视网膜群体密码的结构化“低温”阶段
The Structured `Low Temperature' Phase of the Retinal Population Code
摘要：
实验技术的最新进展已经允许同时记录数百个神经元的群体，从而允许对群体神经活动的集体结构的性质进行更全面的调查。虽然最近的研究报告了相变的参数空间的最大熵模型描述的神经概率分布，这些发现的解释一直存在争议。在这里，我们认为，这种相变可能是一个“结构化”，集体状态的神经元群体的证据。我们表明，这种相变是强大的刺激合奏和适应状态的变化。我们发现，神经元之间的成对相关性的模式具有很好的强度，在强相关的制度，并不需要微调，这表明这种状态是通用的100+神经元的群体。我们发现一个明确的对应出现的相变，并出现吸引子样结构的推断能源景观。一个集体状态的神经元群体，其中神经活动模式自然形成集群，为我们的结果提供了一致的解释。
英文摘要：
Recent advances in experimental techniques have allowed the simultaneous recording of populations of hundreds of neurons, allowing more comprehensive investigation into the nature of the collective structure of population neural activity. While recent studies have reported a phase transition in the parameter space of maximum entropy models describing the neural probability distributions, the interpretation of these findings has been debated. Here, we suggest that this phase transition may be evidence of a `structured', collective state in the neural population. We show that this phase transition is robust to changes in stimulus ensemble and adaptive state. We find that the pattern of pairwise correlations between neurons has a strength that is well within the strongly correlated regime and does not require fine tuning, suggesting that this state is generic for populations of 100+ neurons. We find a clear correspondence between the emergence of a phase transition, and the emergence of attractor-like structure in the inferred energy landscape. A collective state in the neural population, in which neural activity patterns naturally form clusters, provides a consistent interpretation for our results.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
