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Objective: Factors underlying progressive brain volume changes in schizophrenia remain poorly understood. The authors investigated whether a gene polymorphism influencing neuroplasticity may contribute to longitudinal brain volume alterations.Method: High-resolution magnetic resonance (MR) images of the whole brain were obtained for 119 patients with recent-onset schizophrenia spectrum disorders. Changes in brain volumes over an average of 3 years were compared between brain-derived neurotrophic factor (BDNF) val66met genotype groupings. Exploratory analyses were conducted to examine relationships between antipsychotic treatment and brain volume changes as well as the effects of BDNF genotype on changes in cognition and symptoms.Results: Significant genotype effects were observed on within-subject changes in volumes of frontal lobe gray matter, lateral ventricles, and sulcal CSF. Met allele carriers had significantly greater reductions in frontal gray matter volume, with reciprocal volume increases in the lateral ventricles and sulcal (especially frontal and temporal) CSF than Val homozygous patients. Independent of BDNF genotype, more antipsychotic exposure between MRI scans correlated with greater volume reductions in frontal gray matter, particularly among patients who were initially treatment naive. There were no statistically significant genotype effects on within-subject changes in cognition or symptoms.Conclusions: BDNF(Met) variant may be one of several factors affecting progressive brain volume changes in schizophrenia. [ABSTRACT FROM AUTHOR]

Context: Loss of the capacity to experience pleasure (anhedonia) is a core clinical feature of schizophrenia. Although functional imaging techniques have been successful in identifying the neural basis of cognitive impairments in schizophrenia, no attempts to date have been made to investigate neural systems underlying emotional disturbances.Objective: To study the neural basis of emotional processing in schizophrenia by exploring the pattern of brain responses to olfactory stimuli in patients and healthy volunteers.Design: Positron emission tomographic study of patients with schizophrenia and healthy volunteers. Positron emission tomographic data were collected between July 21, 1995, and September 11, 1997, and data analyses were conducted in 1999-2001.Setting: The Mental Health Clinical Research Center at the University of Iowa, Iowa City.Participants: Sixteen healthy volunteers with a mean age of 29.5 years and 18 patients with schizophrenia and a mean age of 30.0 years.Main Outcome Measure: Areas of relative increase or decrease in regional cerebral blood flow, measured using positron emission tomography and the [(15)O]water method while participants performed an emotion-induction olfactory task to determine response to pleasant (vanillin) and unpleasant (4-methylvaleric acid) odors, compared between patients and healthy volunteers.Results: Patients with schizophrenia subjectively experienced unpleasant odors in a manner similar to healthy volunteers but showed impairment in the experience of pleasant odors. The analysis of the regional cerebral blood flow revealed that patients failed to activate limbic/paralimbic regions (eg, insular cortex, nucleus accumbens, and parahippocampal gyrus) during the experience of unpleasant odors, recruiting a compensatory set of frontal cortical regions instead.Conclusion: Abnormalities in the complex functional interactions between mesolimbic and frontal regions may underlie emotional disturbances in schizophrenia. [ABSTRACT FROM AUTHOR]

Schizophrenia is among the most severe and debilitating of psychiatric disorders. Diagnosis is currently by criterion-based systems, including positive (eg, hallucinations and delusions) and negative (eg, avolition and alogia) symptoms. The importance of negative symptoms in the course and outcome of the illness is increasingly being studied. Current research seeks to detect causal mechanisms in schizophrenia through studies of neural connectivity and function, as well as models of genetic transmission, such as polygenic models of inheritance in genetic research. Potential genes have been identified that may confer vulnerability to the illness, perhaps in conjunction with environmental factors. Neuroimaging research with magnetic resonance imaging and positron emission tomography has investigated differences in volumes and functional dysregulation in specific neural subregions. Areas studied include the frontal and temporal cortex, the hippocampus, the thalamus, and the cerebellum. Despite these advances, treatment of symptoms and psychosocial and cognitive impairments remains only partially successful for many patients. [ABSTRACT FROM AUTHOR]

Clinical observation suggests that the aging process affects gyrification, with the brain appearing more 'atrophic' with increasing age. Empirical studies of tissue type indicate that gray matter volume decreases with age while cerebrospinal fluid increases. Quantitative changes in cortical surface characteristics such as sulcal and gyral shape have not been measured, however, due to difficulties in developing a method that separates abutting gyral crowns and opens up the sulci - the 'problem of buried cortex'. We describe a quantitative method for measuring brain surface characteristics that is reliable and valid. This method is used to define the gyral and sulcal characteristics of atrophic and non-atrophic brains and to examine changes that occur with aging in a sample of 148 normal individuals from a broad age range. The shape of gyri and sulci change significantly over time, with the gyri becoming more sharply and steeply curved, while the sulci become more flattened and less curved. Cortical thickness also decreases over time. Cortical thinning progresses more rapidly in males than in females. The progression of these changes appears to be relatively stable during midlife and to begin to progress some time during the fourth decade. Measurements of sulcal and gyral shape may be useful in studying the mechanisms of both neurodevelopmental and neurodegenerative changes that occur during brain maturation and aging. [ABSTRACT FROM AUTHOR]

