Contributions of the input signal and prior activation history to the discharge behaviour of rat motoneurones

Journal of Physiology

Volumn 562, Issue 3, 2005, Pages 707-724

  Powers, R K ^a   Dai, Y ^a   Bell, B M ^b   Percival, D B ^b   Binder, M D ^a  

^a UNIVERSITY OF WASHINGTON SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION POTENTIAL; AFTERHYPERPOLARIZATION; ANALYTIC METHOD; ANIMAL CELL; ARTICLE; CALCULATION; CELL ACTIVATION; CELL FUNCTION; CONTROLLED STUDY; ELECTRIC CURRENT; FEEDBACK SYSTEM; HYPERPOLARIZATION; HYPOGLOSSAL NERVE; LINEAR SYSTEM; MATHEMATICAL MODEL; MOTONEURON; NERVE CELL MEMBRANE POTENTIAL; NERVE CELL STIMULATION; NOISE; NONHUMAN; PREDICTION; PRIORITY JOURNAL; PROBABILITY; RAT; RECORDING; SIGNAL TRANSDUCTION; SPIKE WAVE; STANDARD; WHITE NOISE; ANIMAL TISSUE; COMPUTER SIMULATION; HYPOGLOSSAL NUCLEUS; MATHEMATICAL PARAMETERS; SPIKE EVOKING CURRENT TRAJECTORY; WIENER KERNELS;

ACTION POTENTIALS; ADAPTATION, PHYSIOLOGICAL; ANIMALS; BRAIN STEM; CELLS, CULTURED; COMPUTER SIMULATION; DIFFERENTIAL THRESHOLD; MODELS, NEUROLOGICAL; MOTOR NEURONS; NEURONAL PLASTICITY; RATS; RATS, SPRAGUE-DAWLEY; SYNAPTIC TRANSMISSION;

EID: 13844255550     PISSN: 00223751     EISSN: None     Source Type: Journal    
DOI: 10.1113/jphysiol.2004.069039     Document Type: Article

References (42)

