Publications by authors named "Nancy C Andreasen"

118 Publications

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years.

Hum Brain Mapp 2021 Feb 17. Epub 2021 Feb 17.

Laboratory of Psychiatric Neuroimaging, Departamento e Instituto de Psiquiatria, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo, São Paulo, Brazil.

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.
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http://dx.doi.org/10.1002/hbm.25364DOI Listing
February 2021

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Hum Brain Mapp 2021 Feb 11. Epub 2021 Feb 11.

Department of Psychology, Center for Brain Science, Harvard University, Cambridge, Massachusetts, USA.

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.
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http://dx.doi.org/10.1002/hbm.25320DOI Listing
February 2021

Patients on the psychosis spectrum employ an alternate brain network to engage in complex decision-making.

PLoS One 2020 11;15(9):e0238774. Epub 2020 Sep 11.

University of Iowa, Iowa City, Iowa, United States of America.

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.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0238774PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485831PMC
November 2020

Distributed neural efficiency: Intelligence and age modulate adaptive allocation of resources in the brain.

Trends Neurosci Educ 2019 06 19;15:48-61. Epub 2019 Mar 19.

University of Iowa, Department of Psychiatry, Carver College of Medicine, 200 Hawkins Drive, Iowa City, IA 52242, United States.

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.
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http://dx.doi.org/10.1016/j.tine.2019.02.006DOI Listing
June 2019

John and Alicia Nash: A Beautiful Love Story.

Am J Psychiatry 2015 Aug;172(8):710-3

Dr. Andreasen is a Professor and Andrew H. Woods Chair of Psychiatry, and Director, Iowa Neuroimaging Consortium, Carver College of Medicine, University of Iowa, Iowa City, Iowa. Dr. Andreasen also is Editor-in-Chief Emerita, The American Journal of Psychiatry.

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http://dx.doi.org/10.1176/appi.ajp.2015.15060709DOI Listing
August 2015

The therapeutic potential of the cerebellum in schizophrenia.

Front Syst Neurosci 2014 15;8:163. Epub 2014 Sep 15.

Department of Psychiatry, University of Iowa Iowa City, IA, USA.

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.
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http://dx.doi.org/10.3389/fnsys.2014.00163DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4163988PMC
October 2014

A genome-wide CNV analysis of schizophrenia reveals a potential role for a multiple-hit model.

Am J Med Genet B Neuropsychiatr Genet 2014 Dec 16;165B(8):619-26. Epub 2014 Sep 16.

Interdisciplinary Graduate Program in Genetics, University of Iowa, Iowa City, Iowa; Department of Psychiatry, University of Iowa, Iowa City, Iowa.

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.
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http://dx.doi.org/10.1002/ajmg.b.32266DOI Listing
December 2014

Effects of age on white matter integrity and negative symptoms in schizophrenia.

Schizophr Res 2015 Jan 20;161(1):29-35. Epub 2014 Jun 20.

Department of Psychiatry, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, United States. Electronic address:

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.
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http://dx.doi.org/10.1016/j.schres.2014.05.031DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4272674PMC
January 2015

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data.

Brain Imaging Behav 2014 Jun;8(2):153-82

Imaging Genetics Center, Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, 2001 N. Soto Street, Los Angeles, CA, 90033, USA,

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.
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http://dx.doi.org/10.1007/s11682-013-9269-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4008818PMC
June 2014

Automated parcellation of the brain surface generated from magnetic resonance images.

Front Neuroinform 2013 22;7:23. Epub 2013 Oct 22.

Department of Biomedical Engineering, The University of Iowa Iowa City, IA, USA ; Department of Radiology, The University of Iowa Iowa City, IA, USA.

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.
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http://dx.doi.org/10.3389/fninf.2013.00023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3804771PMC
October 2013

Eyeblink conditioning in unmedicated schizophrenia patients: a positron emission tomography study.

Psychiatry Res 2013 Dec 1;214(3):402-9. Epub 2013 Oct 1.

Department of Psychiatry, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City IA 52242, USA. Electronic address:

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.
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http://dx.doi.org/10.1016/j.pscychresns.2013.07.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3980571PMC
December 2013

The MCIC collection: a shared repository of multi-modal, multi-site brain image data from a clinical investigation of schizophrenia.

