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MRI schizophrenia

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https://www.readbyqxmd.com/read/28079061/progressive-decline-in-hippocampal-ca1-volume-in-individuals-at-ultra-high-risk-for-psychosis-who-do-not-remit-findings-from-the-longitudinal-youth-at-risk-study
#1
New Fei Ho, Daphne J Holt, Mike Cheung, Juan Eugenio Iglesias, Alex Goh, Mingyuan Wang, Joseph Kw Lim, Joshua de Souza, Joann S Poh, Yuen Mei See, Alison R Adcock, Stephen J Wood, Michael Wl Chee, Jimmy Lee, Juan Zhou
Most individuals identified as ultra high-risk for psychosis (UHR) do not develop frank psychosis. They continue to exhibit subthreshold symptoms, or go on to fully remit. Prior work has shown that the volume of CA1, a subfield of the hippocampus, is selectively reduced in the early stages of schizophrenia. Here, we aimed to determine whether patterns of volume change of CA1 are different in UHR individuals who do or do not achieve symptomatic remission. Structural MRI scans were acquired at baseline and at 1-2 follow-up time points (at 12-month intervals) from 147 UHR and healthy control subjects...
January 12, 2017: Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology
https://www.readbyqxmd.com/read/28076640/frontal-lobe-alterations-in-schizophrenia-a-review
#2
Ateeq Mubarik, Hassaan Tohid
Objective: To highlight the changes in the frontal lobe of the human brain in people with schizophrenia. Methods: This was a qualitative review of the literature. Results: Many schizophrenic patients exhibit functional, structural, and metabolic abnormalities in the frontal lobe. Some patients have few or no alterations, while some have more functional and structural changes than others. Magnetic resonance imaging (MRI) shows structural and functional changes in volume, gray matter, white matter, and functional activity in the frontal lobe, but the mechanisms underlying these changes are not yet fully understood...
October 2016: Trends in Psychiatry and Psychotherapy
https://www.readbyqxmd.com/read/28047652/su-f-sps-07-magnetic-resonance-spectroscopy-findings-in-early-phase-psychosis
#3
A Wright, R Ma, T Hummer, M Francis, N Mehdiyoun, U Dydak, A Breier
PURPOSE: Schizophrenia is a psychiatric disorder characterized by disordered thoughts, abnormal social behaviors, flat affect, and auditory or visual hallucinations. The current study aims to investigate alterations in brain metabolism in patients near the onset of psychosis (early-phase psychosis, EPP), to characterize abnormalities during the early stages of schizophrenia. To this end, we used magnetic resonance imaging (MRI) and spectroscopy (MRS) to measure metabolite levels and subsequently monitor the effect of treatment with N-acetylcysteine (NAC)...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28025253/visual-population-receptive-fields-in-people-with-schizophrenia-have-reduced-inhibitory-surrounds
#4
Elaine J Anderson, Marc S Tibber, D Sam Schwarzkopf, Sukhwinder S Shergill, Emilio Fernandez-Egea, Geraint Rees, Steven C Dakin
: People with schizophrenia (SZ) experience abnormal visual perception on a range of visual tasks, which have been linked to abnormal synaptic transmission and an imbalance between cortical excitation and inhibition. However differences in the underlying architecture of visual cortex neurons, which might explain these visual anomalies, have yet to be reported in vivo. Here, we probe the neural basis of these deficits by using functional MRI (fMRI) and population receptive field (pRF) mapping to infer properties of visually responsive neurons in people with SZ...
December 26, 2016: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/28012640/white-matter-integrity-and-symptom-dimensions-of-schizophrenia-a-diffusion-tensor-imaging-study
#5
Miriam H A Bopp, Rebecca Zöllner, Andreas Jansen, Bruno Dietsche, Axel Krug, Tilo T J Kircher
Impaired fiber bundle connectivity between brain regions is a key neuropathological finding in schizophrenia. Symptom dimensions in schizophrenia can be clustered into factor models. Single syndromes have been related to grey and white matter brain structure alterations. We associated all core syndromes of schizophrenia in a single patient group with changes in white matter integrity. Diffusion weighted images (3T MRI) and SAPS/SANS scores were measured in 26 male patients and 26 healthy controls. First, group differences in fractional anisotropy (FA) were calculated with TBSS...
