Computational reconstruction of fMRI-BOLD from neural activity

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In this paper, we model function magnetic resonance imaging signals generated by neural activity (fMRI). fMRI measures changes in metabolic oxygen in blood in brain circuits based on changes in biophysical factors like concentration of total cerebral blood flow, oxy-hemoglobin and deoxy-hemoglobin content. A modified version of the Windkessel model by incorporating compliance has been used with a balloon model to generate cerebellar granular layer and visual cortex blood oxygen-level dependent (BOLD) responses. Spike raster patterns were adapted from a biophysical granular layer model as input. The model fits volume changes in blood flow to predict the BOLD responses in the cerebellum granular layer and in visual cortex. As a comparison, we tested the balloon model and the modified Windkessel model with the mathematically reconstructed BOLD response under the same input condition. Delayed compliance contributed to BOLD signal and reconstructed signals were compared to experimental measurements indicating the usability of the approach. The current study allows to correlate dynamic changes of flow and oxygenation during brain activation which connects single neuron and network activity to clinical measurements.