School of Life Sciences, University of Sussex, Brighton, United Kingdom.
Institute for Ophthalmic Research, University of Tuebingen, Tuebingen, Germany.
PLoS Biol. 2018 Oct 26;16(10):e2006760. doi: 10.1371/journal.pbio.2006760. eCollection 2018 Oct.
Understanding how neurons encode and compute information is fundamental to our study of the brain, but opportunities for hands-on experience with neurophysiological techniques on live neurons are scarce in science education. Here, we present Spikeling, an open source in silico implementation of a spiking neuron that costs £25 and mimics a wide range of neuronal behaviours for classroom education and public neuroscience outreach. Spikeling is based on an Arduino microcontroller running the computationally efficient Izhikevich model of a spiking neuron. The microcontroller is connected to input ports that simulate synaptic excitation or inhibition, to dials controlling current injection and noise levels, to a photodiode that makes Spikeling light sensitive, and to a light-emitting diode (LED) and speaker that allows spikes to be seen and heard. Output ports provide access to variables such as membrane potential for recording in experiments or digital signals that can be used to excite other connected Spikelings. These features allow for the intuitive exploration of the function of neurons and networks mimicking electrophysiological experiments. We also report our experience of using Spikeling as a teaching tool for undergraduate and graduate neuroscience education in Nigeria and the United Kingdom.
了解神经元如何编码和计算信息是我们研究大脑的基础,但在科学教育中,实际接触神经生理学技术的机会很少。在这里,我们介绍了 Spikeling,这是一个开源的、基于计算机的尖峰神经元实现,成本为 25 英镑,可模拟广泛的神经元行为,用于课堂教育和公众神经科学推广。Spikeling 基于一个运行计算效率高的 Izhikevich 尖峰神经元模型的 Arduino 微控制器。微控制器连接到输入端口,模拟突触兴奋或抑制,连接到控制电流注入和噪声水平的刻度盘,连接到一个使 Spikeling 对光敏感的光电二极管,以及一个发光二极管(LED)和扬声器,允许看到和听到尖峰。输出端口提供对膜电位等变量的访问,以便在实验中进行记录,或提供可用于激发其他连接的 Spikelings 的数字信号。这些功能允许直观地探索模仿电生理实验的神经元和网络的功能。我们还报告了我们在尼日利亚和英国使用 Spikeling 作为本科和研究生神经科学教育教学工具的经验。