Neural Decoding & Analysis
- Neural_Decoding - Comprehensive Python package for decoding neural activity using modern machine learning methods including LSTMs, neural networks, and gradient boosting
- Spykes (Documentation) - Python tools for spike data analysis and visualization
- pyglmnet - Python implementation of elastic-net regularized generalized linear models (Paper)
- SpykesML - Machine learning algorithms for spike prediction
- DAD (Distribution Alignment Decoder) - Novel decoder for neural data that aligns distributions
Educational & Teaching Resources
Datasets
Movement & Motor Control
- DREAM Database - Database for Reaching Experiments And Models, containing standardized reaching movement data from multiple labs
- Requires CRCNS login for download
- Includes MATLAB tools and documentation
- Overview paper
Neural Recordings
- Neural Decoding Datasets - Three datasets available with our Neural_Decoding package:
- Motor cortex recordings
- Somatosensory cortex recordings
- Hippocampus recordings
- Available in both MATLAB and Python formats
Open Science Framework
Educational Initiatives
Neuromatch Academy
Neuromatch Academy - Free, online computational neuroscience summer school co-founded by Konrad Kording
- Course Materials - Complete curriculum as interactive Jupyter notebooks
- GitHub Repository - All course content and tutorials
- Topics include: modeling, machine learning, dynamics, causality, and deep learning
- Over 10,000 students trained globally since 2020
Community for Rigor - NIH/NINDS-funded initiative for teaching scientific rigor at scale
- GitHub Organization - Educational tools and materials
- Free online modules covering:
- Confirmation bias and cognitive errors
- Causation vs correlation
- Research question formulation
- Experimental design and randomization
- Statistical analysis best practices
Neuro4Pros
Neuro4Pros Summer School - Training for young computational neuroscience professors
- Co-organized with Gunnar Blohm
- Focus on rigorous science, mentoring, and lab management
Key Publications & Methods
Recent Methods Papers
Theory & Perspectives
Collaborations & Networks
Data Sharing Initiatives
- CRCNS - Collaborative Research in Computational Neuroscience
- Multiple shared datasets and models
- Focus on open science and reproducibility
For Researchers
- Neural Decoding:
pip install neural_decoding
or clone from GitHub
- Spykes:
pip install spykes
for spike analysis
- Data Access: Register at CRCNS for movement datasets
Contributing
- Most repositories accept pull requests
- Issues and bug reports welcome on GitHub
- Contact lab members for collaboration opportunities
For Students
Learning Resources
- Use our project planner app for structuring research
- Access example notebooks in each repository for implementation guidance
For questions about specific resources:
- Software issues: Open an issue on the relevant GitHub repository
- Dataset access: Contact CRCNS for database-specific questions
- Educational materials: Visit Neuromatch or C4R websites
- General inquiries: kording@upenn.edu
Last updated: August 2025