Neuroinformatics 2013 Jul;11(3):367-88

Department of Psychiatry, Massachusetts General Hospital, Building 120, Suite 101D, Charlestown, MA 02129-2000, USA.

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.
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http://dx.doi.org/10.1007/s12021-013-9184-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3727653PMC
July 2013

Relapse duration, treatment intensity, and brain tissue loss in schizophrenia: a prospective longitudinal MRI study.

Am J Psychiatry 2013 Jun;170(6):609-15

Psychiatric Iowa Neuroimaging Consortium, University ofIowa Carver College of Medicine, Iowa City, USA.

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.
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http://dx.doi.org/10.1176/appi.ajp.2013.12050674DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3835590PMC
June 2013

Three-way (N-way) fusion of brain imaging data based on mCCA+jICA and its application to discriminating schizophrenia.

Neuroimage 2013 Feb 26;66:119-32. Epub 2012 Oct 26.

The Mind Research Network and Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM 87106, USA; Dept. of ECE, University of New Mexico, Albuquerque, NM 87131, USA; Dept. of CSEE, University of Maryland, Baltimore County, Baltimore, MD, 21250 USA.

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.
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http://dx.doi.org/10.1016/j.neuroimage.2012.10.051DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3897558PMC
February 2013

Spatial characteristics of white matter abnormalities in schizophrenia.

Schizophr Bull 2013 Sep 16;39(5):1077-86. Epub 2012 Sep 16.

Department of Child and Adolescent Psychiatry, Erasmus Medical Centre, Rotterdam, the Netherlands.

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).
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http://dx.doi.org/10.1093/schbul/sbs106DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3756779PMC
September 2013

Influence of ZNF804a on brain structure volumes and symptom severity in individuals with schizophrenia.

Arch Gen Psychiatry 2012 Sep;69(9):885-92

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA.

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.
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http://dx.doi.org/10.1001/archgenpsychiatry.2011.2116DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852666PMC
September 2012

Creativity in art and science: are there two cultures?

Dialogues Clin Neurosci 2012 Mar;14(1):49-54

Psychiatric Iowa Neuroimaging Consortium; University of Iowa Carver College of Medicine; Iowa City, Iowa, USA.

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.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3341649PMC
March 2012

Eyeblink conditioning in healthy adults: a positron emission tomography study.

Cerebellum 2012 Dec;11(4):946-56

Department of Psychiatry, Roy J. and Lucille A. Carver College of Medicine, University of Iowa, Iowa City, IA, 52242, USA.

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.
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http://dx.doi.org/10.1007/s12311-012-0377-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3835594PMC
December 2012

Cigarette smoking and white matter microstructure in schizophrenia.

Psychiatry Res 2012 Feb 3;201(2):152-8. Epub 2012 Mar 3.

Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, USA.

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.
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http://dx.doi.org/10.1016/j.pscychresns.2011.08.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3319200PMC
February 2012

Sex differences in parietal lobe structure and development.

Gend Med 2012 Feb;9(1):44-55

University of Iowa Doris Duke Clinical Research Fellowship Program, Iowa City, Iowa 52242, USA.

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.
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http://dx.doi.org/10.1016/j.genm.2012.01.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3326392PMC
February 2012

What is post-traumatic stress disorder?

Dialogues Clin Neurosci 2011 ;13(3):240-3

Although post-traumatic stress disorder (PTSD) and traumatic brain injury (TBI) are categorized as separate and discrete disorders, the boundary between them is sometimes indistinct. Their separation is based on the assumption that PTSD results primarily from psychological stress, while TBI is the consequence of an identifiable injury to the brain. This distinction is based on an antiquated polarity between mind and brain, and the separation of the two disorders often becomes arbitrary in day-to-day psychiatric practice and research.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3182007PMC
November 2011

A Data-Driven Investigation of Gray Matter-Function Correlations in Schizophrenia during a Working Memory Task.

Front Hum Neurosci 2011 5;5:71. Epub 2011 Aug 5.

The Mind Research Network Albuquerque, NM, USA.

