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      Neuronal activity regulates the regional vulnerability to amyloid-β deposition

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          Abstract

          Amyloid-β (Aβ) plaque deposition in specific brain regions is a major pathological hallmark of Alzheimer’fs disease (AD). However, the mechanism underlying the regional vulnerability to Aβ deposition in AD is unknown. Herein, we provide evidence that endogenous neuronal activity regulates the regional concentration of interstitial fluid (ISF) Aβ which drives local Aβ aggregation. Using in vivo microdialysis, we show that ISF Aβ levels in multiple brain regions of APP transgenic mice prior to plaque deposition were commensurate with the degree of subsequent plaque deposition and to the concentration of lactate, a marker of neuronal activity. Furthermore, unilateral vibrissae stimulation increased ISF Aβ, and unilateral vibrissae deprivation decreased ISF Aβ and lactate levels in contralateral barrel cortex. Long term unilateral vibrissae deprivation decreased amyloid plaque formation and growth. Our results suggest a mechanism to account for the vulnerability of specific brain regions to Aβ deposition in AD.

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          Most cited references 49

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          A default mode of brain function.

          A baseline or control state is fundamental to the understanding of most complex systems. Defining a baseline state in the human brain, arguably our most complex system, poses a particular challenge. Many suspect that left unconstrained, its activity will vary unpredictably. Despite this prediction we identify a baseline state of the normal adult human brain in terms of the brain oxygen extraction fraction or OEF. The OEF is defined as the ratio of oxygen used by the brain to oxygen delivered by flowing blood and is remarkably uniform in the awake but resting state (e.g., lying quietly with eyes closed). Local deviations in the OEF represent the physiological basis of signals of changes in neuronal activity obtained with functional MRI during a wide variety of human behaviors. We used quantitative metabolic and circulatory measurements from positron-emission tomography to obtain the OEF regionally throughout the brain. Areas of activation were conspicuous by their absence. All significant deviations from the mean hemisphere OEF were increases, signifying deactivations, and resided almost exclusively in the visual system. Defining the baseline state of an area in this manner attaches meaning to a group of areas that consistently exhibit decreases from this baseline, during a wide variety of goal-directed behaviors monitored with positron-emission tomography and functional MRI. These decreases suggest the existence of an organized, baseline default mode of brain function that is suspended during specific goal-directed behaviors.
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            The brain's default network: anatomy, function, and relevance to disease.

            Thirty years of brain imaging research has converged to define the brain's default network-a novel and only recently appreciated brain system that participates in internal modes of cognition. Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment. Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system. Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others. Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems. The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation. The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self-relevant mental simulations. These two subsystems converge on important nodes of integration including the posterior cingulate cortex. The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world. We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer's disease.
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              Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI.

              Recent functional imaging studies have revealed coactivation in a distributed network of cortical regions that characterizes the resting state, or default mode, of the human brain. Among the brain regions implicated in this network, several, including the posterior cingulate cortex and inferior parietal lobes, have also shown decreased metabolism early in the course of Alzheimer's disease (AD). We reasoned that default-mode network activity might therefore be abnormal in AD. To test this hypothesis, we used independent component analysis to isolate the network in a group of 13 subjects with mild AD and in a group of 13 age-matched elderly controls as they performed a simple sensory-motor processing task. Three important findings are reported. Prominent coactivation of the hippocampus, detected in all groups, suggests that the default-mode network is closely involved with episodic memory processing. The AD group showed decreased resting-state activity in the posterior cingulate and hippocampus, suggesting that disrupted connectivity between these two regions accounts for the posterior cingulate hypometabolism commonly detected in positron emission tomography studies of early AD. Finally, a goodness-of-fit analysis applied at the individual subject level suggests that activity in the default-mode network may ultimately prove a sensitive and specific biomarker for incipient AD.
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                Author and article information

                Journal
                9809671
                21092
                Nat Neurosci
                Nature neuroscience
                1097-6256
                1546-1726
                14 March 2011
                1 May 2011
                June 2011
                1 December 2011
                : 14
                : 6
                : 750-756
                Affiliations
                [1 ] Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
                [2 ] Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, 63110, USA
                [3 ] Department of Radiology, Washington University School of Medicine, St. Louis, MO, 63110, USA
                [4 ] Department of Anatomy and Neurobiology, Washington University School of Medicine, St. Louis, MO, 63110, USA
                [5 ] Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, 63110, USA
                [6 ] Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, 63110, USA
                [7 ] Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
                Author notes
                To whom correspondence should be addressed: David M. Holtzman, M.D., Andrew B. and Gretchen P. Jones Professor and Chair, Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave. Campus Box 8111, Saint Louis, MO 63110, Administrator phone: (314) 747-0644, Office phone: (314) 362-9872, Fax: (314) 362-2244, holtzman@ 123456neuro.wustl.edu
                Article
                nihpa279971
                10.1038/nn.2801
                3102784
                21532579

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                Funding
                Funded by: National Institute on Aging : NIA
                Funded by: National Institute of Neurological Disorders and Stroke : NINDS
                Award ID: R37 AG013956-16 ||AG
                Funded by: National Institute on Aging : NIA
                Funded by: National Institute of Neurological Disorders and Stroke : NINDS
                Award ID: P30 NS057105-05 ||NS
                Funded by: National Institute on Aging : NIA
                Funded by: National Institute of Neurological Disorders and Stroke : NINDS
                Award ID: K01 AG029524-05 ||AG
                Funded by: National Institute on Aging : NIA
                Funded by: National Institute of Neurological Disorders and Stroke : NINDS
                Award ID: F31 AG033452-03 ||AG
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                Neurosciences

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