LI-tool: a new toolbox to assess lateralization in functional MR-data.

Area of Science:

• Neuroimaging
• Brain Activation Analysis
• Cognitive Neuroscience

Background:

• The lateralization index (LI) is a standard metric for quantifying brain activation asymmetry in neuroimaging.
• Functional magnetic resonance imaging (fMRI) is frequently used to measure these laterality effects.
• Existing LI calculation methods have known limitations.

Purpose of the Study:

• To critically examine and compare various approaches for computing the lateralization index.
• To identify and address the drawbacks associated with traditional LI calculations.
• To develop and implement improved, standardized methods for assessing laterality effects in fMRI.

Main Methods:

• Evaluation of 100 synthetic datasets and fMRI data from 12 subjects.
• Comparison of different lateralization index calculation strategies.
• Implementation of current and novel approaches within a SPM-based toolbox.

Main Results:

• The standard lateralization index (LI) is susceptible to outliers, data sparsity, and thresholding effects.
• Regional variability in activation is often not adequately considered in LI calculations.
• Investigated optional processing steps demonstrated potential to enhance the reliability of computed indices.

Conclusions:

• Current lateralization index computation methods present significant limitations for robust brain asymmetry analysis.
• Implementing standardized and reproducible evaluation approaches is crucial for laterality research.
• A versatile toolbox integrating improved methods is provided for accessible laterality effect assessment in fMRI.