Objective: Extraversion, a trait associated with individual differences in approach motivation and the experience of positive emotional states, is negatively correlated with certain psychiatric disorders, including depression and social phobia. The authors examined the correlation between extraversion and regional cerebral blood flow (rCBF) while participants were exposed to olfactory stimuli in order to further characterize individual differences in hedonic processing associated with this trait. Method: Twelve healthy participants were exposed to pleasant and unpleasant odors while rCBF was measured using [(15)O] water PET. The NEO Five-Factor Inventory was used to assess extraversion. Associations between extraversion scores and rCBF in each olfactory stimulus condition were assessed by correlational analysis. Results: During the pleasant smell condition, extraversion was correlated with rCBF in the amygdala and occipital cortex. During the unpleasant smell condition, extraversion was correlated with rCBF in the occipital cortex and inferior temporal gyrus. Conclusions: These results provide important evidence for the biological basis of extraversion and indicate that there are systematic individual differences in patterns of brain activation in response to affective stimuli. [ABSTRACT FROM AUTHOR]

OBJECTIVE: The purpose of this study was to evaluate the functional state of glutamatergic neurons in the cerebellar cortex of patients with schizophrenia. METHOD: The authors measured messenger ribonucleic acid (mRNA) levels of three activity-dependent genes expressed by glutamatergic neurons in the cerebellar cortex (GAP-43, BDNF, and GABA (A)-delta subunit) in the tissues of 14 patients with schizophrenia and 14 matched nonpsychiatric comparison subjects. Since its level of expression does not change in response to neuronal activity, gamma-aminobutyric acid(A)-alpha6 subunit mRNA was used as a control. RESULTS: The levels of GAP-43 and BDNF mRNAs were significantly elevated in patients with schizophrenia, and a similar finding was observed for GABA(A)-delta mRNA. In contrast, the levels of the GABA(A)-alpha6 subunit mRNA, which is expressed in cerebellar granule cells in an activity-independent manner, did not differ from comparison subjects. CONCLUSIONS: These results suggest that glutamatergic neurons may be hyperactive in the cerebellar cortices of patients with schizophrenia. [ABSTRACT FROM AUTHOR]

This study explored the association between psychosocial variables and symptoms among patients with schizophrenia-spectrum disorders who have attempted suicide and those who have not attempted suicide. Of 336 patients with a DSM-III-R diagnosis of schizophrenia or schizoaffective disorder who were consecutively evaluated at a university-affiliated clinical research center, 98, or 29.2 percent, reported one or more suicide attempts. Compared with patients who had not attempted suicide, patients who had made an attempt had a greater number of lifetime depressive episodes, an earlier age of onset of their illness, and an earlier age at first hospitalization. [ABSTRACT FROM AUTHOR]

Transcription factors, including the basic helix-loop-helix (bHLH) family, regulate numerous genes and play vital roles in controlling gene expression. Consequently, transcription factor mutations can lead to phenotypic pleiotropy, and may be a candidate mechanism underlying the complex genetics and heterogeneous phenotype of schizophrenia. Neurogenin1 (NEUROG1; a.k.a. Ngn1 or Neurod3), a bHLH transcription factor encoded on a known schizophrenia linkage region in 5q31.1, induces glutamatergic and suppresses GABAergic neuronal differentiation during embryonic neurodevelopment. The goal of this study is to investigate NEUROG1 effects on schizophrenia risk and on phenotypic features of schizophrenia. We tested 392 patients with schizophrenia or schizoaffective disorder and 226 healthy normal volunteers for association with NEUROG1. Major alleles on two NEUROG1-associated SNPs (rs2344484-C-allele and rs8192558-G-allele) were significantly more prevalent among patients (p