The brain is a vastly interconnected organ and methods are needed to investigate its long range structure(S)-function(F) associations to better understand disorders such as schizophrenia that are hypothesized to be due to distributed disconnected brain regions. In previous work we introduced a methodology to reduce the whole brain S-F correlations to a histogram and here we reduce the correlations to brain clusters. The application of our approach to sMRI [gray matter (GM) concentration maps] and functional magnetic resonance imaging data (general linear model activation maps during Encode and Probe epochs of a working memory task) from patients with schizophrenia (SZ, n = 100) and healthy controls (HC, n = 100) presented the following results. In HC the whole brain correlation histograms for GM-Encode and GM-Probe overlap for Low and Medium loads and at High the histograms separate, but in SZ the histograms do not overlap for any of the load levels and Medium load shows the maximum difference. We computed GM-F differential correlation clusters using activation for Probe Medium, and they included regions in the left and right superior temporal gyri, anterior cingulate, cuneus, middle temporal gyrus, and the cerebellum. Inter-cluster GM-Probe correlations for Medium load were positive in HC but negative in SZ. Within group inter-cluster GM-Encode and GM-Probe correlation comparisons show no differences in HC but in SZ differences are evident in the same clusters where HC vs. SZ differences occurred for Probe Medium, indicating that the S-F integrity during Probe is aberrant in SZ. Through a data-driven whole brain analysis approach we find novel brain clusters and show how the S-F differential correlation changes during Probe and Encode at three memory load levels. Structural and functional anomalies have been extensively reported in schizophrenia and here we provide evidences to suggest that evaluating S-F associations can provide important additional information.
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http://dx.doi.org/10.3389/fnhum.2011.00071DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3153862PMC
November 2011

Progressive brain change in schizophrenia: a prospective longitudinal study of first-episode schizophrenia.

Biol Psychiatry 2011 Oct 23;70(7):672-9. Epub 2011 Jul 23.

Psychiatric Iowa Neuroimaging Consortium, The University of Iowa Carver College of Medicine, Iowa City, Iowa 52242, USA.

Background: Schizophrenia has a characteristic onset during adolescence or young adulthood but also tends to persist throughout life. Structural magnetic resonance studies indicate that brain abnormalities are present at onset, but longitudinal studies to assess neuroprogression have been limited by small samples and short or infrequent follow-up intervals.

Methods: The Iowa Longitudinal Study is a prospective study of 542 first-episode patients who have been followed up to 18 years. In this report, we focus on those patients (n = 202) and control subjects (n = 125) for whom we have adequate structural magnetic resonance data (n = 952 scans) to provide a relatively definitive determination of whether progressive brain change occurs over a time interval of up to 15 years after intake.

Results: A repeated-measures analysis showed significant age-by-group interaction main effects that represent a significant decrease in multiple gray matter regions (total cerebral, frontal, thalamus), multiple white matter regions (total cerebral, frontal, temporal, parietal), and a corresponding increase in cerebrospinal fluid (lateral ventricles and frontal, temporal, and parietal sulci). These changes were most severe during the early years after onset. They occur at severe levels only in a subset of patients. They are correlated with cognitive impairment but only weakly with other clinical measures.

Conclusions: Progressive brain change occurs in schizophrenia, affects both gray matter and white matter, is most severe during the early stages of the illness, and occurs only in a subset of patients. Measuring severity of progressive brain change offers a promising new avenue for phenotype definition in genetic studies of schizophrenia.
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http://dx.doi.org/10.1016/j.biopsych.2011.05.017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3496792PMC
October 2011

A journey into chaos: creativity and the unconscious.

Mens Sana Monogr 2011 Jan;9(1):42-53

Andrew H. Woods Chair of Psychiatry, W278GH, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA.

