H. Jeremy Bockholt

Dysregulation of Working Memory and Default- Mode Networks in Schizophrenia Using Independent Component Analysis, an fBIRN and MCIC Study

Deficits in working memory (WM) are a consistent neurocognitive marker for schizophrenia. Previous studies have suggested that WM is the product of coordinated activity in distributed functionally connected brain regions. Independent component analysis (ICA) is a data‐driven approach that can identify temporally coherent networks that underlie fMRI activity. We applied ICA to an fMRI dataset for 115 patients with chronic schizophrenia and 130 healthy controls by performing the Sternberg Item Recognition Paradigm. Here, we describe the first results using ICA to identify differences in the function of WM networks in schizophrenia compared to controls. ICA revealed six networks that showed significant differences between patients with schizophrenia and healthy controls. Four of these networks were negatively task‐correlated and showed deactivation across the posterior cingulate, precuneus, medial prefrontal cortex, anterior cingulate, inferior parietal lobules, and parahippocampus. These networks comprise brain regions known as the default‐mode network (DMN), a well‐characterized set of regions shown to be active during internal modes of cognition and implicated in schizophrenia. Two networks were positively task‐correlated, with one network engaging WM regions such as bilateral DLPFC and inferior parietal lobules while the other network engaged primarily the cerebellum. Our results suggest that DLPFC dysfunction in schizophrenia might be lateralized to the left and intrinsically tied to other regions such as the inferior parietal lobule and cingulate gyrus. Furthermore, we found that DMN dysfunction in schizophrenia exists across multiple subnetworks of the DMN and that these subnetworks are individually relevant to the pathophysiology of schizophrenia. In summary, this large multsite study identified multiple temporally coherent networks, which are aberrant in schizophrenia versus healthy controls and suggests that both task‐correlated and task‐anticorrelated networks may serve as potential biomarkers. Hum Brain Mapp, 2009.

Neuroanatomy of creativity

Creativity has long been a construct of interest to philosophers, psychologists and, more recently, neuroscientists. Recent efforts have focused on cognitive processes likely to be important to the manifestation of novelty and usefulness within a given social context. One such cognitive process – divergent thinking – is the process by which one extrapolates many possible answers to an initial stimulus or target data set. We sought to link well established measures of divergent thinking and creative achievement (Creative Achievement Questionnaire – CAQ) to cortical thickness in a cohort of young (23.7 ± 4.2 years), healthy subjects. Three independent judges ranked the creative products of each subject using the consensual assessment technique (Amabile, 1982) from which a “composite creativity index” (CCI) was derived. Structural magnetic resonance imaging was obtained at 1.5 Tesla Siemens scanner. Cortical reconstruction and volumetric segmentation were performed with the FreeSurfer image analysis suite. A region within the lingual gyrus was negatively correlated with CCI; the right posterior cingulate correlated positively with the CCI. For the CAQ, lower left lateral orbitofrontal volume correlated with higher creative achievement; higher cortical thickness was related to higher scores on the CAQ in the right angular gyrus. This is the first study to link cortical thickness measures to psychometric measures of creativity. The distribution of brain regions, associated with both divergent thinking and creative achievement, suggests that cognitive control of information flow among brain areas may be critical to understanding creative cognition. Hum Brain Mapp, 2010.

Use of tissue water as a concentration reference for proton spectroscopic imaging

A strategy for using tissue water as a concentration standard in 1H 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, FSLs 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. Magn Reson Med, 2006.

Insular cortex abnormalities in schizophrenia: a structural magnetic resonance imaging study of first-episode patients

The insular cortex is a limbic integration region that is engaged in emotional and cognitive functions. To investigate possible insular cortex abnormalities in schizophrenia, we measured insular gray matter volume and cortical surface size in drug-naive first-episode patients. Magnetic resonance images were used to explore the morphology of the insular cortex of 25 healthy male volunteers, and 25 male schizophrenic patients. Groups were matched for age, sex, height, and parental socio-economic status. Clinical dimension scores were correlated with insular gray matter volume and cortical surface area. Patients had a significant reduction in cortical surface area [patients=2020 (206); controls=2142 (204); F=5.83, df=1, 47; P=0.01] and gray matter volume [patients=8.12 (0.77); controls=8.57 (0.94); F=3.93, df=1,47; P=0.05] in the left insular cortex. Insular gray matter volume and cortical surface size correlated negatively and significantly with the psychotic symptom dimension. Schizophrenic patients show morphological abnormalities in the insular cortex at early stages of the illness. These abnormalities are related to the severity of psychotic symptoms. Further investigations are needed to evaluate the role of the insula in the pathophysiology of schizophrenia.