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Brain reward processing mechanisms that underlie complex decision-making are compromised in psychosis. The goal of this research was to advance our understanding of the underlying (1) neural mechanisms and (2) discrete neuro-economic/motivational processes that may be altered in complex decision-making in euthymic patients on the psychosis spectrum (PPS). Utilizing a functional magnetic resonance neuroimaging (fmri) paradigm of a well-validated laboratory measure of complex decision-making (Iowa Gambling Task-IGT), the brain activation patterns of a target group of PPS were compared to a demographically matched healthy comparison group (HMC). These two groups were also evaluated on real-life decision outcomes on day of scan. PPS primarily activate the Dorsal Attentional Network (DAN) in real-life decision outcomes and in achieving similar levels of performance on the IGT as the HMC, in-spite of dysregulated dopamine-based brain-reward circuit and salience network fmri activation patterns. However, PPS report more significant negative outcomes of their decision-making in real-life, compared to HMC. The differential engagement of brain networks by PPS on the IGT appear to be moderated by antipsychotic, dopamine antagonist, medication lifetime/daily dose levels. These findings may also be mediated by extent of dysregulation in brain reward circuitry and salience network associated with psychosis severity in the target PPS group. This is also evident in case studies of unmedicated PPS. We conclude by suggesting that the brain may adapt to this dysregulation by co-opting the DAN network, which is implicated in the related function of problem-solving, towards complex decision-making. The extent of utilization of the DAN network in complex decision-making may be moderated by psychosis severity., Competing Interests: The authors have declared that no competing interests exist.

Whether superior intelligence is associated with global lower resource consumption in the brain remains unresolved. In order to tap fluid intelligence "Gf" cortical networks, 50 neurologically healthy adults were functionally neuro-imaged while solving a modified version of the Raven Advanced Progressive Matrices. "Gf" predicted increased activation of key components of the dorsal attention network (DAN); and age predicted extent of simultaneous deactivation in key components of the default mode network (DMN) during problem-solving. However, there was no significant difference in mean levels of whole brain activation even when cognitively taxed. This suggests that the brain may dynamically switch resource consumption between these anti-correlated DAN and DMN networks, concentrating processing power in regions critical to enhanced cognitive performance. We term this mechanism of activation increase and decrease of these anti-correlated DAN/DMN systems, modulated by "Gf" and age, as "distributed neural efficiency". This may achieve local cost-efficiency trade-offs, while maintaining global energy homeostasis., (Copyright © 2019 Elsevier GmbH. All rights reserved.)

Schizophrenia involves abnormalities in the medial frontal cortex that lead to cognitive deficits. Here we investigate a novel strategy to normalize medial frontal brain activity by stimulating cerebellar projections. We used an interval timing task to study elementary cognitive processing that requires both frontal and cerebellar networks that are disrupted in patients with schizophrenia. We report three novel findings. First, patients with schizophrenia had dysfunctional delta rhythms between 1-4 Hz in the medial frontal cortex. We explored cerebellar-frontal interactions in animal models and found that both frontal and cerebellar neurons were modulated during interval timing and had delta-frequency interactions. Finally, delta-frequency optogenetic stimulation of thalamic synaptic terminals of lateral cerebellar projection neurons rescued timing performance as well as medial frontal activity in a rodent model of schizophrenia-related frontal dysfunction. These data provide insight into how the cerebellum influences medial frontal networks and the role of the cerebellum in cognitive processing.

The current study examined the relationship between white matter integrity as indexed by diffusion tensor imaging and negative symptom severity in schizophrenia. The current study included statistical controls for age effects on the relationship of interest, a major weakness of the existing literature on the subject. Participants included 59 chronic schizophrenia patients, and 31 first-episode schizophrenia patients. Diffusion-weighted neuroimaging was used to calculate fractional anisotropy (FA) in each major brain region (frontal, temporal, parietal, and occipital lobes). Negative symptoms were measured using the Scale for the Assessment of Negative Symptoms (SANS) in all schizophrenia patients. Significant bivariate correlations were observed between global SANS scores and global FA, as well as in most brain regions. These relationships appeared to be driven by SANS items measuring facial expressiveness, poor eye contact, affective flattening, inappropriate affect, poverty of speech, poverty of speech content, alogia, and avolition. However, upon addition of age as a covariate, the observed relationships became non-significant. Further analysis revealed very strong age effects on both FA and SANS scores in the current sample. The findings of this study refute previous reports of significant relationships between DTI variables and negative symptoms in schizophrenia, and they suggest an important confounding variable to be considered in future studies in this population., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Schizophrenia is a chronic and severe psychiatric disorder that is highly heritable. While both common and rare genetic variants contribute to disease risk, many questions still remain about disease etiology. We performed a genome-wide analysis of copy number variants (CNVs) in 166 schizophrenia subjects and 52 psychiatrically healthy controls. First, overall CNV characteristics were compared between cases and controls. The only statistically significant finding was that deletions comprised a greater proportion of CNVs in cases. High interest CNVs were then identified as conservative using the following filtering criteria: (i) known deleterious CNVs; (ii) CNVs > 1 Mb that were novel (not found in a database of control individuals); and (iii) CNVs < 1 Mb that were novel and that overlapped the coding region of a gene of interest. Cases did not harbor a higher proportion of conservative CNVs in comparison to controls. However, similar to previous reports, cases had a slightly higher proportion of individuals with clinically significant CNVs (known deleterious or conservative CNVs > 1 Mb) or with multiple conservative CNVs. Two case individuals with the highest burden of conservative CNVs also share a recurrent 15q11.2 BP1-2 deletion, indicating a role for a potential multiple-hit CNV model for schizophrenia. In total, we report three 15q11.2 BP1-2 deletion individuals with schizophrenia, adding to a growing body of evidence that this CNV is involved in disease etiology., (© 2014 Wiley Periodicals, Inc.)

