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Resting‐state functional magnetic resonance imaging (rsfMRI) is a promising task‐free functional imaging approach, which may complement or replace task‐based fMRI (tfMRI) in patients who have difficulties performing required tasks. However, rsfMRI is highly sensitive to head movement and physiological noise, and validation relative to tfMRI and intraoperative electrocortical mapping is still necessary. In this study, we investigate (a) the feasibility of real‐time rsfMRI for presurgical mapping of eloquent networks with monitoring of data quality in patients with brain tumors and (b) rsfMRI localization of eloquent cortex compared with tfMRI and intraoperative electrocortical stimulation (ECS) in retrospective analysis. Five brain tumor patients were studied with rsfMRI and tfMRI on a clinical 3T scanner using MultiBand(8)‐echo planar imaging (EPI) with repetition time: 400 ms. Moving‐averaged sliding‐window correlation analysis with regression of motion parameters and signals from white matter and cerebrospinal fluid was used to map sensorimotor and language resting‐state networks. Data quality monitoring enabled rapid optimization of scan protocols, early identification of task noncompliance, and head movement‐related false‐positive connectivity to determine scan continuation or repetition. Sensorimotor and language resting‐state networks were identifiable within 1 min of scan time. The Euclidean distance between ECS and rsfMRI connectivity and task‐activation in motor cortex, Broca's, and Wernicke's areas was 5–10 mm, with the exception of discordant rsfMRI and ECS localization of Wernicke's area in one patient due to possible cortical reorganization and/or altered neurovascular coupling. This study demonstrates the potential of real‐time high‐speed rsfMRI for presurgical mapping of eloquent cortex with real‐time data quality control, and clinically acceptable concordance of rsfMRI with tfMRI and ECS localization.

Scores on intelligence tests are strongly predictive of various important life outcomes. However, the gender discrepancy on intelligence quotient (IQ) prediction using brain imaging variables has not been studied. To this aim, we predicted individual IQ scores for males and females separately using whole-brain functional connectivity (FC). Robust predictions of intellectual capabilities were achieved across three independent data sets (680 subjects) and two intelligence measurements (IQ and fluid intelligence) using the same model within each gender. Interestingly, we found that intelligence of males and females were underpinned by different neurobiological correlates, which are consistent with their respective superiority in cognitive domains (visuospatial vs verbal ability). In addition, the identified FC patterns are uniquely predictive on IQ and its sub-domain scores only within the same gender but neither for the opposite gender nor on the IQ-irrelevant measures such as temperament traits. Moreover, females exhibit significantly higher IQ predictability than males in the discovery cohort. This findings facilitate our understanding of the biological basis of intelligence by demonstrating that intelligence is underpinned by a variety of complex neural mechanisms that engage an interacting network of regions—particularly prefrontal–parietal and basal ganglia—whereas the network pattern differs between genders.

Histological studies have reported microstructural hemispheric asymmetries in several cortical areas of the human brain, but reliable in vivo assessment methods have been lacking so far. Here, we used neurite orientation dispersion and density imaging (NODDI) to examine microstructural asymmetries in in vivo and determine if findings are in accordance with what has been reported in histological studies. We examined intra-neurite volume fraction (INVF), neurite orientation dispersion (ODI), and isotropic volume fraction (ISO) asymmetries in two independent samples of healthy adults (n = 269 and n = 251). Over both samples, we found greater left-hemispheric INVF in early auditory, inferior parietal and temporal-parietal-occipital areas. In contrast, we found greater right-hemispheric INVF in the fusiform and inferior temporal gyrus, reflecting what has been reported in histological studies. ODI was asymmetric towards the left hemisphere in frontal areas and towards the right hemisphere in early auditory areas. ISO showed less pronounced asymmetries. There were hardly any effects of sex or handedness on microstructural asymmetry as determined by NODDI. Taken together, these findings suggest substantial microstructural asymmetries in gray matter, making NODDI a promising marker for future genetic and behavioral studies on laterality.

Very few studies have investigated neuroanatomical correlates of “everyday” creative achievement in cohorts of normal subjects. In previous research, we first showed that scores on the Creative Achievement Questionnaire (CAQ) were associated with lower cortical thickness within the left lateral orbitofrontal gyrus (LOFG), and increased thickness of the right angular gyrus (AG) (Jung et al., 2010). Newer studies found the CAQ to be associated with decreased volume of the rostral anterior cingulate cortex (ACC) (Chen, et al., 2014), and that artistic and scientific creativity was associated with increased and decreased volumes within the executive control network and salience network (Shi et al., 2017). We desired to replicate and extend our previous study in a larger cohort (N = 248), comprised of subjects studying and working in science, technology, engineering, and math (STEM). Subjects were youn (Range = 16–32; Mean age = 21.8; s.d. = 3.5) all of whom were administered the CAQ from which we derived artistic and scientific creativity factors. All subjects underwent structural MRI on a 3 T scanner from which cortical thickness, area, and volume measures were obtained using FreeSurfer. Our results showed mostly cortical thinning in relation to total, scientific, and artistic creative achievement encompassing many regions involved in the cognitive control network (CCN) and default mode network (DMN).

Objective: We propose and develop a novel biclustering (N-BiC) approach for performing N-way biclustering of neuroimaging data. Our approach is applicable to an arbitrary number of features from both imaging and behavioral data (e.g., symptoms). We applied it to structural MRI data from patients with schizophrenia. Methods: It uses a source-based morphometry approach [i.e., independent component analysis of gray matter segmentation maps] to decompose the data into a set of spatial maps, each of which includes regions that covary among individuals. Then, the loading parameters for components of interest are entered to an exhaustive search, which incorporates a modified depth-first search technique to carry out the biclustering, with the goal of obtaining submatrices where the selected rows (individuals) show homogeneity in their expressions of selected columns (components) and vice versa. Results: Findings demonstrate that multiple biclusters have an evident association with distinct brain networks for the different types of symptoms in schizophrenia. The study identifies two components: inferior temporal gyrus (16) and brainstem (7), which are related to positive (distortion/excess of normal function) and negative (diminution/loss of normal function) symptoms in schizophrenia, respectively. Conclusion: N-BiC is a data-driven method of biclustering MRI data that can exhaustively explore relationships/substructures from a dataset without any prior information with a higher degree of robustness than earlier biclustering applications. Significance: The use of such approaches is important to investigate the underlying biological substrates of mental illness by grouping patients into homogeneous subjects, as the schizophrenia diagnosis is known to be relatively nonspecific and heterogeneous.

In this paper we describe an open-access collection of multimodal neuroimaging data in schizophrenia for release to the community. Data were acquired from approximately 100 patients with schizophrenia and 100 age-matched controls during rest as well as several task activation paradigms targeting a hierarchy of cognitive constructs. Neuroimaging data include structural MRI, functional MRI, diffusion MRI, MR spectroscopic imaging, and magnetoencephalography. For three of the hypothesis-driven projects, task activation paradigms were acquired on subsets of ~200 volunteers which examined a range of sensory and cognitive processes (e.g., auditory sensory gating, auditory/visual multisensory integration, visual transverse patterning). Neuropsychological data were also acquired and genetic material via saliva samples were collected from most of the participants and have been typed for both genome-wide polymorphism data as well as genome-wide methylation data. Some results are also presented from the individual studies as well as from our data-driven multimodal analyses (e.g., multimodal examinations of network structure and network dynamics and multitask fMRI data analysis across projects). All data will be released through the Mind Research Network’s collaborative informatics and neuroimaging suite (COINS). Electronic supplementary material The online version of this article (doi:10.1007/s12021-017-9338-9) contains supplementary material, which is available to authorized users.