Prediction of manifest Huntington's disease with clinical and imaging measures: a prospective observational study

BACKGROUND Although the association between cytosine-adenine-guanine (CAG) repeat length and age at onset of Huntingtons disease is well known, improved prediction of onset would be advantageous for clinical trial design and prognostic counselling. We compared various measures for tracking progression and predicting conversion to manifest Huntingtons disease. METHODS In this prospective observational study, we assessed the ability of 40 measures in five domains (motor, cognitive, psychiatric, functional, and imaging) to predict time to motor diagnosis of Huntingtons disease, accounting for CAG repeat length, age, and the interaction of CAG repeat length and age. Eligible participants were individuals from the PREDICT-HD study (from 33 centres in six countries [USA, Canada, Germany, Australia, Spain, UK]) with the gene mutation for Huntingtons disease but without a motor diagnosis (a rating below 4 on the diagnostic confidence level from the 15-item motor assessment of the Unified Huntingtons Disease Rating Scale). Participants were followed up between September, 2002, and July, 2014. We used joint modelling of longitudinal and survival data to examine the extent to which baseline and change of measures analysed separately was predictive of CAG-adjusted age at motor diagnosis. FINDINGS 1078 individuals with a CAG expansion were included in this analysis. Participants were followed up for a mean of 5·1 years (SD 3·3, range 0·0-12·0). 225 (21%) of these participants received a motor diagnosis of Huntingtons disease during the study. 37 of 40 cross-sectional and longitudinal clinical and imaging measures were significant predictors of motor diagnosis beyond CAG repeat length and age. The strongest predictors were in the motor, imaging, and cognitive domains: an increase of one SD in total motor score (motor domain) increased the risk of a motor diagnosis by 3·07 times (95% CI 2·26-4·16), a reduction of one SD in putamen volume (imaging domain) increased risk by 3·32 times (2·37-4·65), and a reduction of one SD in Stroop word score (cognitive domain) increased risk by 2·32 times (1·88-2·87). INTERPRETATION Prediction of diagnosis of Huntingtons disease can be improved beyond that obtained by CAG repeat length and age alone. Such knowledge about potential predictors of manifest Huntingtons disease should inform discussions about guidelines for diagnosis, prognosis, and counselling, and might be useful in guiding the selection of participants and outcome measures for clinical trials. FUNDING US National Institutes of Health, US National Institute of Neurological Disorders and Stroke, and CHDI Foundation.

Global White Matter Abnormalities in Schizophrenia: A Multisite Diffusion Tensor Imaging Study

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.

Voxel-based Morphometric Multisite Collaborative Study on Schizophrenia

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.

Cerebral cortex: a topographic segmentation method using magnetic resonance imaging

Remarkable developments in magnetic resonance imaging (MRI) technology provide a broad range of potential applications to explore in vivo morphological characteristics of the human cerebral cortex. MR-based parcellation methods of the cerebral cortex may clarify the structural anomalies in specific brain subregions that reflect underlying neuropathological processes in brain illnesses. The present study describes detailed guidelines for the parcellation of the cerebral cortex into 41 subregions. Our method conserves the topographic uniqueness of individual brains and is based on our ability to visualize the three orthogonal planes, the triangulated gray matter isosurface and the three-dimensional (3D) rendered brain simultaneously. Based upon topographic landmarks of individual sulci, every subregion was manually segmented on a set of serial coronal or transaxial slices consecutively. The reliability study indicated that the cerebral cortex could be parcelled reliably; intraclass correlation coefficients for each subregion ranged from 0.60 to 0.99. The validity of the method is supported by the fact that gyral subdivisions are similar to regions delineated in functional imaging studies conducted in our center. Ultimately, this method will permit us to detect subtle morphometric impairments or to find abnormal patterns of functional activation in circumscribed cortical subregions. The description of a thorough map of regional structural and functional cortical abnormalities will provide further insight into the role that different subregions play in the pathophysiology of brain illnesses.

The COMT Val108/158Met Polymorphism and Medial Temporal Lobe Volumetry in Patients with Schizophrenia and Healthy Adults

Abnormalities of the medial temporal lobe have been consistently demonstrated in schizophrenia. A common functional polymorphism, Val108/158Met, in the putative schizophrenia susceptibility gene, catechol-O-methyltransferase (COMT), has been shown to influence medial temporal lobe function. However, the effects of this polymorphism on volumes of medial temporal lobe structures, particularly in patients with schizophrenia, are less clear. Here we measured the effects of COMT Val108/158Met genotype on the volume of two regions within the medial temporal lobe, the amygdala and hippocampus, in patients with schizophrenia and healthy control subjects. We obtained MRI and genotype data for 98 schizophrenic patients and 114 matched controls. An automated atlas-based segmentation algorithm was used to generate volumetric measures of the amygdala and hippocampus. Regression analyses included COMT met allele load as an additive effect, and also controlled for age, intracranial volume, gender and acquisition site. Across patients and controls, each copy of the COMT met allele was associated on average with a 2.6% increase in right amygdala volume, a 3.8% increase in left amygdala volume and a 2.2% increase in right hippocampus volume. There were no effects of COMT genotype on volumes of the whole brain and prefrontal regions. Thus, the COMT Val108/158Met polymorphism was shown to influence medial temporal lobe volumes in a linear-additive manner, mirroring its effect on dopamine catabolism. Taken together with previous work, our data support a model in which lower COMT activity, and a resulting elevation in extracellular dopamine levels, stimulates growth of medial temporal lobe structures.

Does function follow form?: Methods to fuse structural and functional brain images show decreased linkage in schizophrenia

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.