The role of single neurons in information processing

Nature Neuroscience

Volumn 3, Issue 11s, 2000, Pages 1171-1177

  Koch, Christof ^a   Segev, Idan ^b  

^a CALIFORNIA INSTITUTE OF TECHNOLOGY   (United States)

^b HEBREW UNIVERSITY OF JERUSALEM   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; DENDRITE; INFORMATION PROCESSING; ION CURRENT; MEMBRANE POTENTIAL; MODEL; NERVE CELL; NONLINEAR SYSTEM; PERCEPTION; PERIKARYON; PRIORITY JOURNAL; REVIEW; SYNAPSE;

ACTION POTENTIALS; ANIMALS; CELL MEMBRANE; CELL SIZE; DENDRITES; HUMANS; ION CHANNELS; MODELS, NEUROLOGICAL; NEURONAL PLASTICITY; SYNAPSES;

EID: 0033667243     PISSN: 10976256     EISSN: 15461726     Source Type: Journal    
DOI: 10.1038/81444     Document Type: Article

References (60)

1. McCulloch, W. S. & Pitts, W. A logical calculus of the ideas immanent in nervous activity. Bull. Math. Biophys. 5, 115–133 (1943).
2. Hertz, J., Krogh, A. & Palmer, R.G. Introduction to the Theory of Neural Computation (Addison-Wesley, Redwood City, California, 1991).
3. Chklovskii, D. B. Optimal sizes of dendritic and axonal arbors in a topographic projection. J. Neurophysiol. 83, 2113–2119 (2000).
4. Spencer, W. A. & Kandel, E. R. Electrophysiology of hippocampal neurons: IV. Fast prepotentials. J. Neurophysiol. 24, 272–285 (1961).
5. Yuste, R. & Tank, D. W. Dendritic integration in mammalian neurons, a century after Cajal. Neuron 16, 701–716 (1996).
6. Rall, W. Branching dendritic trees and motoneuron membrane resistivity. Exp. Neurol. 1, 491–527 (1959).
7. Rall, W. in Neural Theory and Modeling (ed. Reiss, R.) 73–97 (Stanford Univ. Press, Stanford, California, 1964).
8. Koch, C., Poggio, T. & Torre, V. Retinal ganglion cells: a functional interpretation of dendritic morphology. Phil. Trans. R. Soc. Lond. B Biol. Sci. 298, 227–263 (1982).
9. Koch, C. & Poggio, T. in Single Neuron Computation (eds. McKenna, T., Davis, J. & Zornetzer, S. F.) 315–345 (Academic, Boston, Massachusetts, 1992).
10. Borg-Graham, L., Monier, C. & Fregnac, Y. Visual input evokes transient and strong shunting inhibition in visual cortical neurons. Nature 393, 369–373 (1998).
11. Taylor, W. R., He, S., Levick, W. R. & Vaney, D. I. Dendritic computation of direction selectivity by retinal ganglion cells. Science 289, 2347–2350 (2000).
12. Konishi, M. The neural algorithm for sound localization in the owl. Harvey Lectures 86, 47–64 (1992).
13. Young, S. R. & Rubel, E. W. Embryogenesis of arborization pattern and topography of individual axons in n. laminaris of the chicken brain-stem. J. Comp. Neurol. 254, 425–459 (1986).
14. Agmon-Snir, H., Carr, C. E. & Rinzel, J. The role of dendrites in auditory coincidence detection. Nature 393, 268–272 (1998).
15. Mainen, Z. F. & Sejnowski, T. J. in Methods in Neuronal Modeling 2nd edn. (eds. Koch, C. & Segev, I.) 171–210 (MIT Press, Cambridge, Massachusetts, 1998).
16. Magee, J. C. in Dendrites (eds. Stuart, G., Spruston, N. & Häusser, M.) 139–160 (Oxford Univ. Press, New York, 1999).
17. Stuart, G. J. & Sakmann, B. Active propagation of somatic action potentials into neocortical pyramidal cell dendrites. Nature 367, 69–72 (1994).
