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Abcdspec-compliantRun on Brainlife.io

app-rereference

This is an app that takes EEG data in MNE Epochs format and recomputes the reference from collection mode to chosen (defaults to average reference)

  1. Input file is mne/Epochs
  2. Input is a choice of average, REST (Reference Electrode Standardization Technique infinity reference), or a list of channels to use.
  3. The output file is mne/Epochs, as well.

Authors

Copyright (c) 2022 brainlife.io The University of Texas at Austin

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your code and publications. Copy and past the following lines into your repository when using this code.

NSF-BCS-1734853NSF-BCS-1636893NSF-ACI-1916518NSF-IIS-1912270NIH-NIBIB-R01EB029272

Citations

We ask that you the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.

  1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/10.25663/bl.app.444 via the "Execute" tab.

Running Locally (on your machine)

  1. git clone this repo.
  2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.
{
"t1": "t1.nii.gz"
}
  1. Launch the App by executing main
./main

Sample Datasets

If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 && mv 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 .

Output

All output file (a resampled T1w NIFTI-1 file) will be generated inside the current working directory (pwd), inside a specifc directory called:

out_dir

Dependencies

This App requires MNE/Python to run.

About

App for rereferencing EEG recordings

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
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Abcdspec-compliantRun on Brainlife.io

app-rereference

This is an app that takes EEG data in MNE Epochs format and recomputes the reference from collection mode to chosen (defaults to average reference)

  1. Input file is mne/Epochs
  2. Input is a choice of average, REST (Reference Electrode Standardization Technique infinity reference), or a list of channels to use.
  3. The output file is mne/Epochs, as well.

Authors

Copyright (c) 2022 brainlife.io The University of Texas at Austin

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your code and publications. Copy and past the following lines into your repository when using this code.

NSF-BCS-1734853NSF-BCS-1636893NSF-ACI-1916518NSF-IIS-1912270NIH-NIBIB-R01EB029272

Citations

We ask that you the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.

  1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/10.25663/bl.app.444 via the "Execute" tab.

Running Locally (on your machine)

  1. git clone this repo.
  2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.
{
"t1": "t1.nii.gz"
}
  1. Launch the App by executing main
./main

Sample Datasets

If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 && mv 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 .

Output

All output file (a resampled T1w NIFTI-1 file) will be generated inside the current working directory (pwd), inside a specifc directory called:

out_dir

Dependencies

This App requires MNE/Python to run.

About

App for rereferencing EEG recordings

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
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Abcdspec-compliantRun on Brainlife.io

app-rereference

This is an app that takes EEG data in MNE Epochs format and recomputes the reference from collection mode to chosen (defaults to average reference)

  1. Input file is mne/Epochs
  2. Input is a choice of average, REST (Reference Electrode Standardization Technique infinity reference), or a list of channels to use.
  3. The output file is mne/Epochs, as well.

Authors

Copyright (c) 2022 brainlife.io The University of Texas at Austin

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your code and publications. Copy and past the following lines into your repository when using this code.

NSF-BCS-1734853NSF-BCS-1636893NSF-ACI-1916518NSF-IIS-1912270NIH-NIBIB-R01EB029272

Citations

We ask that you the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.

  1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/10.25663/bl.app.444 via the "Execute" tab.

Running Locally (on your machine)

  1. git clone this repo.
  2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.
{
"t1": "t1.nii.gz"
}
  1. Launch the App by executing main
./main

Sample Datasets

If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 && mv 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 .

Output

All output file (a resampled T1w NIFTI-1 file) will be generated inside the current working directory (pwd), inside a specifc directory called:

out_dir

Dependencies

This App requires MNE/Python to run.

About

App for rereferencing EEG recordings

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

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Abcdspec-compliantRun on Brainlife.io

app-rereference

This is an app that takes EEG data in MNE Epochs format and recomputes the reference from collection mode to chosen (defaults to average reference)

  1. Input file is mne/Epochs
  2. Input is a choice of average, REST (Reference Electrode Standardization Technique infinity reference), or a list of channels to use.
  3. The output file is mne/Epochs, as well.

Authors

Copyright (c) 2022 brainlife.io The University of Texas at Austin

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your code and publications. Copy and past the following lines into your repository when using this code.

NSF-BCS-1734853NSF-BCS-1636893NSF-ACI-1916518NSF-IIS-1912270NIH-NIBIB-R01EB029272

Citations

We ask that you the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.

  1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/10.25663/bl.app.444 via the "Execute" tab.

Running Locally (on your machine)

  1. git clone this repo.
  2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.
{
"t1": "t1.nii.gz"
}
  1. Launch the App by executing main
./main

Sample Datasets

If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 && mv 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 .

Output

All output file (a resampled T1w NIFTI-1 file) will be generated inside the current working directory (pwd), inside a specifc directory called:

out_dir

Dependencies

This App requires MNE/Python to run.

About

App for rereferencing EEG recordings

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content

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Abcdspec-compliantRun on Brainlife.io

app-rereference

This is an app that takes EEG data in MNE Epochs format and recomputes the reference from collection mode to chosen (defaults to average reference)

  1. Input file is mne/Epochs
  2. Input is a choice of average, REST (Reference Electrode Standardization Technique infinity reference), or a list of channels to use.
  3. The output file is mne/Epochs, as well.

