https://github.com/feilong/searchlights

Precomputed searchlights for surface-based analysis.
https://github.com/feilong/searchlights

brain fmri mvpa searchlight searchlight-analysis surface

Last synced: 3 months ago
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Precomputed searchlights for surface-based analysis.

• Host: GitHub
• URL: https://github.com/feilong/searchlights
• Owner: feilong
• License: bsd-3-clause
• Created: 2022-02-01T21:17:44.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2022-08-01T04:19:28.000Z (over 3 years ago)
• Last Synced: 2024-07-07T22:02:30.791Z (almost 2 years ago)
• Topics: brain, fmri, mvpa, searchlight, searchlight-analysis, surface
• Language: Python
• Homepage: https://feilong.github.io/searchlights/
• Size: 51.8 MB
• Stars: 3
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

          
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`searchlights` is a Python package that provides precomputed searchlights for surface-based analysis of fMRI data.

It only depends on `NumPy`.

## Installation

The package can be installed with pip:

```bash

python -m pip install searchlights

```

## Example usage

The surface-based fMRI data we usually use (e.g., [Feilong et al., 2018](https://doi.org/10.1016/j.neuroimage.2018.08.029)) are in `fsaverage` space, downsampled to a lower resolution (`icoorder5`, approximately 3 mm vertex spacing).

The surface has 9372 vertices for the left hemisphere, and 9370 vertices for the right hemisphere.

The code below shows how to get the searchlights for the left hemisphere with a 20 mm radius.

```python

import numpy as np

from searchlights import get_searchlights

sls = get_searchlights('l', 20, 'fsaverage')

```

See the [documentation](https://feilong.github.io/searchlights/#example) for more examples and details.