Inferring neural population dynamics from multiple partial recordings of the same neural circuit
Inferring neural population dynamics from multiple partial recordings of the same neural circuit
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发表时间：
2013-12
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通讯作者：
Srinivas C. Turaga;Lars Buesing;Adam Packer;Henry Dalgleish;Noah L. Pettit;M. Häusser;J. Macke
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作者：
Srinivas C. Turaga;Lars Buesing;Adam Packer;Henry Dalgleish;Noah L. Pettit;M. Häusser;J. Macke
同时记录大量神经群体的活动是非常有价值的，因为它们可以用来推断局部电路中神经元的动态和相互作用，从而揭示所执行的计算。现在可以使用双光子钙成像来测量数百个神经元的活动。然而，许多计算被认为涉及由数千个神经元组成的电路，例如啮齿动物体感皮层中的皮质桶。在这里，我们贡献了一个统计方法“拼接”成一个模型的神经元顺序成像集的措辞问题，作为拟合一个潜在的动态系统与丢失的意见。这种方法使我们能够大大扩大人口规模，人口动态的特点，超越同时成像的神经元的数量。特别是，我们证明了使用记录在小鼠体感皮层，这种方法使得有可能预测非同时记录的神经元对之间的噪声相关性。
Simultaneous recordings of the activity of large neural populations are extremely valuable as they can be used to infer the dynamics and interactions of neurons in a local circuit, shedding light on the computations performed. It is now possible to measure the activity of hundreds of neurons using 2-photon calcium imaging. However, many computations are thought to involve circuits consisting of thousands of neurons, such as cortical barrels in rodent somatosensory cortex. Here we contribute a statistical method for "stitching" together sequentially imaged sets of neurons into one model by phrasing the problem as fitting a latent dynamical system with missing observations. This method allows us to substantially expand the population-sizes for which population dynamics can be characterized—beyond the number of simultaneously imaged neurons. In particular, we demonstrate using recordings in mouse somatosensory cortex that this method makes it possible to predict noise correlations between non-simultaneously recorded neuron pairs.