Search

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.

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).

Primary brain tumours often occur near eloquent regions, affecting language, motor and memory capacity, with awake mapping and tailored resection designed to preserve higher cognitive functioning. The effects of such tumours on subcortical structures, including the thalamus and basal ganglia, have been largely unexplored, in spite of the known importance of such structures to higher cognitive functioning. We sought to explore the effects of volume changes of subcortical structures on cognition, in 62 consecutive patients diagnosed with primary brain tumour and cavernous malformations, referred to our neurosurgical practice. We found right caudate to be highly predictive of intelligence, left pallidum of total neuropsychological function and right hippocampus of mood. Our study is the largest of its kind in exploring subcortical substrates of higher cognition in consecutive patients with brain tumours. This research supports prior literature, showing subcortical structures to be related to higher cognitive functioning, particularly measures of memory and executive functioning implicated in fronto-subcortical circuits. Furthermore, involvement of right mesial temporal structures in mood, further strengthens the central role of Papez circuit in emotional quality of cognition. Attention to subcortical integrity is likely to be important in discussing postsurgical cognitive outcome with patients and their families., We explored subcortical volume changes on cognition in 62 consecutive patients diagnosed with brain tumour and cavernous malformations. Right caudate volume predicted intelligence; left pallidum volume predicted total neuropsychological function; right hippocampus volume predicted mood. This research supports prior literature implicating fronto-subcortical circuits structural integrity in higher cognitive functioning., Graphical Abstract Graphical Abstract

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 ​

While there are minimal sex differences in overall intelligence, males, on average, have larger total brain volume and corresponding regional brain volumes compared to females, measures that are consistently related to intelligence. Limited research has examined which other brain characteristics may differentially contribute to intelligence in females to facilitate equal performance on intelligence measures. Recent reports of sex differences in the neural characteristics of the brain further highlight the need to differentiate how the structural neural characteristics relate to intellectual ability in males and females. The current study utilized a graph network approach in conjunction with structural equation modeling to examine potential sex differences in the relationship between white matter efficiency, fronto-parietal gray matter volume, and general cognitive ability (GCA). Participants were healthy adults (n = 244) who completed a battery of cognitive testing and underwent structural neuroimaging. Results indicated that in males, a latent factor of fronto-parietal gray matter was significantly related to GCA when controlling for total gray matter volume. In females, white matter efficiency and total gray matter volume were significantly related to GCA, with no specificity of the fronto-parietal gray matter factor over and above total gray matter volume. This work highlights that different neural characteristics across males and females may contribute to performance on intelligence measures. Hum Brain Mapp 37:4006-4016, 2016. © 2016 Wiley Periodicals, Inc.

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.

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.

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

The refinement of localization of intelligence in the human brain is converging onto a distributed network that broadly conforms to the Parieto-Frontal Integration Theory (P-FIT). While this theory has received support in the neuroimaging literature, no functional magnetic resonance imaging study to date has conducted a whole-brain network-wise examination of the changes during engagement in tasks that are reliable measures of general intelligence (e.g., Raven's Progressive Matrices Test; RPM). Seventy-nine healthy subjects were scanned while solving RPM problems and during rest. Functional networks were extracted from the RPM and resting state data using Independent Component Analysis. Twenty-nine networks were identified, 26 of which were detected in both conditions. Fourteen networks were significantly correlated with the RPM task. The networks' spatial maps and functional connectivity measures at 3 frequency levels (low, medium, & high) were compared between the RPM and rest conditions. The regions involved in the networks that were found to be task related were consistent with the P-FIT, localizing to the bilateral medial frontal and parietal regions, right superior frontal lobule, and the right cingulate gyrus. Functional connectivity in multiple component pairs was differentially affected across all frequency levels during the RPM task. Our findings demonstrate that functional brain networks are more stable than previously thought, and maintain their general features across resting state and engagement in a complex cognitive task. The described spatial and functional connectivity alterations that such components undergo during fluid reasoning provide a network-wise framework of the P-FIT that can be valuable for further, network based, neuroimaging inquiries regarding the neural underpinnings of intelligence.

