|
|
||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
* To whom correspondence should be addressed. E-mail: sp1ace{at}ace.bsd.uchicago.edu.
The spike time reliability of motoneurons in the Aplysia buccal motor
ganglion was studied as a function of the amplitude fluctuations in
the neuronal input, expressed as the coefficient of variation (CV),
and their frequency content. Measurements of spike time reliability to
sinusoidal and aperiodic inputs, as well as simulations of a noisy
leaky integrate-and-fire neuron stimulated by spike trains drawn from
a periodically modulated process, demonstrate that there are three
qualitatively different CV-dependent mechanisms that determine
reliability: 1) noise dominated (CV < 0.05 for Aplysia motoneurons)
where spike timing is unreliable regardless of frequency content; 2)
resonance-dominated (CV
0.05-0.25) where reliability is
reduced by removal of input frequencies equal to motoneuron firing
rate; and 3) amplitude dominated (CV > 0.35) where reliability depends
on input frequencies greater than motoneuron firing rate. In the
resonance-dominated regime, changes in the activity of the presynaptic
inhibitory interneuron B4/5 alter motoneuron spike time reliability.
The increases or decreases in reliability occur coincident with small
changes in motoneuron spiking rate due to changes in interneuron
activity. Injection of a hyperpolarizing current into the motoneuron
reproduces the interneuron-induced changes in reliability. The
rate-dependent changes in reliability are similar to those produced
when the phase locking of regularly spiking motoneurons to periodic
inputs is varied. Our observations demonstrate that the ability of a
neuron to support a spike time code can be actively controlled by
varying the properties of the neuron and its input.
This article has been cited by other articles:
![]() |
R. F. Galan, G. B. Ermentrout, and N. N. Urban Optimal Time Scale for Spike-Time Reliability: Theory, Simulations, and Experiments J Neurophysiol, January 1, 2008; 99(1): 277 - 283. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. E. Street and P. B. Manis Action Potential Timing Precision in Dorsal Cochlear Nucleus Pyramidal Cells J Neurophysiol, June 1, 2007; 97(6): 4162 - 4172. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Rubin and K. Josic The Firing of an Excitable Neuron in the Presence of Stochastic Trains of Strong Synaptic Inputs Neural Comput., May 1, 2007; 19(5): 1251 - 1294. [Abstract] [Full Text] [PDF] |
||||
![]() |
B. N. Lundstrom and A. L. Fairhall Decoding stimulus variance from a distributional neural code of interspike intervals. J. Neurosci., August 30, 2006; 26(35): 9030 - 9037. [Abstract] [Full Text] [PDF] |
||||
![]() |
C. P. Billimoria, R. A. DiCaprio, J. T. Birmingham, L. F. Abbott, and E. Marder Neuromodulation of spike-timing precision in sensory neurons. J. Neurosci., May 31, 2006; 26(22): 5910 - 5919. [Abstract] [Full Text] [PDF] |
||||
![]() |
R. M. Glantz and J. P. Schroeter Analysis and Simulation of Gain Control and Precision in Crayfish Visual Interneurons J Neurophysiol, November 1, 2004; 92(5): 2747 - 2761. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. Diba, H. A. Lester, and C. Koch Intrinsic Noise in Cultured Hippocampal Neurons: Experiment and Modeling J. Neurosci., October 27, 2004; 24(43): 9723 - 9733. [Abstract] [Full Text] [PDF] |
||||
![]() |
J.-M. Fellous, P. H. E. Tiesinga, P. J. Thomas, and T. J. Sejnowski Discovering Spike Patterns in Neuronal Responses J. Neurosci., March 24, 2004; 24(12): 2989 - 3001. [Abstract] [Full Text] [PDF] |
||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH |
| Visit Other APS Journals Online |