18. Stuart, G., Spruston, N., Sakmann, B. & Häusser, M. Action potential initiation and backpropagation in neurons of the mammalian CNS. Trends Neurosci. 20, 125–131 (1997).
19. Häusser, M., Spruston, N. & Stuart, G. Electrical and chemical signaling in neuronal dendrites. Science (in press).
20. Segev, I. & Rall, W. Excitable dendrites and spines: earlier theoretical insights elucidate recent direct observations. Trends Neurosci. 21, 453–460 (1998).
21. Rall W. in Cellular Mechanisms Subserving Changes in Neuronal Activity (eds. Woody, C. D., Brown, K. A., Crow, T. J. & Knispel, J. D.) 13–21 (Brain Information Service Research Report No. 3, Univ. of California, Los Angeles, 1974).
22. Shepherd, G. M. The dendritic spine: A multifunctional unit. J. Neurophysiol. 75, 2197–2210 (1996).
23. Koch, C. Biophysics of Computation (Oxford Univ. Press, New York, 1999).
24. Svoboda, K., Tank, D. W. & Denk, W. Direct measurement of coupling between dendritic spines and shafts. Science 272, 716–719 (1996).
25. Koch, C. & Zador, A. The function of dendritic spines: Devices subserving biochemical rather than electrical compartmentalization. J. Neurosci. 13, 413–422 (1993).
26. Yuste, R., Majewska, A. & Holthoff, K. From form to function: Calcium compartmentalization in dendritic spines. Nat. Neurosci. 3, 653–659 (2000).
27. Magee, J. C. & Cook, E. P. Somatic EPSP amplitude is independent of synapse location in hippocampal pyramidal neurons. Nat. Neurosci. 3, 895–903 (2000).
28. Shepherd, G. M., Brayton, R. K., Miller, J. P., Segev, I., Rinzel, J. & Rall, W. Signal enhancement in distal cortical dendrites by means of interactions between active dendritic spines. Proc. Natl. Acad. Sci. USA 82, 2192–2195 (1985).
29. Rall, W. & Segev, I. in Synaptic Function (eds. Edelman, G. M., Gall, W. E. & Cowan, W. M.) 605–636 (Wiley, New York, 1987).
30. Schiller, J., Schiller, Y., Stuart, G. & Sakmann, B. Calcium action potentials restricted to distal apical dendrites of rat neocortical pyramidal neurons. J. Physiol. (Lond.) 505, 605–616 (1997).
31. Larkum, M. E., Zhu, J. J. & Sakmann, B. A new cellular mechanism for coupling inputs arriving at different cortical layers. Nature 398, 338–341 (1999).
32. Svoboda, K., Helmchen, F., Denk, W. & Tank, D. W. Spread of dendritic excitation in layer 2/3 pyramidal neurons in rat barrel cortex in vivo. Nat. Neurosci. 2, 65–73 (1999).
33. Markram, H., Lübke, J., Frotscher, M. & Sakmann, B. Regulation of synaptic efficacy by coincidence of postsynaptic APs and EPSPs. Science 275, 213–215 (1997).
34. Bi, G.-Q. & Poo, M.-M. Synaptic modifications in cultured hippocampal neurons: dependence on spike timing, synaptic strength, and postsynaptic cell type. J. Neurosci. 18, 10464–10472 (1998).
35. Debanne, D., Gähwiler, B. H. & Thompson, S. M. Long-term synaptic plasticity between pairs of individual CA3 pyramidal cells in rat hippocampal slice cultures. J. Physiol. (Lond.) 507, 237–247 (1998).
36. Magee, J. C. & Johnston, D. A synaptically controlled, associative signal for Hebbian plasticity in hippocampal neurons. Science. 275, 209–213 (1997).
37. Kistler, W. M. & van Hemmen, J. L. Modeling synaptic plasticity in conjunction with the timing of pre- and postsynaptic action potentials. Neural Comput. 12, 385–405 (2000).
