Leveraging new technologies to study the brain and movement behaviour of humans during dynamic decision making

这项研究计划的目的是测量人们在做出现实生活中的运动决定时，大脑、身体和周围环境的变化。我将使用新技术来探索在一系列环境中做出的决定，从传统的实验室设置，通过虚拟现实（VR）到真实的世界。这个提议的核心是决策是动态的：首先，因为大脑是动态的，活动总是变化的;第二，因为人们在世界上移动时是动态的;第三，因为世界是动态的，物体会改变位置。尽管如此，大多数以前的工作都是研究静止的人在不动的选择之间做出的决定。在六个项目中，我将测试静止或移动的人与静止或移动的环境互动的组合。在这样做的过程中，我将实现三个短期目标：首先，为了了解大脑的动力学，我们将使用脑电图（EEG）来测量大脑活动。我们的目标是分离出人们在做决定时发生的特定活动模式。第二，为了从实验室过渡到研究真实的世界中的运动决策，我们将探索记录运动的新方法。我们将测试在手机和平板电脑等智能设备上进行的运动是否可以提供有用的运动信息，还将测试机器学习的进步是否可以从常规视频记录中提供详细的运动数据。最后，第三，我们将通过研究物体的相互作用来探索移动的人和移动的环境的融合，人们的移动会导致周围环境的变化。同样，为了实现我们从实验室到真实的世界的目标，我们将在虚拟现实中研究这些行为，并从完全移动的参与者中同时记录同步的眼睛，运动和EEG数据。这项工作的长期影响将在如何应用方面最为明显。考虑不能移动你的手臂来正确刷牙或喂自己，并且必须去治疗。现在想象一下，当您到达治疗室，坐在桌子旁并执行一系列简单的动作时，您的临床医生可以查阅自动生成的报告，详细说明您的运动障碍，以帮助指导您的康复。这只是拟议的研究计划所实现的一个未来。通过扩展我们的能力和多功能性，以捕获和分析有关人们如何看待，思考和移动的高质量数据，我们可以设想许多以前无法想象的未来-从我们如何在体育比赛期间诊断脑震荡到我们如何监测宇航员在太空中的健康状况。这些应用举措的核心是该应用的基本科学目标-要了解人类行为，您必须精确量化大脑，身体和环境如何随时间变化。

The objective of this research program is to measure how people's brains, bodies and surroundings change when they make real-life movement decisions. I will use new technologies to explore decisions made in a range of environments, from traditional laboratory settings, through Virtual Reality (VR) to the real world. At the heart of this proposal is the fact that decision making is dynamic: First, because the brain is dynamic with activity that always changes; Second, because people are dynamic as they move through the world; and Third because the world is dynamic, with objects that change position. Despite this, most previous work has looked at decisions made by stationary people between choice options that don't move. Across six projects, I will test a combination of people who are either stationary or moving while they interact with either stationary or moving environments. In doing so, I will fulfill three short term objectives: First, to understand the dynamics of the brain, we will measure brain activity using electroencephalography (EEG). Our objective will be to isolate specific patterns of activity that occur when someone is making a decision. Second, to make the transition out of the lab to study movement decision making in the real world, we will explore new ways of recording motion. We will test whether movements made on smart-devices like phones and tablets can provide useful movement information, and will also test whether advances in machine learning can provide detailed movement data from regular video recordings. Finally, third, we will explore the convergence of moving people and moving environments by studying object interactions, where people's movements result in changes to their surroundings. Again, to meet our goal of moving from the lab to the real world we will investigate these behaviours in Virtual Reality and from fully mobile participants where we simultaneously record synchronized eye, motion and EEG data. The long-term impact of this work will be most evident in how it is applied. Consider not being able to move your arm to properly brush your teeth or feed yourself, and having to go to therapy for treatment. Now imagine that by the time you arrive in the treatment room, sit at the table and perform a series of simple movements, your clinician can consult an automatically generated report detailing your movement impairments to help guide your rehabilitation. This is just one future enabled by the proposed research program. By expanding our ability and versatility to capture and analyze high quality data about how people, look, think and move we can envision many previously unimaginable futures - from how we diagnose concussions on the sidelines of a sports game to how we monitor astronaut's health in space. At the core of these applied initiatives is the basic science objective of this application - to understand human behaviour you must precisely quantify how brains, bodies and environments change with time.