Mukherjee P, Kaplan E
Laboratory of Biophysics, The Rockefeller University, New York, USA.
Vis Neurosci. 1998 May-Jun;15(3):529-39. doi: 10.1017/s0952523898153063.
The maintained discharge of neurons along the early visual pathway in mammals constitutes the "noise" from which the visual signal must be discriminated. The statistics of this background noise in cat retinal ganglion cells (RGCs) have been shown to conform to that of a gamma-distributed renewal process (Kuffler et al., 1957; Barlow & Levick, 1969), and power spectrum analysis reveals that this property allows for low noise levels at the temporal-frequency range (0-10 Hz) most important for visual performance (Troy & Robson, 1992). In this study, we compare the statistics of the maintained discharge of cat lateral geniculate neurons with those of its RGC input by simultaneous recordings of spikes and S-potentials in single relay cells of the cat lateral geniculate nucleus (LGN). We demonstrate that, during primarily tonic spiking activity, the LGN maintained discharge preserves the renewal process statistics of its RGC input and also generates relatively little noise at the temporal frequencies important for vision. However, during burst spiking activity, the renewal process model breaks down and increased noise is generated at 2-10 Hz. This suggests that optimization of the visual signal/noise ratio is not a prime consideration in the behavioral states associated with bursting activity in the LGN. The occurrence of burst spikes in LGN relay cells is dependent on the activity of T-type calcium channels in their plasma membranes (Jahnsen & Llinas, 1984a,b). We show that a computational model of LGN relay cells that incorporates T-channel kinetics (Mukherjee & Kaplan, 1995) can correctly simulate LGN maintained discharge statistics during both tonic and bursty firing conditions, and indicates an essential role for this ion channel in determining the dynamic noise properties of the LGN. We also use the computational model to predict how the burstiness of the LGN maintained discharge is affected by the statistics of its RGC input.
哺乳动物早期视觉通路中神经元的持续放电构成了视觉信号必须从中区分出来的“噪声”。猫视网膜神经节细胞(RGCs)中这种背景噪声的统计数据已被证明符合伽马分布更新过程的统计数据(库夫勒等人,1957年;巴洛和利维克,1969年),功率谱分析表明,这一特性使得在对视觉性能最重要的时间频率范围(0 - 10赫兹)内噪声水平较低(特洛伊和罗布森,1992年)。在本研究中,我们通过同时记录猫外侧膝状体核(LGN)单个中继细胞中的尖峰和S电位,比较了猫外侧膝状体神经元持续放电的统计数据与其RGC输入的统计数据。我们证明,在主要为紧张性放电活动期间,LGN的持续放电保留了其RGC输入的更新过程统计数据,并且在对视觉重要的时间频率上也产生相对较少的噪声。然而,在爆发性放电活动期间,更新过程模型失效,在2 - 10赫兹处产生更多噪声。这表明在与LGN爆发性活动相关的行为状态中,视觉信号/噪声比的优化并非首要考虑因素。LGN中继细胞中爆发性尖峰的出现取决于其质膜中T型钙通道的活动(扬森和利纳斯,1984a,b)。我们表明,一个纳入T通道动力学的LGN中继细胞计算模型(穆克吉和卡普兰,1995年)可以正确模拟紧张性和爆发性放电条件下LGN的持续放电统计数据,并表明该离子通道在确定LGN的动态噪声特性中起着重要作用。我们还使用该计算模型预测LGN持续放电的爆发性如何受到其RGC输入统计数据的影响。