fMRat: an extension of SPM for a fully automatic analysis of rodent brain functional magnetic resonance series

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• 作者：Cristina Chavarrías ; Verónica García-Vázquez…
• 刊名：Medical and Biological Engineering and Computing
• 出版年：2016
• 出版时间：May 2016
• 年：2016
• 卷：54
• 期：5
• 页码：743-752
• 全文大小：3,284 KB
• 刊物类别：Engineering
• 刊物主题：Biomedical Engineering
  Human Physiology
  Imaging and Radiology
  Computer Applications
  Neurosciences
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1741-0444
• 卷排序：54

文摘

The purpose of this study was to develop a multi-platform automatic software tool for full processing of fMRI rodent studies. Existing tools require the usage of several different plug-ins, a significant user interaction and/or programming skills. Based on a user-friendly interface, the tool provides statistical parametric brain maps (t and Z) and percentage of signal change for user-provided regions of interest. The tool is coded in MATLAB (MathWorks®) and implemented as a plug-in for SPM (Statistical Parametric Mapping, the Wellcome Trust Centre for Neuroimaging). The automatic pipeline loads default parameters that are appropriate for preclinical studies and processes multiple subjects in batch mode (from images in either Nifti or raw Bruker format). In advanced mode, all processing steps can be selected or deselected and executed independently. Processing parameters and workflow were optimized for rat studies and assessed using 460 male-rat fMRI series on which we tested five smoothing kernel sizes and three different hemodynamic models. A smoothing kernel of FWHM = 1.2 mm (four times the voxel size) yielded the highest t values at the somatosensorial primary cortex, and a boxcar response function provided the lowest residual variance after fitting. fMRat offers the features of a thorough SPM-based analysis combined with the functionality of several SPM extensions in a single automatic pipeline with a user-friendly interface. The code and sample images can be downloaded from https://github.com/HGGM-LIM/fmrat.KeywordsfMRIAutomatic analysisRatSPM