NeuralFlow - version 3

Short description

Computational framework for modeling neural activity with continuous latent Langevin dynamics.

Quick installation: pip install git+https://github.com/engellab/neuralflow

The source code for the following publications:

1) M Genkin, KV Shenoy, C Chandrasekaran, TA Engel, The dynamics and geometry of choice in premotor cortex, bioRxiv (2023)

Link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10401920/

2) Genkin, M., Hughes, O. and Engel, T.A. Learning non-stationary Langevin dynamics from stochastic observations of latent trajectories. Nat Commun 12, 5986 (2021).

Link: https://rdcu.be/czqGP

3) Genkin, M., Engel, T.A. Moving beyond generalization to accurate interpretation of flexible models. Nat Mach Intell 2, 674–683 (2020).

Link: https://www.nature.com/articles/s42256-020-00242-6/

Free access: https://rdcu.be/b9cW3

Installation

Package only: pip install git+https://github.com/engellab/neuralflow

Package with examples:

git clone https://github.com/engellab/neuralflow
cd neuralflow
pip install .

If you have issues with Cython extension, and want to use precomplied .c instead, open setup.py and change line 7 to USE_CYTHON = 0

GPU support

If your platform has CUDA-enabled GPU, install cupy package. Then you can use GPU device for optimization. Package passes unit tests with cupy-cuda12x==12.2.0

documentation

https://neuralflow.readthedocs.io/

Getting started

See examples

Deep dive

See tests