Evaluation of multiple comparison correction procedures in drug assessment studies using LORETA maps.

Area of Science:

• Neuroscience
• Pharmacology
• Medical Imaging

Background:

• Identifying drug-affected brain regions is crucial for neuropharmacological drug development.
• Electroencephalography (EEG) source imaging techniques like LORETA are used to pinpoint these brain structures.
• Statistical methods for correcting multiple comparisons are essential for accurate analysis of LORETA maps.

Purpose of the Study:

• To evaluate various multiple comparison correction methods for LORETA maps.
• To apply these methods to a real pharmaco-EEG study investigating benzodiazepine effects.
• To determine the most effective correction method for analyzing drug-induced changes in brain activity.

Main Methods:

• EEG recordings from nine volunteers receiving placebo and escalating doses of alprazolam (0.25, 0.5, 1 mg) in a randomized crossover double-blind design.
• Application of different multiple comparison correction techniques to LORETA-processed EEG data.
• Utilized the cluster mass approach for analyzing pharmacologically induced changes in intracerebral current density.

Main Results:

• The choice of multiple comparison correction procedure critically influenced the identification of statistically significant brain regions.
• The cluster mass method effectively demonstrated that increasing doses of alprazolam led to dose-dependent increases in the intensity and spatial extent of neuropharmacological effects.
• Pharmacologically induced changes in intracerebral current density were quantifiable and dependent on drug dosage.

Conclusions:

• Multiple comparison correction is a critical step in pharmaco-EEG analysis using LORETA, impacting the interpretation of drug effects.
• The cluster mass approach offers a robust method for revealing dose-dependent neuropharmacological changes.
• This study highlights the importance of selecting appropriate statistical methods for accurate drug development and understanding central nervous system effects.