论文标题
潜在的动力学变量在大型生物系统中产生时空临界的特征
Latent dynamical variables produce signatures of spatiotemporal criticality in large biological systems
论文作者
论文摘要
由于可能的细胞 - 细胞相互作用的组合复杂性，很难理解大量神经元的活性。为了降低复杂性，以前已将粗粒剂应用于实验神经记录，该记录显示了自由能，活动方差，特征值光谱和相关时间的二十年缩放，这暗示了小鼠海马在关键方案中运行。我们通过模拟有条件独立的二进制神经元与少数长时间的随机场，然后复制粗粒程序和分析来对实验进行建模。这重现了实验观察到的量表，这表明它们可能是由神经种群活性与潜在动态刺激耦合而产生的。此外，我们模型的参数扫描表明，缩放的出现要求人群中的大多数细胞将其融入潜在的刺激，预测即使是著名的位置细胞也必须对非地位刺激做出反应。
Understanding the activity of large populations of neurons is difficult due to the combinatorial complexity of possible cell-cell interactions. To reduce the complexity, coarse-graining had been previously applied to experimental neural recordings, which showed over two decades of scaling in free energy, activity variance, eigenvalue spectra, and correlation time, hinting that the mouse hippocampus operates in a critical regime. We model the experiment by simulating conditionally independent binary neurons coupled to a small number of long-timescale stochastic fields and then replicating the coarse-graining procedure and analysis. This reproduces the experimentally-observed scalings, suggesting that they may arise from coupling the neural population activity to latent dynamic stimuli. Further, parameter sweeps for our model suggest that emergence of scaling requires most of the cells in a population to couple to the latent stimuli, predicting that even the celebrated place cells must also respond to non-place stimuli.
