How BabelBrain is saving researchers time and money in neuromodulation research

Dr. Samuel Pichardo, PhD, is breaking down barriers to transcranial ultrasound stimulation (TUS) based neuromodulation by creating BabelBrain, a fully open-source, turn-key solution for planning neuromodulation studies and procedures in humans. Traditionally, the planning and set-up of neuromodulation requires highly trained individuals who know how to focus the ultrasound. This is much less trivial than it sounds as safety and efficacy is a huge consideration with neuromodulation. If you send too little energy, you are safe, but you likely won’t obtain the modulatory effect. If you send too much energy, you risk endangering the participant.

The process of setting up TUS requires the calculation of the transmitted acoustic field of brain tissue while preparing and adapting to the distortions caused by the skull; this process can take a couple of hours. Research staff need to have a strong understanding of acoustics and physics to calibrate and place the device correctly. 

BabelBrain uses scans from magnetic resonance imaging (MRI) and computed tomography (CT) to run a simulation that calculates the acoustics and provides the thermal effects that will occur based on the ultrasound technique used. BabelBrain eliminates the education and training barrier that is typically observed in neuromodulation research and increases the speed that preparation is completed by running the simulation based on input values. 

BabelBrain not only drastically increases the speed and efficiency of neuromodulation research but also reduces the cost that researchers encounter when running complex simulations. Pichardo has optimized the code to run efficiently on any computer. It can even be run on old hardware with limited graphics processing power, saving researchers tens of thousands of dollars as a four-GPU workstation which is typically required to run simulations, can cost as much as $30,000. 

To ensure the accessibility of BabelBrain, Pichardo has created versions for all major operating systems that work seamlessly alongside common neuronavigation and visualization software. 

The impact of BabelBrain is already being felt globally; Pichardo receives several emails every week from international collaborators updating him on the progress of their research using the tool and requesting additional modifications to the code. Nearly 600 people have downloaded BabelBrain in 2025 alone and used it to conduct modelling; this has contributed to at least 13 publications from external users who have cited the use of the tool.

Not only is BabelBrain an excellent example of open science in action, it is continuously improving as more open data becomes available, increasing its precision over time. Expanding access to large-scale MRI and CT datasets across diverse populations would further enhance its accuracy.

Over the next five years, Pichardo predicts that the precision will reach clinical standards, along with working to make BabelBrain a real-time calibration tool that can be implemented clinically. His goal is that the moment the device is fitted to the patient, BabelBrain runs the calculations and completes the necessary calibrations, enabling real-time data collection. 

For researchers interested in creating open science outputs, Pichardo recommends that you put yourself in the shoes of the end user. To ensure that your output has a positive impact, you need to reach out to groups who are likely to use your tool, dataset, or knowledge and understand what they need, and what would make your output valuable to them. The energy that you put into building collaborations and reaching out to potential end users will pay off and make your output more useful. 

Curious about this open-source tool? Explore BabelBrain and learn more about Pichardo's published BabelBrain findings.