Statistical physics of cognition

这个项目探讨了诸如雪崩等关键过程的统计力学是如何支撑哺乳动物认知的。这一点很重要，因为自组织临界性已被提出作为对大脑电路结构和操作点的一般解释，但到目前为止还不可能将其与认知功能本身联系起来。我们带来了一个跨学科的方法来承担这个问题，从亚细胞到全脑范围内模拟神经元机制，并采用新的介观神经成像技术来检测雪崩和测量距离临界在非常大的（~ 10，000）群体的神经元在认知任务。这将为健康和疾病状态下的全系统大脑功能带来新的见解。

This project asks how the statistical mechanics of critical processes such as avalanches underpin mammalian cognition. This is important because self-organising criticality has been proposed as a general explanation of the architecture and operating point of brain circuitry, however until now it has not been possible to relate it to cognitive function itself. We bring an inter-disciplinary approach to bear upon this problem, simulating neuronal mechanisms at scales from sub-cellular to brain-wide, and employing a new mesoscopic neuroimaging technology to detect avalanches and measure distance to criticality in very large (~10,000) populations of neurons during a cognitive task. This will bring new insight into system-wide brain function during health and disease states.