The cognitive role of the cerebellum is critically tied to its distributed connections throughout the brain. Accumulating evidence from anatomical, structural and functional imaging, and lesion studies advocate a cognitive network involving indirect connections between the cerebellum and non-motor areas in the prefrontal cortex. Cerebellar stimulation dynamically influences activity in several regions of the frontal cortex and effectively improves cognition in schizophrenia. In this manuscript, we summarize current literature on the cingulocerebellar circuit and we introduce a method to interrogate this circuit combining opotogenetics, neuropharmacology, and electrophysiology in awake-behaving animals while minimizing incidental stimulation of neighboring cerebellar nuclei. We propose the novel hypothesis that optogenetic cerebellar stimulation can restore aberrant frontal activity and rescue impaired cognition in schizophrenia. We focus on how a known cognitive region in the frontal cortex, the anterior cingulate, is influenced by the cerebellum. This circuit is of particular interest because it has been confirmed using tracing studies, neuroimaging reveals its role in cognitive tasks, it is conserved from rodents to humans, and diseases such as schizophrenia and autism appear in its aberrancy. Novel tract tracing results presented here provide support for how these two areas communicate. The primary pathway involves a disynaptic connection between the cerebellar dentate nuclei (DN) and the anterior cingulate cortex. Secondarily, the pathway from cerebellar fastigial nuclei (FN) to the ventral tegmental area, which supplies dopamine to the prefrontal cortex, may play a role as schizophrenia characteristically involves dopamine deficiencies. We hope that the hypothesis described here will inspire new therapeutic strategies targeting currently untreatable cognitive impairments in schizophrenia.

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Previous studies suggest that patients with schizophrenia exhibit dysfunctions in a widely distributed circuit-the cortico-cerebellar-thalamic-cortical circuit, or CCTCC-and that this may explain the multiple cognitive deficits observed in the disorder. This study uses positron emission tomography (PET) with O(15) H₂O to measure regional cerebral blood flow (rCBF) in response to a classic test of cerebellar function, the associative learning that occurs during eyeblink conditioning, in a sample of 20 unmedicated schizophrenia patients and 20 closely matched healthy controls. The PET paradigm examined three phases of acquisition and extinction (early, middle and late). The patients displayed impaired behavioral performance during both acquisition and extinction. The imaging data indicate that, compared to the control subjects, the patients displayed decreases in rCBF in all three components of the CCTCC during both acquisition and extinction. Specifically, patients had less rCBF in the middle and medial frontal lobes, anterior cerebellar lobules I/V and VI, as well as the thalamus during acquisition and although similar areas were found in the frontal lobe, ipsilateral cerebellar lobule IX showed consistently less activity in patients during extinction. Thus this study provides additional support for the hypothesis that patients with schizophrenia have a cognitive dysmetria--an inability to smoothly coordinate many different types of mental activity--that affects even a very basic cognitive task that taps into associative learning., (© 2013 Elsevier Ireland Ltd. All rights reserved.)

We have developed a fast and reliable pipeline to automatically parcellate the cortical surface into sub-regions. The pipeline can be used to study brain changes associated with psychiatric and neurological disorders. First, a genus zero cortical surface for one hemisphere is generated from the magnetic resonance images at the parametric boundary of the white matter and the gray matter. Second, a hemisphere-specific surface atlas is registered to the cortical surface using geometry features mapped in the spherical domain. The deformation field is used to warp statistic labels from the atlas to the subject surface. The Dice index of the labeled surface area is used to evaluate the similarity between the automated labels with the manual labels on the subject. The average Dice across 24 regions on 14 testing subjects is 0.86. Alternative evaluations have also chosen to show the accuracy and flexibility of the present method. The point-wise accuracy of 14 testing subjects is above 86% in average. The experiment shows that the present method is highly consistent with FreeSurfer (>99% of the surface area), using the same set of labels.

