Understanding the brain requires aligning high-dimensional stimuli with large-scale neuronal recordings. Experanto is a Python framework designed to bridge this gap, providing a unified interface for interpolating and aligning time series (calcium imaging, continuous behavior such as running speed), events (spiking data, action-based behavior), and media (images, video). Optimized for deep learning, Experanto recently powered OmniMouse, a large-scale multimodal neural predictive model.
The core strength of Experanto is its flexibility: it allows users to resample frequencies, filter data by behavioral criteria (e.g., “only when running”), and integrate multiple experiments into a single pipeline.
The goal of this project is to expand Experanto’s functionality, visualization tools, and robustness. Proposed focus areas include:
- Open-Source Data Integration: Currently supporting the Allen Brain Calcium Imaging dataset, we aim to expand to the Brain Wide Map and Allen Neuropixels datasets. Ideally, this involves creating a “brainsets-style” library to automatically download and map these datasets to Experanto.
- Extend experanto functionality:
- Enhanced Filtering & Parsing: Developing a string-based configuration interface for complex data filtering—for example: (treadmill > 0 and eye is not nan) & screen == video.
- Event-Driven Data Handling: Explicitly adding support for event-based data types to better process free-animal behavior experiments.
- Visualization & Documentation: Building built-in visualization tools and expanding tutorials for data analysis and neural predictive modeling.
Skill level: Beginner/intermediate
Required skills: Strong coding foundation in python, including object oriented programming and writing tests, familiarity with git and git CI/CD. Some knowledge of digital signal processing and interest in neuroscience is preferred.
Time commitment: Flexible (175/350 h, 350 preferred)
Lead mentor: Fabian Sinz
Project website: GitHub - sensorium-competition/experanto: Python package to interpolate recordings and stimuli of neuroscience experiments · GitHub
Backup mentors: Polina Turishcheva, René Burghardt, Tom Olschewski
Tech keywords: Python, object oriented programming, digital signal processing, open science, timeseries, calcium imaging, electrophysiology, datasets