Clinical and cognitive symptoms domain-based subtyping in schizophrenia (Sz) has been critiqued due to the lack of neurobiological correlates and heterogeneity in symptom scores. We, therefore, present a novel data-driven framework using biclustered independent component analysis to detect subtypes from the reliable and stable gray matter concentration (GMC) of patients with Sz. The developed methodology consists of the following steps: source-based morphometry (SBM) decomposition, selection and sorting of two component loadings, subtype component reconstruction using group information-guided ICA (GIG-ICA). This framework was applied to the top two group discriminative components namely the insula/superior temporal gyrus/inferior frontal gyrus (I-STG-IFG component) and the superior frontal gyrus/middle frontal gyrus/medial frontal gyrus (SFG-MiFG-MFG component) from our previous SBM study, which showed diagnostic group difference and had the highest effect sizes. The aggregated multisite dataset consisted of 382 patients with Sz regressed of age, gender, and site voxelwise. We observed two subtypes (i.e., two different subsets of subjects) each heavily weighted on these two components, respectively. These subsets of subjects were characterized by significant differences in positive and negative syndrome scale (PANSS) positive clinical symptoms (p = 0.005). We also observed an overlapping subtype weighing heavily on both of these components. The PANSS general clinical symptom of this subtype was trend level correlated with the loading coefficients of the SFG-MiFG-MFG component (r = 0.25; p = 0.07). The reconstructed subtype-specific component using GIG-ICA showed variations in voxel regions, when compared to the group component. We observed deviations from mean GMC along with conjunction of features from two components characterizing each deciphered subtype. These inherent variations in GMC among patients with Sz could possibly indicate the need for personalized treatment and targeted drug development.

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.

There is increasing interest in learning how human brain networks vary as a function of a continuous trait, but flexible and efficient procedures to accomplish this goal are limited. We develop a Bayesian semiparametric model, which combines low-rank factorizations and flexible Gaussian process priors to learn changes in the conditional expectation of a network-valued random variable across the values of a continuous predictor, while including subject-specific random effects. The formulation leads to a general framework for inference on changes in brain network structures across human traits, facilitating borrowing of information and coherently characterizing uncertainty. We provide an efficient Gibbs sampler for posterior computation along with simple procedures for inference, prediction and goodness-of-fit assessments. The model is applied to learn how human brain networks vary across individuals with different intelligence scores. Results provide interesting insights on the association between intelligence and brain connectivity, while demonstrating good predictive performance., 22 pages, 7 figures

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.

A 1H magnetic resonance spectroscopic imaging study at 3T and short echo time was conducted to evaluate both the reproducibility, as measured by the interscan coefficient of variation (CV), and test-retest reliability, as measured by the intraclass correlation coefficient (ICC), of measurements of glutamate (Glu), combined glutamate and glutamine (Glx), myo-inositol (mI), N-acetylaspartate, creatine, and choline in 21 healthy subjects. The effect of partial volume correction on these measures and the relationship of reproducibility and reliability to data quality were also examined. A 1H magnetic resonance spectroscopic imaging slice was prescribed above the lateral ventricles and single repeat scans were performed within 30 min to minimize physiologic variability. Interscan CVs based on all the voxels varied from 0.05 to 0.07 for N-acetylaspartate, creatine, and choline to 0.10-0.13 for mI, Glu, and Glx. Findings on the reproducibility of gray and white matter estimates of N-acetylaspartate, creatine, and choline are consistent with previous studies using longer echo times, with CVs in the range of 0.02-0.04 and ICC in the range of 0.65-0.90. CVs for Glu, Glx, and mI are much lower than reported in previous studies at 1.5 T, while white matter mI (CV=0.04, ICC=0.93) and gray matter Glx (CV=0.04, ICC=0.68) demonstrated both high reproducibility and test-retest reliability.

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.

The parieto-frontal integration theory (P-FIT) nominates several areas distributed throughout the brain as relevant for intelligence. This theory was derived from previously published studies using a variety of both imaging methods and tests of cognitive ability. Here we test this theory in a new sample of young healthy adults (N = 100) using a psychometric battery tapping fluid, crystallized, and spatial intelligence factors. High resolution structural MRI scans (3T) were obtained and analyzed with Voxel-based Morphometry (VBM). The main findings are consistent with the P-FIT, supporting the view that general intelligence (g) involves multiple cortical areas throughout the brain. Key regions include the dorsolateral prefrontal cortex, Broca's and Wernicke's areas, the somato-sensory association cortex, and the visual association cortex. Further, estimates of crystallized and spatial intelligence with g statistically removed, still share several brain areas with general intelligence, but also show some degree of uniqueness.

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.

There is increasing evidence relating psychometric measures of general intelligence and reasoning to regional brain structure and function assessed with a variety of neuroimaging techniques. Cognitive dimensions independent of general intelligence can also be identified psychometrically and studied for any neuroanatomical correlates. Here we investigated two such dimensions, rotation–verbal and focus–diffusion. We used structural MRI and voxel-based morphometry (VBM) in two independent samples to identify gray and white matter correlates of both dimensions. Based on statistical conjunction of both samples, (N = 45; p