Context: Antipsychotic treatment is the first-line treatment option for schizophrenia. Individual studies suggested they can significantly affect brain structure and account for progressive brain changes observed during the illness., Objectives: To quantitatively examine the effect of antipsychotics as compared to illness related factors on progressive brain changes in schizophrenia., Data Sources: Electronic databases were searched until April 2012. All magnetic resonance imaging studies reporting progressive brain changes in schizophrenia subjects and antipsychotic exposure were retrieved., Study Selection: 30 longitudinal MRI studies with antipsychotic administration in schizophrenia patients met the inclusion criteria., Data Extraction: Brain volumes before and after antipsychotic exposure, duration of illness, severity of psychotic symptoms as well as demographic, clinical, and methodological variables were extracted from each publication, or obtained directly from its authors., Data Synthesis: The overall sample was of 1046 schizophrenia patients and 780 controls for a median duration of follow-up of 72.4 weeks. At baseline, patients showed significant whole brain volume reductions and enlarged lateral ventricle (LV) volumes compared to controls. No baseline volumetric abnormalities were detected in the gray matter volumes (GMV), white matter volumes, cerebrospinal fluid and caudate nucleus. Longitudinally, there were progressive GMV decreases and LV enlargements in patients but not in controls. The GMV decreases were inversely correlated with cumulative exposure to antipsychotic treatments, while no effects were observed for duration of illness or illness severity., Conclusions: Schizophrenia is characterized by progressive gray matter volume decreases and lateral ventricular volume increases. Some of these neuroanatomical alterations may be associated with antipsychotic treatment., (Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.)

There is considerable evidence implicating brain white matter (WM) abnormalities in the pathophysiology of schizophrenia; however, the spatial localization of WM abnormalities reported in the existing studies is heterogeneous. Thus, the goal of this study was to quantify the spatial characteristics of WM abnormalities in schizophrenia. One hundred and fourteen patients with schizophrenia and 138 matched controls participated in this multisite study involving the Universities of Iowa, Minnesota, and New Mexico, and the Massachusetts General Hospital. We measured fractional anisotropy (FA) in brain WM regions extracted using 3 different image-processing algorithms: regions of interest, tract-based spatial statistics, and the pothole approach. We found that FA was significantly lower in patients using each of the 3 image-processing algorithms. The region-of-interest approach showed multiple regions with lower FA in patients with schizophrenia, with overlap at all 4 sites in the corpus callosum and posterior thalamic radiation. The tract-based spatial statistic approach showed (1) global differences in 3 of the 4 cohorts and (2) lower frontal FA at the Iowa site. Finally, the pothole approach showed a significantly greater number of WM potholes in patients compared to controls at each of the 4 sites. In conclusion, the spatial characteristics of WM abnormalities in schizophrenia reflect a combination of a global low-level decrease in FA, suggesting a diffuse process, coupled with widely dispersed focal reductions in FA that vary spatially among individuals (ie, potholes).

Expertly collected, well-curated data sets consisting of comprehensive clinical characterization and raw structural, functional and diffusion-weighted DICOM images in schizophrenia patients and sex and age-matched controls are now accessible to the scientific community through an on-line data repository (coins.mrn.org). The Mental Illness and Neuroscience Discovery Institute, now the Mind Research Network (MRN, http://www.mrn.org/ ), comprised of investigators at the University of New Mexico, the University of Minnesota, Massachusetts General Hospital, and the University of Iowa, conducted a cross-sectional study to identify quantitative neuroimaging biomarkers of schizophrenia. Data acquisition across multiple sites permitted the integration and cross-validation of clinical, cognitive, morphometric, and functional neuroimaging results gathered from unique samples of schizophrenia patients and controls using a common protocol across sites. Particular effort was made to recruit patients early in the course of their illness, at the onset of their symptoms. There is a relatively even sampling of illness duration in chronic patients. This data repository will be useful to 1) scientists who can study schizophrenia by further analysis of this cohort and/or by pooling with other data; 2) computer scientists and software algorithm developers for testing and validating novel registration, segmentation, and other analysis software; and 3) educators in the fields of neuroimaging, medical image analysis and medical imaging informatics who need exemplar data sets for courses and workshops. Sharing provides the opportunity for independent replication of already published results from this data set and novel exploration. This manuscript describes the inclusion/exclusion criteria, imaging parameters and other information that will assist those wishing to use this data repository.

