Abstract
The central nervous system is subject to many different forms of noise, which have fascinated researchers since the beginning of electrophysiological recordings. In cerebral cortex, the largest amplitude noise source is the “synaptic noise,” which is dominant in intracellular recordings in vivo. The consequences of this background activity are a classic theme of modeling studies. In the last 20 years, this field tremendously progressed as the synaptic noise was measured for the first time using quantitative methods. These measurements have allowed computational models not only to be more realistic and closer to the biological data but also to investigate the consequences of synaptic noise in more quantitative terms, measurable in experiments. As a consequence, the “high-conductance state” conferred by this intense activity in vivo could also be replicated in neurons maintained in vitro using dynamic-clamp techniques. In addition, mathematical approaches of stochastic systems provided new methods to analyze synaptic noise and obtain critical information such as the optimal conductance patterns leading to spike discharges. It is only through such a combination of different disciplines, such as experiments, computational models, and theory, that we will be able to understand how noise participates to neural computations.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Barrett JN (1975) Motoneuron dendrites: role in synaptic integration. Fed Proc 34:1398–1407
Barrett JN, Crill WE (1974) Influence of dendritic location and membrane properties on the effectiveness of synapses on cat motoneurones. J Physiol 293:325–345
Bernander O, Douglas RJ, Martin KA, Koch C (1991) Synaptic background activity influences spatiotemporal integration in single pyramidal cells. Proc Natl Acad Sci USA 88:11569–11573
Borg-Graham LJ, Monier C, Frégnac Y (1998) Visual input evokes transient and strong shunting inhibition in visual cortical neurons. Nature 393:369–373
Bryant HL, Segundo JP (1976) Spike initiation by transmembrane current: a white-noise analysis. J Physiol 260:279–314
Chance FS, Abbott LF, Reyes AD (2002) Gain modulation from background synaptic input. Neuron 35:773–782
Contreras D, Timofeev I, Steriade M (1996) Mechanisms of long lasting hyperpolarizations underlying slow sleep oscillations in cat corticothalamic networks. J Physiol 494:251–264
De Schutter E, Bower JM (1994) Simulated responses of cerebellar Purkinje cells are independent of the dendritic location of granule cell synaptic inputs. Proc Natl Acad Sci USA 91:4736–4740
Destexhe A (2007) High-conductance state. Scholarpedia 2:1341. http://www.scholarpedia.org/article/High-Conductance State
Destexhe A, Bal T (eds) (2009) The dynamic-clamp: from principles to applications. Springer, New York
Destexhe A, Paré D (1999) Impact of network activity on the integrative properties of neocortical pyramidal neurons in vivo. J Neurophysiol 81:1531–1547
Destexhe A, Rudolph M (2004) Extracting information from the power spectrum of synaptic noise. J Comput Neurosci 17:327–345
Destexhe A, Rudolph M (2012) Neuronal noise. Springer, New York
Destexhe A, Contreras D, Steriade M (1999) Spatiotemporal analysis of local field potentials and unit discharges in cat cerebral cortex during natural wake and sleep states. J Neurosci 19:4595–4608
Destexhe A, Rudolph M, Fellous J-M, Sejnowski TJ (2001) Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons. Neuroscience 107:13–24
Destexhe A, Mand R, Paré D (2003) The high-conductance state of neocortical neurons in vivo. Nat Rev Neurosci 4:739–751
El Boustani S, Pospischil M, Rudolph-Lilith Mand Destexhe A (2007) Activated cortical states: experiments, analyses and models. J Physiol Paris 101:99–109
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. Neuroscience 122:811–829
Gammaitoni L, Hanggi P, Jung P, Marchesoni F (1998) Stochastic resonance. Rev Mod Phys 70:223–287
Greenhill SD, Jones RS (2007) Simultaneous estimation of global background synaptic inhibition and excitation from membrane potential fluctuations in layer III neurons of the rat entorhinal cortex in vitro. Neuroscience 147:884–892
Haider B, McCormick DA (2009) Rapid neocortical dynamics: cellular and network mechanisms. Neuron 62:171–189
Haider B, Duque A, Hasenstaub AR, McCormick DA (2006) Neocortical network activity in vivo is generated through a dynamic balance of excitation and inhibition. J Neurosci 26:4535–4545
Higgs MH, Slee SJ, Spain WJ (2006) Diversity of gain modulation by noise in neocortical neurons: regulation by the slow after-hyperpolarization conductance. J Neurosci 26:8787–8799
Hirsch JA, Alonso JM, Reid RC, Martinez LM (1998) Synaptic integration in striate cortical simple cells. J Neurosci 18:9517–9528
Hô N, Destexhe A (2000) Synaptic background activity enhances the responsiveness of neocortical pyramidal neurons. J Neurophysiol 84:1488–1496
Ho EC, Zhang L, Skinner FK (2009) Inhibition dominates in shaping spontaneous CA3 hippocampal network activities in vitro. Hippocampus 19:152–165
Holmes WR, Woody CD (1989) Effects of uniform and non-uniform synaptic “activation-distributions” on the cable properties of modeled cortical pyramidal neurons. Brain Res 505:12–22
Lindner B, Longtin A (2006) Comment on “Characterization of subthreshold voltage fluctuations in neuronal membranes”, by M. Rudolph and A. Destexhe. Neural Comput 18:1896–1931
Llinas RR, Jahnsen H (1982) Electrophysiology of thalamic neurones in vitro. Nature 297:406–408
