Sensitivity of firing rate to input fluctuations depends on time scale separation between fast and slow variables in single neurons
Open accessAbstract
Neuronal responses are often characterized by the firing rate as a function of the stimulus mean, or the f-I curve. We introduce a novel classification of neurons into Types A, B-, and B+ according to how f-I curves are modulated by input fluctuations. In Type A neurons, the f-I curves display little sensitivity to input fluctuations when the mean current is large. In contrast, Type B neurons display sensitivity to fluctuations throughout the entire range of input means. Type B- neurons do not fire repetitively for any constant input, whereas Type B+ neurons do. We show that Type B+ behavior results from a separation of time scales between a slow and fast variable. A voltage-dependent time constant for the recovery variable can facilitate sensitivity to input fluctuations. Type B+ firing rates can be approximated using a simple "energy barrier" model.
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The sensitivity of individual neurons to synaptic fluctuations can vary with neural subtype or cortical area and with biophysical cellular properties, such as membrane capacitance and conductance.
“Furthermore, the sensitivity of individual neurons to synaptic fluctuations can vary with neural subtype or cortical area and with biophysical cellular properties, such as membrane capacitance and conductance89–93.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [92]
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References 49 · Cited by 53
- Authors
- Lundstrom, B. N., Famulare, M., Sorensen, L. B., Spain, W. J., & Fairhall, A. L.
- Affiliations
- University of Washington (US)
- Corresponding author
- Lundstrom, Brian Nils
- Venue
- Journal of Computational Neuroscience
- Published
- 2009-04-08
- Volume
- 27
- Issue
- 2
- Pages
- 277-290
- ISSN
- 0929-5313 (ISSN-L)
- 1573-6873
- OpenAlex
- W2155792611
- Cited by
- 53
- References
- 49
- Citations by year
- 2026: 1 · 2024: 1 · 2023: 2 · 2022: 2 · 2021: 4 · 2020: 3 · 2019: 2 · 2017: 3 · 2016: 4 · 2015: 5 · 2014: 5 · 2013: 3 · 2012: 5
- FWCI
- 2.74
- Type
- journal article
- Language
- en
- Open access
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Computational Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (submittedVersion)
- Funders
- U.S. Department of Veterans Affairs (I01 BX000386)
- McKnight Foundation
- National Institute of General Medical Sciences
- National Institute of Neurological Disorders and Stroke (F30NS055650)
- 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 › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Ion channel regulation and function
- Keywords
- firing rate, time-scale separation, single neurons, neuron classification, repetitive firing, average current
- MeSH terms
- Action Potentials, Algorithms, Animals, Cell Membrane, Central Nervous System, Computer Simulation, Humans, Membrane Potentials, Nerve Net, Neurons, Time Factors
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