EZFragility
Science Score: 39.0%
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○Scientific vocabulary similarity
Low similarity (16.5%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: Jiefei-Wang
- Language: R
- Default Branch: main
- Size: 132 MB
Statistics
- Stars: 2
- Watchers: 2
- Forks: 3
- Open Issues: 2
- Releases: 0
Metadata Files
README.md
EZFragility: Epileptogenic Zone Localization Based on neural Fragility EEG marker
Introduction
The goal of this Rpackage is to allow neuroscientists to reproduce and test the neural fragility method described in (Li et al. 2017, 2021). This method implements an intracranial EEG (iEEG) marker of the epileptogenic zone localization. In this method, seizures are conceptualized as transitions from a stable networked system to an unstable one. To quantify this, node fragility is computed from linear network models, measuring each node’s susceptibility to destabilization. There are significant details missing in (Li et al. 2017, 2021) to reproduce the neural fragility method and adjust the parameters. This Rpackage aims to identify and fill up the implementation details. It will also allow users to test the method parameters on their data.
Installation
To install the package from GitHub
r
devtools::install_github("Jiefei-Wang/EZFragility")
EZFragility package tutorial
To load the package
r
library(EZFragility)
If you are working with the source code, you can load the package with
r
devtools::load_all()
The package contains an example data. To see the first 5 rows and columns of the data, type
r
pt01EcoG[1:5, 1:5]
The package contains an example results. To see it, type
r
pt01Frag
For explanations on how to use the package please refer to the vignette.
r
vignette("Intro_to_EZFragility", package = "EZFragility")
Implementation details
The method is based on building a discrete time linear system computing
a stable adjacency matrix A for the evolution of x(t).
$x(t+1)=A x(t)$ with $x_i(t)$ the iEEG signal at time $t$ for electrode
$i$. A is computed for a series of time windows to derive the fragility
row.
In this package, we are applying a ridge regression to solve the matrix
A. In (Li et al. 2017, 2021), a regularization parameter value of 1e-4
is recommended, however testing on the data from patient pt01 from the
Fragility data set (data subset available in this package) this value
does not ensure that A is always stable. To tackle this issue, we have
implemented a dichotomy to search for the lowest stable lambda value
rendering the matrix A stable (see R function ridgeSearch in file
ridge.r).
The method to compute the row perturbation is also not clear. To compute the fragility row, a minimum 2-induced norm additive row perturbation $\Delta$ is computed to destabilize the linear network placing an eigenvalue of $A+\Delta$ at $\lambda=\sigma+j\omega$. The minimum norm is a function of $\lambda$ given in (Li et al. 2017) (see function fragilityRow in the scrip fragility.r), however the paper does not describe how to choose $\lambda$ with $|\lambda|=1$. To tackle this issue, we search for the value that minimize the norm of $\Delta$.
References
Owner
- Name: Jiefei Wang
- Login: Jiefei-Wang
- Kind: user
- Location: Buffalo
- Company: University at Buffalo
- Repositories: 9
- Profile: https://github.com/Jiefei-Wang
GitHub Events
Total
- Create event: 43
- Issues event: 4
- Watch event: 3
- Delete event: 40
- Issue comment event: 12
- Member event: 1
- Push event: 181
- Pull request review comment event: 36
- Pull request review event: 40
- Pull request event: 70
- Fork event: 1
Last Year
- Create event: 43
- Issues event: 4
- Watch event: 3
- Delete event: 40
- Issue comment event: 12
- Member event: 1
- Push event: 181
- Pull request review comment event: 36
- Pull request review event: 40
- Pull request event: 70
- Fork event: 1
Issues and Pull Requests
Last synced: 10 months ago
All Time
- Total issues: 2
- Total pull requests: 65
- Average time to close issues: 6 days
- Average time to close pull requests: 2 days
- Total issue authors: 1
- Total pull request authors: 3
- Average comments per issue: 0.0
- Average comments per pull request: 0.28
- Merged pull requests: 48
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 2
- Pull requests: 65
- Average time to close issues: 6 days
- Average time to close pull requests: 2 days
- Issue authors: 1
- Pull request authors: 3
- Average comments per issue: 0.0
- Average comments per pull request: 0.28
- Merged pull requests: 48
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- Jiefei-Wang (2)
Pull Request Authors
- Jiefei-Wang (28)
- imalagaris (20)
- CecileLes (19)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- cran 98 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 2
- Total maintainers: 1
cran.r-project.org: EZFragility
Compute Neural Fragility for Ictal iEEG Time Series
- Homepage: https://github.com/Jiefei-Wang/EZFragility
- Documentation: http://cran.r-project.org/web/packages/EZFragility/EZFragility.pdf
- License: GPL (≥ 3)
-
Latest release: 2.0.1
published 10 months ago
Rankings
Maintainers (1)
Dependencies
- R >= 2.10 depends