Microstructural brain differences predict functional hemodynamic responses in a reward processing task

A selective review of multimodal fusion methods in schizophrenia

Schizophrenia (SZ) is one of the most cryptic and costly mental disorders in terms of human suffering and societal expenditure (van Os and Kapur, 2009). Though strong evidence for functional, structural, and genetic abnormalities associated with this disease exists, there is yet no replicable finding which has proven accurate enough to be useful in clinical decision making (Fornito et al., 2009), and its diagnosis relies primarily upon symptom assessment (Williams et al., 2010a). It is likely in part that the lack of consistent neuroimaging findings is because most models favor only one data type or do not combine data from different imaging modalities effectively, thus missing potentially important differences which are only partially detected by each modality (Calhoun et al., 2006a). It is becoming increasingly clear that multimodal fusion, a technique which takes advantage of the fact that each modality provides a limited view of the brain/gene and may uncover hidden relationships, is an important tool to help unravel the black box of schizophrenia. In this review paper, we survey a number of multimodal fusion applications which enable us to study the schizophrenia macro-connectome, including brain functional, structural, and genetic aspects and may help us understand the disorder in a more comprehensive and integrated manner. We also provide a table that characterizes these applications by the methods used and compare these methods in detail, especially for multivariate models, which may serve as a valuable reference that helps readers select an appropriate method based on a given research question.

Extensive abnormality of brain white matter integrity in pathological gambling

Several magnetic resonance imaging (MRI) studies in substance use disorders have shown brain white matter integrity abnormalities, but there are no studies in pathological gambling, a form of behavioral addiction. Our objective was to investigate possible changes in regional brain gray and white matter volumes, and axonal white matter integrity in pathological gamblers compared to healthy controls. Twenty-four subjects (12 clinically diagnosed male pathological gamblers and 12 age-matched healthy male volunteers) underwent structural and diffusion weighted brain MRI scans, which were analyzed with voxel-based morphometry and tract based spatial statistics. In pathological gamblers, widespread lower white matter integrity (lower fractional anisotropy, higher mean diffusivity) was seen in multiple brain regions including the corpus callosum, the cingulum, the superior longitudinal fascicle, the inferior fronto-occipital fascicle, the anterior limb of internal capsule, the anterior thalamic radiation, the inferior longitudinal fascicle and the uncinate/inferior fronto-occipital fascicle. There were no volumetric differences in gray or white matter between pathological gamblers and controls. The results suggest that pathological gambling is associated with extensive lower integrity of several brain white matter tracts. The diffusion abnormality closely resembles previous findings in individuals with substance addictions.

Social reward dependence and brain white matter microstructure

People show consistent differences in their cognitive and emotional responses to environmental cues, manifesting, for example, as variability in social reward processing and novelty-seeking behavior. However, the neurobiological foundation of human temperament and personality is poorly understood. A likely hypothesis is that personality traits rely on the integrity and function of distributed neurocircuitry. In this diffusion tensor imaging (DTI) study, this hypothesis was tested by examining the associations between reward dependence (RD) and novelty seeking (NS), as measured by Cloninger's Temperament and Character Inventory, and fractional anisotropy (FA) and mean diffusivity (MD) as DTI-derived indices of white matter (WM) microstructure across the brain. The results supported the hypothesis. RD was associated with WM architecture coherence as indicated by a negative correlation between RD and FA in frontally distributed areas including pathways connecting important constituents of reward-related neurocircuitry. The associations between RD and FA could not be explained by age, sex, alcohol consumption, or trait anxiety. In contrast, no effects were observed for NS. These findings support the theory that WM fiber tract properties modulate individual differences in social reward processing.

Motivational salience modulates hippocampal repetition suppression and functional connectivity in humans

Repetition suppression (RS) is a rapid decrease of stimulus-related neuronal responses upon repeated presentation of a stimulus. Previous studies have demonstrated that negative emotional salience of stimuli enhances RS. It is, however, unclear how motivational salience of stimuli, such as reward-predicting value, influences RS for complex visual stimuli, and which brain regions might show differences in RS for reward-predicting and neutral stimuli. Here we investigated the influence of motivational salience on RS of complex scenes using event-related functional magnetic resonance imaging. Thirty young healthy volunteers performed a monetary incentive delay task with complex scenes (indoor vs. outdoor) serving as neutral or reward-predicting cue pictures. Each cue picture was presented three times. In line with previous findings, reward anticipation was associated with activations in the ventral striatum, midbrain, and orbitofrontal cortex (OFC). Stimulus repetition was associated with pronounced RS in ventral visual stream areas like the parahippocampal place area (PPA). An interaction of reward anticipation and RS was specifically observed in the anterior hippocampus, where a response decrease across repetitions was observed for the reward-predicting scenes only. Functional connectivity analysis further revealed specific activity-dependent connectivity increases of the hippocampus and the PPA and OFC. Our results suggest that hippocampal RS is sensitive to reward-predicting properties of stimuli and might therefore reflect a rapid, adaptive neural response mechanism for motivationally salient information.

