The Nature of Shared Cortical Variability.
The Nature of Shared Cortical Variability.
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DOI：
10.1016/j.neuron.2015.06.035
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发表时间：
2015-08-05
期刊：
影响因子：
16.2
通讯作者：
Harris KD
中科院分区：
文献类型：
--
作者：
Lin IC;Okun M;Carandini M;Harris KD
感觉皮层的神经元反应是高度可变的，这种可变性在神经元之间是相关的。为了评估可变性如何反映神经元群中共享的因素，我们分析了视觉皮层中同时记录的许多神经元的活动。我们开发了一个简单的模型，其中包含两个共享可变性的来源：一个乘法增益，它均匀地缩放每个神经元的感觉驱动，以及一个加性偏移，它在不同程度上影响不同的神经元。该模型捕获了脉冲计数的可变性，并再现了对神经元调谐和刺激方向的两两相关性的依赖性。加性和乘性波动的相对贡献可能随时间而变化，并对种群编码产生显著影响。这些观察结果表明，感觉皮层中神经元群体的共同变异性可以在很大程度上由两个调节整个群体的因素来解释。V1神经元群体的反应变异性在很大程度上是在神经元之间共享的。共享的变异性包括两个因素：乘法增益和加性补偿。这两个因素在单次试验中预测了大群体的感觉反应，它们决定了成对相关性并约束了信息编码。Lin等人使用V1的大规模记录表明，这种可变性在神经元之间是共享的，涉及两个简单的因素：乘法和加法。这些因素塑造了大量神经元的关节变异性。
Neuronal responses of sensory cortex are highly variable, and this variability is correlated across neurons. To assess how variability reflects factors shared across a neuronal population, we analyzed the activity of many simultaneously recorded neurons in visual cortex. We developed a simple model that comprises two sources of shared variability: a multiplicative gain, which uniformly scales each neuron’s sensory drive, and an additive offset, which affects different neurons to different degrees. This model captured the variability of spike counts and reproduced the dependence of pairwise correlations on neuronal tuning and stimulus orientation. The relative contributions of the additive and multiplicative fluctuations could vary over time and had marked impact on population coding. These observations indicate that shared variability of neuronal populations in sensory cortex can be largely explained by two factors that modulate the whole population. Response variability in V1 neuronal populations is largely shared across neurons Shared variability involves two factors: a multiplicative gain and an additive offset These two factors predict sensory responses of large populations on single trials They determine pairwise correlations and constrain information coding Cortical responses are highly variable. Using large-scale recordings in V1, Lin et al. show that this variability is shared across neurons and involves two simple factors: multiplicative and additive. These factors shape the joint variability of large populations of neurons.