Open source instruments for brain research

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Useful tools will usually set you back a few bucks, as a rule of thumb. Yet, a surprising fraction of the sophisticated software systems that quietly subserve our daily lives are open source – free of charge, and licensed to the public on the condition that derivative works properly acknowledge the original author.

This article appeared in the Spring 2013 issue of Current Exchange Magazine.

Household examples are Android, Firefox and Linux. Slightly more obscure examples are Apache (a common web server that effectively runs the majority of the Internet), MySQL (a database platform that powers commercial and consumer information systems), and Python (a powerful, intuitive programming language). Open source software is found everywhere from the phone in your pocket to the critical computers that power nuclear submarines for the US department of defense. It is ubiquitous because it is too good to be true – it is powerful, transparent, often brilliantly engineered, and free.

While almost fifteen years have proven that open source software can actually be sensible for business, a three year old legal definition applying the same principles of open source to entire electronic devices remains largely untested. Open Source Hardware (OSH), in general terms, are any electronic devices whose design files and firmware are free and licensed in the public domain. A paper definition contributes a sense of identity, but what has really propelled open source hardware into being is the advent of open source microcontroller and computing platforms like Arduino, Beagleboard and LeafLabs. As a person not educated in the intricacies of assembly language (very few people on Earth are), these technologies allow someone with rudimentary programming skills to use a microcontroller – a programmable computer on a chip – to intelligently control something they design for as little as $3. These game changing platforms have found their initial niche powering commercial hobby products – for example, 3d printers (MakerBot), thermocyclers (Open PCR) and submarines (OpenROV), but have been largely absent from business and academic research. What is missing is a precedent to generate trust.

Behavioral Systems Neuroscience, the field of research seeking to understand how a live brain functions at the circuit level to produce behavior, is a natural candidate for testing the reach of Open Source Hardware. It is a tinkerer’s science by necessity, a Cell Biology waiting for its electron microscope. Three key applications in this field necessitate rapidly evolving electronic devices which are often proprietary and very expensive: 1. acquiring weak electrical or optical signals from the brain and storing them to disk, 2. electrically or optically manipulating brain activity, and 3. precisely controlling and capturing aspects of the subject’s environment. Signals acquired from the brain are aligned to the record of the environment, and decrypted to determine what information they contain about manipulations and behavioral events. Using this strategy, the codes used by the brain to represent faces, places, sounds, judgement errors, movements and visual scenes to name a few, have been at least partially solved.

An open hardware toolset in Behavioral Systems Neuroscience would provide flexibility in experimental design – since the process of changing how the equipment functions under the hood (or knowing this information at all) begins as simply as looking up the design files in a public repository. With technological sophistication, our era has heavily delegated the task of reimagining bioscience methods that depend on electronics to commercial bioscience engineers who generally keep their innovations secret, and enormous potential for bench-side innovation by bioscience researchers goes unrealized. Though it is arguable that this division is necessary for either professional to achieve expertise, perhaps it has gone too far. With some well-funded and forward thinking laboratories being the exception, it is generally the case that when the answer to an idea is to hire a consulting engineer, good ideas end up going unexplored.

Thankfully, development of an open source toolset for Systems Neuroscience is already well underway, and the initial results are quite promising. The Open Ephys project was spearheaded by graduate student co-founders Josh Siegle and Jakob Voigts in the Picower Institute for Learning and Memory at MIT. The Open Ephys team has engineered a full-featured electrophysiology acquisition system that has been validated on awake, behaving mice. In plain terms, their instrument amplifies up to 128 weak electrical signals captured from brain probes (often only tens of microvolts in amplitude), converts them to a digital format that a computer can read, filters parts of the signals that are useful for analysis, and stores the processed data to disk – and it does this for each of its 128 channels 30,000 times per second. A comparable instrument from leading commercial vendors (e.g. Neuralynx, Tucker Davis Technologies, Blackrock Microsystems) typically costs well over $80,000, while Open Ephys weighs in at well less than a twentieth of that price if assembled in-house. The development time course of Open Ephys was greatly accelerated by the decision to use bioamplifier chips from Intan Technologies, a company that has been very supportive of the team’s goal of keeping the design completely open. In the past month, the team has upgraded their original design to include an embedded accelerometer for recording head motion – a sensible innovation that simply isn’t available in commercial alternatives. Cost and hardware advantages aside, where Open Ephys really outshines commercial instruments is in its software. The Open Ephys application takes stylistic cues from pro audio processing suites like Ableton Live and Reason, providing the ability to define a sequence of digital processing steps for each channel by dragging and dropping configurable filters onto a visual pipeline. Unlike commercial alternatives which sometimes still rely on configuring cryptic text files for configuration, the experience is rife with elegant visualizations, feels intuitive and makes the behavior of the instrument explicit. These categorical improvements upon existing methods illustrate the power of a tool that is actively curated in the same setting where it is used for research. Though its inception required the design of an open source instrument from scratch, since the design files and software are in the public domain, the barrier for researchers to add similar-minded improvements as their needs arise is now much, much lower.

While Open Ephys has done a spectacular job open-sourcing the process of acquiring data from the brain, a complementary project to develop open-source hardware for orchestrating brain manipulation and stimulus control has taken root here at Cold Spring Harbor Laboratory. The instrument is called Pulse Pal, and it presently powers almost a dozen ongoing research projects by controlling lasers and generating simple psychoacoustic waveforms. Pulse Pal can be assembled at a soldering bench in under one hour, costs less than $200 in common electronic parts, and improves upon the functionality of commercial instruments costing thousands (eg. AMPI Master8). The project is in the final preparation stages for its public debut, and a more sophisticated derivative work based on newer surface mount technology is slated to converge with the Open Ephys project.

So far, both initiatives have been graduate student side projects – but graduate students eventually graduate. These projects are different from open source software tools which can often still do useful work out of the box if they are perfected and released without further active support. Even with thorough documentation, the assembly process in low quantity orders (as is almost always the case in an academic setting) requires expertise, and people willing to dedicate their time to learn the ropes. Finding these technically minded researchers is less difficult in institutions that foster an engineering culture like at MIT, where Open Ephys got its start – and a much taller order for institutions that specialize in non-engineering disciplines. The instruments could be produced commercially, but it remains an open question whether a business model based on open source scientific instruments can survive on its profits alone. Regardless of whether they are actually produced, the availability of transparent, quality instrument designs in the public domain has the potential to transform what possibilities researchers think to entertain, and how well they understand the black-boxes that empower their research. The public availability of these designs will also encourage commercial instrument designers to innovate more quickly to stay above the bar.

Behavioral systems neuroscience research is critical to understanding how the brain functions in health and in disease; yet as a field, it is especially throttled by the sophistication of its instruments. Perhaps, a family of rapidly evolving open source tools can leverage good ideas contributed by the research community at large, allow more ambitious research to proceed in settings with tight funding, and generally bridge disciplines to un-throttle our rate of progress along several fronts in the quest to understand the brain.

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