“Is there a biology of intelligence which is characteristic of the normal human nervous system?” Here we review 37 modern neuroimaging studies in an attempt to address this question posed by Halstead (1947) as he and other icons of the last century endeavored to understand how brain and behavior are linked through the expression of intelligence and reason. Reviewing studies from functional (i.e., functional magnetic resonance imaging, positron emission tomography) and structural (i.e., magnetic resonance spectroscopy, diffusion tensor imaging, voxel-based morphometry) neuroimaging paradigms, we report a striking consensus suggesting that variations in a distributed network predict individual differences found on intelligence and reasoning tasks. We describe this network as theParieto-Frontal Integration Theory(P-FIT). The P-FIT model includes, by Brodmann areas (BAs): the dorsolateral prefrontal cortex (BAs 6, 9, 10, 45, 46, 47), the inferior (BAs 39, 40) and superior (BA 7) parietal lobule, the anterior cingulate (BA 32), and regions within the temporal (BAs 21, 37) and occipital (BAs 18, 19) lobes. White matter regions (i.e., arcuate fasciculus) are also implicated. The P-FIT is examined in light of findings from human lesion studies, including missile wounds, frontal lobotomy/leukotomy, temporal lobectomy, and lesions resulting in damage to the language network (e.g., aphasia), as well as findings from imaging research identifying brain regions under significant genetic control. Overall, we conclude that modern neuroimaging techniques are beginning to articulate a biology of intelligence. We propose that the P-FIT provides a parsimonious account for many of the empirical observations, to date, which relate individual differences in intelligence test scores to variations in brain structure and function. Moreover, the model provides a framework for testing new hypotheses in future experimental designs.

It is unclear whether brain mechanisms underlying human intelligence are distributed throughout the brain or mainly concentrated in the frontal lobes. Data are inconsistent possibly due, at least in part, to the different ways the construct of intelligence is measured. Here we apply the method of correlated vectors to determine how the general factor of intelligence (g) is related to regional gray matter and white matter volumes. This is a re-analysis of an earlier study showing regional gray matter and white matter volume is correlated to Full Scale IQ (FSIQ). However, it is well-known that FSIQ taps several cognitive abilities and skills in addition to g. The results now show that the g factor accounts for several but not all FSIQ/gray matter correlations distributed throughout the brain and these areas may differ for young and older adults.

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.

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.

A lower level of intelligence, as measured by IQ, has historically been the central defining criterion of mental retardation (MR). The use of IQ scores in terms of standard deviation units from the mean is the basis for defining MR in the ICD-10 and DSM-IV-TR, and more recently for defining intellectual disability (ID) in the DSM-5. Similarly, ID is defined by the American Association on Intellectual and Developmental Disabilities as an IQ score approximately two standard deviations below the mean 1. However, in recent years, an increasing number of researchers and clinicians have expressed the view that measurements of IQ fail to capture individual differences in cognitive dysfunction. The heterogeneity of cognitive dysfunction and consequent adaptive behavior profile in persons with MR is one of the reasons leading the working group in charge of this issue within the revision of the ICD-10 to propose a new definition for intellectual developmental disorders (IDD) in the upcoming 11th edition of the diagnostic system 2. In 2011, the WPA Section on Psychiatry of Intellectual Disability started a mini-Delphi process with an international panel of experts to produce a consensus document on this issue. The present letter reports the results of the systematic mapping 3 of the international literature included in this process, focusing on current models of intelligence, multi-component and specific cognitive functions, and the relationship between intellectual and affective assessment, as relevant for defining IDD. A total of 7,948 articles matched the key words. After titles were checked, 3,179 were selected. After abstracts were read, 2,497 were excluded as they were not relevant to the mapping topic, and 114 were excluded because they were not in English. After reading the remaining articles in full, 177 papers were included as relevant to search questions. The mapping of current theoretical approaches identified limitations of IQ as an indicator of the adaptive complexity and dynamism of human intellectual functioning and pointed out the need for a shared model and comprehensive definition of intelligence. Of the available approaches, the most frequently used refers to a unitary capacity, articulated in complex functions. A second evolving group of theories identifies a key role of interdependent but specialized factors, such as specific cognitive functions. There is a neuro-bio-psychological evidence in support of both approaches, but multi-component models seem to prevail. Experimental data indicate that the same IQ score can correspond to very different cognitive profiles, and that functional limitations and problem behaviors associated with IDD correlate with impairment of specific cognitive functions more than with IQ 4,5. To address the limitations of the current conceptualization of MR, the ICD-11 working group proposed revised diagnostic criteria for IDD, based on a more articulated model of cognitive impairment. This approach juxtaposes a new concept of cognitive characterization to that of intelligence and complements the measurement of IQ with the assessment of specific cognitive functions and a contextualised description of consequent adaptive and learning difficulties 2. Within this new approach, cognitive skills should be assessed through tests, semi-structured observations, and direct clinical examination. The tests should combine the measurement of IQ with that of several aspects of executive functioning, including perceptual reasoning, processing speed, verbal comprehension, as well as the assessment of attention, perception and working memory. The evaluation should aim to identify the cognitive dysfunctions that have the greatest negative impact in terms of behavior, adjustment, autonomy, and above all quality of life, across the lifespan. The instruments to assess specific cognitive functions should have a low cost, in order to allow fast assimilation by professionals practicing in low-income countries 6. Production and distribution by international non-profit organizations could greatly facilitate this effort. In conclusion, within the proposed ICD-11 framework for characterization of IDD, there is a need for neuropsychological measures that can be readily adapted to different levels of severity, and that are easy to apply in clinical and research practice. The evolving understanding of how environmental and cultural factors influence development should promote a continuing search for assessment models and practices that capture developmental pathways of cognition in persons with IDD. Naturalistic, multidisciplinary and multicentric studies could provide useful data to this purpose 7.

