In a previous oddball task study, it was shown that the inclusion of electrophysiology (EEG), that is, single-trial P3 ERP parameters, in the analysis of fMRI responses can detect activation that is not apparent with conventional fMRI data modeling strategies [Warbrick, T., Mobascher, A., Brinkmeyer, J., Musso, F., Richter, N., Stoecker, T., et al. Single-trial P3 amplitude and latency informed event-related fMRI models yield different BOLD response patterns to a target detection task. Neuroimage, 47, 1532–1544, 2009]. Given that P3 is modulated by nicotine, including P3 parameters in the fMRI analysis might provide additional information about nicotine effects on brain function. A 1-mg nasal nicotine spray (0.5 mg each nostril) or placebo (pepper) spray was administered in a double-blind, placebo-controlled, within-subject, randomized, cross-over design. Simultaneous EEG-fMRI and behavioral data were recorded from 19 current smokers in response to an oddball-type visual choice RT task. Conventional general linear model analysis and single-trial P3 amplitude informed general linear model analysis of the fMRI data were performed. Comparing the nicotine with the placebo condition, reduced RTs in the nicotine condition were related to decreased BOLD responses in the conventional analysis encompassing the superior parietal lobule, the precuneus, and the lateral occipital cortex. On the other hand, reduced RTs were related to increased BOLD responses in the precentral and postcentral gyri, and ACC in the EEG-informed fMRI analysis. Our results show how integrated analyses of simultaneous EEG-fMRI data can be used to detect nicotine effects that would not have been revealed through conventional analysis of either measure in isolation. This emphasizes the significance of applying multimodal imaging methods to pharmacoimaging.

Human brain lesion studies first investigated the biological roots of cognitive functions including language in the late 1800s. Neuroimaging studies have reported correlation findings with general intelligence predominantly in fronto-parietal cortical areas. However, there is still little evidence about the relationship between verbal intelligence and structural properties of the brain. We predicted that verbal performance is related to language regions of Broca's and Wernicke's areas. Verbal intelligence quotient (vIQ) was assessed in 30 healthy young subjects. T1-weighted MRI and diffusion tensor imaging data sets were acquired. Voxel-wise regression analyses were used to correlate fractional anisotropy (FA) and mean diffusivity values with vIQ. Moreover, regression analyses of regional brain volume with vIQ were performed adopting voxel-based morphometry (VBM) and ROI methodology. Our analyses revealed a significant negative correlation between vIQ and FA and a significant positive correlation between vIQ and mean diffusivity in the left-hemispheric Broca's area. VBM regression analyses did not show significant results, whereas a subsequent ROI analysis of Broca's area FA peak cluster demonstrated a positive correlation of gray matter volume and vIQ. These findings suggest that cortical thickness in Broca's area contributes to verbal intelligence. Diffusion parameters predicted gray matter ratio in Broca's area more sensitive than VBM methodology.