为什么神经连接权重是相关神经活动的弱预测因子？
Why is neural connection weight a weak predictor of correlated neural activity?
摘要：
随着连接组学领域的成熟，它已经从绘制大脑组件之间连接的存在扩展到测量连接的强度。这些信息越来越多地通过方法学获得，例如在同一人类受试者中配对功能性磁共振（MR）成像和MR纤维束成像，以及使用光遗传学在非人类动物中的新方法。近年来，系统和网络神经科学广泛关注于根据脑成分的连通性程度来解释脑中功能活动的相关模式，即所谓的功能连接-结构连接关系（SC-FC）。令人惊讶的是，SC-FC的相关性是如此之低。为什么连接更好的大脑部分似乎不会在它们之间产生更多的相关活动？人们提出了几种解释，但有一种可能性尚未被考虑：也许更多的神经活动并不意味着更多的功能参与。本文探讨了这种可能性，并提出了一个新的一般框架，了解大脑网络动力学的基础上的设计约束的大规模网络通信系统。有了这个新的视角，我们可以开始回答文章的主要问题，也许还有其他问题。
英文摘要：
As the field of connectomics has matured, it has expanded from mapping the existence of connections between brain components to measuring the strength of connections. This information is increasingly accessible via methodologies such as pairing functional magnetic resonance (MR) imaging and MR tractography in the same human subject, as well as novel methods in non-human animals using optogenetics. Systems and network neuroscience have in recent years focused extensively on explaining correlation patterns of functional activity in the brain in terms of the degree of connectedness of brain components, the so-called functional connectivity-structural connectivity relationship (SC-FC). What has been surprising has been how low the SC-FC correlations are. Why is it that brain parts that are more well-connected appear not to engender more correlated activity between them? Several explanations have been proposed but one possibility has not been considered: perhaps more neural activity doesn't imply more functional involvement. This article examines this possibility and proposes a new general framework for understanding brain network dynamics based on the design constraints of large-scale network communication systems. With this new perspective, we may start to answer the article's main question, and perhaps others.
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。
