论文标题
使用现象序列重新归一化组检验临界大脑假设
Testing the critical brain hypothesis using a phenomelogical renormalization group
论文作者
论文摘要
我们提出了一项系统的研究，以测试最近引入的现象学重归其化组，该研究对神经活动的相关性矩阵提出了粗粒神经活性数据。该方法至少原则上允许确定尖峰神经元网络的集体行为是否由非高斯临界固定点描述。我们在各种模型中测试了这种重新归一化过程，尤其是在接触过程上，该模型以$λ=λ_c$在静音状态和活动状态之间显示吸收相变。我们发现，粗粒的结果并不取决于长距离交互的存在，但是超临界系统中的某些缩放功能持续到$ 10 \％$与$λ_c$ $ 10 \％$。我们的结果提供了有关将这种现象学方法直接应用于数据以推断关键签名时需要考虑的可能的细微之处的见解。
We present a systematic study to test a recently introduced phenomenological renormalization group, proposed to coarse-grain data of neural activity from their correlation matrix. The approach allows, at least in principle, to establish whether the collective behavior of the network of spiking neurons is described by a non-Gaussian critical fixed point. We test this renormalization procedure in a variety of models focusing in particular on the contact process, which displays an absorbing phase transition at $λ= λ_c$ between a silent and an active state. We find that the results of the coarse-graining do not depend on the presence of long-range interactions, but some scaling features persist in the super-critical system up to a distance of $10\%$ from $λ_c$. Our results provide insights on the possible subtleties that one needs to consider when applying such phenomenological approaches directly to data to infer signatures of criticality.
