https://github.com/webstorms/NeuralPred
Tip revision: 9eccfe575524736f25f4f3759fe04648f22554de authored by Luke Taylor on 09 April 2024, 14:00:54 UTC
Added brainbox version.
Added brainbox version.
Tip revision: 9eccfe5
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.