December 21, 2016: Schizophrenia Research
https://www.readbyqxmd.com/read/28012424/white-matter-microstructure-and-volitional-motor-activity-in-schizophrenia-a-diffusion-kurtosis-imaging-study
#6
Lise Docx, Louise Emsell, Wim Van Hecke, Timo De Bondt, Paul M Parizel, Bernard Sabbe, Manuel Morrens
Avolition is a core feature of schizophrenia and may arise from altered brain connectivity. Here we used diffusion kurtosis imaging (DKI) to investigate the association between white matter (WM) microstructure and volitional motor activity. Multi-shell diffusion MRI and 24-h actigraphy data were obtained from 20 right-handed patients with schizophrenia and 16 right-handed age and gender matched healthy controls. We examined correlations between fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), and motor activity level, as well as group differences in these measures...
October 15, 2016: Psychiatry Research
https://www.readbyqxmd.com/read/27989645/effects-of-environmental-risks-and-polygenic-loading-for-schizophrenia-on-cortical-thickness
#7
Emma Neilson, Catherine Bois, Jude Gibson, Barbara Duff, Andrew Watson, Neil Roberts, Nicholas J Brandon, John Dunlop, Jeremy Hall, Andrew M McIntosh, Heather C Whalley, Stephen M Lawrie
There are established differences in cortical thickness (CT) in schizophrenia (SCZ) and bipolar (BD) patients when compared to healthy controls (HC). However, it is unknown to what extent environmental or genetic risk factors impact on CT in these populations. We have investigated the effect of Environmental Risk Scores (ERS) and Polygenic Risk Scores for SCZ (PGRS-SCZ) on CT. Structural MRI scans were acquired at 3T for patients with SCZ or BD (n=57) and controls (n=41). Cortical reconstructions were generated in FreeSurfer (v5...
December 15, 2016: Schizophrenia Research
https://www.readbyqxmd.com/read/27987389/structural-differences-in-hippocampal-subfields-among-schizophrenia-patients-major-depressive-disorder-patients-and-healthy-subjects
#8
Miho Ota, Noriko Sato, Shinsuke Hidese, Toshiya Teraishi, Norihide Maikusa, Hiroshi Matsuda, Kotaro Hattori, Hiroshi Kunugi
Many MRI studies have reported a volume reduction of the hippocampus in psychiatric diseases. However, disease-related volume differences in hippocampus subfields remain unclear. Here we compared the volumes of hippocampus subfields in patients with schizophrenia, patients with major depressive disorder (MDD), and healthy subjects as controls. T2-weighted images were acquired in 20 patients with schizophrenia, 36 with MDD, and 35 healthy volunteers by 3-Tesla MRI. Hippocampal subfields were segmented using an automatic algorithm, Automatic Segmentation of Hippocampal Subfields (ASHS)...
January 30, 2017: Psychiatry Research
https://www.readbyqxmd.com/read/27987251/simultaneous-rsfmri-and-eeg-recordings-of-functional-connectivity-in-patients-with-schizophrenia
#9
Eiji Kirino, Shoji Tanaka, Mayuko Fukuta, Rie Inami, Heii Arai, Reiichi Inoue, Shigeki Aoki
AIMS: It remains unclear how functional connectivity (FC) may be related to specific cognitive domains in neuropsychiatric disorders. Here we used simultaneous resting-state functional MRI (rsfMRI) and electroencephalography (EEG) recording in patients with schizophrenia, to evaluate FC within and outside the default mode network (DMN). METHODS: Our study population included 14 patients with schizophrenia and 15 healthy control participants. From all participants, we acquired rsfMRI data, and simultaneously recorded EEG data using an MR-compatible amplifier...
December 17, 2016: Psychiatry and Clinical Neurosciences
https://www.readbyqxmd.com/read/27968850/multimodal-mri-characterisation-of-schizophrenia-a-discriminative-analysis
#10
Han Yang, Hongjian He, Jianhui Zhong
BACKGROUND: Recent studies on MRI-based discrimination of schizophrenia have shown promise. Considering that, in general, pathological changes should display characteristic markers in both brain function and anatomy, machine-learning methods using multimodal MRI features of brain networks might provide a deeper insight into the pathological mechanism of schizophrenia. We aimed to assess the discriminative power of multimodal MRI features and to extract these features of high discriminative information for classification of patients with schizophrenia...
