Abstract
A19 Detecting task-based fMRI compliance using plan abandonment techniques
Ramon Fraga Pereira, Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi
Task-based fMRI is a powerful approach to understand brain processes for a certain task. However, fMRI images are usually preprocessed hours, days or even months after the scan. During the functional image preprocessing stage, defects in images are detected and, in some cases, cannot be corrected. For example, technical problems with the scanner or lack of collaboration from the subject to perform the given tasks. For these cases it is necessary to realize a new scan. In order to mitigate lost scans due to patient non-compliance, we need an approach to detect such non-compliance during the scan.
A22 NeuroView: a customizable browser-base utility
Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi
The amount of data acquired for an fMRI experiment dimension wise is very large and a challenge for neuroscience studies, in particular for data analysis and visualization. Diverse tools have been developed to confront these challenges, but their analytical results can differ. Addressing those differences is not facilitated by existing tools. The goal of this Brainhack project was to build a flexible utility to analyze fMRI experimental results. This utility is called NeuroView. NeuroView allows researchers to extend the visualizations to their context: every visual behavior or interactions of this tool is customizable. We implemented NeuroView to work in Web-browsers, using JavaScript and the libraries D3.js and jQuery.
Ramon Fraga Pereira, Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi
Task-based fMRI is a powerful approach to understand brain processes for a certain task. However, fMRI images are usually preprocessed hours, days or even months after the scan. During the functional image preprocessing stage, defects in images are detected and, in some cases, cannot be corrected. For example, technical problems with the scanner or lack of collaboration from the subject to perform the given tasks. For these cases it is necessary to realize a new scan. In order to mitigate lost scans due to patient non-compliance, we need an approach to detect such non-compliance during the scan.
A22 NeuroView: a customizable browser-base utility
Anibal Sólon Heinsfeld, Alexandre Rosa Franco, Augusto Buchweitz, Felipe Meneguzzi
The amount of data acquired for an fMRI experiment dimension wise is very large and a challenge for neuroscience studies, in particular for data analysis and visualization. Diverse tools have been developed to confront these challenges, but their analytical results can differ. Addressing those differences is not facilitated by existing tools. The goal of this Brainhack project was to build a flexible utility to analyze fMRI experimental results. This utility is called NeuroView. NeuroView allows researchers to extend the visualizations to their context: every visual behavior or interactions of this tool is customizable. We implemented NeuroView to work in Web-browsers, using JavaScript and the libraries D3.js and jQuery.
| Original language | English |
|---|---|
| Journal | Gigascience |
| Volume | 5 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2016 |