Society for Neuroscience (SfN) 2024
This was my second time attending SfN and I got the chance to be a returning face in the community! This year, I was registered as an exhibitor with Sensapex and a poster presenter. This extra credential allowed me to showcase my work to potential customers at the Sensapex exhibit booth and talk to them as a partner of Sensapex. I geared more of my focus this year on networking with various industry partners and expanding the reach of my project, Pinpoint. Now that I was more familiar with who was in attendance and how many vendors knew about my project, I was able to establish new partnerships. I was able to speak with the representatives from Scientifica and LabMaker and establish partnerships with them to integrate their manipulator platforms into Pinpoint. I felt this year that I was breaking out of the learning phase of conference-going and could use the networking opportunity to push my project forward.
This experience represents the culmination of my learning-by-doing philosophy reaching full maturity. Years of coursework in computer science, hands-on research development, and previous conference experiences all converged to enable this level of productivity and professional impact. Rather than simply absorbing information as a student, I found myself positioned as a valuable contributor to the neuroscience community—my undergraduate research work had evolved into something industry partners actively sought to integrate with their platforms. This transformation from learner to leader exemplifies how my interdisciplinary approach and commitment to practical application created tangible value. The scientist within me had developed expertise worth commercializing, while my communication skills allowed me to effectively bridge technical concepts with business applications. Standing at that exhibit booth, discussing technical integrations with industry representatives, I witnessed firsthand how my learning-by-doing approach had prepared me not just academically, but professionally, demonstrating that undergraduate research can achieve serious impact when approached with genuine commitment to discovery and application.
My Abstract
In vivo electrophysiology experiments, particularly those with multiple probes, face challenges in equipment management, efficiency, and reproducibility. The increasing focus on brain-wide coverage further exacerbates these challenges. To address these issues, we have developed a software platform called Pinpoint that enables remote control and automation of electrophysiology experiments. To reduce the stresses of equipment management in electrophysiology experiments, our software enables experimenters to view and manage micromanipulators from a web application on their own devices separate from the rig. Pinpoint’s modular components provide an interactive 3D visualization of the brain for experimenters to plan complex insertions, a communication platform for micromanipulators, and an automation pipeline for running experiments. During experiments with multiple probes, our remote platform handles most of the insertion process, including safeguards for preventing damage to the brain and collisions between probes. To automate the insertion process, our platform solves three challenges for experimenters: coordinating the movements of multiple probes to their entry coordinates, driving probes to their target depth at safe speeds, and coordinating the removal of multiple probes from the brain. Pinpoint takes planned insertions and automatically controls micromanipulators to maneuver the probes to their respective entry coordinates, then once through the dura, Pinpoint ensures that the probes are driven according to a set of rules designed to minimize tissue damage and improve the signal-to-noise ratio of the recording. In the future, integration of cameras and computer vision will allow our software to automatically insert probes through the dura surface, as well as detect obstructions and failed penetrations. Together, these open-source tools for remotely managing and automating multi-probe insertions enable the next generation of reproducible, high-efficiency, brain-wide electrophysiology data collection.