October 2016: Lancet
https://www.readbyqxmd.com/read/27951456/unrealistic-self-overconfidence-in-schizophrenia-is-associated-with-left-presubiculum-atrophy-and-impaired-episodic-memory
#11
Maria Donata Orfei, Fabrizio Piras, Nerisa Banaj, Giorgio Di Lorenzo, Alberto Siracusano, Carlo Caltagirone, Pier Luca Bandinelli, Giuseppe Ducci, Gianfranco Spalletta
The study aimed at investigating the role of the hippocampal subfields in cognitive insight and the clinical and neuropsychological underpinnings of the related two sub-dimensions, Self-Reflectiveness (SR), i.e., openness to external feedback, and Self-Certainty (SC), i.e., unrealistic overconfidence in one's opinions. In order to do this, 45 patients with a diagnosis of schizophrenia and 45 age- and gender-matched healthy control subjects (HC) were administered the Beck Cognitive Insight Scale (BCIS), along with neuropsychological, clinical and psychopathological assessment, and underwent an MRI investigation...
November 17, 2016: Cortex; a Journal Devoted to the Study of the Nervous System and Behavior
https://www.readbyqxmd.com/read/27941946/using-deep-belief-network-modelling-to-characterize-differences-in-brain-morphometry-in-schizophrenia
#12
Walter H L Pinaya, Ary Gadelha, Orla M Doyle, Cristiano Noto, André Zugman, Quirino Cordeiro, Andrea P Jackowski, Rodrigo A Bressan, João R Sato
Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging results mirrors the heterogeneity of the disorder. Machine learning methods capable of representing invariant features could circumvent this problem. In this structural MRI study, we trained a deep learning model known as deep belief network (DBN) to extract features from brain morphometry data and investigated its performance in discriminating between healthy controls (N = 83) and patients with schizophrenia (N = 143)...
December 12, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27930915/anatomical-dysconnectivity-in-bipolar-disorder-compared-with-schizophrenia-a-selective-review-of-structural-network-analyses-using-diffusion-mri
#13
REVIEW
Stefani O'Donoghue, Laurena Holleran, Dara M Cannon, Colm McDonald
BACKGROUND: The dysconnectivity hypothesis suggests that psychotic illnesses arise not from regionally specific focal pathophysiology, but rather from impaired neuroanatomical integration across networks of brain regions. Decreased white matter organization has been hypothesized to be a feature of psychotic illnesses in general, which is supported by meta-analyses of DTI studies in bipolar disorder and schizophrenia. Although many diffusion MRI studies investigate bipolar disorder and schizophrenia alone, relatively few studies directly compare structural features in these psychotic illnesses...
February 2017: Journal of Affective Disorders
https://www.readbyqxmd.com/read/27922632/a-phenome-wide-examination-of-neural-and-cognitive-function
#14
R A Poldrack, E Congdon, W Triplett, K J Gorgolewski, K H Karlsgodt, J A Mumford, F W Sabb, N B Freimer, E D London, T D Cannon, R M Bilder
This data descriptor outlines a shared neuroimaging dataset from the UCLA Consortium for Neuropsychiatric Phenomics, which focused on understanding the dimensional structure of memory and cognitive control (response inhibition) functions in both healthy individuals (130 subjects) and individuals with neuropsychiatric disorders including schizophrenia (50 subjects), bipolar disorder (49 subjects), and attention deficit/hyperactivity disorder (43 subjects). The dataset includes an extensive set of task-based fMRI assessments, resting fMRI, structural MRI, and high angular resolution diffusion MRI...
December 6, 2016: Scientific Data
https://www.readbyqxmd.com/read/27919751/less-head-motion-during-mri-under-task-than-resting-state-conditions
#15
Willem Huijbers, Koene R A Van Dijk, Meta M Boenniger, Rüdiger Stirnberg, Monique M B Breteler
Head motion reduces data quality of neuroimaging data. In three functional magnetic resonance imaging (MRI) experiments we demonstrate that people make less head movements under task than resting-state conditions. In Experiment 1, we observed less head motion during a memory encoding task than during the resting-state condition. In Experiment 2, using publicly shared data from the UCLA Consortium for Neuropsychiatric Phenomics LA5c Study, we again found less head motion during several active task conditions than during a resting-state condition, although some task conditions also showed comparable motion...
