Literature DB >> 12750422

Neocortical pyramidal cells respond as integrate-and-fire neurons to in vivo-like input currents.

Alexander Rauch1, Giancarlo La Camera, Hans-Rudolf Luscher, Walter Senn, Stefano Fusi.   

Abstract

In the intact brain neurons are constantly exposed to intense synaptic activity. This heavy barrage of excitatory and inhibitory inputs was recreated in vitro by injecting a noisy current, generated as an Ornstein-Uhlenbeck process, into the soma of rat neocortical pyramidal cells. The response to such in vivo-like currents was studied systematically by analyzing the time development of the instantaneous spike frequency, and when possible, the stationary mean spike frequency as a function of both the mean and the variance of the input current. All cells responded with an in vivo-like action potential activity with stationary statistics that could be sustained throughout long stimulation intervals (tens of seconds), provided the frequencies were not too high. The temporal evolution of the response revealed the presence of mechanisms of fast and slow spike frequency adaptation, and a medium duration mechanism of facilitation. For strong input currents, the slow adaptation mechanism made the spike frequency response nonstationary. The minimal frequencies that caused strong slow adaptation (a decrease in the spike rate by more than 1 Hz/s), were in the range 30-80 Hz and depended on the pipette solution used. The stationary response function has been fitted by two simple models of integrate-and-fire neurons endowed with a frequency-dependent modification of the input current. This accounts for all the fast and slow mechanisms of adaptation and facilitation that determine the stationary response, and proved necessary to fit the model to the experimental data. The coefficient of variability of the interspike interval was also in part captured by the model neurons, by tuning the parameters of the model to match the mean spike frequencies only. We conclude that the integrate-and-fire model with spike-frequency-dependent adaptation/facilitation is an adequate model reduction of cortical cells when the mean spike-frequency response to in vivo-like currents with stationary statistics is considered.

Entities:  

Mesh:

Year:  2003        PMID: 12750422     DOI: 10.1152/jn.00293.2003

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  78 in total

Review 1.  Neurophysiological and computational principles of cortical rhythms in cognition.

Authors:  Xiao-Jing Wang
Journal:  Physiol Rev       Date:  2010-07       Impact factor: 37.312

2.  Backward reasoning the formation rules.

Authors:  Walter Senn; João Sacramento
Journal:  Nat Neurosci       Date:  2015-12       Impact factor: 24.884

3.  Dynamics of the instantaneous firing rate in response to changes in input statistics.

Authors:  Nicolas Fourcaud-Trocmé; Nicolas Brunel
Journal:  J Comput Neurosci       Date:  2005-06       Impact factor: 1.621

4.  Action potential onset dynamics and the response speed of neuronal populations.

Authors:  B Naundorf; T Geisel; F Wolf
Journal:  J Comput Neurosci       Date:  2005-06       Impact factor: 1.621

5.  Predicting spike timing of neocortical pyramidal neurons by simple threshold models.

Authors:  Renaud Jolivet; Alexander Rauch; Hans-Rudolf Lüscher; Wulfram Gerstner
Journal:  J Comput Neurosci       Date:  2006-04-22       Impact factor: 1.621

6.  Spike-frequency adaptation and intrinsic properties of an identified, looming-sensitive neuron.

Authors:  Fabrizio Gabbiani; Holger G Krapp
Journal:  J Neurophysiol       Date:  2006-03-29       Impact factor: 2.714

7.  The parameters of the stochastic leaky integrate-and-fire neuronal model.

Authors:  Petr Lansky; Pavel Sanda; Jufang He
Journal:  J Comput Neurosci       Date:  2006-07-28       Impact factor: 1.621

8.  Fast numerical methods for simulating large-scale integrate-and-fire neuronal networks.

Authors:  Aaditya V Rangan; David Cai
Journal:  J Comput Neurosci       Date:  2006-07-28       Impact factor: 1.621

9.  Nonlinear local electrovascular coupling. I: A theoretical model.

Authors:  Jorge J Riera; Xiaohong Wan; Juan Carlos Jimenez; Ryuta Kawashima
Journal:  Hum Brain Mapp       Date:  2006-11       Impact factor: 5.038

10.  Attentional modulation of firing rate and synchrony in a model cortical network.

Authors:  Calin Buia; Paul Tiesinga
Journal:  J Comput Neurosci       Date:  2006-04-22       Impact factor: 1.621

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.