DYNAMICS OF NEURONS IN THE CAT LATERAL GENICULATE-NUCLEUS - IN-VIVO ELECTROPHYSIOLOGY AND COMPUTATIONAL MODELING
DYNAMICS OF NEURONS IN THE CAT LATERAL GENICULATE-NUCLEUS - IN-VIVO ELECTROPHYSIOLOGY AND COMPUTATIONAL MODELING
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DOI：
10.1152/jn.1995.74.3.1222
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发表时间：
1995-09-01
影响因子：
2.5
通讯作者：
KAPLAN, E
中科院分区：
文献类型：
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作者：
MUKHERJEE, P;KAPLAN, E
1.我们研究了猫外侧膝状核(LGN)丘脑皮质中继细胞对其视网膜输入的时间域转换，并利用计算模型探索了决定LGN中继细胞在活体内动力学的生物物理性质。我们同时记录了50个猫LGN中继细胞在不同时间频率的漂移正弦光栅刺激下的输入(S电位)和输出(动作电位)。根据这些数据得到神经元的时间调制传递函数(TMTF)。用客观标准评估了LGN脉冲序列的突发性。我们发现TMTF的形式在不同细胞之间有很大的变化，从低通到强带通。带通神经元的最佳时间频率为2~8赫兹。此外，一些细胞的TMTF是非平稳的：它们的时间调谐随时间变化。细胞的时间调谐与其棘波序列的突发性程度直接相关。强直神经放电的中继神经元具有低通的TMTF，而最强的突发性神经元表现出最尖锐的带通传递函数。改变其时间调谐的单个细胞也是如此：向更多带通调谐的转变与棘波序列的突发性增加相关，反之亦然。我们构建了LGN中继小区的计算机仿真。该模型是McCormick和Huguenard的丘脑皮质神经元模型的简化的五通道版本。它结合了钙离子T通道以及Hodgkin-Huxley Na+和K+通道的定量动力学，作为唯一的活性膜电流。为了模拟中继细胞的在体动力学，模型的输入由一连串的突触电位组成，在我们的生理实验中被记录为S电位。当模型神经元的静息膜电位相对去极化时，模型的TMTF是低通的，在模拟的棘波序列中没有明显的爆发。然而，在超极化静止膜电位下，模型的TMTF是带通的，具有频繁的猝发放电。因此，生物物理模型不仅再现了在真实LGN中继细胞中看到的动力学范围，而且还再现了整体动力学对棘波序列突发性的依赖。然而，如果没有T通道，这两种现象都无法模拟。因此，模拟结果表明，T型钙通道对于解释生理实验中观察到的LGN动力学是必要的和充分的。我们得出结论，LGN中继小区的时间特性是动态的，而不是静态的。我们的数据不支持LGN有两种截然不同的状态(爆发或强直)的观点。相反，他们表明，LGN神经元的调谐随着棘波序列中爆发的水平而不断变化。我们的计算模型的结果表明，猝发和调节都是由细胞的静息膜电位控制的，这是通过它对T型钙通道活动的影响来实现的。对LGN的神经调制作用来源于视皮层和脑干觉醒中枢，可以调节中继细胞的静息膜电位。通过这种方式，LGN可以充当视觉信息的“可调时间过滤器”，在昏昏欲睡或注意力不集中的状态下筛选出稳态活动，同时仍允许在清醒、警觉的行为期间忠实地传输视网膜输入。
1. We investigated the time domain transformation that thalamocortical relay cells of the cat lateral geniculate nucleus (LGN) perform on their retinal input, and used computational modeling to explore the biophysical properties that determine the dynamics of the LGN relay cells in vivo.2. We recorded simultaneously the input (S potentials) and output (action potentials) of 50 cat LGN relay cells stimulated by drifting sinusoidal gratings of varying temporal frequency. The temporal modulation transfer functions (TMTFs) of the neurons were derived from these data. The burstiness of the LGN spike trains was also assessed using objective criteria.3. We found that the form of the TMTF was quite variable among cells, ranging from low-pass to strongly band-pass. The optimal temporal frequency of band-pass neurons was between 2 and 8 Hz. In addition, the TMTF of some cells was nonstationary: their temporal tuning changed with time.4. The temporal tuning of a cell was directly related to the degree of burstiness of its spike train. Tonically firing relay cells had low-pass TMTFs, whereas the most bursty neurons exhibited the most sharply band-pass transfer functions. This was also true for single cells that altered their temporal tuning: a shift to more band-pass tuning was associated with increased burstiness of the spike train, and vice versa.5. We constructed a computer simulation of the LGN relay cell. The model was a simplified five-channel version of the thalamocortical neuron model of McCormick and Huguenard. It incorporated the quantitative kinetics of the Ca2+ T channel, as well as the Hodgkin-Huxley Na+ and K+ channels, as the only active membrane currents. To simulate the in vivo dynamics of the relay cell, the input to the model consisted of trains of synaptic potentials, recorded as S potentials in our physiological experiments.6. When the resting membrane potential of the model neuron was relatively depolarized, the model's TMTF was low-pass, with no bursting evident in the simulated spike train. At hyperpolarized resting membrane potentials, however, the modeled TMTF was band-pass, with frequent burst discharges. Thus the biophysical model reproduced not only the range of dynamics seen in real LGN relay cells, but also the dependence of the overall dynamics on the burstiness of the spike train. However, neither of these phenomena could be simulated without the T channel. Thus the simulations demonstrated that the T-type Ca2+ channel was necessary and sufficient to explain the LGN dynamics observed in physiological experiments.7. We conclude that the temporal properties of LGN relay cells are dynamic, not static. Our data do not support the view of the LGN as having two distinct states (bursting or tonic). Instead, they show that the tuning of LGN neurons varies continuously with the level of bursting in the spike train. The results from our computational modeling indicate that bursting and tuning are both governed by the resting membrane potential of the cell, through its influence on the activity of the T-type Ca2+ channel.8. Neuromodulatory influences on the LGN, which originate from visual cortex and from brain stem arousal centers, can regulate the resting membrane potential of relay cells. In this way, the LGN can act as a ''tunable temporal filter'' of visual information, screening out steady-state activity during drowsy or inattentive states yet still allowing for the faithful transmission of the retinal input during awake, alert behavior.