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Despite significant advances in multimodal imaging techniques and analysis approaches, unimodal studies are still the predominant way to investigate brain changes or group differences, including structural magnetic resonance imaging (sMRI), functional MRI (fMRI), diffusion tensor imaging (DTI) and electroencephalography (EEG). Multimodal brain studies can be used to understand the complex interplay of anatomical, functional and physiological brain alterations or development, and to better comprehend the biological significance of multiple imaging measures. To examine the function-structure associations of the brain in a more comprehensive and integrated manner, we reviewed a number of multimodal studies that combined two or more functional (fMRI and/or EEG) and structural (sMRI and/or DTI) modalities. In this review paper, we specifically focused onmultimodal neuroimaging studies on cognition, aging, disease and behavior. We also compared multiple analysis approaches, including univariate and multivariate methods. The possible strengths and limitations of each method are highlighted, which can guide readers when selecting a method based on a given research question. In particular, we believe that multimodal fusion approaches will shed further light on the neuronalmechanisms underlying the major structural and functional pathophysiological features of both the healthy brain (e.g. development) or the diseased brain (e. g. mental illness) and, in the latter case, may provide a more sensitive measure than unimodal imaging for disease classification, e. g. multimodal biomarkers, which potentially can be used to support clinical diagnosis based on neuroimaging techniques. (C) 2013 Elsevier Inc. All rights reserved.

When both structural magnetic resonance imaging (sMRI) and functional MRI (fMRI) data are collected they are typically analyzed separately and the joint information is not examined. Techniques that examine joint information can help to find hidden traits in complex disorders such as schizophrenia. The brain is vastly interconnected, and local brain morphology may influence functional activity at distant regions. In this paper we introduce three methods to identify inter-correlations among sMRI and fMRI voxels within the whole brain. We apply these methods to examine sMRI gray matter data and fMRI data derived from an auditory sensorimotor task from a large study of schizophrenia. In Method 1 the sMRI-fMRI cross-correlation matrix is reduced to a histogram and results show that healthy controls (HC) have stronger correlations than do patients with schizophrenia (SZ). In Method 2 the spatial information of sMRI-fMRI correlations is retained. Structural regions in the cerebellum and frontal regions show more positive and more negative correlations, respectively, with functional regions in HC than in SZ. In Method 3 significant sMRI-fMRI inter-regional links are detected, with regions in the cerebellum showing more significant positive correlations with functional regions in HC relative to SZ. Results from all three methods indicate that the linkage between gray matter and functional activation is stronger in HC than SZ. The methods introduced can be easily extended to comprehensively correlate large data sets.

Ab initio molecular orbital calculations (Hartree–Fock, HF and density functional theory, DFT) of the 17 O NMR electrical field gradient (EFG) parameters for the bridging oxygen (O B ) in the model cluster H 4 P 2 O 7 are presented. The variation of the quadrupolar coupling constant ( C Q ) and asymmetry parameter ( η Q ) for the EFG of the bridging oxygen was shown to be a function of both the bridging P–O B –P bond angle and the OP–O B –PO conformation. These ab initio calculations allowed empirical relationships between the 17 O NMR EFG parameters and the P–O B –P bond angle to be tabulated for a wide range of OP–O B –PO conformations. For experimentally realistic ranges of the P–O B –P bond angle, the 17 O NMR EFG parameters are dominated by variations in the P–O B –P bond angle, with minor changes due to the OP–O B –PO conformation. These calculations also demonstrated systematic differences in the predicted 17 O EFG parameters obtained using HF and DFT level of theory.