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    An integrative dynamic model of brain energy metabolism using in vivo neurochemical measurements


    Cloutier, Mathieu, Bolger, Fiachra B., Lowry, John P. and Wellstead, Peter (2009) An integrative dynamic model of brain energy metabolism using in vivo neurochemical measurements. Journal of Computational Neuroscience. ISSN 0929-5313

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    Abstract

    An integrative, systems approach to the modelling of brain energy metabolism is presented. Mechanisms such as glutamate cycling between neurons and astrocytes and glycogen storage in astrocytes have been implemented. A unique feature of the model is its calibration using in vivo data of brain glucose and lactate from freely moving rats under various stimuli. The model has been used to perform simulated perturbation experiments that show that glycogen breakdown in astrocytes is significantly activated during sensory (tail pinch) stimulation. This mechanism provides an additional input of energy substrate during high consumption phases. By way of validation, data from the perfusion of 50μM propranolol in the rat brain was compared with the model outputs. Propranolol affects the glucose dynamics during stimulation, and this was accurately reproduced in the model by a reduction in the glycogen breakdown in astrocytes. The model’s predictive capacity was verified by using data from a sensory stimulation (restraint) that was not used for model calibration. Finally, a sensitivity analysis was conducted on the model parameters, this showed that the control of energy metabolism and transport processes are critical in the metabolic behaviour of cerebral tissue.
    Item Type: Article
    Keywords: Astrocytes; Brain energy metabolism; Kinetic modelling; Neurons; Systems biology.
    Academic Unit: Faculty of Science and Engineering > Chemistry
    Item ID: 1664
    Depositing User: Hamilton Editor
    Date Deposited: 16 Nov 2009 15:51
    Journal or Publication Title: Journal of Computational Neuroscience
    Publisher: Springer Science+Business Media
    Refereed: Yes
    URI: https://mu.eprints-hosting.org/id/eprint/1664
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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