The capacity to be creative, to produce new concepts, ideas, inventions, objects or art, is perhaps the most important attribute of the human brain. We know very little, however, about the nature of creativity or its neural basis. Some important questions include how should we define creativity? How is it related (or unrelated) to high intelligence? What psychological processes or environmental circumstance cause creative insights to occur? How is it related to conscious and unconscious processes? What is happening at the neural level during moments of creativity? How is it related to health or illness, and especially mental illness? This paper will review introspective accounts from highly creative individuals. These accounts suggest that unconscious processes play an important role in achieving creative insights. Neuroimaging studies of the brain during "REST" (random episodic silent thought, also referred to as the default state) suggest that the association cortices are the primary areas that are active during this state and that the brain is spontaneously reorganising and acting as a self-organising system. Neuroimaging studies also suggest that highly creative individuals have more intense activity in association cortices when performing tasks that challenge them to "make associations." Studies of creative individuals also indicate that they have a higher rate of mental illness than a noncreative comparison group, as well as a higher rate of both creativity and mental illness in their first-degree relatives. This raises interesting questions about the relationship between the nature of the unconscious, the unconscious and the predisposition to both creativity and mental illness.
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http://dx.doi.org/10.4103/0973-1229.77424DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3115302PMC
January 2011

Cannabinoid receptor 1 gene polymorphisms and marijuana misuse interactions on white matter and cognitive deficits in schizophrenia.

Schizophr Res 2011 May 21;128(1-3):66-75. Epub 2011 Mar 21.

Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA 5224, USA.

Marijuana exposure during the critical period of adolescent brain maturation may disrupt neuro-modulatory influences of endocannabinoids and increase schizophrenia susceptibility. Cannabinoid receptor 1 (CB1/CNR1) is the principal brain receptor mediating marijuana effects. No study to-date has systematically investigated the impact of CNR1 on quantitative phenotypic features in schizophrenia and inter-relationships with marijuana misuse. We genotyped 235 schizophrenia patients using 12 tag single nucleotide polymorphisms (tSNPs) that account for most of CB1 coding region genetic variability. Patients underwent a high-resolution anatomic brain magnetic resonance scan and cognitive assessment. Almost a quarter of the sample met DSM marijuana abuse (14%) or dependence (8%) criteria. Effects of CNR1 tSNPs and marijuana abuse/dependence on brain volumes and neurocognition were assessed using ANCOVA, including co-morbid alcohol/non-marijuana illicit drug misuse as covariates. Significant main effects of CNR1 tSNPs (rs7766029, rs12720071, and rs9450898) were found in white matter (WM) volumes. Patients with marijuana abuse/dependence had smaller fronto-temporal WM volumes than patients without heavy marijuana use. More interestingly, there were significant rs12720071 genotype-by-marijuana use interaction effects on WM volumes and neurocognitive impairment; suggestive of gene-environment interactions for conferring phenotypic abnormalities in schizophrenia. In this comprehensive evaluation of genetic variants distributed across the CB1 locus, CNR1 genetic polymorphisms were associated with WM brain volume variation among schizophrenia patients. Our findings suggest that heavy cannabis use in the context of specific CNR1 genotypes may contribute to greater WM volume deficits and cognitive impairment, which could in turn increase schizophrenia risk.
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http://dx.doi.org/10.1016/j.schres.2011.02.021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3085576PMC
May 2011

Long-term antipsychotic treatment and brain volumes: a longitudinal study of first-episode schizophrenia.

Arch Gen Psychiatry 2011 Feb;68(2):128-37

Departments of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA 52242, USA.

Context: Progressive brain volume changes in schizophrenia are thought to be due principally to the disease. However, recent animal studies indicate that antipsychotics, the mainstay of treatment for schizophrenia patients, may also contribute to brain tissue volume decrement. Because antipsychotics are prescribed for long periods for schizophrenia patients and have increasingly widespread use in other psychiatric disorders, it is imperative to determine their long-term effects on the human brain.

Objective: To evaluate relative contributions of 4 potential predictors (illness duration, antipsychotic treatment, illness severity, and substance abuse) of brain volume change.

Design: Predictors of brain volume changes were assessed prospectively based on multiple informants.

Setting: Data from the Iowa Longitudinal Study.

Patients: Two hundred eleven patients with schizophrenia who underwent repeated neuroimaging beginning soon after illness onset, yielding a total of 674 high-resolution magnetic resonance scans. On average, each patient had 3 scans (≥2 and as many as 5) over 7.2 years (up to 14 years).

Main Outcome Measure: Brain volumes.

