Population decoding in rat barrel cortex: optimizing the linear readout of correlated population responses.
Population decoding in rat barrel cortex: optimizing the linear readout of correlated population responses.
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DOI：
10.1371/journal.pcbi.1003415
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发表时间：
2014-01
影响因子：
4.3
通讯作者：
Arabzadeh E
中科院分区：
文献类型：
--
作者：
Adibi M;McDonald JS;Clifford CW;Arabzadeh E
感觉信息被编码在神经元群体的反应中。下游神经元如何解码这些信息？在这里，我们分析了同时记录的桶皮层神经元对不同振幅的正弦振动的反应，这些正弦振动之前有三个幅度为0，6和12 µm的适应刺激。使用信号检测理论的框架，我们量化了线性解码器的性能，该解码器在应用一组最佳权重后对神经元的响应进行求和。通过Fisher线性判别分析的平均信噪比最大化的解析解找到最佳权重。这提供了一个生物学上合理的解码器，考虑到神经元的变异性，协变性和信号相关性。最佳的解码器实现了一致的改善，在简单的池的歧视性能。解相关的神经元反应试验洗牌显示，不像池，最佳解码器的性能受噪声相关性的影响最小。在非自适应状态下，噪声相关增强了某些种群的最优解码器的性能。然而，在自适应下，噪声相关性总是降低最佳解码器的性能。尽管如此，感官适应提高了最佳解码器的性能，主要是通过增加信号相关性比噪声相关性。适应引起的信号和噪声的相对方向的系统变化很小。因此，在非自适应状态下优化的解码器在自适应状态下很好地推广。在自然环境中，动物经常受到感官刺激。系统神经科学中的一个关键问题是如何从一群脑细胞的活动中“读出”感官刺激的属性。我们选择在大鼠胡须介导的触觉系统中研究这个问题，因为它具有良好的解剖学和精致的功能。触须系统是啮齿类动物获取周围环境感觉信息的主要通道之一。脑细胞的反应特性动态地调整以适应感官刺激的流行饮食，这一过程称为感官适应。在这里，我们应用了一个生物学上合理的方案，即不同的脑细胞有助于感官读出不同的权重。我们建立了一组权重，提供不同状态下的适应最佳读数。结果产生的编码感觉信息的效率的上限。我们发现，解码感官信息的能力随着适应而提高。然而，不适应适应状态的读出机制仍然可以表现得非常好。
Sensory information is encoded in the response of neuronal populations. How might this information be decoded by downstream neurons? Here we analyzed the responses of simultaneously recorded barrel cortex neurons to sinusoidal vibrations of varying amplitudes preceded by three adapting stimuli of 0, 6 and 12 µm in amplitude. Using the framework of signal detection theory, we quantified the performance of a linear decoder which sums the responses of neurons after applying an optimum set of weights. Optimum weights were found by the analytical solution that maximized the average signal-to-noise ratio based on Fisher linear discriminant analysis. This provided a biologically plausible decoder that took into account the neuronal variability, covariability, and signal correlations. The optimal decoder achieved consistent improvement in discrimination performance over simple pooling. Decorrelating neuronal responses by trial shuffling revealed that, unlike pooling, the performance of the optimal decoder was minimally affected by noise correlation. In the non-adapted state, noise correlation enhanced the performance of the optimal decoder for some populations. Under adaptation, however, noise correlation always degraded the performance of the optimal decoder. Nonetheless, sensory adaptation improved the performance of the optimal decoder mainly by increasing signal correlation more than noise correlation. Adaptation induced little systematic change in the relative direction of signal and noise. Thus, a decoder which was optimized under the non-adapted state generalized well across states of adaptation. In the natural environment, animals are constantly exposed to sensory stimulation. A key question in systems neuroscience is how attributes of a sensory stimulus can be “read out” from the activity of a population of brain cells. We chose to investigate this question in the whisker-mediated touch system of rats because of its well-established anatomy and exquisite functionality. The whisker system is one of the major channels through which rodents acquire sensory information about their surrounding environment. The response properties of brain cells dynamically adjust to the prevailing diet of sensory stimulation, a process termed sensory adaptation. Here, we applied a biologically plausible scheme whereby different brain cells contribute to sensory readout with different weights. We established the set of weights that provide the optimal readout under different states of adaptation. The results yield an upper bound for the efficiency of coding sensory information. We found that the ability to decode sensory information improves with adaptation. However, a readout mechanism that does not adjust to the state of adaptation can still perform remarkably well.
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