While the behavior of “being musically creative”— improvising, composing, songwriting, etc.—is undoubtedly a complex and highly variable one, recent neuroscientific investigation has offered significant insight into the neural underpinnings of many of the creative processes contributing to such behavior. A previous study from our research group (Bashwiner et al., 2016), which examined two aspects of brain structure as a function of creative musical experience, found significantly increased cortical surface area or subcortical volume in regions of the default-mode network, a motor planning network, and a “limbic” network. The present study sought to determine how these regions coordinate with one another and with other regions of the brain in a large number of participants (n ​= ​218) during a task-neutral period, i.e., during the “resting state.” Deriving from the previous study’s results a set of eleven regions of interest (ROIs), the present study analyzed the resting-state functional connectivity (RSFC) from each of these seed regions as a function of creative musical experience (assessed via our Musical Creativity Questionnaire). Of the eleven ROIs investigated, nine showed significant correlations with a total of 22 clusters throughout the brain, the most significant being located in bilateral cerebellum, right inferior frontal gyrus, midline thalamus (particularly the mediodorsal nucleus), and medial premotor regions. These results support prior reports (by ourselves and others) implicating regions of the default-mode, executive, and motor-planning networks in musical creativity, while additionally—and somewhat unanticipatedly—including a potentially much larger role for the salience network than has been previously reported in studies of musical creativity.

Creative cognition, as measured through divergent thinking (DT), offers insight into one’s ability to generate novel ideas. Relatively little work has been done exploring the relationship between creative idea generation tasks and white matter integrity via fractional anisotropy (FA). Our previous work has shown that higher scores on DT tasks were related to reduced fractional anisotropy (FA) within the left hemisphere anterior thalamic radiation (Jung et al., 2010). However, Takeuchi et al., 2010, found positive correlations with FA and DT tasks in the prefrontal cortex and genu of the corpus callosum. The present study assessed subjects studying or working in science, technology, engineering and mathematics (STEM; N ​= ​178) for correlations in white matter FA, as related to a measure of DT. Healthy normal subjects aged (16–32 years, mean age ​= ​22.0 ​± ​3.8; F ​= ​89/178). Three idea generation DT measures were scored by three raters (α ​= ​0.71) using the consensual assessment technique, from which a composite creativity index (CCI) was derived. We found that CCI was inversely related to FA (all p ​

Creativity plays an important role in numerical problem solving. Although the neural underpinnings of creativity have been studied over decades, very little is known about neural mechanisms of the creative process that relates to numerical problem solving. In the present study, we employed a numerical analogical reasoning task with functional Magnetic Resonance Imaging (fMRI) to investigate the neural correlates of divergent production of rules in numerical analogical reasoning. Participants performed two tasks: a multiple solution analogical reasoning task and a single solution analogical reasoning task. Results revealed that divergent production of rules involves significant activations at Brodmann area (BA) 10 in the right middle frontal cortex, BA 40 in the left inferior parietal lobule, and BA 8 in the superior frontal cortex. The results suggest that right BA 10 and left BA 40 are involved in the generation of novel rules, and BA 8 is associated with the inhibition of initial rules in numerical analogical reasoning. The findings shed light on the neural mechanisms of creativity in numerical processing.

Objectives: One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of brain networks using graph theory and related these to GCA in healthy controls and individuals with schizophrenia. Methods: Participants (N=116 controls, 80 patients with schizophrenia) were recruited from four sites. GCA was represented by the first principal component of a large battery of neurocognitive tests. Graph metrics were derived from diffusion-weighted imaging. Results: The global metrics of longer characteristic path length and reduced overall connectivity predicted lower GCA across groups, and group differences were noted for both variables. Measures of clustering, efficiency, and modularity did not differ across groups or predict GCA. Follow-up analyses investigated three topological types of connectivity—connections among high degree “rich club” nodes, “feeder” connections to these rich club nodes, and “local” connections not involving the rich club. Rich club and local connectivity predicted performance across groups. In a subsample (N=101 controls, 56 patients), a genetic measure reflecting mutation load, based on rare copy number deletions, was associated with longer characteristic path length. Conclusions: Results highlight the importance of characteristic path lengths and rich club connectivity for GCA and provide no evidence for group differences in the relationships between graph metrics and GCA. (JINS, 2016, 22, 240–249)

An influential model of the neural mechanisms of creative thought suggests that creativity is manifested in the joint contributions of the Default Mode Network (DMN; a set of regions in the medial PFC, lateral and medial parietal cortex, and the medial temporal lobes) and the executive networks within the dorsolateral PFC. Several empirical reports have offered support for this model by showing that complex interactions between these brain systems account for individual differences in creative performance. The present study examined whether the engagement of these regions in idea generation is modulated by one’s eminence in a creativity-related field. Twenty (n ​= ​20) healthy eminent creators from diverse fields of expertise and a ‘smart’ comparison group of sixteen (n ​= ​16) age- and education-matched non-eminent thinkers were administered a creative generation task (an adaptation of the Alternative Uses Task) and a control perceptual task, while undergoing functional magnetic resonance imaging (fMRI). The participants’ verbal responses were recorded through a noise-canceling microphone and were later coded for fluency and accuracy. Behavioral and fMRI analyses revealed commonalities between groups, but also distinct patterns of activation in default mode and executive brain regions between the eminent and the non-eminent participants during creative thinking. We interpret these findings in the context of the well-documented contributions of these regions in the generation of creative ideas as modulated, in this study, by participants’ creative eminence.

Nearly everyone has the ability for creative thought. Yet, certain individuals create works that propel their fields, challenge paradigms, and advance the world. What are the neurobiological factors that might underlie such prominent creative achievement? In this study, we focus on morphometric differences in brain structure between high creative achievers from diverse fields of expertise and a 'smart' comparison group of age-, intelligence-, and education-matched average creative achievers. Participants underwent a high-resolution structural brain imaging scan and completed a series of intelligence, creative thinking, personality, and creative achievement measures. We examined whether high and average creative achievers could be distinguished based on the relationship between morphometric brain measures (cortical area and thickness) and behavioral measures. Although participants' performance on the behavioral measures did not differ between the two groups aside from creative achievement, the relationship between posterior parietal cortex morphometry and creativity, intelligence, and personality measures depended on group membership. These results suggest that extraordinary creativity may be associated with measurable structural brain differences, especially within parietal cortex.

Previous research has demonstrated that individuals with higher intelligence are more likely to have larger gray matter volume in brain areas predominantly located in parieto-frontal regions. These findings were usually interpreted to mean that individuals with more cortical brain volume possess more neurons and thus exhibit more computational capacity during reasoning. In addition, neuroimaging studies have shown that intelligent individuals, despite their larger brains, tend to exhibit lower rates of brain activity during reasoning. However, the microstructural architecture underlying both observations remains unclear. By combining advanced multi-shell diffusion tensor imaging with a culture-fair matrix-reasoning test, we found that higher intelligence in healthy individuals is related to lower values of dendritic density and arborization. These results suggest that the neuronal circuitry associated with higher intelligence is organized in a sparse and efficient manner, fostering more directed information processing and less cortical activity during reasoning., Previous studies suggest that individual differences in intelligence correlate with circuit complexity and dendritic arborization in the brain. Here the authors use NODDI, a diffusion MRI technique, to confirm that neurite density and arborization are inversely related to measures of intelligence.

