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      Biophysical model for integrating neuronal activity, EEG, fMRI and metabolism.

      Neuroimage

      Alzheimer Disease, diagnosis, physiopathology, Biophysics, methods, Brain, Brain Mapping, Computer Simulation, Diagnosis, Computer-Assisted, Electroencephalography, Glucose, metabolism, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Models, Neurological, Neurons, Oxygen, Positron-Emission Tomography, Systems Integration

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          Abstract

          Our goal is to model the coupling between neuronal activity, cerebral metabolic rates of glucose and oxygen consumption, cerebral blood flow (CBF), electroencephalography (EEG) and blood oxygenation level-dependent (BOLD) responses. In order to accomplish this, two previous models are coupled: a metabolic/hemodynamic model (MHM) for a voxel, linking BOLD signals and neuronal activity, and a neural mass model describing the neuronal dynamics within a voxel and its interactions with voxels of the same area (short-range interactions) and other areas (long-range interactions). For coupling both models, we take as the input to the BOLD model, the number of active synapses within the voxel, that is, the average number of synapses that will receive an action potential within the time unit. This is obtained by considering the action potentials transmitted between neuronal populations within the voxel, as well as those arriving from other voxels. Simulations are carried out for testing the integrated model. Results show that realistic evoked potentials (EP) at electrodes on the scalp surface and the corresponding BOLD signals for each voxel are produced by the model. In another simulation, the alpha rhythm was reproduced and reasonable similarities with experimental data were obtained when calculating correlations between BOLD signals and the alpha power curve. The origin of negative BOLD responses and the characteristics of EEG, PET and BOLD signals in Alzheimer's disease were also studied.

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          Journal
          17919931
          10.1016/j.neuroimage.2007.08.001

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