An Electrophysiological Investigation of Power-Amplification in the Ballistic Mantis Shrimp Punch.

Mantis shrimp are aggressive, burrowing crustaceans that hunt using one the fastest movements in the natural world. These stomatopods can crack the calcified shells of prey or spear down unsuspecting fish with lighting speed. Their strike makes use of power-amplification mechanisms to move their limbs much faster than is possible by muscles alone. Other arthropods such as crickets and grasshoppers also use power-amplified kicks that allow these animals to rapidly jump away from predator threats. Here we present a template laboratory exercise for studying the electrophysiology of power-amplified limb movement in arthropods, with a specific focus on mantis shrimp strikes. The exercise is designed in such a way that it can be applied to other species that perform power-amplified limb movements (e.g., house crickets, Acheta domesticus) and species that do not (e.g., cockroaches, Blaberus discoidalis). Students learn to handle the animals, make and implant electromyogram (EMG) probes, and finally perform experiments. This integrative approach introduces the concept of power-amplified neuromuscular control; allows students to develop scientific methods, and conveys high-level insights into behavior, and convergent evolution, the process by which different species evolve similar traits. Our power-amplification laboratory exercise involves a non-terminal preparation which allows electrophysiological recordings across multiple days from arthropods using a low-cost EMG amplifier. Students learn the principles of electrophysiology by fabricating their own electrode system and performing implant surgeries. Students then present behaviorally-relevant stimuli that generate attack strikes in the animals during the electrophysiology experiments to get insight into the underlying mechanisms of power amplification. Analyses of the EMG data (spike train burst duration, firing rate, and spike amplitude) allow students to compare mantis shrimp with other power-amplifying species, as well as a non-power-amplifying one. The major learning goal of this exercise is to empower students by providing an experience to develop their own setup to examine a complex biological principle. By contrasting power-amplifiers with non-power-amplifiers, these analyses highlight the peculiarity of power amplification at multiple levels of analysis, from behavior to physiology. Our comparative design requires students to consider the behavioral function of the movement in different species alongside the neuromuscular underpinnings of each movement. This laboratory exercise allows students to develop methodology, problem-solving and inquisitive skills crucial for pursuing science.

Grasshopper DCMD: An Undergraduate Electrophysiology Lab for Investigating Single-Unit Responses to Behaviorally-Relevant Stimuli.

Avoiding capture from a fast-approaching predator is an important survival skill shared by many animals. Investigating the neural circuits that give rise to this escape behavior can provide a tractable demonstration of systems-level neuroscience research for undergraduate laboratories. In this paper, we describe three related hands-on exercises using the grasshopper and affordable technology to bring neurophysiology, neuroethology, and neural computation to life and enhance student understanding and interest. We simplified a looming stimuli procedure using the Backyard Brains SpikerBox bioamplifier, an open-source and low-cost electrophysiology rig, to extracellularly record activity of the descending contralateral movement detector (DCMD) neuron from the grasshopper's neck. The DCMD activity underlies the grasshopper's motor responses to looming monocular visual cues and can easily be recorded and analyzed on an open-source iOS oscilloscope app, Spike Recorder. Visual stimuli are presented to the grasshopper by this same mobile application allowing for synchronized recording of stimuli and neural activity. An in-app spike-sorting algorithm is described that allows a quick way for students to record, sort, and analyze their data at the bench. We also describe a way for students to export these data to other analysis tools. With the protocol described, students will be able to prepare the grasshopper, find and record from the DCMD neuron, and visualize the DCMD responses to quantitatively investigate the escape system by adjusting the speed and size of simulated approaching objects. We describe the results from 22 grasshoppers, where 50 of the 57 recording sessions (87.7%) had a reliable DCMD response. Finally, we field-tested our experiment in an undergraduate neuroscience laboratory and found that a majority of students (67%) could perform this exercise in one two-hour lab setting, and had an increase in interest for studying the neural systems that drive behavior.

Neurorobotics Workshop for High School Students Promotes Competence and Confidence in Computational Neuroscience.

Understanding the brain is a 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. Over the past decade there has been a growing effort to introduce neuroscience in primary and secondary schools, however, hands-on laboratories have been limited to anatomical or electrophysiological activities. Modern neuroscience research labs are increasingly using computational tools to model circuits of the brain to understand information processing. Here we introduce the use of neurorobots - robots controlled by computer models of biological brains - as an introduction to computational neuroscience in the classroom. Neurorobotics has enormous potential as an education technology because it combines multiple activities with clear educational benefits including neuroscience, active learning, and robotics. We describe a 1-week introductory neurorobot workshop that teaches high school students how to use neurorobots to investigate key concepts in neuroscience, including spiking neural networks, synaptic plasticity, and adaptive action selection. Our do-it-yourself (DIY) neurorobot uses wheels, a camera, a speaker, and a distance sensor to interact with its environment, and can be built from generic parts costing about $170 in under 4 h. Our Neurorobot App visualizes the neurorobot's visual input and brain activity in real-time, and enables students to design new brains and deliver dopamine-like reward signals to reinforce chosen behaviors. We ran the neurorobot workshop at two high schools (n = 295 students total) and found significant improvement in students' understanding of key neuroscience concepts and in students' confidence in neuroscience, as assessed by a pre/post workshop survey. Here we provide DIY hardware assembly instructions, discuss our open-source Neurorobot App and demonstrate how to teach the Neurorobot Workshop. By doing this we hope to accelerate research in educational neurorobotics and promote the use of neurorobots to teach computational neuroscience in high school.