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      Combination of Resting State fMRI, DTI, and sMRI Data to Discriminate Schizophrenia by N-way MCCA + jICA

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          Abstract

          Multimodal brain imaging data have shown increasing utility in answering both scientifically interesting and clinically relevant questions. Each brain imaging technique provides a different view of brain function or structure, while multimodal fusion capitalizes on the strength of each and may uncover hidden relationships that can merge findings from separate neuroimaging studies. However, most current approaches have focused on pair-wise fusion and there is still relatively little work on N-way data fusion and examination of the relationships among multiple data types. We recently developed an approach called “mCCA + jICA” as a novel multi-way fusion method which is able to investigate the disease risk factors that are either shared or distinct across multiple modalities as well as the full correspondence across modalities. In this paper, we applied this model to combine resting state fMRI (amplitude of low-frequency fluctuation, ALFF), gray matter (GM) density, and DTI (fractional anisotropy, FA) data, in order to elucidate the abnormalities underlying schizophrenia patients (SZs, n = 35) relative to healthy controls (HCs, n = 28). Both modality-common and modality-unique abnormal regions were identified in SZs, which were then used for successful classification for seven modality-combinations, showing the potential for a broad applicability of the mCCA + jICA model and its results. In addition, a pair of GM-DTI components showed significant correlation with the positive symptom subscale of Positive and Negative Syndrome Scale (PANSS), suggesting that GM density changes in default model network along with white-matter disruption in anterior thalamic radiation are associated with increased positive PANSS. Findings suggest the DTI anisotropy changes in frontal lobe may relate to the corresponding functional/structural changes in prefrontal cortex and superior temporal gyrus that are thought to play a role in the clinical expression of SZ.

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          Most cited references68

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          The positive and negative syndrome scale (PANSS) for schizophrenia.

          The variable results of positive-negative research with schizophrenics underscore the importance of well-characterized, standardized measurement techniques. We report on the development and initial standardization of the Positive and Negative Syndrome Scale (PANSS) for typological and dimensional assessment. Based on two established psychiatric rating systems, the 30-item PANSS was conceived as an operationalized, drug-sensitive instrument that provides balanced representation of positive and negative symptoms and gauges their relationship to one another and to global psychopathology. It thus constitutes four scales measuring positive and negative syndromes, their differential, and general severity of illness. Study of 101 schizophrenics found the four scales to be normally distributed and supported their reliability and stability. Positive and negative scores were inversely correlated once their common association with general psychopathology was extracted, suggesting that they represent mutually exclusive constructs. Review of five studies involving the PANSS provided evidence of its criterion-related validity with antecedent, genealogical, and concurrent measures, its predictive validity, its drug sensitivity, and its utility for both typological and dimensional assessment.
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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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              An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF.

              Most of the resting-state functional magnetic resonance imaging (fMRI) studies demonstrated the correlations between spatially distinct brain areas from the perspective of functional connectivity or functional integration. The functional connectivity approaches do not directly provide information of the amplitude of brain activity of each brain region within a network. Alternatively, an index named amplitude of low-frequency fluctuation (ALFF) of the resting-state fMRI signal has been suggested to reflect the intensity of regional spontaneous brain activity. However, it has been indicated that the ALFF is also sensitive to the physiological noise. The current study proposed a fractional ALFF (fALFF) approach, i.e., the ratio of power spectrum of low-frequency (0.01-0.08 Hz) to that of the entire frequency range and this approach was tested in two groups of resting-state fMRI data. The results showed that the brain areas within the default mode network including posterior cingulate cortex, precuneus, medial prefrontal cortex and bilateral inferior parietal lobule had significantly higher fALFF than the other brain areas. This pattern was consistent with previous neuroimaging results. The non-specific signal components in the cistern areas in resting-state fMRI were significantly suppressed, indicating that the fALFF approach improved the sensitivity and specificity in detecting spontaneous brain activities. Its mechanism and sensitivity to abnormal brain activity should be evaluated in the future studies.
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                Author and article information

                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                29 May 2013
                2013
                : 7
                : 235
                Affiliations
                [1] 1The Mind Research Network, Lovelace Biomedical and Environmental Research Institute , Albuquerque, NM, USA
                [2] 2LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences , Beijing, China
                [3] 3Department of ECE, University of New Mexico , Albuquerque, NM, USA
                [4] 4Division of Natural Science, New College of Florida , Sarasota, FL, USA
                [5] 5Olin Neuropsychiatry Research Center , Hartford, CT, USA
                [6] 6Department of Psychiatry, Yale University , New Haven, CT, USA
                [7] 7Department of Neurobiology, Yale University , New Haven, CT, USA
                [8] 8Department of Psychiatry, University of New Mexico , Albuquerque, NM, USA
                [9] 9Department of Neuroscience, University of New Mexico , Albuquerque, NM, USA
                [10] 10Psychiatry Research Program, New Mexico VA Health Care System , Albuquerque, NM, USA
                Author notes

                Edited by: Veronika Schöpf, Medical University Vienna, Austria

                Reviewed by: Robert C. Welsh, University of Michigan, USA; Georg Langs, Medical University of Vienna, Austria

                *Correspondence: Jing Sui, The Mind Research Network, 1101 Yale Blvd, NE, Albuquerque, NM 87106, USA e-mail: kittysj@ 123456gmail.com

                Jing Sui and Hao He are co-first authors for this paper.

                Article
                10.3389/fnhum.2013.00235
                3666029
                23755002
                841030dc-d3b5-47c5-801a-58d5dca0c026
                Copyright © 2013 Sui, He, Yu, Chen, Rogers, Pearlson, Mayer, Bustillo, Canive and Calhoun.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.

                History
                : 14 January 2013
                : 15 May 2013
                Page count
                Figures: 4, Tables: 4, Equations: 5, References: 87, Pages: 14, Words: 11161
                Categories
                Neuroscience
                Original Research

                Neurosciences
                multimodal fusion,mcca + jica,resting state fmri,dti,smri,schizophrenia,alff,gm
                Neurosciences
                multimodal fusion, mcca + jica, resting state fmri, dti, smri, schizophrenia, alff, gm

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