Research map / Probabilistic and scientific modeling / Dynamical systems
Extracting computational mechanisms from neural data using low-rank RNNs
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| fit low-rank RNN with LINT instead of truncating SVD of the full-rank connectivity | full-rank RNN trained on CDM · CDM trajectory similarity | trajectory fit: rank 1 vs rank 4 or 5 for comparable accuracy | Helped |
| fit low-rank RNN with LINT instead of truncating SVD | full-rank RNN trained on DMS · DMS trajectory similarity | trajectory fit | Helped |
| increase rank of inferred lrRNN beyond 1 (CDM) or 2 (DMS) (ablation) | LINT · CDM and DMS full-rank fits | goodness of fit | No clear effect |
| increase rank of inferred network on monkey recordings (ablation) | LINT · monkey A and F recordings | R2 | No clear effect |
| constrain fitted network to rank one instead of full rank, when subsampling neurons (ablation) | LINT on CDM full-rank network · subsampled neurons | trajectory similarity | Mixed |
Closest papers by meaning
- Inferring stochastic low-rank recurrent neural networks from neural data (NeurIPS 2024 · similarity 0.93)
- Learning Reveals Invisible Structure in Low-Rank RNNs (NeurIPS 2026 · similarity 0.90)
- Inference of Neural Dynamics Using Switching Recurrent Neural Networks (NeurIPS 2024 · similarity 0.90)
- Probabilistic Decomposed Linear Dynamical Systems for Robust Discovery of Latent Neural Dynamics (NeurIPS 2024 · similarity 0.89)
- Mechanistic Interpretability of RNNs emulating Hidden Markov Models (NeurIPS 2025 · similarity 0.89)
- Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems (NeurIPS 2024 · similarity 0.88)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.