Neurocognitive dysfunction and brain injury on magnetic resonance imaging (MRI) are common in patients with systemic lupus erythematosus (SLE) and are associated with increased morbidity and mortality. However, brain MRI is expensive, is restricted by payers, and requires high expertise. Neurocognitive assessment is an easily available, safe, and inexpensive clinical tool that may select patients needing brain MRI. In this cross-sectional and controlled study, 76 SLE patients (69 women, age 37 ± 12 years) and 26 age and gender-matched healthy subjects (22 women, age 34 ± 11 years) underwent assessment of attention, memory, processing speed, executive function, motor function, and global neurocognitive function. All subjects underwent brain MRI with T1-weighted, fluid-attenuated inversion recovery (FLAIR), and diffusion-weighted imaging. Hemispheric and whole brain lesion load in cm3 were determined using semi-automated methods. Neurocognitive z-scores in all clinical domains were significantly lower and whole brain and right and left hemispheres brain lesion load were significantly greater in patients than in controls (all p ≤ 0.02). There was significant correlation between neurocognitive z-scores in all domains and whole brain lesion load: processing speed (r = − 0.46; p

Openness/Intellect (i.e., openness to experience) is the Big Five personality factor most consistently associated with individual differences in creativity. Recent psychometric evidence has demonstrated that this factor consists of two distinct aspects-Intellect and Openness. Whereas Intellect reflects perceived intelligence and intellectual engagement, Openness reflects engagement with fantasy, perception, and aesthetics. We investigated the extent to which Openness and Intellect are associated with variations in brain structure as measured by cortical thickness, area, and volume (N = 185). Our results demonstrated that Openness was correlated inversely with cortical thickness and volume in left middle frontal gyrus (BA 6), middle temporal gyrus (MTG, BA 21), and superior temporal gyrus (BA 41), and exclusively with cortical thickness in left inferior parietal lobule (BA 40), right inferior frontal gyrus (IFG, BA 45), and MTG (BA 37). When age and sex were statistically controlled for, the inverse correlations between Openness and cortical thickness remained statistically significant for all regions except left MTG, whereas the correlations involving cortical volume remained statistically significant only for left middle frontal gyrus. There was no statistically significant correlation between Openness and cortical area, and no statistically significant correlation between Intellect and cortical thickness, area, or volume. Our results demonstrate that individual differences in Openness are correlated with variation in brain structure-particularly as indexed by cortical thickness. Given the involvement of the above regions in processes related to memory and cognitive control, we discuss the implications of our findings for the possible contribution of personality to creative cognition.

In this study we employed joint independent component analysis (jICA) to perform a novel multivariate integration of magnetoencephalography (MEG) and diffusion tensor imaging (DTI) data to investigate the link between function and structure. This model-free approach allows one to identify covariation across modalities with different temporal and spatial scales [temporal variation in MEG and spatial variation in fractional anisotropy (FA) maps]. Healthy controls (HC) and patients with schizophrenia (SP) participated in an auditory/visual multisensory integration paradigm to probe cortical connectivity in schizophrenia. To allow direct comparisons across participants and groups, the MEG data were registered to an average head position and regional waveforms were obtained by calculating the local field power of the planar gradiometers. Diffusion tensor images obtained in the same individuals were preprocessed to provide FA maps for each participant. The MEG/FA data were then integrated using the jICA software (http://mialab.mrn.org/software/fit). We identified MEG/FA components that demonstrated significantly different (p < 0.05) covariation in MEG/FA data between diagnostic groups (SP vs. HC) and three components that captured the predominant sensory responses in the MEG data. Lower FA values in bilateral posterior parietal regions, which include anterior/posterior association tracts, were associated with reduced MEG amplitude (120-170 ms) of the visual response in occipital sensors in SP relative to HC. Additionally, increased FA in a right medial frontal region was linked with larger amplitude late MEG activity (300-400 ms) in bilateral central channels for SP relative to HC. Step-wise linear regression provided evidence that right temporal, occipital and late central components were significant predictors of reaction time and cognitive performance based on the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) cognitive assessment battery. These results point to dysfunction in a posterior visual processing network in schizophrenia, with reduced MEG amplitude, reduced FA and poorer overall performance on the MATRICS. Interestingly, the spatial location of the MEG activity and the associated FA regions are spatially consistent with white matter regions that subserve these brain areas. This novel approach provides evidence for significant pairing between function (electrophysiology) and structure (white matter integrity) and demonstrates the sensitivity of this multivariate, multimodal integration technique to group differences in function and structure.

Creative behaviors are among the most complex that humans engage in, involving not only highly intricate, domain-specific knowledge and skill, but also domain-general processing styles and the affective drive to create. This study presents structural imaging data indicating that musically creative people (as indicated by self-report) have greater cortical surface area or volume in a) regions associated with domain-specific higher-cognitive motor activity and sound processing (dorsal premotor cortex, supplementary and pre-supplementary motor areas and planum temporale), b) domain-general creative-ideation regions associated with the default mode network (dorsomedial prefrontal cortex, middle temporal gyrus and temporal pole) and c) emotion-related regions (orbitofrontal cortex, temporal pole and amygdala). These findings suggest that domain-specific musical expertise, default-mode cognitive processing style and intensity of emotional experience might all coordinate to motivate and facilitate the drive to create music.

We present constrained source-based morphometry (SBM), a multivariate semiblind data-driven approach, to explore a possible brain-wide structural network in both gray matter (GM) and white matter (WM) associated with the functional default mode network (DMN). With this approach, we utilize seed regions associated with the DMN as constraints on GM maps and derive a joint GM and WM structural network automatically through a multivariate data-driven approach. In this article, we first provide a simulation to validate the constrained SBM approach. The approach was then applied to structural magnetic resonance imaging and diffusion tensor imaging data obtained from 102 healthy controls. Regions that have consistently reported to be associated with the DMN were used to create an a priori mask that was integrated within an independent component analysis framework to derive the structural network associated with the DMN. We identified a set of GM and corresponding WM regions contributing to a structural network underlying the functional DMN. The GM regions consisted mainly of the precuneus, superior and medial frontal gyri, middle temporal gyrus, hippocampus, cuneus, and cerebellum. The WM regions included the cingulum, corpus callosum, corona radiata, association fibers, and middle cerebellar peduncle. Significant gender differences in the relationship between intelligence quotient (IQ) and the identified structural network were observed. Our findings suggest that the functional DMN is underpinned by a corresponding brain-wide structural network. The constrained SBM approach is additionally applicable to a wide variety of problems identifying structural networks from seed regions.

Despite intensive study, the role of the dorsal medial frontal cortex (dMFC) in error monitoring and conflict processing remains actively debated. The current experiment manipulated conflict type (stimulus conflict only or stimulus and response selection conflict) and utilized a novel modeling approach to isolate error and conflict variance during a multimodal numeric Stroop task. Specifically, hemodynamic response functions resulting from two statistical models that either included or isolated variance arising from relatively few error trials were directly contrasted. Twenty-four participants completed the task while undergoing event-related functional magnetic resonance imaging on a 1.5-Tesla scanner. Response times monotonically increased based on the presence of pure stimulus or stimulus and response selection conflict. Functional results indicated that dMFC activity was present during trials requiring response selection and inhibition of competing motor responses, but absent during trials involving pure stimulus conflict. A comparison of the different statistical models suggested that relatively few error trials contributed to a disproportionate amount of variance (i.e., activity) throughout the dMFC, but particularly within the rostral anterior cingulate gyrus (rACC). Finally, functional connectivity analyses indicated that an empirically derived seed in the dorsal ACC/pre-SMA exhibited strong connectivity (i.e., positive correlation) with prefrontal and inferior parietal cortex but was anti-correlated with the default-mode network. An empirically derived seed from the rACC exhibited the opposite pattern, suggesting that sub-regions of the dMFC exhibit different connectivity patterns with other large scale networks implicated in internal mentations such as daydreaming (default-mode) versus the execution of top-down attentional control (fronto-parietal).

