https://github.com/webstorms/NeuralPred
Tip revision: 1484b1ae509bf58a2cc2f711e525fd1d225b9b79 authored by Luke Taylor on 07 October 2023, 15:17:28 UTC
typo fix
typo fix
Tip revision: 1484b1a
README.md
Part of the accompanying code repository to the "Hierarchical temporal prediction captures motion processing along the visual pathway" paper. This repo contains the code to perform the neural V1 fits.
## Installation
```bash
conda env create -f envs/environment.yml
conda env create -f envs/prednet.yml
```
## Clone control model repos
Clone repos into the project's ```dependencies``` folder.
```bash
git clone https://github.com/coxlab/prednet.git
git clone https://github.com/sacadena/Cadena2019PlosCB.git
git clone https://github.com/ben-willmore/bwt.git
git clone https://github.com/webstorms/StackTP.git
```
## Download V1 data
Image V1 dataset obtainable from Cadena et al. 2019: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1006897
Movie V1 dataset obtainable from Nahaus and Ringach, 2007: https://crcns.org/data-sets/vc/pvc-1
Movie dataset needs to be further processed using ```scripts/build_dataset.py``` and both tensorized responses are built using ```scripts/neuron_to_tensor.py```.
## Building PC model activity dataset
```bash
conda activate neuralpred
```
All build scripts can be found under ```scripts/build_pca```. You will need to activate ```prednetbuild``` for building the prednet responses.
## Training
All readout fitting scripts can be found under ```scripts/fit_models```.
## Inspecting models
See ```notebooks/Inspection.ipynb``` to view results.
## License
Code released under the MIT license.