Mitchell SJ, Silver RA (2003) Shunting inhibition modulates neuronal gain during synaptic excitation. Neuron 38:433–445
Monier C, Chavane F, Baudot P, Graham LJ, Frégnac Y (2003) Orientation and direction selectivity of synaptic inputs in visual cortical neurons: a diversity of combinations produces spike tuning. Neuron 37:663–680
Monier C, Fournier J, Frégnac Y (2008) In vitro and in vivo measures of evoked excitatory and inhibitory conductance dynamics in sensory cortices. J Neurosci Methods 169:323–365
Paré D, Shink E, Gaudreau H, Destexhe A, Lang EJ (1998) Impact of spontaneous synaptic activity on the resting properties of cat neocortical neurons in vivo. J Neurophysiol 79:1450–1460
Piwkowska Z, Pospischil M, Brette R, Sliwa J, Rudolph-Lilith M, Bal T, Destexhe A (2008) Characterizing synaptic conductance fluctuations in cortical neurons and their influence on spike generation. J Neurosci Methods 169:302–322
Pospischil M, Piwkowska Z, Rudolph M, Bal T, Destexhe A (2007) Calculating event-triggered average synaptic conductances from the membrane potential. J Neurophysiol 97:2544–2552
Prescott SA, De Koninck Y (2003) Gain control of firing rate by shunting inhibition: roles of synaptic noise and dendritic saturation. Proc Natl Acad Sci USA 100:2076–2081
Rapp M, Yarom Y, Segev I (1992) The impact of parallel fiber background activity on the cable properties of cerebellar Purkinje cells. Neural Comput 4:518–533
Richardson MJ (2004) Effects of synaptic conductance on the voltage distribution and firing rate of spiking neurons. Phys Rev E 69:051918
Risken H (1984) The Fokker Planck equation: methods of solution and application. Springer, Berlin
Robinson HP, Kawai N (1993) Injection of digitally synthesized synaptic conductance transients to measure the integrative properties of neurons. J Neurosci Methods 49:157–165
Rudolph M, Destexhe A (2001) Correlation detection and resonance in neural systems with distributed noise sources. Phys Rev Lett 86:3662–3665
Rudolph M, Destexhe A (2003a) Characterization of subthreshold voltage fluctuations in neuronal membranes. Neural Comput 15:2577–2618
Rudolph M, Destexhe A (2003b) A fast-conducting, stochastic integrative mode for neocortical dendrites in vivo. J Neurosci 23:2466–2476
Rudolph M, Destexhe A (2005) An extended analytic expression for the membrane potential distribution of conductance-based synaptic noise. Neural Comput 17:2301–2315
Rudolph M, Destexhe A (2006) On the use of analytic expressions for the voltage distribution to analyze intracellular recordings. Neural Comput 18:917–922
Rudolph M, Piwkowska Z, Badoual M, Bal T, Destexhe A (2004) A method to estimate synaptic conductances from membrane potential fluctuations. J Neurophysiol 91:2884–2896
Rudolph M, Pelletier J-G, Paré D, Destexhe A (2005) Characterization of synaptic conductances and integrative properties during electrically-induced EEG-activated states in neocortical neurons in vivo. J Neurophysiol 94:2805–2821
Rudolph M, Pospischil M, Timofeev I, Destexhe A (2007) Inhibition determines membrane potential dynamics and controls action potential generation in awake and sleeping cat cortex. J Neurosci 27:5280–5290
Sharp AA, O’Neil MB, Abbott LF, Marder E (1993) The dynamic clamp: artificial conductances in biological neurons. Trends Neurosci 16:389–394
Shu Y, Hasenstaub A, Badoual M, Bal T, McCormick DA (2003) Barrages of synaptic activity control the gain and sensitivity of cortical neurons. J Neurosci 23:10388–10401
Softky W (1994) Sub-millisecond coincidence detection in active dendritic trees. Neuroscience 58:13–41
Steriade M (2003) Neuronal substrates of sleep and epilepsy. Cambridge University Press, Cambridge, UK
Steriade M, Timofeev I, Grenier F (2001) Natural waking and sleep states: a view from inside neocortical neurons. J Neurophysiol 85:1969–1985
Tuckwell HC (1988) Introduction to theoretical neurobiology. Cambridge University Press, Cambridge, UK
Wehr M, Zador AM (2003) Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex. Nature 426:442–446
Wiesenfeld K, Moss F (1995) Stochastic resonance and the benefits of noise: from ice ages to crayfish and SQUIDs. Nature 373:33–36
Wilent W, Contreras D (2005) Dynamics of excitation and inhibition underlying stimulus selectivity in rat somatosensory cortex. Nat Neurosci 8:1364–1370
Wolfart J, Debay D, Le Masson G, Destexhe A, Bal T (2005) Synaptic background activity controls spike transfer from thalamus to cortex. Nat Neurosci 8:1760–1767
Acknowledgments
The experimental data shown here were obtained in collaboration with Thierry Bal, Diego Contreras, Jean-Marc Fellous, Denis Paré, Zuzanna Piwkowska, Mircea Steriade and Igor Timofeev. The models and analyses were done in collaboration with Sami El Boustani, Martin Pospischil, Michelle Rudolph and Terrence Sejnowski. Research supported by the CNRS, ANR (HR-CORTEX project), HFSP and the European Community (FACETS project FP6-15879; BrainScales project FP7-269921).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this chapter
Cite this chapter
Destexhe, A. (2013). 20 Years of “Noise”: Contributions of Computational Neuroscience to the Exploration of the Effect of Background Activity on Central Neurons. In: Bower, J. (eds) 20 Years of Computational Neuroscience. Springer Series in Computational Neuroscience, vol 9. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-1424-7_8
Download citation
DOI: https://doi.org/10.1007/978-1-4614-1424-7_8
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-1423-0
Online ISBN: 978-1-4614-1424-7
eBook Packages: Biomedical and Life SciencesBiomedical and Life Sciences (R0)