Transcranial direct current stimulation (TDCS) is a non-invasive form of brain stimulation applied via a weak electrical current passed between electrodes on the scalp. In recent studies, TDCS has been shown to improve learning when applied to the prefrontal cortex (e.g., Kincses et al. in Neuropsychologia 42:113-117, 2003; Clark et al. Neuroimage in 2010). The present study examined the effects of TDCS delivered at the beginning of training (novice) or after an hour of training (experienced) on participants' ability to detect cues indicative of covert threats. Participants completed two 1-h training sessions. During the first 30 min of each training session, either 0.1 mA or 2.0 mA of anodal TDCS was delivered to the participant. The anode was positioned near F8, and the cathode was placed on the upper left arm. Testing trials immediately followed training. Accuracy in classification of images containing and not-containing threat stimuli during the testing sessions indicated: (1) that mastery of threat detection significantly increased with training, (2) that anodal TDCS at 2 mA significantly enhanced learning, and (3) TDCS was significantly more effective in enhancing test performance when applied in novice learners than in experienced learners. The enhanced performance following training with TDCS persisted into the second session when TDCS was delivered early in training.

Background: Emerging evidence implicates white matter (WM) abnormalities in the pathophysiology of schizophrenia. However, there is considerable heterogeneity in the presentation of WM abnormalities in the existing studies. The object of this study was to evaluate WM integrity in a large sample of patients with first-episode (FE) and chronic schizophrenia in comparison to matched control groups. Our goal was to assess whether WM findings occurred early in the illness or whether these abnormalities developed with the illness over time. Methods: Participants included 114 patients with schizophrenia (31 FE and 83 chronic patients) and 138 matched controls. High-resolution structural and diffusion tensor images were obtained on all participants. Measures of fractional anisotropy (FA) were calculated for the 4 cortical lobes and the cerebellum and brain stem. Results: FA was significant lower in patients vs controls in the whole brain and individually in the frontal, parietal, occipital, and temporal lobes. FA was not significantly different in the brain stem or cerebellum. FA differences were significant only in patients with chronic schizophrenia and not in the FE group. Conclusions: We found global differences in the WM microstructure in patients with chronic but not FE schizophrenia. These findings suggest progressive alterations in WM microstructure.

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.

A broadly accepted definition of creativity refers to the production of something both novel and useful within a given social context. Studies of patients with neurological and psychiatric disorders and neuroimaging studies of healthy controls have each drawn attention to frontal and temporal lobe contributions to creativity. Based on previous magnetic resonance (MR) spectroscopy studies demonstrating relationships between cognitive ability and concentrations ofN-acetyl-aspartate (NAA), a common neurometabolite, we hypothesized that NAA assessed in gray and white matter (from a supraventricular slab) would relate to laboratory measures of creativity. MR imaging and divergent thinking measures were obtained in a cohort of 56 healthy controls. Independent judges ranked the creative products of each participant, from which a “Composite Creativity Index” (CCI) was created. Different patterns of correlations between NAA and CCI were found in higher verbal ability versus lower verbal ability participants, providing neurobiological support for a critical “threshold” regarding the relationship between intelligence and creativity. To our knowledge, this is the first report assessing the relationship between brain chemistry and creative cognition, as measured with divergent thinking, in a cohort comprised exclusively of normal, healthy participants.

Regional gray matter (GM) abnormalities are well known to exist in patients with chronic schizophrenia. Voxel-based morphometry (VBM) has been previously used on structural magnetic resonance images (MRI) data to characterize these abnormalities. Two multisite schizophrenia studies, the Functional Biomedical Informatics Research Network and the Mind Clinical Imaging Consortium, which include 9 data collection sites, are evaluating the efficacy of pooling structural imaging data across imaging centers. Such a pooling of data could yield the increased statistical power needed to elucidate effects that may not be seen with smaller samples. VBM analyses were performed to evaluate the consistency of patient versus control gray matter concentration (GMC) differences across the study sites, as well as the effects of combining multisite data. Integration of data from both studies yielded a large sample of 503 subjects, including 266 controls and 237 patients diagnosed with schizophrenia, schizoaffective or schizophreniform disorder. The data were analyzed using the combined sample, as well as analyzing each of the 2 multisite studies separately. A consistent pattern of reduced relative GMC in schizophrenia patients compared with controls was found across all study sites. Imaging center-specific effects were evaluated using a region of interest analysis. Overall, the findings support the use of VBM in combined multisite studies. This analysis of schizophrenics and controls from around the United States provides continued supporting evidence for GM deficits in the temporal lobes, anterior cingulate, and frontal regions in patients with schizophrenia spectrum disorders.

The brain's default network (DN) has been a topic of considerable empirical interest. In fMRI research, DN activity is associated with spontaneous and self‐generated cognition, such as mind‐wandering, episodic memory retrieval, future thinking, mental simulation, theory of mind reasoning, and creative cognition. Despite large literatures on developmental and disease‐related influences on the DN, surprisingly little is known about the factors that impact normal variation in DN functioning. Using structural equation modeling and graph theoretical analysis of resting‐state fMRI data, we provide evidence that Openness to Experience—a normally distributed personality trait reflecting a tendency to engage in imaginative, creative, and abstract cognitive processes—underlies efficiency of information processing within the DN. Across two studies, Openness predicted the global efficiency of a functional network comprised of DN nodes and corresponding edges. In Study 2, Openness remained a robust predictor—even after controlling for intelligence, age, gender, and other personality variables—explaining 18% of the variance in DN functioning. These findings point to a biological basis of Openness to Experience, and suggest that normally distributed personality traits affect the intrinsic architecture of large‐scale brain systems. Hum Brain Mapp 37:773–779, 2016. © 2015 Wiley Periodicals, Inc.

© The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved.Analyses of gray matter concentration (GMC) deficits in patients with schizophrenia (Sz) have identified robust changes throughout the cortex. We assessed the relationships between diagnosis, overall symptom severity, and patterns of gray matter in the largest aggregated structural imaging dataset to date. We performed both sourcebased morphometry (SBM) and voxel-based morphometry (VBM) analyses on GMC images from 784 Sz and 936 controls (Ct) across 23 scanning sites in Europe and the United States. After correcting for age, gender, site, and diagnosis by site interactions, SBM analyses showed 9 patterns of diagnostic differences. They comprised separate cortical, subcortical, and cerebellar regions. Seven patterns showed greater GMC in Ct than Sz, while 2 (brainstem and cerebellum) showed greater GMC for Sz. The greatest GMC deficit was in a single pattern comprising regions in the superior temporal gyrus, inferior frontal gyrus, and medial frontal cortex, which replicated over analyses of data subsets. VBM analyses identified overall cortical GMC loss and one small cluster of increased GMC in Sz, which overlapped with the SBM brainstem component. We found no significant association between the component loadings and symptom severity in either analysis. This mega-analysis confirms that the commonly found GMC loss in Sz in the anterior temporal lobe, insula, and medial frontal lobe form a single, consistent spatial pattern even in such a diverse dataset. The separation of GMC loss into robust, repeatable spatial patterns across multiple datasets paves the way for the application of these methods to identify subtle genetic and clinical cohort effects.

