An NWB extension for storing the cortical surface of subjects in ECoG experiments
Project description
ndx-ecog Extension for NWB:N
Author: Ben Dichter
There are three data types, Surface
, CorticalSurfaces
, and ECoGSubject
. CorticalSurfaces
is simply a group (like a folder) to put Surface
objects into. Surface
holds surface mesh data (vertices and triangular faces) for sections of cortex. ECoGSubject
is an extension of Subject
that allows you to add the CorticalSurfaces
object to /general/subject
.
Usage
python
install:
pip install ndx_ecog
write:
import pynwb
from ndx_ecog import CorticalSurfaces, ECoGSubject
nwbfile = pynwb.NWBFile(...)
...
cortical_surfaces = CorticalSurfaces()
## loop me
cortical_surfaces.create_surface(name=name, faces=faces, vertices=veritices)
##
nwbfile.subject = ECoGSubject(cortical_surfaces=cortical_surfaces)
You can optionally attach images of the subject's brain:
from pynwb.base import Images
from pynwb.image import GrayscaleImage
subject.images = Images(name='subject images', images=[GrayscaleImage('image1', data=image_data)])
read:
import nwbext_ecog
from pynwb import NWBHDF5IO
io = NWBHDF5IO('path_to_file.nwb','r')
nwb = io.read()
nwb.subject.cortical_surfaces
MATLAB
install:
generateExtension('/path/to/ndx-ecog/spec/ndx-ecog.namespace.yaml');
write:
cortical_surfaces = types.ecog.CorticalSurfaces;
%%% loop me
surf = types.ecog.Surface('faces', faces, 'vertices', vertices);
cortical_surfaces.surface.set(surface_name, surf);
%%%
file.subject = types.ecog.ECoGSubject(name, cortical_surfaces);
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
ndx-ecog-0.1.1.tar.gz
(14.7 kB
view hashes)
Built Distribution
Close
Hashes for ndx_ecog-0.1.1-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 88e40f5d0403889198815144602ea16c84a20a88a4044b437546996b9ac15d15 |
|
MD5 | 09f5160a9d0168b0539ff92233374990 |
|
BLAKE2b-256 | d3da10586604f20f586471e2c34d93ab850e3279e827e52bb9209acc21500d76 |