1. Abeles M (1991). Corticonics: Neural Circuits of the Cerebral Cortex. Cambridge University Press, Cambridge, UK.
2. Aguera y Arcas B & Fairhall AL (2003). What causes a neuron to spike? Neural Comput 15, 1789-1807.
3. Aguera y Arcas B, Fairhall AL & Bialek W (2003). Computation in a single neuron: Hodgkin and Huxley revisited. Neural Comput 15, 1715-1749.
4. Berry MJ & Meister M (1998). Refractoriness and neural precision. J Neurosci 18, 2200-2211.
5. Binder MD, Poliakov A & Powers RK (1999). Functional identification of input-output transforms of mammalian motoneurones. J Physiol (Paris) 93, 29-42.
6. 2+-dependent spiking and plateau potentials under pharmacological treatment. J Neurophysiol 78 3371-3385.
7. Bryant HL & Segundo JP (1976). Spike initiation by transmembrane current: a white-noise analysis. J Physiol 260, 279-314.
8. de Boer E & Kuyper P (1968). Triggered correlation. IEEE Trans Biomed Engr 15, 169-179.
9. Fellous JM, Rudolph M, Destexhe A & Sejnowski TJ (2003). Synaptic background noise controls the input/output characteristics of single cells in an in vitro model of in vivo activity. Neurosci 122, 811-829.
10. Gaumond RP, Molnar CE & Kim DO (1982). Stimulus and recovery dependence of cat cochlear nerve fiber spike discharge probability. J Neurophysiol 48, 856-873.
11. Gutkin B, Ermentrout GB & Rudolph M (2003). Spike generating dynamics and the conditions for spike-time precision in cortical neurons. J Comput Neurosci 15, 91-103.
12. Hunter IW & Korenberg MJ (1986). The identification of nonlinear biological systems: Wiener and Hammerstein cascade models. Biol Cybern 55, 135-144.
13. Joeken S, Schwegler H & Richter CP (1997). Modeling stochastic spike train responses of neurons: an extended Wiener series analysis of pigeon auditory nerve fibers. Biol Cybern 76, 153-162.
14. Keat J, Reinagel P, Reid RC & Meister M (2001). Predicting every spike: a model for the responses of visual neurons. Neuron 30, 803-817.
15. Kistler WM, Gerstner W & Leo van Hemmen J (1997). Reduction of the Hodgkin-Huxley equations to a single-variable threshold model. Neural Computation 9, 1015-1045.
16. Mainen ZF & Sejnowski TJ (1995). Reliability of spike timing in neocortical neurons. Science 268, 1503-1506.
17. Mainen ZF & Sejnowski TJ (1996). Influence of dendritic structure on firing pattern in model neocortical neurons. Nature 382, 363-6.
18. Marmarelis VC, Citron MC & Vivo CP (1986). Minimum-order Wiener modelling of spike-output systems. Biol Cybern 54, 115-123.
19. Matthews PBC (1996). Relationship of firing intervals of human motor units to the trajectory of post-spike after-hyperpolarization and synaptic noise. J Physiol 492, 597-628.
20. Miller MI & Wang J (1993). A new stochastic model for auditory-nerve discharge. J Acoust Soc Am 94, 2093-2107.
21. Paninski L, Pillow JW & Simoncelli EP (2004). Maximum likelihood estimation of a stochastic integrate-and-fire neural encoding model. Neural Comput 16, 2533-61.
22. Pillow J & Simoncelli EP (2003). Biases in white noise analysis due to non-Poisson spike generation. Neurocomputing 52-54, 109-15.
23. Pinsky PF & Rinzel J (1994). Intrinsic and network rhythmogenesis in a reduced Traub model for CA3 neurons. J Comput Neurosci 1, 39-60.
24. Poliakov AV, Powers RK & Binder MD (1997). Functional identification of the input-output transforms of motoneurones in the rat and cat. J Physiol 504, 401-424.
25. Powers RK & Binder MD (2000). Relationship between the time course of the afterhyperpolarization and discharge variability in cat spinal motoneurones. J Physiol 528, 131-150.
26. Press WH, Flannery BP, Teukolsky SA & Vetterling WT (1992). Numerical Recipes: the Art of Scientific Computing, 2nd edn. Cambridge University Press, Cambridge.
27. Rieke F, Warland D, van Steveninck R & Bialek W (1996). Spikes: Exploring the Neural Code. Cambridge, Massachusetts: MIT Press.
28. + currents in neurones: types, physiological roles and modulation. Trends Neurosci 19 150-154.
29. Sawczuk A, Powers RK & Binder MD (1995). Spike frequency adaptation studied in hypoglossal motoneurons of the rat. J Neurophysiol 73, 1799-1810.
30. Sawczuk A, Powers RK & Binder MD (1997). Contribution of outward currents to spike-frequency adaptation in hypoglossal motoneurons of the rat. J Neurophysiol 78, 2246-2253.
31. Schmich RM & Miller MI (1997). Stochastic threshold characterization of the intensity of active channel dynamical action potential generation. J Neurophysiol 78, 2616-2630.
32. Schreiber S, Fellous JM, Tiesinga P & Sejnowski TJ (2004). Influence of ionic conductances on spike timing reliability of cortical neurons for suprathreshold rhythmic inputs. J Neurophysiol 91 194-205.
33. Shadlen MN & Newsome WT (1994). Noise, neural codes and cortical organization. Cur Opin Neurobiol 4, 569-579.
34. Snedecor GW & Cochran WG (1989). Statistical Methods, 8th edn. State University Press, Iowa.
35. Svirskis G, Kotak V, Sanes DH & Rinzel J (2002). Enhancement of signal-to-noise ratio and phase locking for small inputs by a low-threshold outward current in auditory neurons. J Neurosci 22 11019-11025.
36. Svirskis G, Kotak V, Sanes D & Rinzel J (2004). Sodium along with low threshold potassium currents enhance coincidence detection of subthreshold noisy signals in MSO neurons. J Neurophysiol 91, 2465-2473.
37. Svirskis G & Rinzel J (2003). Influence of subthreshold nonlinearities on signal-to-noise ratio and timing precision for small signals in neurons: minimal model analysis. Network 14, 137-150.
38. Viana F, Bayliss DA & Berger AJ (1993). Multiple potassium conductances and their role in action potential repolarization and repetitive firing behavior of neonatal rat hypoglossal motoneurons. J Neurophysiol 69, 2150-2163.
39. Viana F, Bayliss DA & Berger AJ (1994). Postnatal changes in rat hypoglossal motoneuron membrane properties. Neuroscience 59 131-48.
40. Viana F, Bayliss DA & Berger AJ (1995). Repetitive firing properties of developing rat brainstem motoneurones. J Physiol 486, 745-761.
41. Viana F, Gibbs L & Berger AJ (1990). Double- and triple-labeling of functionally characterized central neurons projecting to peripheral targets studied in vitro. Neurosci 38, 829-841.
42. Wetmore DZ & Baker SN (2004). Post-spike distance-to-threshold trajectories of neurones in monkey motor cortex. J Physiol 555, 831-850.