Mapping brain connectivity based on neuroimaging data is a promising new tool for understanding brain structure and function. In this methods paper, we demonstrate that group independent component analysis (GICA) can be used to perform a dual parcellation of the brain based on its connectivity matrix (cmICA). This dual parcellation consists of a set of spatially independent source maps, and a corresponding set of paired dual maps that define the connectivity of each source map to the brain. These dual maps are called the connectivity profiles of the source maps. Traditional analysis of connectivity matrices has been used previously for brain parcellation, but the present method provides additional information on the connectivity of these segmented regions. In this paper, the whole brain structural connectivity matrices were calculated on a 5 mm(3) voxel scale from diffusion imaging data based on the probabilistic tractography method. The effect of the choice of the number of components (30 and 100) and their stability were examined. This method generated a set of spatially independent components that are consistent with the canonical brain tracts provided by previous anatomic descriptions, with the high order model yielding finer segmentations. The corpus-callosum example shows how this method leads to a robust parcellation of a brain structure based on its connectivity properties. We applied cmICA to study structural connectivity differences between a group of schizophrenia subjects and healthy controls. The connectivity profiles at both model orders showed similar regions with reduced connectivity in schizophrenia patients. These regions included forceps major, right inferior fronto-occipital fasciculus, uncinate fasciculus, thalamic radiation, and corticospinal tract. This paper provides a novel unsupervised data-driven framework that summarizes the information in a large global connectivity matrix and tests for brain connectivity differences. It has the potential for capturing important brain changes related to disease in connectivity-based disorders.

The ability to reliably respond to stimuli could be an important biological determinant of differences in fluid intelligence (Gf). However, most electrophysiological studies of Gf employ event-related potential (ERP) measures that average brain activity over trials, and hence have limited power to quantify neural variability. Time-frequency analyses can capture cross-trial variation in the phase of neural activity, and thus can help address the importance of neural reliability to differences in Gf. This study recruited a community sample of healthy adults and measured inter-trial phase clustering (ITPC), total spectral power, and ERP amplitudes elicited by Repeated and Novel non-target stimuli during two visual oddball tasks. Condition effects, relations among the EEG measures, and relations with Gf were assessed. Early visual responses to Repeated stimuli elicited higher ITPC, yet only ITPC elicited by Novel stimuli was associated with Gf. Analyses of spectral power further highlighted the contribution of phase consistency to the findings. The link between Gf and reliable responding to changing inputs suggests an important role for flexible resource allocation in fluid intellectual skills.

Creative cognition emerges from a complex network of interacting brain regions. This study investigated the relationship between the structural organization of the human brain and aspects of creative cognition tapped by divergent thinking tasks. Diffusion weighted imaging (DWI) was used to obtain fiber tracts from 83 segmented cortical regions. This information was represented as a network and metrics of connectivity organization, including connectivity strength, clustering and communication efficiency were computed, and their relationship to individual levels of creativity was examined. Permutation testing identified significant sex differences in the relationship between global connectivity and creativity as measured by divergent thinking tests. Females demonstrated significant inverse relationships between global connectivity and creative cognition, whereas there were no significant relationships observed in males. Node specific analyses revealed inverse relationships across measures of connectivity, efficiency, clustering and creative cognition in widespread regions in females. Our findings suggest that females involve more regions of the brain in processing to produce novel ideas to solutions, perhaps at the expense of efficiency (greater path lengths). Males, in contrast, exhibited few, relatively weak positive relationships across these measures. Extending recent observations of sex differences in connectome structure, our findings of sexually dimorphic relationships suggest a unique topological organization of connectivity underlying the generation of novel ideas in males and females.

We examined the relationship between structural brain variation and general intelligence using voxel-based morphometric analysis of MRI data in men and women with equivalent IQ scores. Compared to men, women show more white matter and fewer gray matter areas related to intelligence. In men IQ/gray matter correlations are strongest in frontal and parietal lobes (BA 8, 9, 39, 40), whereas the strongest correlations in women are in the frontal lobe (BA10) along with Broca's area. Men and women apparently achieve similar IQ results with different brain regions, suggesting that there is no singular underlying neuroanatomical structure to general intelligence and that different types of brain designs may manifest equivalent intellectual performance.

Total brain volume accounts for about 16% of the variance in general intelligence scores (IQ), but how volumes of specific regions-of-interest (ROIs) relate to IQ is not known. We used voxel-based morphometry (VBM) in two independent samples to identify substantial gray matter (GM) correlates of IQ. Based on statistical conjunction of both samples (N = 47; P < 0.05 corrected for multiple comparisons), more gray matter is associated with higher IQ in discrete Brodmann areas (BA) including frontal (BA 10, 46, 9), temporal (BA 21, 37, 22, 42), parietal (BA 43 and 3), and occipital (BA 19) lobes and near BA 39 for white matter (WM). These results underscore the distributed neural basis of intelligence and suggest a developmental course for volume--IQ relationships in adulthood.

Background Altered functional connectivity in critical networks has been associated with chronic alcohol abuse. In turn, changes in connectivity in executive control networks (ECNs) may undermine the ability to control alcohol consumption. It was hypothesized that network connectivity would be reduced in individuals with problematic alcohol use (ALC) compared with controls and that diminished network connectivity would be associated with greater failure to control drinking. Methods Resting-state functional magnetic resonance imaging was analyzed to identify 14 previously identified intrinsic connectivity networks (ICNs) using a priori regions of interest in cases ranging from binge drinkers to those with severe alcohol use disorder, as well as control subjects. Analyses tested for differences in network connectivity strength between 255 ALC cases and 87 age- and gender-matched controls. Further, structural equation analysis, using 383 ALC cases, tested whether functional connectivity strength mediated the relationship between years of regular drinking and alcohol problems. Results The age- and gender-matched analysis showed that ALC had significantly lower network connectivity strength than controls in the left executive control (LECN), basal ganglia, and primary visual networks. For all ALC, LECN connectivity strength is negatively correlated with failed control and alcohol disorder severity. Edges connecting parietal regions with dorsolateral prefrontal, middle frontal, and temporal regions within the LECN drove these relationships. A positive association between years of drinking and severity of alcohol problems was mediated by reduced ECN connectivity. Conclusions This study reports relationships between network strength and problematic alcohol use, suggesting that chronic drinking negatively impacts brain connectivity, specifically in the LECN. Altered functional connectivity, related to chronic alcohol abuse, may contribute to the etiology of alcohol dependence and relapse.

Gerstmann syndrome (GS) comprises four interlaced neuropsychological symptoms including finger agnosia, right-left confusion, agraphia, and acalculia. While GS is commonly associated with focal lesions to the region of the left angular gyrus, it has also been associated with numerous diffuse etiologies including atrophy, alcoholism, carbon monoxide poisoning, lead intoxication and anaphylactic shock. Thus, a vigorous debate has emerged as to whether GS represents a syndrome arising from general brain decline or a distinct and localizing lesion. We report a right-handed patient who developed neuropsychological dysfunction secondary to systemic lupus erythematosus (SLE). Neuropsychological evaluation found the patient to exhibit symptoms consistent with the GS tetrad, as well as general cognitive decline. Magnetic resonance imaging revealed a distinct focal lesion of the left parieto-occipital white matter underlying the angular gyrus as well as diffuse atrophy. (1)H-magnetic resonance spectroscopy revealed substantial metabolic derangement in a voxel placed within the visible lesion, although substantial metabolic derangement was observed in regions remote from the focal pathology. Thus, GS in this first case in SLE would appear to comprise a focal neurological tetrad of disorders within a more general pattern of cognitive decline and metabolic derangement.

