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      A multi-site resting state fMRI study on the amplitude of low frequency fluctuations in schizophrenia

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          Abstract

          Background: This multi-site study compares resting state fMRI amplitude of low frequency fluctuations (ALFF) and fractional ALFF (fALFF) between patients with schizophrenia (SZ) and healthy controls (HC).

          Methods: Eyes-closed resting fMRI scans (5:38 min; n = 306, 146 SZ) were collected from 6 Siemens 3T scanners and one GE 3T scanner. Imaging data were pre-processed using an SPM pipeline. Power in the low frequency band (0.01–0.08 Hz) was calculated both for the original pre-processed data as well as for the pre-processed data after regressing out the six rigid-body motion parameters, mean white matter (WM) and cerebral spinal fluid (CSF) signals. Both original and regressed ALFF and fALFF measures were modeled with site, diagnosis, age, and diagnosis × age interactions.

          Results: Regressing out motion and non-gray matter signals significantly decreased fALFF throughout the brain as well as ALFF in the cortical edge, but significantly increased ALFF in subcortical regions. Regression had little effect on site, age, and diagnosis effects on ALFF, other than to reduce diagnosis effects in subcortical regions. There were significant effects of site across the brain in all the analyses, largely due to vendor differences. HC showed greater ALFF in the occipital, posterior parietal, and superior temporal lobe, while SZ showed smaller clusters of greater ALFF in the frontal and temporal/insular regions as well as in the caudate, putamen, and hippocampus. HC showed greater fALFF compared with SZ in all regions, though subcortical differences were only significant for original fALFF.

          Conclusions: SZ show greater eyes-closed resting state low frequency power in frontal cortex, and less power in posterior lobes than do HC; fALFF, however, is lower in SZ than HC throughout the cortex. These effects are robust to multi-site variability. Regressing out physiological noise signals significantly affects both total and fALFF measures, but does not affect the pattern of case/control differences.

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          Most cited references43

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          Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI.

          In children with attention deficit hyperactivity disorder (ADHD), functional neuroimaging studies have revealed abnormalities in various brain regions, including prefrontal-striatal circuit, cerebellum, and brainstem. In the current study, we used a new marker of functional magnetic resonance imaging (fMRI), amplitude of low-frequency (0.01-0.08Hz) fluctuation (ALFF) to investigate the baseline brain function of this disorder. Thirteen boys with ADHD (13.0+/-1.4 years) were examined by resting-state fMRI and compared with age-matched controls. As a result, we found that patients with ADHD had decreased ALFF in the right inferior frontal cortex, [corrected] and bilateral cerebellum and the vermis as well as increased ALFF in the right anterior cingulated cortex, left sensorimotor cortex, and bilateral brainstem. This resting-state fMRI study suggests that the changed spontaneous neuronal activity of these regions may be implicated in the underlying pathophysiology in children with ADHD.
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            A method for functional network connectivity among spatially independent resting-state components in schizophrenia.

            Functional connectivity of the brain has been studied by analyzing correlation differences in time courses among seed voxels or regions with other voxels of the brain in healthy individuals as well as in patients with brain disorders. The spatial extent of strongly temporally coherent brain regions co-activated during rest has also been examined using independent component analysis (ICA). However, the weaker temporal relationships among ICA component time courses, which we operationally define as a measure of functional network connectivity (FNC), have not yet been studied. In this study, we propose an approach for evaluating FNC and apply it to functional magnetic resonance imaging (fMRI) data collected from persons with schizophrenia and healthy controls. We examined the connectivity and latency among ICA component time courses to test the hypothesis that patients with schizophrenia would show increased functional connectivity and increased lag among resting state networks compared to controls. Resting state fMRI data were collected and the inter-relationships among seven selected resting state networks (identified using group ICA) were evaluated by correlating each subject's ICA time courses with one another. Patients showed higher correlation than controls among most of the dominant resting state networks. Patients also had slightly more variability in functional connectivity than controls. We present a novel approach for quantifying functional connectivity among brain networks identified with spatial ICA. Significant differences between patient and control connectivity in different networks were revealed possibly reflecting deficiencies in cortical processing in patients.
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              Amplitude of low frequency fluctuation within visual areas revealed by resting-state functional MRI.

