Synaptic background noise controls the input/output characteristics of single cells in an in vitro model of in vivo activity

Neuroscience

Volumn 122, Issue 3, 2003, Pages 811-829

  Fellous, J M ^a   Rudolph, M ^b   Destexhe, A ^b   Sejnowski, T J ^a,c  

^a HOWARD HUGHES MEDICAL INSTITUTE   (United States)

^b CNRS   (France)

^c UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

Author keywords

Computational model; Dynamic clamp; Gain; Synapse; Variance detection

Indexed keywords

4 AMINOBUTYRIC ACID; ALPHA AMINO 3 HYDROXY 5 METHYL 4 ISOXAZOLEPROPIONIC ACID; GLUTAMIC ACID;

ANALYTIC METHOD; ANIMAL CELL; ANIMAL EXPERIMENT; ARTICLE; BRAIN NERVE CELL; CELL ACTIVITY; CELL MEMBRANE; CELL MEMBRANE POTENTIAL; CLAMP; CONDUCTANCE; CONTROLLED STUDY; CORRELATION ANALYSIS; DEPOLARIZATION; DYNAMICS; EXCITATION; GABAERGIC SYSTEM; IMPEDANCE; IN VITRO STUDY; IN VIVO STUDY; INHIBITION KINETICS; INJECTION; NEOCORTEX; NOISE REDUCTION; NONHUMAN; PARAMETER; PREFRONTAL CORTEX; PRIORITY JOURNAL; RAT; RECORDING; SIMULATION; STOCHASTIC MODEL; SYNAPSE; SYNAPTIC TRANSMISSION; TECHNIQUE; TIME;

EID: 0142141489     PISSN: 03064522     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neuroscience.2003.08.027     Document Type: Article

References (70)