This study examined the association between size of the caudate nuclei and intelligence. Based on the central role of the caudate in learning, as well as neuroimaging studies linking greater caudate volume to better attentional function, verbal ability, and dopamine receptor availability, we hypothesized the existence of a positive association between intelligence and caudate volume in three large independent samples of healthy adults (total N = 517). Regression of IQ onto bilateral caudate volume controlling for age, sex, and total brain volume indicated a significant positive correlation between caudate volume and intelligence, with a comparable magnitude of effect across each of the three samples. No other subcortical structures were independently associated with IQ, suggesting a specific biological link between caudate morphology and intelligence. Hum Brain Mapp 36:1407–1416, 2015. © 2014 Wiley Periodicals, Inc.

Proton magnetic resonance spectroscopy (1H-MRS) offers a unique non-invasive approach to measurement of N-acetylaspartate (NAA) and choline (Cho), putative markers of neuronal and glial integrity. Previous studies revealed that these neurochemicals predict cognitive impairment in diseased subjects, although little is known about their relationship to cognitive functioning in healthy people. We measured the concentrations of NAA and Cho in the left occipitoparietal white matter of 26 healthy adults and compared them with intellectual performance assessed by the Wechsler Adult Intelligence Scale-3. We found that NAA (b = 0.6, p < 0.01) and Cho (b = -0.42, p < 0.01) were independently associated with the Full-Scale Intelligence Quotient. Together, these metabolites accounted for a large proportion of the variance in intelligence (r2 = 0.45). Possible mechanisms underlying these correlations, such as mitochondrial function and myelin turnover, are discussed. 1H-MRS is a sensitive new tool to assess the neuronal underpinnings of cognitive function non-invasively.

MRS) was used to acquire in vivo spectra from the bilateral anterior cingulate of 10 healthy subjects while they received a subanesthetic dose of either placebo or ketamine, an NMDAR antagonist. Assessments given before and after ketamine or placebo administration included the Brief Rating Psychiatric Rating Scale, the Scale for the Assessment of Negative Symptoms, the Clinician-Administered Dissociative States Scale, and the Stroop task. Results: As predicted, there was a significant increase in anterior cingulate glutamine, a putative marker of glutamate neurotransmitter release, with ketamine administration. This increase was not related to schizophrenia-like positive or negative symptoms but was marginally related to Stroop performance. Conclusions: In humans as in animals, an acute hypofunctional NMDAR state is associated with increased glutamatergic activity in the anterior cingulate. (Am J Psychiatry 2005; 162:394–396) A ccording to the N-methyl-D-aspartate receptor (NMDAR) hypofunction model of schizophrenia (1, 2), NMDAR blockade results in inhibition of γ-aminobutyric acid neurons, causing disinhibition of glutamatergic neurons that converge onto pyramidal neurons in widely distributed cortical regions. NMDAR hypofunction and/or the downstream surge of glutamate in corticolimbic regions may be related to positive and negative symptoms in schizophrenia. Directly supporting this hypothesis, extracellular glutamate concentrations in the prefrontal cortex were found to increase in awake rats when they were given ketamine, an NMDAR antagonist (3). However, to our knowledge, no studies assessing the effects of NMDAR antagonism on glutamatergic activity in humans have been reported. The current study investigated the effects of ketamine on anterior cingulate glutamatergic activity and the relationship to ketamine-induced schizophrenia-like features in healthy humans. Glutamine, the major metabolite of synaptic glutamate (4, 5), was measured with 4-T 1 H proton magnetic resonance spectroscopy ( 1 H-MRS). We hypothesized that there would be a significant increase in anterior cingulate glutamine with ketamine administration, and that this increase would be directly related to schizophrenia-like positive and negative symptoms.

The study of individual differences encompasses broad constructs including intelligence, creativity, and personality. However, substantially less research is devoted to the study of specific aptitudes in spite of their importance to educational, occupational, and avocational success. We sought to determine subcortical brain structural correlates of several broad aptitudes including Math, Vocabulary, Foresight, Paper Folding, and Inductive Reasoning in a large (N = 107), healthy, young (age range = 16–29) cohort. Subcortical volumes were measured using an automated technique (FreeSurfer) across structures including bilateral caudate, putamen, globus pallidus, thalamus, nucleus accumbens, hippocampus, amygdala, and five equal regions of the corpus callosum. We found that performance on measures of each aptitude was predicted by different subcortical structures: Math – higher right nucleus accumbens volume; Vocabulary – higher left hippocampus volume; Paper Folding – higher right thalamus volume; Foresight – lower right thalamus and higher mid anterior corpus callosum volume; Inductive Reasoning – higher mid anterior corpus callosum volume. Our results support general findings, within the cognitive neurosciences, showing lateralization of structure-function relationships, as well as more specific relationships between individual structures (e.g., left hippocampus) and functions relevant to particular aptitudes (e.g., Vocabulary).

The incidence of blast-induced mild traumatic brain injury (mTBI) has been rising in US veterans due to the widespread use of improvised explosive devices. Blast-injured veterans report cognitive impairments, collectively termed post-concussive syndrome, similar to ones that follow more severe forms of TBI. These are due to diffuse axonal injury, which disrupts the neuronal cytoskeleton and commonly goes undetected by computed tomography and conventional magnetic resonance imaging (MRI). We looked for cortical function abnormalities in a group of blast mTBI subjects using independent component analysis of resting state functional MRI data, which may be more sensitive to small differences. Resting state networks of 13 mTBI veterans with moderate post-concussive syndrome and 50 control subjects were compared across 3 fMRI domains: blood oxygenation level-dependent spatial maps, time course spectra, and functional connectivity. The mTBI group exhibited hyperactivity in the temporo-parietal junctions and hypoactivity in the left inferior temporal gyrus. Abnormal frequencies in default-mode (DMN), sensorimotor, attentional, and frontal networks were detected. Functional connectivity was disrupted in 6 network pairs: DMN-basal ganglia, attention-sensorimotor, frontal-DMN, attention-sensorimotor, attention-frontal, and sensorimotor-sensorimotor. The results suggest white matter disruption across certain attentional networks and that the temporo-parietal junctions may be compensating for damage in other cortical regions.

