EnsemblePursuit-- a sparse matrix factorization algorithm for extracting co-activating neurons from large-scale recordings
Ensemble Pursuit is a matrix factorization algorithm that extracts sparse neural components of co-activating cells.
The matrix U is a sparse matrix (because of an L0 penalty in the cost function) that encodes which neurons belong to a component. V is an average timecourse of these neurons, e.g. component time course.
For more details see the wiki and our Statistical Analysis of Neural Data 2019 workshop poster
Ensembles learned using EnsemblePursuit from recordings in V1 have Gabor receptive fields.
Some ensembles are well explained by behavior PC's extracted from mouse orofacial movies.
Metadata
Release files for EnsemblePursuit 0.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| EnsemblePursuit-0.0.3.tar.gz | 5.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| EnsemblePursuit-0.0.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 23.0 kB
Release files / EnsemblePursuit-0.0.3.tar.gz
| Download URL | EnsemblePursuit-0.0.3.tar.gz |
|---|---|
| Size | 5.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
10a40bfd2bca5f32f97a2293f59f000e70a3624c5132298aa5136baf7b8488ab
|
|
BLAKE2b-256 checksum How to use checksums |
235f1d8ecff042d35565d41e17ceb6fd6b8c7992d6776d997fc4740257c1e18c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4
|
Release files / EnsemblePursuit-0.0.3-py3-none-any.whl
| Download URL | EnsemblePursuit-0.0.3-py3-none-any.whl |
|---|---|
| Size | 18.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8f529e180a7edcc067c5d232395a19916a6b149332130429548b4974a057def9
|
|
BLAKE2b-256 checksum How to use checksums |
492f59b080622824f89d7a31189998175d364c79a1c91d614d6778b594437f23
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/2.0.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.6.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4
|