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.

Currently, connectomes (e.g., functional or structural brain graphs) can be estimated in humans at $\approx 1~mm^3$ scale using a combination of diffusion weighted magnetic resonance imaging, functional magnetic resonance imaging and structural magnetic resonance imaging scans. This manuscript summarizes a novel, scalable implementation of open-source algorithms to rapidly estimate magnetic resonance connectomes, using both anatomical regions of interest (ROIs) and voxel-size vertices. To assess the reliability of our pipeline, we develop a novel nonparametric non-Euclidean reliability metric. Here we provide an overview of the methods used, demonstrate our implementation, and discuss available user extensions. We conclude with results showing the efficacy and reliability of the pipeline over previous state-of-the-art., Published as part of 2013 IEEE GlobalSIP conference

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.

NPSLE is a treacherous disease in which an ill-considered or simplistic approach can be fatal for the patient and disastrous for the physician. The wide array of physical and behavioral manifestations of NPSLE necessitate considerable clinical judgment, selected application of imaging and laboratory modalities, and careful consideration and consultation before therapy to avoid misdiagnosis and inappropriate over- or undertreatment. The physician must recognize that the initial diagnosis in these patients is often incorrect, and the clinician must therefore remain vigilant to react appropriately with further studies and consultation if the patient is not improving. However, despite the recognized difficulties in diagnosis, the neurologic complications of NPSLE can be approached in a careful, logical manner with gratifying results.

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.

The human brain and the neuronal networks comprising it are of immense interest to the scientific community. In this work, we focus on the structural connectivity of human brains, investigating sex differences across male and female connectomes (brain-graphs) for the knowledge discovery problem "Which brain regions exert differences in connectivity across the two sexes?". One of our main findings discloses the statistical difference at the pars orbitalis of the connectome between sexes, which has been shown to function in language production. Moreover, we use these discriminative regions for the related learning problem "Can we classify a given human connectome to belong to one of the sexes just by analyzing its connectivity structure?" . We show that we can learn decision tree as well as support vector machine classification models for this task. We show that our models achieve up to 79% prediction accuracy with only a handful of brain regions as discriminating factors. Importantly, our results are consistent across two data sets, collected at two different centers, with two different scanning sequences, and two different age groups (children and elderly). This is highly suggestive that we have discovered scientifically meaningful sex differences.

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

Based upon earlier studies relating task-unrelated image and thought (TUIT) frequency to circadian activity levels and to decreases with increased age in adulthood it was hypothesized that increased cortical arousal would result in greater TUIT frequency. In a double-blind study, six young men had arousal induced at two dosages of caffeine, 100 mg and 300 mg. When unintentional and deliberate TUIT frequency at the 100 mg and 300 mg dosages was contrasted with the placebo no significant effects were noted. Change in TUIT frequency between placebo and the 300 mg dosage was significantly correlated with the personality trait of Agreeableness. Lack of compliance, caffeine withdrawal influences, and insufficiently high arousal are discussed as possible sources of the lack of relationship obtained between caffeine dosage and TUIT frequency.

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.

A significant body of evidence has accumulated suggesting that individual variation in intellectual ability, whether assessed directly by intelligence tests or indirectly through proxy measures, is related to risk of developing Alzheimer's disease (AD) in later life. Important questions remain unanswered, however, such as the specificity of risk for AD vs. other forms of dementia, and the specific links between premorbid intelligence and development of the neuropathology characteristic of AD. Lower premorbid intelligence has also emerged as a risk factor for greater mortality across myriad health and mental health diagnoses. Genetic covariance contributes importantly to these associations, and pleiotropic genetic effects may impact diverse organ systems through similar processes, including inefficient design and oxidative stress. Through such processes, the genetic underpinnings of intelligence, specifically, mutation load, may also increase the risk of developing AD. We discuss how specific neurobiologic features of relatively lower premorbid intelligence, including reduced metabolic efficiency, may facilitate the development of AD neuropathology. The cognitive reserve hypothesis, the most widely accepted account of the intelligence-AD association, is reviewed in the context of this larger literature.

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.