Heberto Mayorquin
Heberto Mayorquin
Heberto Mayorquin holds a BSc in Physics, an MSc in Complexity Science, and a PhD in Computational Neuroscience. After a brief stint in the private sector optimizing SQL queries, he returned to science by joining CatalystNeuro. At CatalystNeuro, he helps neuroscience labs standardize their data—from extracting information buried in proprietary binary formats to streamlining metadata documentation and optimizing data layouts for long-term cloud storage. Within the organization, he serves as the lead maintainer of NeuroConv and is also a maintainer of SpikeInterface. His focus is on developing open-source tools and workflows that make it easier for researchers to share and reuse their own data, as he believes that open collaboration is a catalyst for scientific progress.
Sessions
Neuroscientists record brain activity using probes that capture rapid voltage changes ('spikes') from neurons. Spike sorting, the process of isolating these signals and attributing them to specific neurons, faces significant challenges: incompatible file formats, diverse algorithms, and inconsistent quality control. SpikeInterface provides a unified Python framework that standardizes data handling across technologies and enables reproducibility. In this talk, we will discuss: 1) SpikeInterface's modular components for I/O, processing, and sorting; 2) containerized dependency management that eliminates complex installation conflicts between diverse spike sorters; and 3) parallelization tools optimized for the memory-intensive nature of large-scale electrophysiology recordings.
The NWB format has emerged as a standard in neurophysiology, but converting data to NWB presents challenges due to diverse formats, variable metadata, and large data sizes. Neuroconv is an open-source Python library automating this process. This talk demonstrates how Neuroconv leverages the scientific Python ecosystem to enable memory-efficient processing and cloud-optimized data organization. We'll also discuss our experience with engineering challenges such as continuous integration for a large variety of source formats, multi-OS compatibility hurdles, and a modular dependency approach that minimizes installation footprint.