38. Abbott, L. F. & Nelson, S. B. Synaptic plasticity: taming the beast. Nat. Neurosci. 3, 1178–1183 (2000).
39. Segev, I. & Rall, W. Computational study of an excitable dendritic spine. J. Neurophysiol. 60, 499–523 (1988).
40. Softky, W. R. Sub-millisecond coincidence detection in active dendritic trees. Neuroscience 58, 15–41 (1994).
41. Berman, N. J. & Maler, L. Neural architecture of the electrosensory lateral line lobe: adaptations for coincidence detection, a sensory searchlight and frequency-dependent adaptive filtering. J. Exp. Biol. 202, 1243–1253 (1999).
42. Siegel, M., Körding, K. P. & König, P. Integrating top-down and bottom-up sensory processing by somato-dendritic interactions. J. Comput. Neurosci. 8, 161–173 (2000).
43. Salinas, E. & Thier, P. Gain modulation: a major computational principle of the central nervous system. Neuron 27, 15–21 (2000).
44. Mel, B. W. Synaptic integration in an excitable dendritic tree. J. Neurophysiol. 70, 1086–1101 (1993).
45. Mel, B. W. Information processing in dendritic trees. Neural Comput. 6, 1031–1085 (1994).
46. Mel, B. W. in Dendrites (eds. Stuart, G., Spruston, N. & Häusser, M.) 271–289 (Oxford Univ. Press, Oxford, 1999).
47. Mel, B. W., Ruderman, D. L. & Archie, K. A. Translation-invariant orientationtuning in visual “complex” cells could derive from intradendritic computations. J. Neurosci. 18, 4325–4334 (1998).
48. Hubel, D. & Wiesel, T. Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. J. Physiol. (Lond.) 160, 106–154 (1962).
49. Bell, A. J. Self-organization in real neurons: Anti-Hebb in “channel space”. Neural Information Processing Systems 4, 59–67 (1992).
50. LeMasson, W., Marder, E. & Abbott, L. F. Activity-dependent regulation of conductances in model neurons. Science 259, 1915–1917 (1993).
51. Stemmler, M. & Koch, C. How voltage-dependent conductances can adapt to maximize the information encoded by neuronal firing rate. Nat. Neurosci. 2, 521–527 (1999).
52. Laughlin, S. B., van Steveninck, R. R. D. & Anderson, J. C. The metabolic cost of neural information. Nat. Neurosci. 1, 36–41 (1998).
53. Turrigiano, G. G. & Nelson, S. B. Hebb and homestasis in neuronal plasticity. Curr. Opin. Neurobiol 10, 358–364 (2000).
54. Riesenhuber, M. & Poggio, T. Models of object recognition. Nat. Neurosci. 3, 1199–1204 (2000).
55. Segev, I. Sound grounds for computing dendrites. Nature 393, 207–208 (1998).
56. Schlotterer, G. Responses of the locust descending movement detector neuron to rapidly approaching and withdrawing visual stimuli. Can. J. Zool. 55, 1372–1376 (1977).
57. Rowell, C. H. F., O’Shea, M. & Williams, J. L. D. The neuronal basis of a sensory analyser, the acridid movement detector system. IV. The preference for small field stimuli. J. Exp. Biol. 68, 157–185 (1977).
58. Hatsopoulos, N., Gabbiani, F. & Laurent, G. Elementary computation of object approach by a wide field visual neuron. Science 270, 1000–1003 (1995).
59. Gabbiani, F., Krapp, H. G. & Laurent, G. Computation of object approach by a wide-field, motion-sensitive neuron. J. Neurosci. 19, 1122–1141 (1999).
60. Koch, C., Bernander, Ö. & Douglas, R. J. Do neurons have a voltage or a current threshold for action potential initiation. J. Comput. Neurosci. 2, 63–82 (1995).