December 2, 2016: NeuroImage
https://www.readbyqxmd.com/read/27882449/diametrical-relationship-between-gray-and-white-matter-volumes-in-autism-spectrum-disorder-and-schizophrenia
#16
Serge A Mitelman, Marie-Cecile Bralet, M Mehmet Haznedar, Eric Hollander, Lina Shihabuddin, Erin A Hazlett, Monte S Buchsbaum
Autism spectrum disorders and schizophrenia have been variously characterized as separate nosological entities with overlapping deficits in social cognition or diametrical extremes of a phenotypic continuum. This study aimed to determine how these models apply to comparative morphometric data. MRI scans of the brain were obtained in 49 subjects with schizophrenia, 20 subjects with autism and 39 healthy controls. Images were parcellated into 40 Brodmann areas and entered into repeated-measures ANOVA for between-group comparison of global and localized gray and white matter volumes...
November 23, 2016: Brain Imaging and Behavior
https://www.readbyqxmd.com/read/27872811/failure-to-mobilize-cognitive-control-for-challenging-tasks-correlates-with-symptom-severity-in-schizophrenia
#17
Bengi Baran, F Işık Karahanoğlu, Yigal Agam, Leonidas Mantonakis, Dara S Manoach
Deficits in the adaptive, flexible control of behavior contribute to the clinical manifestations of schizophrenia. We used functional MRI and an antisaccade paradigm to examine the neural correlates of cognitive control deficits and their relations to symptom severity. Thirty-three chronic medicated outpatients with schizophrenia and 31 healthy controls performed an antisaccade paradigm. We examined differences in recruitment of the cognitive control network and task performance for Hard (high control) versus Easy (low control) antisaccade trials within and between groups...
2016: NeuroImage: Clinical
https://www.readbyqxmd.com/read/27863935/association-of-sflt-1-and-worsening-psychopathology-in-relatives-at-high-risk-for-psychosis-a-longitudinal-study
#18
Paulo L Lizano, Jeffrey K Yao, Neeraj Tandon, Suraj Sarvode Mothi, Debra M Montrose, Matcheri S Keshavan
BACKGROUND: Angiogenic dysfunction and abnormalities in psychopathology and brain structure have been reported in schizophrenia, but their relationships are mostly unknown. We recently demonstrated that sFlt-1, anti-angiogenic factor, was significantly elevated in patients at familial high-risk for psychosis (FHR). We hypothesized that elevated sFlt-1 correlates with baseline and longitudinal changes in psychopathology, cognition, and brain structure. METHODS: Plasma sFlt-1 in FHR (n=35) and HC (n=39) was obtained at baseline...
November 15, 2016: Schizophrenia Research
https://www.readbyqxmd.com/read/27834215/diffusion-weighted-imaging-uncovers-likely-sources-of-processing-speed-deficits-in-schizophrenia
#19
Peter Kochunov, Laura M Rowland, Els Fieremans, Jelle Veraart, Neda Jahanshad, George Eskandar, Xiaoming Du, Florian Muellerklein, Anya Savransky, Dinesh Shukla, Hemalatha Sampath, Paul M Thompson, L Elliot Hong
Schizophrenia, a devastating psychiatric illness with onset in the late teens to early 20s, is thought to involve disrupted brain connectivity. Functional and structural disconnections of cortical networks may underlie various cognitive deficits, including a substantial reduction in the speed of information processing in schizophrenia patients compared with controls. Myelinated white matter supports the speed of electrical signal transmission in the brain. To examine possible neuroanatomical sources of cognitive deficits, we used a comprehensive diffusion-weighted imaging (DWI) protocol and characterized the white matter diffusion signals using diffusion kurtosis imaging (DKI) and permeability-diffusivity imaging (PDI) in patients (n = 74), their nonill siblings (n = 41), and healthy controls (n = 113)...
November 22, 2016: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/27829096/cognitive-subtypes-of-schizophrenia-characterized-by-differential-brain-volumetric-reductions-and-cognitive-decline
#20
Danielle Weinberg, Rhoshel Lenroot, Isabella Jacomb, Katherine Allen, Jason Bruggemann, Ruth Wells, Ryan Balzan, Dennis Liu, Cherrie Galletly, Stanley V Catts, Cynthia Shannon Weickert, Thomas W Weickert
Importance: Cognitively distinct subgroups of schizophrenia have been defined based on premorbid and current IQ, but little is known about the neuroanatomical differences among these cognitive subgroups. Objectives: To confirm previous findings related to IQ-based subgroups of patients with schizophrenia in an independent sample and extend those findings to determine the extent to which brain volumetric differences correspond to the IQ-based subgroups. Design, Setting, and Participants: A total of 183 participants were assessed at the outpatient settings of Neuroscience Research Australia and Lyell McEwin Hospital from September 22, 2009, to August 1, 2012...
December 1, 2016: JAMA Psychiatry
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