ObjectivesThe aim of this study was to determine whether Libman-Sacks endocarditis is a pathogenic factor for cerebrovascular disease (CVD) in systemic lupus erythematosus (SLE).BackgroundA cardioembolic pathogenesis of SLE CVD manifested as: 1) neuropsychiatric systemic lupus erythematosus (NPSLE), including stroke and transient ischemic attacks (TIA); 2) neurocognitive dysfunction; and 3) magnetic resonance imaging of focal brain lesions has not been established.MethodsA 6-year study of 30 patients with acute NPSLE (27 women, 38 ± 12 years of age), 46 age- and sex-matched SLE controls without NPSLE (42 women, 36 ± 12 years of age), and 26 age- and sex-matched healthy controls (22 women, 34 ± 11 years of age) who underwent clinical and laboratory evaluations, transesophageal echocardiography, carotid duplex ultrasound, transcranial Doppler ultrasound, neurocognitive testing, and brain magnetic resonance imaging/magnetic resonance angiography. Patients with NPSLE were re-evaluated after 4.5 months of therapy. All patients were followed clinically for a median of 52 months.ResultsLibman-Sacks vegetations (87%), cerebromicroembolism (27% with 2.5 times more events per hour), neurocognitive dysfunction (60%), and cerebral infarcts (47%) were more common in NPSLE than in SLE (28%, 20%, 33%, and 0%) and healthy controls (8%, 0%, 4%, and 0%, respectively) (all p ≤ 0.009). Patients with vegetations had 3 times more cerebromicroemboli per hour, lower cerebral blood flow, more strokes/TIA and overall NPSLE events, neurocognitive dysfunction, cerebral infarcts, and brain lesion load than those without (all p ≤ 0.01). Libman-Sacks vegetations were independent risk factors of NPSLE (odds ratio [OR]: 13.4; p < 0.001), neurocognitive dysfunction (OR: 8.0; p = 0.01), brain lesions (OR: 5.6; p = 0.004), and all 3 outcomes combined (OR: 7.5; p < 0.001). Follow-up re-evaluations in 18 of 23 (78%) surviving patients with NPSLE demonstrated improvement of vegetations, microembolism, brain perfusion, neurocognitive dysfunction, and lesion load (all p ≤ 0.04). Finally, patients with vegetations had reduced event-free survival time to stroke/TIA, cognitive disability, or death (p = 0.007).ConclusionsThe presence of Libman-Sacks endocarditis in patients with SLE was associated with a higher risk for embolic CVD. This suggests that Libman-Sacks endocarditis may be a source of cerebral emboli.

Patients diagnosed with Systemic Lupus Erythematosus have similar levels of neuropsychological dysfunction (i.e., 20-50%) as those with Neuropsychiatric Systemic Lupus Erythematosus (NPSLE). We hypothesized a gradient between cognition and white matter integrity, such that strongest brain-behavior relationships would emerge in NPSLE, intermediate in non-NPSLE, and minimal in controls. We studied thirty-one patients (16 non-NPSLE; 15 NPSLE), ranging in age from 18 to 59 years old (100% female), and eighteen age and gender matched healthy controls. DTI examinations were performed on a 1.5T scanner. A broad neuropsychological battery was administered, tapping attention, memory, processing speed, and executive functioning. The Total z-score consisted of the combined sum of all neuropsychological measures. In control subjects, we found no significant FA-Total z-score correlations. NPSLE, non-NPSLE, and control subjects differed significantly in terms of Total z-score (NPSLE = -2.25+/-1.77, non-NPSLE = -1.22+/-1.03, Controls = -0.10+/-.57; F = 13.2, p

To investigate the biochemical correlates of normal personality we utilized proton magnetic resonance spectroscopy ((1)H-MRS). Our sample consisted of 60 subjects ranging in age from 18 to 32 (27 females). Personality was assessed with the NEO Five-Factor Inventory (NEO-FFI). We measured brain biochemistry within the precuneus, the cingulate cortex, and underlying white matter. We hypothesized that brain biochemistry within these regions would predict individual differences across major domains of personality functioning. Biochemical models were fit for all personality domains including Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness. Our findings involved differing concentrations of Choline (Cho), Creatine (Cre), and N-acetylaspartate (NAA) in regions both within (i.e., posterior cingulate cortex) and white matter underlying (i.e., precuneus) the Default Mode Network (DMN). These results add to an emerging literature regarding personality neuroscience, and implicate biochemical integrity within the default mode network as constraining major personality domains within normal human subjects.

Background Neuropsychiatric systemic lupus erythematosus (NPSLE) is associated with increased morbidity and mortality. Methods We used Diffusion Tensor Imaging (DTI) to assess white matter abnormalities in seventeen NPSLE patients, sixteen SLE patients without NPSLE, and twenty age- and gender-matched controls. Results NPSLE patients differed significantly from SLE and control patients in white matter integrity of the body of the corpus callosum, the left arm of the forceps major and the left anterior corona radiata. Conclusions Several possible mechanisms of white matter injury are explored, including vascular injury, medication effects, and platelet or fibrin macro- or microembolism from Libman-Sacks endocarditis.

Within systemic lupus erythematosus (SLE) patients can be divided into groups with and without central nervous system involvement, the latter being subcategorized as neuropsychiatric systemic lupus erythematosus (NPSLE). While a number of research groups have investigated NPSLE, there remains a lack of consistent application of this diagnostic criteria within neuroimaging studies. Previous neuroimaging research suggests that SLE patients have reduced subcortical and regional gray matter volumes when compared to controls, and that these group differences may be driven by SLE patients with neuropsychiatric symptoms. The current study sought to compare measures of cortical thickness and subcortical structure volume between NPSLE, SLE, and healthy controls. We hypothesized that patients with NPSLE (N = 21) would have thinner cortex and reduced subcortical gray matter volumes when compared to SLE (N = 16) and control subjects (N = 21). All subjects underwent MRI examinations on a 1.5 Tesla Siemens Sonata scanner. Anatomical reconstruction and segmentation were performed using the FreeSurfer image analysis suite. Cortical and subcortical volumes were extracted from FreeSurfer and analyzed for group differences, controlling for age. The NPSLE group exhibited decreased cortical thickness in clusters of the left frontal and parietal lobes as well as in the right parietal and occipital lobes compared to control subjects. Compared to the SLE group, the NPSLE group exhibited comparable thinning in clusters of the frontal and temporal lobes. Controlling for age, we found that between group effects for subcortical gray matter structures were significant for the thalamus (F = 3.06, p = .04), caudate nucleus (F = 3.19, p = .03), and putamen (F = 4.82, p = .005). These results clarify previous imaging work identifying cortical atrophy in a mixed SLE and NPSLE group, and suggest that neuroanatomical abnormalities are specific to SLE patients diagnosed with neuropsychiatric symptoms. Future work should help elucidate the underlying mechanisms underlying the emerging neurobiological profile seen in NPSLE, as well as clarify the apparent lack of overlap between cortical thinning and functional activation results and other findings pointing to increased functional activation during cognitive tasks.

Objective To determine the histopathologic basis of altered brain neurometabolites in neuropsychiatric systemic lupus erythematosus (NPSLE). Methods Brain neurometabolite concentrations in a 20-voxel area of the brain were determined premortem by magnetic resonance spectroscopy (MRS) in 7 individuals with NPSLE. Absolute concentrations of neurometabolite for N-acetylaspartate (NAA), choline, creatine, and lactate were measured. After the death of the patients, histopathologic changes were determined at autopsy of the brain and were matched voxel-by-voxel with the neurometabolites. Results The mean ± SD absolute concentrations of NAA (9.15 ± 1.78 mM in patients versus 12.2 ± 0.8 mM in controls; P < 0.01) and creatine (6.43 ± 0.16 mM in patients versus 6.90 ± 0.60 mM in controls; P < 0.003) were significantly reduced and the concentration of choline (2.51 ± 0.42 mM in patients versus 1.92 ± 0.32 mM in controls; P < 0.04) was significantly elevated in NPSLE patients as compared with controls. Widespread heterogeneous changes in the histologic features of the brain were present, including microinfarcts, microhemorrhages, bland angiopathy, thrombotic angiopathy with platelet and fibrin thrombi, neuronal necrosis in various states of resolution, reduced numbers of axons and neurons, vacuole and space formation among the fibers, reduced numbers of oligodendrocytes, reactive microglia and astrocytes, lipid-laden macrophages, and cyst formation. Neurometabolite abnormalities were closely associated with underlying histopathologic changes in the brain: 1) elevated choline levels were independently associated with gliosis, vasculopathy, and edema (r = 0.75, P < 0.004 in the multivariate model); 2) reduced creatine levels with reduced neuronal–axonal density and gliosis (r = 0.72, P < 0.002 in the multivariate model); 3) reduced NAA levels with reduced neuronal–axonal density (r = 0.66, P < 0.001 in the multivariate model); and 4) the presence of lactate with necrosis, microhemorrhages, and edema (r = 0.996, P < 0.0001 in the multivariate model). Conclusion Altered neurometabolites in NPSLE patients, as determined by MRS, are a grave prognostic sign, indicating serious underlying histologic brain injury.