              Most studies of resting-state functional magnetic resonance imaging (fMRI) have applied the temporal correlation in the time courses to investigate the functional connectivity between brain regions. Alternatively, the power of low frequency fluctuation (LFF) may also be used as a biomarker to assess spontaneous activity. The purpose of the current study is to evaluate whether the amplitude of the LFF (ALFF) relates to cerebral physiological states. Ten healthy subjects underwent four resting-state fMRI scanning sessions, two for eyes-open (EO) and two for eyes-closed (EC) conditions, with two sets of parameters (TR=400 ms and 2 s, respectively). After data preprocessing, ALFF was obtained by calculating the square root of the power spectrum in the frequency range of 0.01-0.08 Hz. Our results showed that the ALFF in EO was significantly higher than that in EC (P<0.05, corrected) in the bilateral visual cortices. Furthermore, the ALFF in EO was significantly reduced in the right paracentral lobule (PCL) than in EC (P<0.05, corrected). Region of interest (ROI) analysis showed that the ALFF differences between EO and EC were consistent for each subject. In contrast, no significant ALFF differences were found between EO and EC (P<0.381) in the posterior cingulate cortex. All these results agree well with previous studies comparing EO and EC states. Our finding of the distinct ALFF difference between EO and EC in the visual cortex implies that the ALFF may be a novel biomarker for physiological states of the brain.
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                Author and article information

                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                08 August 2013
                2013
                : 7
                : 137
                Affiliations
                [1] 1Mind Research Network Albuquerque, NM, USA
                [2] 2Department of Psychiatry, University of New Mexico Albuquerque, NM, USA
                [3] 3Department of Psychiatry and Human Behavior, University of California Irvine Irvine, CA, USA
                [4] 4Department of Psychiatry, University of California, San Francisco San Francisco, CA, USA
                [5] 5San Francisco VA Medical Center San Francisco, CA, USA
                [6] 6Department of Radiology, Brain Imaging and Analysis Center, Duke University Durham, NC, USA
                [7] 7Department of Psychiatry, University of Minnesota Minneapolis, MN, USA
                [8] 8Department of Psychiatry, University of North Carolina School of Medicine Chapel Hill, NC, USA
                [9] 9Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA, USA
                [10] 10Electrical Engineering, University of New Mexico Albuquerque, NM, USA
                Author notes

                Edited by: Thomas J. Grabowski, University of Washington School of Medicine, USA

                Reviewed by: Natalia M. Kleinhans, University of Washington, USA; Javier Gonzalez-Castillo, National Institute of Mental Health, USA

                *Correspondence: Jessica A. Turner, Mind Research Network, 1101 Yale Blvd. NE, Albuquerque, NM 87106, USA e-mail: jturner@ 123456mrn.org

                This article was submitted to Frontiers in Brain Imaging Methods, a specialty of Frontiers in Neuroscience.

                Article
                10.3389/fnins.2013.00137
                3737471
                23964193
                66ba1f1c-86c5-453b-a76a-7ea88486535c
                Copyright © 2013 Turner, Damaraju, van Erp, Mathalon, Ford, Voyvodic, Mueller, Belger, Bustillo, McEwen, Potkin, FBIRN and Calhoun.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 15 February 2013
                : 16 July 2013
                Page count
                Figures: 9, Tables: 6, Equations: 1, References: 69, Pages: 13, Words: 11580
                Categories
                Neuroscience
                Original Research Article

                Neurosciences
                resting state fmri,lfo,alff,schizophrenia,multi-site studies,effect size
                Neurosciences
                resting state fmri, lfo, alff, schizophrenia, multi-site studies, effect size

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