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      Altered Functional Connectivity of Fusiform Gyrus in Subjects with Amnestic Mild Cognitive Impairment: A Resting-State fMRI Study

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          Abstract

          Visual cognition such as face recognition requests a high degree of functional integration between distributed brain areas of a network. It has been reported that the fusiform gyrus (FG) is an important brain area involved in facial cognition; altered connectivity of FG to some other regions may lead to a deficit in visual cognition especially face recognition. However, whether functional connectivity between the FG and other brain areas changes remains unclear in the resting state in amnestic mild cognitive impairment (aMCI) subjects. Here, we employed a resting-state functional MRI (fMRI) to examine alterations in functional connectivity of left/right FG comparing aMCI patients with age-matched control subjects. Forty-eight aMCI and 38 control subjects from the Alzheimer’s disease Neuroimaging Initiative were analyzed. We concentrated on the correlation between low frequency fMRI time courses in the FG and those in all other brain regions. Relative to the control group, we found some discrepant regions in the aMCI group which presented increased or decreased connectivity with the left/right FG including the left precuneus, left lingual gyrus, right thalamus, supramarginal gyrus, left supplementary motor area, left inferior temporal gyrus, and left parahippocampus. More importantly, we also obtained that both left and right FG have increased functional connections with the left middle occipital gyrus (MOG) and right anterior cingulate gyrus (ACC) in aMCI patients. That was not a coincidence and might imply that the MOG and ACC also play a critical role in visual cognition, especially face recognition. These findings in a large part supported our hypothesis and provided a new insight in understanding the important subtype of MCI.

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          Most cited references62

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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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            Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations.

            A previous report of correlations in low-frequency resting-state fluctuations between right and left hemisphere motor cortices in rapidly sampled single-slice echoplanar data is confirmed using a whole-body echoplanar MRI scanner at 1.5 T. These correlations are extended to lower sampling rate multislice echoplanar acquisitions and other right/left hemisphere-symmetric functional cortices. The specificity of the correlations in the lower sampling-rate acquisitions is lower due to cardiac and respiratory-cycle effects which are aliased into the pass-band of the low-pass filter. Data are combined for three normal right-handed male subjects. Correlations to left hemisphere motor cortex, visual cortex, and amygdala are measured in long resting-state scans.
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              Frequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data.

              In subjects performing no specific cognitive task ("resting state"), time courses of voxels within functionally connected regions of the brain have high cross-correlation coefficients ("functional connectivity"). The purpose of this study was to measure the contributions of low frequencies and physiological noise to cross-correlation maps. In four healthy volunteers, task-activation functional MR imaging and resting-state data were acquired. We obtained four contiguous slice locations in the "resting state" with a high sampling rate. Regions of interest consisting of four contiguous voxels were selected. The correlation coefficient for the averaged time course and every other voxel in the four slices was calculated and separated into its component frequency contributions. We calculated the relative amounts of the spectrum that were in the low-frequency (0 to 0.1 Hz), the respiratory-frequency (0.1 to 0.5 Hz), and cardiac-frequency range (0.6 to 1.2 Hz). For each volunteer, resting-state maps that resembled task-activation maps were obtained. For the auditory and visual cortices, the correlation coefficient depended almost exclusively on low frequencies (<0.1 Hz). For all cortical regions studied, low-frequency fluctuations contributed more than 90% of the correlation coefficient. Physiological (respiratory and cardiac) noise sources contributed less than 10% to any functional connectivity MR imaging map. In blood vessels and cerebrospinal fluid, physiological noise contributed more to the correlation coefficient. Functional connectivity in the auditory, visual, and sensorimotor cortices is characterized predominantly by frequencies slower than those in the cardiac and respiratory cycles. In functionally connected regions, these low frequencies are characterized by a high degree of temporal coherence.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                27 August 2015
                2015
                : 9
                : 471
                Affiliations
                [1] 1School of Life Science and Technology, Xidian University , Xi’an, China
                Author notes

                Edited by: Shuhei Yamaguchi, Shimane University, Japan

                Reviewed by: Hidenao Fukuyama, Kyoto University, Japan; Keiichi Onoda, Shimane University, Japan

                *Correspondence: Minghao Dong and Liyu Huang, School of Life Science and Technology, Xidian University, Xi’an, Shaanxi 710071, China, dminghao2013@ 123456163.com ; huangly@ 123456mail.xidian.edu.cn

                Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database ( adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found here.

                Article
                10.3389/fnhum.2015.00471
                4550786
                26379534
                c6b2e1e1-e734-40f9-87fb-9fe15383f03d
                Copyright © 2015 Cai, Chong, Zhang, Li, von Deneen, Ren, Dong and Huang for the Alzheimer’s Disease Neuroimaging Initiative.

                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
                : 11 May 2015
                : 12 August 2015
                Page count
                Figures: 5, Tables: 4, Equations: 0, References: 88, Pages: 13, Words: 9942
                Funding
                Funded by: National Key Basic Research and Development Program (973)
                Award ID: 2011CB707700
                Funded by: National Natural Science Foundation of China 10.13039/501100001809
                Award ID: 31271063, 81401478
                Funded by: Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant) 10.13039/100007333
                Award ID: U01 AG024904
                Funded by: DOD Alzheimer’s Disease Neuroimaging Initiative (ADNI) (Department of Defense)
                Award ID: W81XWH-12-2-0012
                Categories
                Neuroscience
                Original Research

                Neurosciences
                fusiform gyrus,face recognition,visual cognition,amnestic mild cognitive impairment,functional connectivity,functional mri

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