Rate response of neurons subject to fast or frozen noise : from stochastic and homogeneous to deterministic and heterogeneous populations
Alijani, Azadeh and Richardson, Magnus J. E.. (2011) Rate response of neurons subject to fast or frozen noise : from stochastic and homogeneous to deterministic and heterogeneous populations. Physical Review E, Vol.84 (No.1). ISSN 1539-3755Full text not available from this repository.
Official URL: http://dx.doi.org/10.1103/PhysRevE.84.011919
The response of a neuronal population to afferent drive can be expected to be sensitive to both the distribution and dynamics of membrane voltages within the population. Voltage fluctuations can be driven by synaptic noise, neuromodulators, or cellular inhomogeneities: processes ranging from millisecond autocorrelation times to effectively static or "frozen" noise. Here we extend previous studies of filtered fluctuations to the experimentally verified exponential integrate-and-fire model. How fast or frozen fluctuations affect the steady-state rate and firing-rate response are both examined using perturbative solutions and limits of a 1 + 2 dimensional Fokker-Planck equation. The central finding is that, under conditions of a more-or-less constant population voltage variance, the firing-rate response is only weakly dependent on the fluctuation filter constant: The voltage distribution is the principal determinant of the population response. This result is unexpected given the nature of the systems underlying the extreme limits of fast and frozen fluctuations; the first limit represents a homogeneous population of neurons firing stochastically, whereas the second limit is equivalent to a heterogeneous population of neurons firing deterministically.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics
Q Science > QH Natural history > QH301 Biology
|Divisions:||Faculty of Science > Mathematics
Faculty of Science > Centre for Systems Biology
|Library of Congress Subject Headings (LCSH):||Neurons -- Research, Neurons -- Mathematical models, Neural transmission|
|Journal or Publication Title:||Physical Review E|
|Publisher:||American Physical Society|
|Date:||25 July 2011|
|Access rights to Published version:||Restricted or Subscription Access|
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