Sparse component analysis: A method that uncovers separable computations within neural population activity

2026/07/01 by Andrew J. Zimnik, Xinyue An, K. Cora Ames +9 · 1 voice
Biochemistry, Genetics and Molecular Biology · Neuroscience · #Cell Image Analysis Techniques #Functional Brain Connectivity Studies #Neural dynamics and brain function

paper · doi:10.1016/j.neuron.2026.05.022

crossref issued 2026/07/01 · crossref published 2026/07/01 · crossref published-print 2026/07/01 · openalex publication_date 2026/07/01 · crossref created 2026/07/02 · openalex created_date 2026/07/03 · crossref deposited 2026/07/04 · crossref indexed 2026/07/04 · openalex updated_date 2026/07/27

Citations

• Sparse Principal Component Analysis
• Independent component analysis: algorithms and applications
• Computation Through Neural Population Dynamics
• Compositional neural dynamics during reaching
• Improving Dictionary Learning with Gated Sparse Autoencoders
• Sparse Autoencoders Find Highly Interpretable Features in Language Models
• Geometric Optimisation on Manifolds with Applications to Deep Learning
• Attractor and integrator networks in the brain
• Targeted Neural Dynamical Modeling
• PyTorch: An Imperative Style, High-Performance Deep Learning Library
• Spike Sorting by Convolutional Dictionary Learning
• Adam: A Method for Stochastic Optimization
• Opening the Black Box: Low-Dimensional Dynamics in High-Dimensional Recurrent Neural Networks

Discussions

• Please find the original paper and #SCA implementation here: 📄 doi.org/10.1016/j.ne... 👨‍💻 github.com/glaserlab/sca #Neuroscience #CompNeuro #NeuralDynamics [bsky, 1 points, 1 comments]