Objective: Longitudinal structural MRI studies have shown that patients with schizophrenia have progressive brain tissue loss after onset. Recurrent relapses are believed to play a role in this loss, but the relationship between relapse and structural MRI measures has not been rigorously assessed. The authors analyzed longitudinal data to examine this question., Methods: The authors studied data from 202 patients drawn from the Iowa Longitudinal Study of first-episode schizophrenia for whom adequate structural MRI data were available (N=659 scans) from scans obtained at regular intervals over an average of 7 years. Because clinical follow-up data were obtained at 6-month intervals, the authors were able to compute measures of relapse number and duration and relate them to structural MRI measures. Because higher treatment intensity has been associated with smaller brain tissue volumes, the authors also examined this countereffect in terms of dose-years., Results: Relapse duration was related to significant decreases in both general (e.g., total cerebral volume) and regional (e.g., frontal) brain measures. Number of relapses was unrelated to brain measures. Significant effects were also observed for treatment intensity., Conclusions: Extended periods of relapse may have a negative effect on brain integrity in schizophrenia, suggesting the importance of implementing proactive measures that may prevent relapse and improve treatment adherence. By examining the relative balance of effects, that is, relapse duration versus antipsychotic treatment intensity, this study sheds light on a troublesome dilemma that clinicians face. Relapse prevention is important, but it should be sustained using the lowest possible medication dosages that will control symptoms.

Background: Adolescent marijuana use is associated with increased risk for schizophrenia. We previously reported that marijuana misuse in conjunction with specific cannabinoid receptor 1 (CNR1) genetic variants (rs12720071-G-allele carriers) contributed to white-matter (WM) brain volume deficits in schizophrenia patients. In this study, we assessed the influence of another cannabinoid-related gene, mitogen-activated protein kinase 14 (MAPK14), and potential MAPK14-CNR1 gene-gene interactions in conferring brain volume abnormalities among schizophrenia patients with marijuana abuse/dependence. MAPK14 encodes a member of the MAPK family involved in diverse cellular processes, including CNR1-induced apoptosis., Method: We genotyped 235 schizophrenia patients on nine MAPK14 tag single nucleotide polymorphisms (tSNPs). Approximately one quarter of the sample had marijuana abuse or dependence. Differential effects of MAPK14 tSNPs on brain volumes across patients with versus without marijuana abuse/dependence were examined using ANCOVA., Results: Of the MAPK14 tSNPs, only rs12199654 had significant genotype effects and genotype × marijuana misuse interaction effects on WM volumes. rs12199654-A homozygotes with marijuana abuse/dependence had significantly smaller total cerebral and lobar WM volumes. The effects of MAPK14 rs12199654 on WM volume deficits remained significant even after controlling for the CNR1 rs12720071 genotype. There were significant main effects of the MAPK14 CNR1 diplotype and diplotype × marijuana interaction on WM brain volumes, with both genetic variants having additive contributions to WM volume deficits only in patients with marijuana misuse., Conclusions: Given that CNR1-induced apoptosis is preceded by increased MAPK phosphorylation, our study suggests that potential MAPK14-CNR1 gene-gene interactions may mediate brain morphometric features in schizophrenia patients with heavy marijuana use.

Multimodal fusion is an effective approach to better understand brain diseases. However, most such instances have been limited to pair-wise fusion; because there are often more than two imaging modalities available per subject, there is a need for approaches that can combine multiple datasets optimally. In this paper, we extended our previous two-way fusion model called "multimodal CCA+joint ICA", to three or N-way fusion, that enables robust identification of correspondence among N data types and allows one to investigate the important question of whether certain disease risk factors are shared or distinct across multiple modalities. We compared "mCCA+jICA" with its alternatives in a 3-way fusion simulation and verified its advantages in both decomposition accuracy and modal linkage detection. We also applied it to real functional Magnetic Resonance Imaging (fMRI)-Diffusion Tensor Imaging (DTI) and structural MRI fusion to elucidate the abnormal architecture underlying schizophrenia (n=97) relative to healthy controls (n=116). Both modality-common and modality-unique abnormal regions were identified in schizophrenia. Specifically, the visual cortex in fMRI, the anterior thalamic radiation (ATR) and forceps minor in DTI, and the parietal lobule, cuneus and thalamus in sMRI were linked and discriminated between patients and controls. One fMRI component with regions of activity in motor cortex and superior temporal gyrus individually discriminated schizophrenia from controls. Finally, three components showed significant correlation with duration of illness (DOI), suggesting that lower gray matter volumes in parietal, frontal, and temporal lobes and cerebellum are associated with increased DOI, along with white matter disruption in ATR and cortico-spinal tracts. Findings suggest that the identified fractional anisotropy changes may relate to the corresponding functional/structural changes in the brain that are thought to play a role in the clinical expression of schizophrenia. The proposed "mCCA+jICA" method showed promise for elucidating the joint or coupled neuronal abnormalities underlying mental illnesses and improves our understanding of the disease process., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Eyeblink conditioning is a paradigm commonly used to investigate the neural mechanisms underlying motor learning. It involves the paired presentation of a tone-conditioning stimulus which precedes and co-terminates with an airpuff unconditioned stimulus. Following repeated paired presentations a conditioned eyeblink develops which precedes the airpuff. This type of learning has been intensively studied and the cerebellum is known to be essential in both humans and animals. The study presented here was designed to investigate the role of the cerebellum during eyeblink conditioning in humans using positron emission tomography (PET). The sample includes 20 subjects (10 male and 10 female) with an average age of 29.2 years. PET imaging was used to measure regional cerebral blood flow (rCBF) changes occurring during the first, second, and third blocks of conditioning. In addition, stimuli-specific rCBF to unpaired tones and airpuffs ("pseudoconditioning") was used as a baseline level that was subtracted from each block. Conditioning was performed using three, 15-trial blocks of classical eyeblink conditioning with the last five trials in each block imaged. As expected, subjects quickly acquired conditioned responses. A comparison between the conditioning tasks and the baseline task revealed that during learning there was activation of the cerebellum and recruitment of several higher cortical regions. Specifically, large peaks were noted in cerebellar lobules IV/V, the frontal lobes, and cingulate gyri.