We investigated glutamate-related neuronal dysfunction in the anterior cingulate (AC) early in schizophrenia before and after antipsychotic treatment. A total of 14 minimally treated schizophrenia patients and 10 healthy subjects were studied with single-voxel proton magnetic resonance spectroscopy (1H-MRS) of the AC, frontal white matter and thalamus at 4 T. Concentrations of N-acetylaspartate (NAA), glutamate (Glu), glutamine (Gln) and Gln/Glu ratios were determined and corrected for the partial tissue volume. Patients were treated with antipsychotic medication following a specific algorithm and 1H-MRS was repeated after 1, 6 and 12 months. There were group × region interactions for baseline NAA (P = 0.074) and Gln/Glu (P = 0.028): schizophrenia subjects had lower NAA (P = 0.045) and higher Gln/Glu (P = 0.006) in the AC before treatment. In addition, AC Gln/Glu was inversely related to AC NAA in the schizophrenia (P = 0.0009) but not in the control group (P = 0.92). Following antipsychotic treatment, there were no further changes in NAA, Gln/Glu or any of the other metabolites in any of the regions studied. We conclude that early in the illness, schizophrenia patients already show abnormalities in glutamatergic metabolism and reductions in NAA consistent with glutamate-related excitotoxicity.

Although cognitive dysfunction is a primary characteristic of schizophrenia, only recently have investigations begun to pinpoint when the dysfunction develops in the individual afflicted by the disorder. Research to date provides evidence for significant cognitive impairments prior to disorder onset. Less is known about the course of cognitive dysfunction from onset to the chronic phase of schizophrenia. Although longitudinal studies are optimal for assessing stability of cognitive deficits, practice effects often confound assessments, and large and representative subject samples have not been followed over long periods of time. We report results of a cross-sectional study of cognitive deficits early and late in the course of schizophrenia carried out at four different geographic locations to increase sample size and generalizability of findings. We examined a broad set of cognitive functions in 41 recent-onset schizophrenia patients and 106 chronic schizophrenia patients. The study included separate groups of 43 matched controls for the recent-onset sample and 105 matched controls for the chronic schizophrenia sample in order to evaluate the effects of cohort (i.e., age) and diagnosis (i.e., schizophrenia) on cognitive functions. All measures of cognitive function showed effects of diagnosis; however, select time-based measures of problem solving and fine motor dexterity exhibited interactions of diagnosis and cohort indicating that these deficits may progress beyond what is expected with normal aging. Also, worse recall of material in episodic memory was associated with greater length of illness. Nevertheless, findings indicate that nearly all cognitive deficits are comparably impaired across recent-onset and chronic schizophrenia.

General intelligence (g) is highly correlated with working-memory capacity (WMC). It has been argued that these central psychological constructs should share common neural systems. The present study examines this hypothesis using structural magnetic resonance imaging to determine any overlap in brain areas where regional grey matter volumes are correlated to measures of general intelligence and to memory span. In normal volunteers (N = 48) the results (p < .05, corrected for multiple comparisons) indicate that a common anatomic framework for these constructs implicates mainly frontal grey matter regions belonging to Brodmann area (BA) 10 (right superior frontal gyrus and left middle frontal gyrus) and, to a lesser degree, the right inferior parietal lobule (BA 40). These findings support the nuclear role of a discrete parieto-frontal network.

Reduced brain N-acetyl-aspartate (NAA) has been repeatedly found in chronic schizophrenia and suggests neuronal loss or dysfunction. However, the potential confounding effect of antipsychotic drugs on NAA has not been resolved. We studied 32 minimally treated schizophrenia patients and 21 healthy subjects with single-voxel proton magnetic resonance spectroscopy ((1)H-MRS) of the frontal and occipital lobes, caudate nucleus, and cerebellum. Concentrations of NAA, Choline, and Cre were determined and corrected for the proportion of cerebrospinal fluid (CSF) in the voxel. Patients were treated in a randomized-controlled double-blind manner with either haloperidol or quetiapine. (1)H-MRS was repeated every 6 months for up to 2 years. There was a group main effect for baseline NAA with lower global NAA in schizophrenia subjects before treatment compared to healthy controls. Global NAA was directly related to measures of global cognitive performance in the whole subject sample. Following treatment with haloperidol or quetiapine, there were no changes in NAA in any of the regions studied. Early in the illness, schizophrenia patients already demonstrate subtle reductions in NAA. Treatment with typical or atypical antipsychotic medications for several months does not result in NAA changes.

A strategy for using tissue water as a concentration standard in (1)H magnetic resonance spectroscopic imaging studies on the brain is presented, and the potential errors that may arise when the method is used are examined. The sensitivity of the method to errors in estimates of the different water compartment relaxation times is shown to be small at short echo times (TEs). Using data from healthy human subjects, it is shown that different image segmentation approaches that are commonly used to account for partial volume effects (SPM2, FSL's FAST, and K-means) lead to different estimates of metabolite levels, particularly in gray matter (GM), owing primarily to variability in the estimates of the cerebrospinal fluid (CSF) fraction. While consistency does not necessarily validate a method, a multispectral segmentation approach using FAST yielded the lowest intersubject variability in the estimates of GM metabolites. The mean GM and white matter (WM) levels of N-acetyl groups (NAc, primarily N-acetylaspartate), choline (Ch), and creatine (Cr) obtained in these subjects using the described method with FAST multispectral segmentation are reported: GM [NAc] = 17.16 +/- 1.19 mM; WM [NAc] = 14.26 +/- 1.38 mM; GM [Ch] = 3.27 +/- 0.47 mM; WM [Ch] = 2.65 +/- 0.25 mM; GM [Cr] = 13.98 +/- 1.20 mM; and WM [Cr] = 7.10 +/- 0.67 mM.

Response time (RT) generally slows with aging, but the contribution of structural brain changes to this slowing is unknown. We used voxel-based morphometry (VBM) to determine gray matter (GM) and white matter (WM) brain volumes in 9 middle-aged adults (38-58 years old) and 9 seniors (66-82 years old). We correlated brain volumes with RT assessed in both a simple visual stimulus-response task and a visual continuous recognition memory task. No GM correlations with simple RT were significant; there was one WM correlation in the right fusiform gyrus. In the memory task, faster RT was correlated (p < .05, corrected) with less GM in the globus pallidus, the parahippocampus, and the thalamus for both groups. Several Brodmann areas (BA) differed between the groups such that in each area, less GM was correlated with slower RTs in the middle-aged group but with faster RTs in the senior group (BAs 19, 37, 46, 9, 8, 6, 13, 10, 41, and 7). The results suggest that individual differences in specific brain structure volumes should be considered as potential moderating factors in cognitive brain imaging studies.