reading, MA: Addison-Wesley.
14. Ramcharan, E., Gnadt, J., & Sherman, S. (2001). The effects of saccadic eye movements on the activity of geniculate relay neurons in the monkey. Visual Neuroscience, 18(2), 253-258.
15. Rieke, F., Warland, D., de Ruyter van Steveninck, R., & Bialek, W. (1997). Spikes - exploring the neural code. Cambridge, MA: MIT Press.
16. Verschure, P. (1991). Chaos-based learning. Complex Systems, 5, 359-370.
17. Wyss, R., König, P., & Verschure, P. (2003). Invariant representations of visual patterns in a temporal population code. Proceedings of the National Academy of Sciences, USA, 100(1), 324-329.
18. Wyss, R., & Verschure, P. (in press). Bounded invariance and the formation of place fields. In S. Thrun, L. Saul, & B. Schölkopf (Eds.), Advances in neural information processing systems. Cambridge, MA: MIT Press.
19. Wyss, R., Verschure, P., & König, P. (2003). On the properties of a temporal population code. Reviews in the Neurosciences, 14(1-2), 21-33.