The effect of correlated neuronal firing and neuronal heterogeneity on population coding accuracy in guinea pig inferior colliculus.
The effect of correlated neuronal firing and neuronal heterogeneity on population coding accuracy in guinea pig inferior colliculus.
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DOI：
10.1371/journal.pone.0081660
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Shamir M
中科院分区：
文献类型：
--
作者：
Zohar O;Shackleton TM;Palmer AR;Shamir M
有人认为，单细胞对刺激的反应中相当大的噪音可以通过汇集来自大群体的信息来克服。理论研究表明，不同神经元的反应中的试验到试验波动的相关性可能会限制由于池化而导致的改善。随后的理论研究表明，固有的神经元多样性，即，调谐曲线的不均匀性和优先调谐到相同刺激的神经元的其它响应特性可以提供克服该限制的手段。在这里，我们研究了尖峰计数相关性和固有的神经元异质性的能力，从大型神经群体提取信息的效果。我们使用豚鼠下丘的电生理数据来捕获固有的神经元异质性和单细胞统计，并人工引入响应相关性。为此，我们产生伪群体响应，基于单细胞记录的神经元响应不同的双耳相关性的听觉刺激。通常，当从单细胞数据生成假群体时，群体内的响应在统计学上是独立的。因此，人口的信息量将随着其规模的增加而无限增加。相比之下，在这里，我们应用一个简单的算法，使我们能够生成具有可变尖峰计数相关性的伪群体响应。这使我们能够研究神经元相关性对传统速率码准确性的影响。我们表明，在一个同质的人口，即使存在低级别的相关性，信息内容是有界的。相比之下，利用简单的线性读出，其考虑了神经群体内的自然异质性，甚至是优先调谐到相同刺激的神经元的异质性，可以克服相关噪声并获得其准确性随着群体的大小线性增长的读出。
It has been suggested that the considerable noise in single-cell responses to a stimulus can be overcome by pooling information from a large population. Theoretical studies indicated that correlations in trial-to-trial fluctuations in the responses of different neurons may limit the improvement due to pooling. Subsequent theoretical studies have suggested that inherent neuronal diversity, i.e., the heterogeneity of tuning curves and other response properties of neurons preferentially tuned to the same stimulus, can provide a means to overcome this limit. Here we study the effect of spike-count correlations and the inherent neuronal heterogeneity on the ability to extract information from large neural populations. We use electrophysiological data from the guinea pig Inferior-Colliculus to capture inherent neuronal heterogeneity and single cell statistics, and introduce response correlations artificially. To this end, we generate pseudo-population responses, based on single-cell recording of neurons responding to auditory stimuli with varying binaural correlations. Typically, when pseudo-populations are generated from single cell data, the responses within the population are statistically independent. As a result, the information content of the population will increase indefinitely with its size. In contrast, here we apply a simple algorithm that enables us to generate pseudo-population responses with variable spike-count correlations. This enables us to study the effect of neuronal correlations on the accuracy of conventional rate codes. We show that in a homogenous population, in the presence of even low-level correlations, information content is bounded. In contrast, utilizing a simple linear readout, that takes into account the natural heterogeneity, even of neurons preferentially tuned to the same stimulus, within the neural population, one can overcome the correlated noise and obtain a readout whose accuracy grows linearly with the size of the population.
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影响因子：
3
作者：
Gordon, Noam;Shackleton, Trevor M.;Nelken, Israel
通讯作者：
Nelken, Israel
影响因子：
25
作者：
Deneve, S;Latham, PE;Pouget, A
通讯作者：
Pouget, A
DOI：
10.1007/s10162-005-0005-8
发表时间：
2005-09-01
影响因子：
2.4
作者：
Shackleton, TM;Arnott, RH;Palmer, AR
通讯作者：
Palmer, AR
影响因子：
5.3
作者：
Shackleton, TM;Skottun, BC;Palmer, AR
通讯作者：
Palmer, AR
影响因子：
25
作者：
Rothschild, Gideon;Nelken, Israel;Mizrahi, Adi
通讯作者：
Mizrahi, Adi