Examining Population Coding Underlying Complex Behavior in Freely Moving Primates

描述 摘要： 我提出了一项新技术，它将从根本上改变我们对大脑功能以及与行为的关系的理解。检测复杂的功能，如视觉、听力、记忆、注意力、决策或睡眠，传统上是通过在实验室环境中研究非人类灵长类动物的大脑来执行的，在实验室环境中，头和身体受到限制，而合成刺激被呈现在计算机显示器上。然而，人们越来越多地认识到，在受限的实验室设备中研究大脑对我们理解大脑回路功能的能力构成了严重限制。事实上，当在自然环境中测量单个神经元的反应时，它们往往与在实验室环境中测量时不同。此外，当动物在其自然环境中自由活动时，是否可以复制在实验室条件下很好地描述的现象，如适应、学习或决策，一直不清楚。为了克服这些限制，我将构建一个无线系统，使神经科学家能够在非人类灵长类动物在自然环境中自由活动的情况下，在种群水平上研究皮质动力学和可塑性。在不受限制的环境中研究大脑功能将打开新的机会。在实验台上很难或不可能观察到的现象，如觅食、睡眠或社会行为，现在可以进行研究。我们的技术将使我们能够以比今天可能的速度更快的速度，获得比在活体受试者中收集的更多的大脑数据。这种系统记录的大量连续神经数据将对研究正常和功能失调神经网络的一般性质的临床医生和理论家产生极大的兴趣。我们的系统不仅将引导人们对大脑紊乱机制的医学洞察，而且还将引导神经专业人员的实际应用。

DESCRIPTION Abstract: I propose a new technology that will fundamentally change our understanding of brain function and the relationship with behavior. Examining complex functions, such as vision, hearing, memory, attention, decision making, or sleep, have been traditionally performed by studying the brain of nonhuman primates in a laboratory environment in which the head and body are restrained while synthetic stimuli are presented on a computer monitor. However, it has become increasingly understood that studying the brain in a restrained laboratory rig poses severe limits on our capacity to understand the function of brain circuits. Indeed, when responses of individual neurons are measured in naturalistic settings they tend to be different compared to when they are measured in the laboratory environment. In addition, it has always been unclear whether phenomena well described in laboratory conditions, such as adaptation, learning, or decision making, can be replicated when animals freely move in their natural environment. To overcome these limitations, I will construct a wireless system that will allow neuroscientists to study cortical dynamics and plasticity at the population level while nonhuman primates are moving freely in their natural environment. Studying brain function in an unconstrained environment will open new opportunities. Phenomena that were difficult or impossible to observe in an experimental rig, such as foraging, sleep, or social behavior will now become possible to study. Our technology will allow us to acquire vastly more brain data than has ever been gathered in live subjects, at a much higher rate than is possible today. The large quantity of contiguous neural data recorded by such a system will be of great interest to clinicians and theorists studying general properties of normal and dysfunctional neural networks. Our system will lead not only to medical insights into the mechanisms of brain disorders, but also to practical applications for neuronal pros