Unique features of action potential initiation in cortical neurons

Nature

Volumn 440, Issue 7087, 2006, Pages 1060-1063

  Naundorf, Björn ^a   Wolf, Fred ^a   Volgushev, Maxim ^b,c  

^a UNIVERSITY OF GÖTTINGEN   (Germany)

^b RUHR UNIVERSITY BOCHUM   (Germany)

^c INSTITUTE OF HIGHER NERVOUS ACTIVITY AND NEUROPHYSIOLOGY   (Russian Federation)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; MATHEMATICAL MODELS; SODIUM;

HODGKIN-HUXLEY THEORY; NEURONS; SODIUM CHANNEL;

NEUROLOGY;

SODIUM CHANNEL;

BRAIN; NERVOUS SYSTEM; NEUROLOGY; NUMERICAL MODEL;

ACTION POTENTIAL; ANIMAL CELL; ANIMAL EXPERIMENT; ANIMAL TISSUE; ARTICLE; BIOPHYSICS; BRAIN CELL; BRAIN SLICE; CAT; DYNAMICS; HODGKIN HUXLEY EQUATION; NERVE CELL MEMBRANE POTENTIAL; NONHUMAN; PREDICTION; PRIORITY JOURNAL; PROBABILITY; QUANTITATIVE ANALYSIS; RECEPTOR DENSITY; SPIKE; VISUAL CORTEX;

EID: 33646187200     PISSN: 00280836     EISSN: 14764687     Source Type: Journal    
DOI: 10.1038/nature04610     Document Type: Article

References (18)

1. Bernstein, J. Ueber den zeitlichen Verlauf der negativen Schwankung des Nervenstroms. Pflugers Arch. 1, 173-207 (1868).
2. Huxley, A. F. Nobel Lectures, Physiology or Medicine 1963-1970 (Elsevier, Amsterdam, 1972).
3. Fourcaud-Trocmé, N., Hansel, D., van Vreeswijk, C. & Brunel, N. How spike generation mechanisms determine the neuronal response to fluctuating inputs. J. Neurosci. 23, 11628-11640 (2003).
4. Naundorf, B., Geisel, T. & Wolf, F. Action potential onset dynamics and the response speed of neuronal populations. J. Comput. Neurosci. 18, 297-309 (2005).
5. Destexhe, A. & Paré, D. Impact of network activity on the integrative properties of neocortical pyramidal neurons in vivo. J. Neurophysiol. 81, 1531-1547 (1999).
6. Azouz, R. & Gray, C. M. Dynamic spike threshold reveals a mechanism for synaptic coincidence detection in cortical neurons in vivo. Proc. Natl Acad. Sci. USA 97, 8110-8115 (2000).
7. Volgushev, M., Pernberg, J. & Eysel, U. T. A novel mechanism of response selectivity of neurons in cat visual cortex. J. Physiol. (Lond.) 540, 307-320 (2002).
8. Azouz, R. & Gray, C. M. Adaptive coincidence detection and dynamic gain control in visual cortical neurons in vivo. Neuron 37, 513-532 (2003).
9. Henze, D. A. & Buzsaki, G. Action potential threshold of hippocampal pyramidal cells in vivo is increased by recent spiking activity. Neuroscience 105, 121-130 (2001).
10. Wang, X. J., Liu, Y., Sanchez-Vives, M. V. & McCormick, D. A. Adaptation and temporal decorrelation by single neurons in the primary visual cortex. J. Neurophysiol. 89, 3279-3293 (2003).
11. Schneidman, E., Freedman, B. & Segev, I. Ion channel stochasticity may be critical in determining the reliability and precision of spike timing. Neural Comput. 10, 1679-1703 (1998).
12. + channels. Physiol. Rev. 71, 1047-1080 (1991).
13. + conductances in rat neocortical neurons: appearance of a slowly inactivating component. J. Neurophysiol. 59, 778-795 (1988).
14. Colbert, C. M. & Pan, E. Ion channel properties underlying axonal action potential initiation in pyramidal neurons. Nature Neurosci. 5, 533-538 (2002).
15. Aldrich, R. W., Corey, D. P. & Stevens, C. F. A reinterpretation of mammalian sodium channel gating based on single channel recording. Nature 306, 436-441 (1983).
16. Goldman, L. Stationarity of sodium channel gating kinetics in excised patches from neurobastoma N1E 115. Biophys. J. 69, 2364-2368 (1995).
17. Attwell, D. & Laughlin, S. B. An energy budget for signaling in the grey matter of the brain. J. Cereb. Blood Flow Metab. 21, 1133-1145 (2001).
18. Lennie, P. The cost of cortical computation. Curr. Biol. 13, 493-497 (2003).