Authors

Copyright (c) 2022 brainlife.io The University of Texas at Austin

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your code and publications. Copy and past the following lines into your repository when using this code.

NSF-BCS-1734853NSF-BCS-1636893NSF-ACI-1916518NSF-IIS-1912270NIH-NIBIB-R01EB029272

Citations

We ask that you the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.

  1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/10.25663/bl.app.444 via the "Execute" tab.

Running Locally (on your machine)

  1. git clone this repo.
  2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.
{
"t1": "t1.nii.gz"
}
  1. Launch the App by executing main
./main

Sample Datasets

If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 && mv 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 .

Output

All output file (a resampled T1w NIFTI-1 file) will be generated inside the current working directory (pwd), inside a specifc directory called:

out_dir

Dependencies

This App requires MNE/Python to run.

About

App for rereferencing EEG recordings

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

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9 Commits

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Abcdspec-compliantRun on Brainlife.io

app-rereference

This is an app that takes EEG data in MNE Epochs format and recomputes the reference from collection mode to chosen (defaults to average reference)

  1. Input file is mne/Epochs
  2. Input is a choice of average, REST (Reference Electrode Standardization Technique infinity reference), or a list of channels to use.
  3. The output file is mne/Epochs, as well.

Authors

Copyright (c) 2022 brainlife.io The University of Texas at Austin

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your code and publications. Copy and past the following lines into your repository when using this code.

NSF-BCS-1734853NSF-BCS-1636893NSF-ACI-1916518NSF-IIS-1912270NIH-NIBIB-R01EB029272

Citations

We ask that you the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.

  1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/10.25663/bl.app.444 via the "Execute" tab.

Running Locally (on your machine)

  1. git clone this repo.
  2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.
{
"t1": "t1.nii.gz"
}
  1. Launch the App by executing main
./main

Sample Datasets

If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 && mv 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 .

Output

All output file (a resampled T1w NIFTI-1 file) will be generated inside the current working directory (pwd), inside a specifc directory called:

out_dir

Dependencies

This App requires MNE/Python to run.

About

App for rereferencing EEG recordings

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

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9 Commits

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Abcdspec-compliantRun on Brainlife.io

app-rereference

This is an app that takes EEG data in MNE Epochs format and recomputes the reference from collection mode to chosen (defaults to average reference)

  1. Input file is mne/Epochs
  2. Input is a choice of average, REST (Reference Electrode Standardization Technique infinity reference), or a list of channels to use.
  3. The output file is mne/Epochs, as well.

Authors

Copyright (c) 2022 brainlife.io The University of Texas at Austin

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your code and publications. Copy and past the following lines into your repository when using this code.

NSF-BCS-1734853NSF-BCS-1636893NSF-ACI-1916518NSF-IIS-1912270NIH-NIBIB-R01EB029272

Citations

We ask that you the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.

  1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/10.25663/bl.app.444 via the "Execute" tab.

Running Locally (on your machine)

  1. git clone this repo.
  2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.
{
"t1": "t1.nii.gz"
}
  1. Launch the App by executing main
./main

Sample Datasets

If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 && mv 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 .

Output

All output file (a resampled T1w NIFTI-1 file) will be generated inside the current working directory (pwd), inside a specifc directory called:

out_dir

Dependencies

This App requires MNE/Python to run.

About

App for rereferencing EEG recordings

Topics

Resources

Stars

0 stars

Watchers

0 watching

Forks

Releases

Packages

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Abcdspec-compliantRun on Brainlife.io

app-rereference

This is an app that takes EEG data in MNE Epochs format and recomputes the reference from collection mode to chosen (defaults to average reference)

  1. Input file is mne/Epochs
  2. Input is a choice of average, REST (Reference Electrode Standardization Technique infinity reference), or a list of channels to use.
  3. The output file is mne/Epochs, as well.

Authors

Copyright (c) 2022 brainlife.io The University of Texas at Austin

Funding Acknowledgement

brainlife.io is publicly funded and for the sustainability of the project it is helpful to Acknowledge the use of the platform. We kindly ask that you acknowledge the funding below in your code and publications. Copy and past the following lines into your repository when using this code.

NSF-BCS-1734853NSF-BCS-1636893NSF-ACI-1916518NSF-IIS-1912270NIH-NIBIB-R01EB029272

Citations

We ask that you the following articles when publishing papers that used data, code or other resources created by the brainlife.io community.

  1. Avesani, P., McPherson, B., Hayashi, S. et al. The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services. Sci Data 6, 69 (2019). https://doi.org/10.1038/s41597-019-0073-y

Running the App

On Brainlife.io

You can submit this App online at https://doi.org/10.25663/bl.app.444 via the "Execute" tab.

Running Locally (on your machine)

  1. git clone this repo.
  2. Inside the cloned directory, create config.json with something like the following content with paths to your input files.
{
"t1": "t1.nii.gz"
}
  1. Launch the App by executing main
./main

Sample Datasets

If you don't have your own input file, you can download sample datasets from Brainlife.io, or you can use Brainlife CLI.

npm install -g brainlife
bl login
mkdir input
bl dataset download 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 && mv 5a0f0fad2c214c9ba8624376#5a050966eec2b300611abff2 .

Output

All output file (a resampled T1w NIFTI-1 file) will be generated inside the current working directory (pwd), inside a specifc directory called:

out_dir

Dependencies

This App requires MNE/Python to run.

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App for rereferencing EEG recordings

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