Characterizing neuronal activity by describing the membrane potential as a stochastic process.
Abstract
Cortical neurons behave similarly to stochastic processes, as a consequence of their irregularity and dense connectivity. Their firing pattern is close to a Poisson process, and their membrane potential (V(m)) is analogous to colored noise. One way to characterize this activity is to identify V(m) to a multidimensional stochastic process. We review here this approach and how it can be used to extract important statistical signatures of neuronal activity. The "VmD method" consists of fitting the V(m) distribution obtained intracellularly to analytic expressions derived from stochastic processes, and thereby deduce synaptic conductance parameters. However, this method requires at least two levels of V(m), which prevents applications to single-trial measurements. We also discuss methods that can be applied to single V(m) traces, such as power spectral analysis and the "STA method" to calculate spike-triggered average conductances based on a maximum likelihood procedure. A recently proposed method, the "VmT method", is based on the fusion of these two concepts. This method is analogous to the VmD method and estimates the mean excitatory and inhibitory conductances and their variances. However, it does so by using a maximum-likelihood estimation, and can thus be applied to single V(m) traces. All methods were tested using controlled conductance injection in dynamic-clamp experiments.
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The bell-shaped distribution of the membrane potential is commonly observed in neurons embedded in an active network.
“The bell-shaped distribution of the membrane potential is commonly observed in neurons embedded in an active network [66].”
From Neural dynamics as sampling: a model for stochastic computation in recurrent networks of spiking neurons (2011) · cites this paper as [66]
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Buesing, L., Bill, J., Nessler, B., & Maass, W. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002211 · Cited by 384 · see citing works
- Authors
- Pospischil, M., Piwkowska, Z., Bal, T., & Destexhe, A.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Venue
- Journal of Physiology-Paris
- Publisher
- Elsevier BV
- Published
- 2009-01
- Volume
- 103
- Issue
- 1-2
- Pages
- 98-106
- ISSN
- 0928-4257 (ISSN-L)
- OpenAlex
- W2145735014
- Cited by
- 7
- References
- 44
- Citations by year
- 2021: 1 · 2016: 2
- FWCI
- 0.65
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Physiology-Paris (publishedVersion)
- PubMed (publishedVersion)
- HAL (submittedVersion)
- Funders
- Centre National de la Recherche Scientifique
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › stochastic dynamics and bifurcation
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- neuronal membrane potential, stochastic processes, colored noise, power spectrum analysis, maximum likelihood estimation, dynamic clamp, single-trial analysis, cortical neurons
- MeSH terms
- Animals, Computer Simulation, Membrane Potentials, Models, Neurological, Neurons, Stochastic Processes, Visual Cortex, Neural Networks, Computer, Patch-Clamp Techniques, Synaptic Potentials
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