1. Azouz R., Gray C.M. Cellular mechanisms contributing to response variability of cortical neurons in vivo. J Neurosci. 19:1999;2209-2223.
2. Bair W. Spike timing in the mammalian visual system. Curr Opin Neurobiol. 9:1999;447-453.
3. Barry P.H. JPCalc, a software package for calculating liquid junction potential corrections in patch-clamp, intracellular, epithelial and bilayer measurements and for correcting junction potential measurements. J Neurosci Methods. 51:1994;107-116.
4. Barry P.H., Lynch J.W. Liquid junction potentials and small cell effects in patch-clamp analysis. J Membr Biol. 121:1991;101-117.
5. Bazhenov M., Stopfer M., Rabinovich M., Huerta R., Abarbanel H.D., Sejnowski T.J., Laurent G. Model of transient oscillatory synchronization in the locust antennal lobe. Neuron. 30:2001;553-567.
6. Bernander O., Douglas R.J., Martin K.A., Koch C. Synaptic background activity influences spatiotemporal integration in single pyramidal cells. Proc Natl Acad Sci USA. 88:1991;11569-11573.
7. Borg-Graham L.J., Monier C., Fregnac Y. Visual input evokes transient and strong shunting inhibition in visual cortical neurons. Nature. 393:1998;369-373.
8. Chance F.S., Abbott L.F., Reyes A.D. Gain modulation from background synaptic input. Neuron. 35:2002;773-782.
9. Contreras D., Steriade M. Cellular basis of EEG slow rhythms a study of dynamic corticothalamic relationships . J Neurosci. 15:1995;604-622.
10. Contreras D., Timofeev I., Steriade M. Mechanisms of long-lasting hyperpolarizations underlying slow sleep oscillations in cat corticothalamic networks. J Physiol. 494:1996;251-264.
11. deCharms R.C., Zador A. Neural representation and the cortical code. Annu Rev Neurosci. 23:2000;613-647.
12. DeFelipe J., Fariñas I. The pyramidal neuron of the cerebral cortex morphological and chemical characteristics of the synaptic inputs . Prog Neurobiol. 39:1992;563-607.
13. Destexhe A., Mainen Z.F., Sejnowski T.J. Synthesis of models for excitable membranes, synaptic transmission and neuromodulation using a common kinetic formalism. J Comput Neurosci. 1:1994;195-230.
14. Destexhe A., Paré D. Impact of network activity on the integrative properties of neocortical pyramidal neurons in vivo. J Neurophysiol. 81:1999;1531-1547.
15. Destexhe A., Rudolph M., Fellous J.M., Sejnowski T.J. Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons. Neuroscience. 107:2001;13-24.
16. Destexhe, A, Rudolph, M, Pare, D (2003) The high-conductance state of neocortical neurons in vivo. Nat Rev Neurosci 4:739-751.
17. Fabre-Thorpe M., Delorme A., Marlot C., Thorpe S. A limit to the speed of processing in ultra-rapid visual categorization of novel natural scenes. J Cogn Neurosci. 13:2001;171-180.
18. Fellous J.M., Houweling A.R., Modi R.H., Rao R.P., Tiesinga P.H., Sejnowski T.J. Frequency dependence of spike timing reliability in cortical pyramidal cells and interneurons. J Neurophysiol. 85:2001;1782-1787.
19. Fellous J.-M., Linster C. Computational models of neuromodulation. Neural computation. 10:1998;771-805.
20. Fries P., Reynolds J.H., Rorie A.E., Desimone R. Modulation of oscillatory neuronal synchronization by selective visual attention. Science. 291:2001;1560-1563.
21. Galarreta M., Hestrin S. Spike transmission and synchrony detection in networks of GABAergic interneurons. Science. 292:2001;2295-2299.
22. Gawne T.J., Richmond B.J. How independent are the messages carried by adjacent inferior temporal cortical neurons? J Neurosci. 13:1993;2758-2771.
23. Gillespie D.T. The mathematics of Brownian motion and Johnson noise. Am J Physics. 64:1996;225-240.
24. Hasselmo M.E. Neuromodulation and cortical function modeling the physiological basis of behavior . Behav Brain Res. 67:1995;1-27.
25. Henze D.A., Borhegyi Z., Csicsvari J., Mamiya A., Harris K.D., Buzsaki G. Intracellular features predicted by extracellular recordings in the hippocampus in vivo. J Neurophysiol. 84:2000;390-400.
26. Hines M.L., Carnevale N.T. The NEURON simulation environment. Neural Comput. 9:1997;1179-1209.
27. Hô N., Destexhe A. Synaptic background activity enhances the responsiveness of neocortical pyramidal neurons. J Neurophysiol. 84:2000;1488-1496.
28. Holt G.R., Softky W.R., Koch C., Douglas R.J. Comparison of discharge variability in vitro and in vivo in cat visual cortex neurons. J Neurophysiol. 75:1996;1806-1814.
29. Hughes S.W., Cope D.W., Crunelli V. Dynamic clamp study of Ih modulation of burst firing and delta oscillations in thalamocortical neurons in vitro. Neuroscience. 87:1998;541-550.
30. + conductances in rat neocortical neurons appearance of a slowly inactivating component . J Neurophysiol. 59:1988;778-795.
31. Jaeger D., Bower J.M. Synaptic control of spiking in cerebellar Purkinje cells dynamic current clamp based on model conductances . J Neurosci. 19:1999;6090-6101.
32. Keysers C., Xiao D.K., Foldiak P., Perrett D.I. The speed of sight. J Cogn Neurosci. 13:2001;90-101.
33. Kisley M.A., Gerstein G.L. Trial-to-trial variability and state-dependent modulation of auditory-evoked responses in cortex. J Neurosci. 19:1999;10451-10460.
