Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons

被引:463
|
作者
Destexhe, A
Rudolph, M
Fellous, JM
Sejnowski, TJ
机构
[1] CNRS, Unite Neurosci Integrat & Computat, UPR 2191, F-91198 Gif Sur Yvette, France
[2] Howard Hughes Med Inst, La Jolla, CA 92037 USA
[3] Salk Inst Biol Studies, La Jolla, CA 92037 USA
[4] Univ Calif San Diego, Dept Biol, La Jolla, CA 92093 USA
关键词
computational models; pyramidal neurons; dynamic clamp; synaptic bombardment; high-conductance states; CV;
D O I
10.1016/S0306-4522(01)00344-X
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
To investigate the basis of the fluctuating activity present in neocortical neurons in vivo, we have combined computational models with whole-cell recordings using the dynamic-clamp technique. A simplified 'point-conductance' model was used to represent the currents generated by thousands of stochastically releasing synapses. Synaptic activity was represented by two independent fast glutamatergic and GABAergic conductances described by stochastic random-walk processes. An advantage of this approach is that all the model parameters can be determined from voltage-clamp experiments. We show that the point-conductance model captures the amplitude and spectral characteristics of the synaptic conductances during background activity. To determine if it can recreate in vivo-like activity, we injected this point-conductance model into a single-compartment model. or in rat prefrontal cortical neurons in vitro using dynamic clamp. This procedure successfully recreated several properties of neurons intracellularly recorded in vivo, such as a depolarized membrane potential, the presence of high-amplitude membrane potential fluctuations, a low-input resistance and irregular spontaneous firing activity. In addition, the point-conductance model could simulate the enhancement of responsiveness due to background activity. We conclude that many of the characteristics of cortical neurons in vivo can be explained by fast glutamatergic and GABAergic conductances varying stochastically. (C) 2001 IBRO. Published by Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:13 / 24
页数:12
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