A biologically-inspired, interactive digital device to introduce K12 students to computational neuroscience

项目总结 理解大脑是一项深刻而迷人的挑战，吸引着科学界和 公众都一样。缺乏对大多数大脑疾病的有效治疗使下一代的培训 神经科学家、工程师和内科医生的问题是一个关键问题。然而，许多神经科学被认为是 在学校里学不会太难。已经推出了由NIH资助的学生友好型 将基于项目的学习的电生理工具引入K12教育，后院大脑现在的目标是 通过开发与我们的电生理学相对应的“计算SpikerBox”来扩大影响 蜘蛛盒。这款带有可调参数的嵌入式数字设备将通过扬声器发出声音，通过手机查看 设备显示，并通过传感器做出反应。通过调节离子通道和改变离子电导 通过模型，学生将深入了解镇痛剂和各种毒液对神经元的影响。高中 老师和学生在研讨会上对我们的原型设备进行了评估，并表示这确实有助于他们 通过计算模型发展对生物神经元的直觉。在第一阶段，我们将完善和 将我们的计算SpikerBox用于课堂并构建合作应用程序。这个 拟议的设备将允许进行以前在教室里不可能进行的实验，包括 不限于观察阈值下神经元活动或突触前和突触后的电压。为了缓解 学习过程，使其有趣和直观，该应用程序将有一个直观的拖放界面，以 通过在刺激参数内关闭或打开离子通道来构建神经元行为的建模， 将电压值映射到离子电流，可视化离子通道调制的结果并预测 基于构建神经元活动的正确序列的患病神经元的结果。我们的目标 在增强硬件和软件的同时，还将开发与NGSS一致的创新课程 密歇根州底特律一间神经科学教室里的基于计算蜘蛛盒的计划。《实施》 该课程计划将由Rockman等人评估，他们将评估学生的内容知识， 对科学的态度和兴趣，以及作为科学家的自我效能。我们第一阶段的总体目标是让 学生了解神经元生物学特性的基本原理，所有这些都在NGSS中 框架。在第二阶段，我们计划扩展我们的计算SpikerBox的课程和功能， 将重点从单个神经元的行为扩展到少数神经元和 它如何与大脑的更高级别的计算模型相关联。我们的长期目标是让K12学生 培养对关键神经网络概念的实际理解，并从事计算思维(CT)； 一种通过打破复杂问题来解决问题、设计系统和理解世界的方法 分解成更小的组件。

PROJECT SUMMARY Understanding the brain is a profound and fascinating challenge, captivating the scientific community and the public alike. The lack of effective treatment for most brain disorders makes the training of the next generation of neuroscientists, engineers, and physicians a key concern. However, much of neuroscience is perceived to be too difficult to be taught in school. Having already introduced student-friendly, NIH-funded electrophysiological tools for project-based learning into K12 education, Backyard Brains is now aiming to broaden the impact by developing “Computational SpikerBox”, a counterpart to our electrophysiological SpikerBox. This embedded digital device with adjustable parameters will sound via a speaker, see via a mobile device display, and react via sensors. By modulating ion channels and changing ionic conductances in this model, students will gain insight into how neurons are affected by analgesics and various venoms. High school teachers and students evaluated our prototype devices in a workshop and stated that it did help them to develop intuition about biological neurons through the computational model. In Phase I, we will refine and ruggedize our Computational SpikerBox for the classroom and build out the partnering application. The proposed device will allow for experiments that had previously been impossible in the classroom, including but not limited to observing subthreshold neuron activity or pre- and post-synaptic voltages. To alleviate the learning process and make it fun and intuitive, the app will have an intuitive drag-and-drop interface to construct modeling of neuron behavior via closing or opening of ion channels within the stimulus parameters, mapping the voltage values to the ionic currents, visualizing their result of ion channel modulation and predict outcomes in a diseased neuron based on the correct sequence of constructing the neuronal activity. Our aims to enhance the hardware and software will be accompanied by developing an innovative NGSS-aligned lesson plan based on the Computational SpikerBox in a Neuroscience classroom in Detroit, MI. The implementation of this lesson plan will be assessed by Rockman et al Cooperative, who will evaluate student content knowledge, attitudes and interest in Science, and Self-Efficacy as a scientist. Our overall Phase I goal is to empower students to understand the fundamentals of the biological properties of neurons, all within the NGSS framework. In Phase II, we plan to expand the curriculum and the capabilities of our Computational SpikerBox, extending the focus from a single neuron behavior to connections between a small number of neurons and how it relates to higher-level computational modeling of the brain. Our long-term aim is for K12 students to develop a practical understanding of key neural network concepts and engage in computational thinking (CT), a way of solving problems, designing systems, and understanding the world by breaking complex problems down into smaller components.