A dynamical systems approach to fundamental questions in neuroscience

描述（由申请人提供） 摘要：大脑不仅是一个非凡的计算器官--能够完成阻碍最好的计算机和机器人的壮举--它还是我们思想和行动的发生器。然而，现代系统神经科学主要研究大脑如何将输入转化为输出。这种方法有着深刻的历史根源：笛卡尔和谢林顿都认为神经系统是一种复杂的反射。这种方法也产生了关键的早期成功：蒙特卡斯尔、胡贝尔和威尔德对感觉刺激如何驱动单神经元反应的描述。然而，大脑显然不仅仅是一个被美化的输入输出设备。其中的神经网络不仅对外部刺激做出反射性反应，它们还产生自己的活动。在这样做的过程中，他们产生思想，计划，决定和行动。随着对这些过程的研究越来越成为系统神经科学的核心，我们将需要越来越关注内部神经动力学：神经回路如何塑造和产生反应，使我们能够对世界采取行动。我们对单个神经元如何反映外部刺激的兴趣将变得越来越小。我们将对神经活动如何随着时间的推移而维持和塑造自己的动态感兴趣。我相信，这种对内部神经动力学的兴趣将推动系统神经科学所采用的概念，分析和实验范式的巨大变化。第一个变化将集中在收集，可视化和分析数据，这些数据可以揭示潜在的动态：神经回路在一个时间点的状态如何合法地导致神经回路在净时间点的状态。然后，重点将转移到设计最有效地探测动力学的实验。这些实验将借用物理科学和工程学的技术，但最初将基于系统神经科学的传统行为范式，即训练动物产生严格控制的行为。然而，我相信传统的实验框架将让位于新的框架。我们将直接监控和操作性调节内部产生的神经活动本身，而不是通过操作性调节行为间接影响神经活动。这种方法将建立在 它将基于最近为神经运动假体服务而开发的技术平台，但将服务于一个基本的科学目的：它将使实验者对他们试图理解的系统进行前所未有的控制，并允许对有关动力学的假设进行严格的测试。我的目标是帮助建立这种新兴的范式。接下来的一个同等重要的目标是利用我们对神经动力学不断增长的理解。我相信我们应该能够开发出一种新的神经假体设备，它利用运动皮层活动的动态模式来驱动人工运动。我相信这是证明我们来之不易的动力学知识是有意义的最好方法，也是开发神经运动假体的最有效方法之一，可以帮助很多人。 公共卫生相关性：这项拟议中的研究旨在提高我们对大脑如何产生活动模式的理解，包括那些允许我们移动四肢和行走的活动模式。我们建议利用这些知识来建立一个概念验证的神经假肢，允许直接神经控制运动，这可以大大改善数十万四肢瘫痪者的生活。这项研究也与许多疾病有关，这些疾病失去了产生正常模式神经活动的能力：最明显的是运动障碍，如帕金森病，以及潜在的认知障碍。

DESCRIPTION (Provided by the applicant) Abstract: The brain is not only a remarkable computational organ - capable of feats that stymie the best computers and robots - it is the generator of our thoughts and actions. Yet modern systems neuroscience has principally asked how the brain transforms inputs into outputs. This approach has deep historical roots: both Descartes and Sherrington saw the nervous system as a massively elaborated reflex. The approach also produced critical early successes: the descriptions by Mountcastle, Hubel, and Wiesel, of how sensory stimuli drive single- neuron responses. Yet the brain is clearly more than a glorified input-output device. The neural networks within it do not just respond reflexively to external stimuli, they also generate their ow activity. In doing so they produce thoughts, plans, decisions and actions. As the study of such processes becomes increasingly central to systems neuroscience, we will need to become increasingly concerned with internal neural dynamics: how neural circuitry shapes and generates the responses that allow us to act upon the world. We will become less interested in how individual neurons reflect external stimuli. We will become much more interested in the dynamics of how neural activity sustains and shapes itself over time. I believe this rising interes in internal neural dynamics will drive large changes in the conceptual, analytical, and experimental paradigms employed by systems neuroscience. The first changes will focus on collecting, visualizing, and analyzing data that can reveal underlying dynamics: how the state of the neural circuit at one point in time leads lawfully to the state of the neural circuit at the net point in time. The focus will then shift to designing experiments that most effectively probe dynamics. Such experiments will borrow techniques from the physical sciences and from engineering, but will initially be based on the traditional behavioral paradigm of systems neuroscience in which animals are trained to produce tightly-controlled behavior. However, I believe the traditional experimental framework will give way to a new one. Instead of indirectly influencing neural activity by operantly conditioning behavior, we will directly monitor and operantly condition the internally generated neural activity itself. This methodology will be built upon the technical platform recently developed in the service of neuro-motor prostheses, but will serve a basic scientific purpose: it will give the experimenter unprecedented control over the system they are trying to understand, and allow stringent tests of hypotheses regarding dynamics. My goal is to help build this emerging paradigm. A subsequent but equal goal is to leverage our growing understanding of neural dynamics. I believe that we should be able to develop a new class of neural prosthetic device that uses the dynamic patterns of motor cortex activity to drive artificial locomotion. I believe this is both the best way to demonstrate that ou hard-won knowledge of dynamics is meaningful, and that it may be one of the most effective ways to develop a neuro-motor prosthesis that will help significant numbers of people. Public Health Relevance: The proposed research aims to improve our understanding of how the brain generates patterns of activity, including those patterns of activity that allow us to mov our limbs and to walk. We propose to leverage that knowledge to build a proof-of-concept neural prosthetic that allows direct neural control of locomotion, something that could greatly improve the live the hundreds of thousands of tetra- and quadriplegics. The proposed research is also of relevance to the many diseases where the ability to generate normally patterned neural activity is lost: most obviously motor disorders such as Parkinson's disease, and potentially cognitive disorders as well.