A review of multivariate methods for multimodal fusion of brain imaging data

The development of various neuroimaging techniques is rapidly improving the measurements of brain function/structure. However, despite improvements in individual modalities, it is becoming increasingly clear that the most effective research approaches will utilize multi-modal fusion, which takes advantage of the fact that each modality provides a limited view of the brain. The goal of multi-modal fusion is to capitalize on the strength of each modality in a joint analysis, rather than a separate analysis of each. This is a more complicated endeavor that must be approached more carefully and efficient methods should be developed to draw generalized and valid conclusions from high dimensional data with a limited number of subjects. Numerous research efforts have been reported in the field based on various statistical approaches, e.g. independent component analysis (ICA), canonical correlation analysis (CCA) and partial least squares (PLS). In this review paper, we survey a number of multivariate methods appearing in previous multimodal fusion reports, mostly fMRI with other modality, which were performed with or without prior information. A table for comparing optimization assumptions, purpose of the analysis, the need of priors, dimension reduction strategies and input data types is provided, which may serve as a valuable reference that helps readers understand the trade-offs of the 7 methods comprehensively. Finally, we evaluate 3 representative methods via simulation and give some suggestions on how to select an appropriate method based on a given research.

The effect of dopamine therapy on ventral and dorsal striatum-mediated cognition in Parkinson's disease: support from functional MRI

The central aim of our study was to elucidate functions mediated by the ventral and dorsal striatum, respectively, to better understand the cognitive effects of dopamine replacement in Parkinson's disease. We proposed that the ventral striatum underlies general learning of stimulus associations, whereas the dorsal striatum promotes integration of various influences on selecting. In Parkinson's disease, dopamine depletion is substantially less notable in the ventral relative to the dorsal striatum, and therefore greater improvements are expected for dorsal striatum-mediated functions with dopamine replacement. Using a simple selection task, we found that dopamine replacement impaired encoding and facilitation of consistent stimulus-stimulus relations across trials. This finding was in line with our contention that ventral striatum mediates learning stimulus associations, even when explicit feedback or reward is not provided. In contrast, dopamine replacement enhanced interference related to assimilating conflicting influences on selection across trials, consistent with our hypothesis that the dorsal striatum supports deciding in ambiguous contexts. We further confirmed these separable roles for the ventral and dorsal striatum in our selection task with healthy young volunteers using functional magnetic resonance imaging. In summary, we present a within-subject, double dissociation of the effects of dopamine replacement in patients with Parkinson's disease for ventral striatum-mediated facilitation and dorsal striatum-mediated interference, confirmed in a separate functional magnetic resonance imaging experiment. Defining the distinct functions of the ventral and dorsal striatum will have direct clinical implications. Titration of therapy in Parkinson's disease is generally geared towards optimizing dorsal striatum-mediated motor symptoms, possibly at the expense of ventral striatum operations, a consequence that is only beginning to be recognized. Enhanced awareness of these different processes will translate into medication strategies that take into account those symptoms that dopamine replacement might hinder, as well as improve. Here, we show impairments in learning new stimulus associations compared with improvements in integrating varied influences related to selection. Ultimately, this knowledge will lead clinicians to survey a broader range of symptoms in determining optimal therapy based on individual patient priorities.

Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA+ joint ICA model

Diverse structural and functional brain alterations have been identified in both schizophrenia and bipolar disorder, but with variable replicability, significant overlap and often in limited number of subjects. In this paper, we aimed to clarify differences between bipolar disorder and schizophrenia by combining fMRI (collected during an auditory oddball task) and diffusion tensor imaging (DTI) data. We proposed a fusion method, "multimodal CCA+ joint ICA", which increases flexibility in statistical assumptions beyond existing approaches and can achieve higher estimation accuracy. The data collected from 164 participants (62 healthy controls, 54 schizophrenia and 48 bipolar) were extracted into "features" (contrast maps for fMRI and fractional anisotropy (FA) for DTI) and analyzed in multiple facets to investigate the group differences for each pair-wised groups and each modality. Specifically, both patient groups shared significant dysfunction in dorsolateral prefrontal cortex and thalamus, as well as reduced white matter (WM) integrity in anterior thalamic radiation and uncinate fasciculus. Schizophrenia and bipolar subjects were separated by functional differences in medial frontal and visual cortex, as well as WM tracts associated with occipital and frontal lobes. Both patients and controls showed similar spatial distributions in motor and parietal regions, but exhibited significant variations in temporal lobe. Furthermore, there were different group trends for age effects on loading parameters in motor cortex and multiple WM regions, suggesting that brain dysfunction and WM disruptions occurred in identified regions for both disorders. Most importantly, we can visualize an underlying function-structure network by evaluating the joint components with strong links between DTI and fMRI. Our findings suggest that although the two patient groups showed several distinct brain patterns from each other and healthy controls, they also shared common abnormalities in prefrontal thalamic WM integrity and in frontal brain mechanisms.

Language learning under working memory constraints correlates with microstructural differences in the ventral language pathway

The present study combined behavioral measures and diffusion tensor imaging to investigate the neuroanatomical basis of language learning in relation to phonological working memory (WM). Participants were exposed to simplified artificial languages under WM constraints. The results underscore the role of the rehearsal subcomponent of WM in successful speech segmentation and rule learning. Moreover, when rehearsal was blocked task performance was correlated to the white matter microstructure of the left ventral pathway connecting frontal and temporal language-related cortical areas through the extreme/external capsule. This ventral pathway may therefore play an important additional role in language learning when the main dorsal pathway-dependent rehearsal mechanisms are not available.