Alessio Buccino
I am an engineer and software developer focused on methods and analysis tools for neuroscience research, especially for extracellular electrophysiology. I am passionate about science, software, and engineering, and my mission is to support neuroscientists and facilitate their research efforts by providing state-of-the-art analysis methods and software tools. Among these, I am the core developer of several open-source scientific tools, including SpikeInterface, a widely used software framework to unify and simplify the analysis of extracellular electrophysiology data.
In March 2022, I joined the Allen Institute for Neural Dynamics team as an electrophysiology pipeline development engineer consultant, with the goal of building open-source and computationally efficient processing pipelines to analyze large amounts of electrophysiological data. Since July 2020, I have been working part-time at CatalystNeuro, a consulting company with the mission of facilitating collaborations in neuroscience and standardizing data analysis and data storage solutions.
Previously, I was a Postdoctoral Fellow at the Bio Engineering Lab at ETH, working on multimodal approaches to probe neural activity and to construct detailed biophysical models. Before that I was at the Center for Integrated Neuroplasticity CINPLA, at the University of Oslo, where I received my PhD.
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.