34. Larkman A.U. Dendritic morphology of pyramidal neurones of the visual cortex of the rat III. Spine distributions . J Comp Neurol. 306:1991;332-343.
35. Levin J.E., Miller J.P. Broadband neural encoding in the cricket cercal sensory system enhanced by stochastic resonance. Nature. 380:1996;165-168.
36. Lewis B.L., O'Donnell P. Ventral tegmental area afferents to the prefrontal cortex maintain membrane potential 'up' states in pyramidal neurons via D(1) dopamine receptors. Cereb Cortex. 10:2000;1168-1175.
37. Longtin A. Stochastic resonance in neuron models. J Stat Physics. 70:1993;309-327.
38. Lytton W.W. Optimizing synaptic conductance calculation for network simulations. Neural Comput. 8:1996;501-509.
39. Mainen Z.F., Sejnowski T.J. Reliability of spike timing in neocortical neurons. Science. 268:1995;1503-1506.
40. McAllister A.K., Stevens C.F. Nonsaturation of AMPA and NMDA receptors at hippocampal synapses. Proc Natl Acad Sci USA. 97:2000;6173-6178.
41. McNamara B., Wiesenfeld K. Theory of stochastic resonance. Phys Rev A. 39:1989;4854-4869.
42. Mel B.W. Information processing in dendritic trees. Neural Comput. 6:1994;1031-1085.
43. Neher E. Voltage offsets in Patch-clamp experiments. Sakmann B., Neher E. Single-channel recording. 1995;147-153 Plenum Press, New York.
44. Nelder J.A., Mead R. A simplex method for function minimization. Comput J. 7:1965;308-313.
45. Paré D., Shink E., Gaudreau H., Destexhe A., Lang E.J. Impact of spontaneous synaptic activity on the resting properties of cat neocortical pyramidal neurons in vivo. J Neurophysiol. 79:1998;1450-1460.
46. Reinagel P., Reid R.C. Precise firing events are conserved across neurons. J Neurosci. 22:2002;6837-6841.
47. Rudolph M., Destexhe A. Correlation detection and resonance in neural systems with distributed noise sources. Phys Rev Lett. 86:2001;3662-3665.
48. Salinas E., Sejnowski T.J. Impact of correlated synaptic input on output firing rate and variability in simple neuronal models. J Neurosci. 20:2000;6193-6209.
49. Salinas E., Sejnowski T.J. Correlated neuronal activity and the flow of neural information. Nat Rev Neurosci. 2:2001;539-550.
50. Sejnowski T.J. On the stochastic dynamics of neuronal interaction. Biol Cybern. 22:1976;203-211.
51. Sejnowski T.J. Skeleton filters in the brain; parallel models of associative memory. 1981;Lawrence Erlbaum Associates, Hillsdale, New Jersey.
52. Servan-Schreiber D., Printz H., Cohen J.D. A network model of catecholamine effects gain, signal-to-noise ratio, and behavior . Science. 249:1990;892-895.
53. Shadlen M.N., Newsome W.T. Noise, neural codes and cortical organization. Curr Opin Neurobiol. 4:1994;569-579.
54. Shadlen M.N., Newsome W.T. The variable discharge of cortical neurons implications for connectivity, computation, and information coding . J Neurosci. 18:1998;3870-3896.
55. Sharp A.A., O'Neil M.B., Abbott L.F., Marder E. Dynamic clamp computer-generated conductances in real neurons . J Neurophysiol. 69:1993;992-995.
56. Softky W.R., Koch C. The highly irregular firing of cortical cells is inconsistent with temporal integration of random EPSPs. J Neurosci. 13:1993;334-350.
57. Stacey W.C., Durand D.M. Stochastic resonance improves signal detection in hippocampal CA1 neurons. J Neurophysiol. 83:2000;1394-1402.
58. Stacey W.C., Durand D.M. Synaptic noise improves detection of subthreshold signals in hippocampal CA1 neurons. J Neurophysiol. 86:2001;1104-1112.
59. Steinmetz P.N., Roy A., Fitzgerald P.J., Hsiao S.S., Johnson K.O., Niebur E. Attention modulates synchronized neuronal firing in primate somatosensory cortex. Nature. 404:2000;187-190.
60. Steriade M., Nunez A., Amzica F. A novel slow (<1 Hz) oscillation of neocortical neurons in vivo depolarizing and hyperpolarizing components . J Neurosci. 13:1993;3252-3265.
61. Svirskis G., Rinzel J. Influence of temporal correlation of synaptic input on the rate and variability of firing in neurons. Biophys J. 79:2000;629-637.
62. Tiesinga P.H., Jose J.V., Sejnowski T.J. Comparison of current-driven and conductance-driven neocortical model neurons with Hodgkin-Huxley voltage-gated channels. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 62:2000;8413-8419.
63. Traub R.D., Miles R. Neuronal networks of the hippocampus. 1991;Cambridge University Press, Cambridge, UK.
64. Troyer T.W., Miller K.D. Physiological gain leads to high ISI variability in a simple model of a cortical regular spiking cell. Neural Comput. 9:1997;971-983.
65. Uhlenbeck G.E., Ornstein L.S. On the theory of Brownian motion. Phys Rev. 36:1930;823-841.
66. Watt A.J., van Rossum M.C., MacLeod K.M., Nelson S.B., Turrigiano G.G. Activity coregulates quantal AMPA and NMDA currents at neocortical synapses. Neuron. 26:2000;659-670.
67. White E.L. Cortical circuits. 1989;Birkhauser, Boston.
68. White J.A., Klink R., Alonso A., Kay A.R. Noise from voltage-gated ion channels may influence neuronal dynamics in the entorhinal cortex. J Neurophysiol. 80:1998;262-269.
69. Zador A. Impact of synaptic unreliability on the information transmitted by spiking neurons. J Neurophysiol. 79:1998;1219-1229.
70. Zador A. Thalamocortical synapses sparse but stentorian . Neuron. 23:1999;198-200.