Results: During longitudinal follow-up, antipsychotic treatment reflected national prescribing practices in 1991 through 2009. Longer follow-up correlated with smaller brain tissue volumes and larger cerebrospinal fluid volumes. Greater intensity of antipsychotic treatment was associated with indicators of generalized and specific brain tissue reduction after controlling for effects of the other 3 predictors. More antipsychotic treatment was associated with smaller gray matter volumes. Progressive decrement in white matter volume was most evident among patients who received more antipsychotic treatment. Illness severity had relatively modest correlations with tissue volume reduction, and alcohol/illicit drug misuse had no significant associations when effects of the other variables were adjusted.

Conclusions: Viewed together with data from animal studies, our study suggests that antipsychotics have a subtle but measurable influence on brain tissue loss over time, suggesting the importance of careful risk-benefit review of dosage and duration of treatment as well as their off-label use.
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http://dx.doi.org/10.1001/archgenpsychiatry.2010.199DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3476840PMC
February 2011

Neuropsychological testing and structural magnetic resonance imaging as diagnostic biomarkers early in the course of schizophrenia and related psychoses.

Neuroinformatics 2011 Dec;9(4):321-33

Brain Sciences Center (11B), Veterans Affairs Medical Center, One Veterans Drive, Minneapolis, MN 55417, USA.

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.
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http://dx.doi.org/10.1007/s12021-010-9094-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116989PMC
December 2011

WITHDRAWN: Erratum to "Does function follow form?: Methods to fuse structural and functional brain images show decreased linkage in schizophrenia" [NeuroImage 49 (2010) 2626-2637].

Neuroimage 2010 Mar 5. Epub 2010 Mar 5.

The Mind Research Network, Albuquerque, NM 87106, USA; Center for Imaging Science, Rochester Institute of Technology, Rochester, NY 14623, USA.

This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.
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http://dx.doi.org/10.1016/j.neuroimage.2010.02.057DOI Listing
March 2010

Posttraumatic stress disorder: a history and a critique.

Ann N Y Acad Sci 2010 Oct;1208:67-71

Psychiatric Iowa Neuroimaging Consortium, Iowa City, Iowa 52242, USA.

Although posttraumatic stress disorder (PTSD) is sometimes considered to be a relatively new diagnosis, as the name first appeared in 1980, the concept of the disorder has a very long history. That history has often been linked to the history of war, but the disorder has also been frequently described in civilian settings involving natural disasters, mass catastrophes, and serious accidental injuries. The diagnosis first appeared in the official nomenclature when Diagnostic and Statistical Manual of Mental Disorders (DSM)-I was published in 1952 under the name gross stress reaction. It was omitted, however, in the next edition in 1968, after a long period of relative peace. When DSM-III was developed in the mid-1980s the recent occurrence of the Vietnam War provoked a more thorough examination of the disorder. PTSD was defined as a stress disorder that is a final common pathway occurring as a consequence of many different types of stressors, including both combat and civilian stress. The definition of PTSD has filled an important niche in clinical psychiatry. Its definition continues to raise important questions about the relationship between a stressor, the individual experiencing it, and the characteristic symptoms.
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http://dx.doi.org/10.1111/j.1749-6632.2010.05699.xDOI Listing
October 2010

The lifetime trajectory of schizophrenia and the concept of neurodevelopment.

Dialogues Clin Neurosci 2010 ;12(3):409-15

Department of Psychiatry, University of Iowa Health Care, Iowa City, USA.

Defining the lifetime trajectory of schizophrenia and the mechanisms that drive it is one of the major challenges of schizophrenia research. Kraepelin assumed that the mechanisms were neurodegenerative ("dementia praecox"), and the early imaging work using computerized tomography seemed to support this model. Prominent ventricular enlargement and increased cerebrospinal fluid on the brain surface suggested that the brain had atrophied. In the 1980s, however, both neuropathological findings and evidence from magnetic resonance imaging (MRI) provided evidence suggesting that neurodevelopmental mechanisms might be a better explanation. This model is supported by both clinical and MRI evidence, particularly the fact that brain abnormalities are already present in first-episode patients. However, longitudinal studies of these patients have found evidence that brain tissue is also lost during the years after onset. The most parsimonious explanation of these findings is that neurodevelopment is a process that is ongoing throughout life, and that schizophrenia occurs as a consequence of aberrations in neurodevelopmental processes that could occur at various stages of life.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3181981PMC
November 2010
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