Department of Brain and Behavioral Sciences, University of Pavia, and Brain Connectivity Center, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Mondino Foundation, Pavia, Italy.
Institut National de la Santé et de la Recherche Médicale (INSERM) Unité 1106, Centre National de la Recherche Scientifique (CNRS), and University of Aix-Marseille, Marseille, France.
Trends Neurosci. 2022 Oct;45(10):777-790. doi: 10.1016/j.tins.2022.06.007. Epub 2022 Jul 27.
Addressing the multiscale organization of the brain, which is fundamental to the dynamic repertoire of the organ, remains challenging. In principle, it should be possible to model neurons and synapses in detail and then connect them into large neuronal assemblies to explain the relationship between microscopic phenomena, large-scale brain functions, and behavior. It is more difficult to infer neuronal functions from ensemble measurements such as those currently obtained with brain activity recordings. In this article we consider theories and strategies for combining bottom-up models, generated from principles of neuronal biophysics, with top-down models based on ensemble representations of network activity and on functional principles. These integrative approaches are hoped to provide effective multiscale simulations in virtual brains and neurorobots, and pave the way to future applications in medicine and information technologies.
解决大脑的多尺度组织问题仍然具有挑战性，这是器官动态表现的基础。原则上，应该有可能详细地对神经元和突触进行建模，然后将它们连接成大型神经元集合，以解释微观现象、大脑的大规模功能和行为之间的关系。从目前通过脑活动记录获得的整体测量结果中推断神经元功能则更加困难。在本文中，我们考虑了将基于神经元生物物理原理的自下而上模型与基于网络活动整体表示和功能原理的自上而下模型相结合的理论和策略。这些综合方法有望在虚拟大脑和神经机器人中提供有效的多尺度模拟，并为未来在医学和信息技术中的应用铺平道路。
