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Measuring the Motions of Mice: Open source tracking with the KineMouse Wheel
Who says you can't reinvent the wheel?! This running wheel for head-fixed mice allows 3D reconstruction of body kinematics using a single camera and DeepLabCut (or similar) software. A lightweight, transparent polycarbonate floor and a mirror mounted on the inside allow two views to be captured simultaneously. All parts are commercially available or laser cut
The Open-Source UCLA Miniscope Project
The Miniscope Project -- an open-source collaborative effort—was created to accelerate innovation of miniature microscope technology and to increase global access to this technology. Currently, we are working on advancements ranging from optogenetic stimulation and wire-free operation to simultaneous optical and electrophysiological recording. Using these systems, we have uncovered mechanisms underlying temporal memory linking and investigated causes of cognitive deficits in temporal lobe epilepsy. Through innovation and optimization, this work aims to extend the reach of neuroscience research and create new avenues of scientific inquiry.
Autopilot v0.4.0 - Distributing development of a distributed experimental framework
Autopilot is a Python framework for performing complex behavioral neuroscience experiments by coordinating a swarm of Raspberry Pis. It was designed to not only give researchers a tool that allows them to perform the hardware-intensive experiments necessary for the next generation of naturalistic neuroscientific observation, but also to make it easier for scientists to be good stewards of the human knowledge project. Specifically, we designed Autopilot as a framework that lets its users contribute their technical expertise to a cumulative library of hardware interfaces and experimental designs, and produce data that is clean at the time of acquisition to lower barriers to open scientific practices. As autopilot matures, we have been progressively making these aspirations a reality. Currently we are preparing the release of Autopilot v0.4.0, which will include a new plugin system and wiki that makes use of semantic web technology to make a technical and contextual knowledge repository. By combining human readable text and semantic annotations in a wiki that makes contribution as easy as possible, we intend to make a communal knowledge system that gives a mechanism for sharing the contextual technical knowledge that is always excluded from methods sections, but is nonetheless necessary to perform cutting-edge experiments. By integrating it with Autopilot, we hope to make a first of its kind system that allows researchers to fluidly blend technical knowledge and open source hardware designs with the software necessary to use them. Reciprocally, we also hope that this system will support a kind of deep provenance that makes abstract "custom apparatus" statements in methods sections obsolete, allowing the scientific community to losslessly and effortlessly trace a dataset back to the code and hardware designs needed to replicate it. I will describe the basic architecture of Autopilot, recent work on its community contribution ecosystem, and the vision for the future of its development.
OpenFlexure
OpenFlexure is a 3D printed flexure translation stage, developed by a group at the Bath University. The stage is capable of sub-micron-scale motion, with very small drift over time. Which makes it quite good, among other things, for time-lapse protocols that need to be done over days/weeks time, and under space restricted areas, such as fume hoods.
Open-source tools for systems neuroscience
Open-source tools are gaining an increasing foothold in neuroscience. The rising complexity of experiments in systems neuroscience has led to a need for multiple parts of experiments to work together seamlessly. This means that open-source tools that freely interact with each other and can be understood and modified more easily allow scientists to conduct better experiments with less effort than closed tools. Open Ephys is an organization with team members distributed all around the world. Our mission is to advance our understanding of the brain by promoting community ownership of the tools we use to study it. We are making and distributing cutting edge tools that exploit modern technology to bring down the price and complexity of neuroscience experiments. A large component of this is to take tools that were developed in academic labs and helping with documentation, support, and distribution. More recently, we have been working on bringing high-quality manufacturing, distribution, warranty, and support to open source tools by partnering with OEPS in Portugal. We are now also establishing standards that make it possible to combine methods, such as miniaturized microscopes, electrode drive implants, and silicon probes seamlessly in one system. In the longer term, our development of new tools, interfaces and our standardization efforts have the goal of making it possible for scientists to easily run complex experiments that span from complex behaviors and tasks, multiple recording modalities, to easy access to data processing pipelines.
Feeding Exprementation Device ver3 (FED3)
FED3 is a device for behavioral training of mice in vivarium home-cages. Mice interact with FED3 through two nose-pokes and FED3 responds with visual stimuli, auditory stimuli, and by dispensing pellets. As it is used in the home-cage FED3 can be used for around-the-clock training of mice over several weeks. FED3 is open-source and can be built by users for ~10-20x less than commercial solutions for training mice. The control code is also open-source and was designed to be easily modified by users.
An open-source experimental framework for automation of cell biology experiments
Modern biological methods often require a large number of experiments to be conducted. For example, dissecting molecular pathways involved in a variety of biological processes in neurons and non-excitable cells requires high-throughput compound library or RNAi screens. Another example requiring large datasets - modern data analysis methods such as deep learning. These have been successfully applied to a number of biological and medical questions. In this talk we will describe an open-source platform allowing such experiments to be automated. The platform consists of an XY stage, perfusion system and an epifluorescent microscope with autofocusing. It is extremely easy to build and can be used for different experimental paradigms, ranging from immunolabeling and routine characterisation of large numbers of cell lines to high-throughput imaging of fluorescent reporters.
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