Although schizophrenia is generally considered to occur as a consequence of multiple genes that interact with one another, very few methods have been developed to model epistasis. Phenotype definition has also been a major challenge for research on the genetics of schizophrenia. In this report, we use novel statistical techniques to address the high dimensionality of genomic data, and we apply a refinement in phenotype definition by basing it on the occurrence of brain changes during the early course of the illness, as measured by repeated magnetic resonance scans (i.e., an 'intermediate phenotype.') The method combines a machine-learning algorithm, the ensemble method using stochastic gradient boosting, with traditional general linear model statistics. We began with 14 genes that are relevant to schizophrenia, based on association studies or their role in neurodevelopment, and then used statistical techniques to reduce them to five genes and 17 single nucleotide polymorphisms (SNPs) that had a significant statistical interaction: five for PDE4B, four for RELN, four for ERBB4, three for DISC1 and one for NRG1. Five of the SNPs involved in these interactions replicate previous research in that, these five SNPs have previously been identified as schizophrenia vulnerability markers or implicate cognitive processes relevant to schizophrenia. This ability to replicate previous work suggests that our method has potential for detecting a meaningful epistatic relationship among the genes that influence brain abnormalities in schizophrenia.

CONTEXT The single-nucleotide polymorphism rs1344706 in the gene ZNF804a has been associated with schizophrenia and with quantitative phenotypic features, including brain structure volume and the core symptoms of schizophrenia. OBJECTIVE To evaluate associations of rs1344706 with brain structure and the core symptoms of schizophrenia. DESIGN Case-control analysis of covariance. SETTING University-based research hospital. PARTICIPANTS Volunteer sample of 335 individuals with schizophrenia spectrum disorders (306 with core schizophrenia) and 198 healthy volunteers. MAIN OUTCOME MEASURES Cerebral cortical gray matter and white matter (WM) volumes (total and frontal, parietal, temporal, and occipital lobes), lateral ventricular cerebrospinal fluid volume, and symptom severity from the Scale for the Assessment of Negative Symptoms and the Scale for the Assessment of Positive Symptoms divided into 3 domains: psychotic, negative, and disorganized. RESULTS The rs1344706 genotype produced significant main effects on total, frontal, and parietal lobe WM volumes (F = 3.98, P = .02; F = 4.95, P = .007; and F = 3.08, P = .05, respectively). In the schizophrenia group, rs1344706 produced significant simple effects on total (F = 3.93, P = .02) and frontal WM volumes (F = 7.16, P < .001) and on psychotic symptom severity (F = 6.07, P = .003); the pattern of effects was concordant with risk allele carriers having larger volumes and more severe symptoms of disease than nonrisk homozygotes. In the healthy volunteer group, risk allele homozygotes had increased total WM volume compared with nonrisk allele carriers (F = 4.61, P = .03), replicating a previously reported association. CONCLUSIONS A growing body of evidence suggests that the risk allele of rs1347706 is associated with a distinctive set of phenotypic features in healthy volunteers and individuals with schizophrenia. Our study supports this assertion by finding that specific genotypes of the polymorphism are associated with brain structure volumes in individuals with schizophrenia and healthy volunteers and with symptom severity in schizophrenia.

The study of creativity is characterized by a variety of key questions, such as the nature of the creative process, whether there are multiple types of creativity, the relationship between high levels of creativity ("Big C") and everyday creativity ("little c"), and the neural basis of creativity. Herein we examine the question of the relationship between creativity in the arts and the sciences, and use functional magnetic resonance imaging to explore the neural basis of creativity in a group of "Big C" individuals from both domains using a word association protocol. The findings give no support for the notion that the artists and scientists represent "two cultures. " Rather, they suggest that very gifted artists and scientists have association cortices that respond in similar ways. Both groups display a preponderance of activation in brain circuits involved in higher-order socioaffective processing and Random Episodic Silent Thought /the default mode.

