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Biophysical Models: Neurovascular Coupling, Cortical Microcircuits, and Metabolism

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Encyclopedia of Computational Neuroscience

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Forward-generative models of functional neuroimaging data

Definition

Forward-generative models are considered crucial to interpret and integrate data obtained with different functional neuroimaging modalities (Riera 2014). Typically, these models are formulated to represent biological principles at the mesoscopic scale, which basically stand for an average voxel (1 mm3) in any brain imaging technique. To this end, biophysical models for neuronal activity, which are mostly available from the neuronal computationcommunity, have been modified to incorporate general physiological mechanisms governing glial cell activity, vascular dynamics, and metabolism. For the cerebral cortex, the most relevant brain structure in functional neuroimaging, a variety of such extended biophysical models has been consolidating around three main research topics over the last decade: (a) the principles for neurovascular coupling, (b) the organization of cortical microcircuits, and (c) the cellular...

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Authors and Affiliations

  1. Department of Biomedical Engineering, Florida International University, Miami, FL, USA

    Jorge Riera

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  1. Jorge Riera
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Correspondence to Jorge Riera .

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Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

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Riera, J. (2014). Biophysical Models: Neurovascular Coupling, Cortical Microcircuits, and Metabolism. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_522-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_522-1

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  • Online ISBN: 978-1-4614-7320-6

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