The majority of patients with schizophrenia smoke cigarettes. Both nicotine use and schizophrenia have been associated with alterations in brain white matter microstructure as measured by diffusion tensor imaging (DTI). The purpose of this study was to examine fractional anisotropy (FA) in smoking and non-smoking patients with schizophrenia and in healthy volunteers. A total of 43 patients (28 smoking and 15 non-smoking) with schizophrenia and 40 healthy, non-smoking participants underwent DTI. Mean FA was calculated in four global regions of interest (ROIs) (whole brain, cerebellum, brainstem, and total cortical) as well as in four regional ROIs (frontal, temporal, parietal and occipital lobes). The non-smoking patient group had a significantly higher intellectual quotient (IQ) compared with the patients who smoked, and our results varied according to whether IQ was included as a covariate. Without IQ correction, significant between-group effects for FA were found in four ROIs: total brain, total cortical, frontal lobe and the occipital lobe. In all cases the FA was lower among the smoking patient group, and highest in the control group. Smoking patients differed significantly from non-smoking patients in the frontal lobe ROI. However, these differences were no longer significant after IQ correction. FA differences between non-smoking patients and controls were not significant. Among smoking and non-smoking patients with schizophrenia but not healthy controls, FA was correlated with IQ. In conclusion, group effects of smoking on FA in schizophrenia might be mediated by IQ. Further, low FA in specific brain areas may be a neural marker for complex pathophysiology and risk for diverse problems such as schizophrenia, low IQ, and nicotine addiction., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

Structural magnetic resonance imaging studies provide evidence for sex differences in the human brain. Differences in surface area and the proportion of gray to white matter volume are observed, in particular in the parietal lobe. To our knowledge, no studies have examined sex differences in parietal lobe structure in younger populations or in the context of development. The present study evaluated sex differences in the structure of the parietal lobe in children aged 7 to 17 years. In addition, by adding a cohort of previously studied adults aged 18 to 50 years, sex differences in parietal lobe structure were examined across the age span of 7 to 50 years. Compared with the adult sample, the younger sample showed that the ratio of parietal lobe cortex to white matter was greater in female brains, but no sex differences in surface area. When examining the effects of age, surface area exhibited a significant sex-age interaction. In male brains, there was essentially no decrease in surfaces area over time, whereas in female brains, there was a significant decrease in surface area over time. These findings support the notion of structural sex differences in the parietal lobe, not only in the context of cross-sectional assessment but also in terms of differences in developmental trajectories., (Copyright © 2012 Elsevier HS Journals, Inc. All rights reserved.)

Making an accurate diagnosis of schizophrenia and related psychoses early in the course of the disease is important for initiating treatment and counseling patients and families. In this study, we developed classification models for early disease diagnosis using structural MRI (sMRI) and neuropsychological (NP) testing. We used sMRI measurements and NP test results from 28 patients with recent-onset schizophrenia and 47 healthy subjects, drawn from the larger sample of the Mind Clinical Imaging Consortium. We developed diagnostic models based on Linear Discriminant Analysis (LDA) following two approaches; namely, (a) stepwise (STP) LDA on the original measurements, and (b) LDA on variables created through Principal Component Analysis (PCA) and selected using the Humphrey-Ilgen parallel analysis. Error estimation of the modeling algorithms was evaluated by leave-one-out external cross-validation. These analyses were performed on sMRI and NP variables separately and in combination. The following classification accuracy was obtained for different variables and modeling algorithms. sMRI only: (a) STP-LDA: 64.3% sensitivity and 76.6% specificity, (b) PCA-LDA: 67.9% sensitivity and 72.3% specificity. NP only: (a) STP-LDA: 71.4% sensitivity and 80.9% specificity, (b) PCA-LDA: 78.5% sensitivity and 91.5% specificity. Combined sMRI-NP: (a) STP-LDA: 64.3% sensitivity and 83.0% specificity, (b) PCA-LDA: 89.3% sensitivity and 93.6% specificity. (i) Maximal diagnostic accuracy was achieved by combining sMRI and NP variables. (ii) NP variables were more informative than sMRI, indicating that cognitive deficits can be detected earlier than volumetric structural abnormalities. (iii) PCA-LDA yielded more accurate classification than STP-LDA. As these sMRI and NP tests are widely available, they can increase accuracy of early intervention strategies and possibly be used in evaluating treatment response.