Normal brain function is critically dependent on a continuous supply of blood flow so that even a few seconds of disrupted blood flow can hinder brain function. Our body has employed tight regulatory mechanisms to maintain cerebral blood flow and avoid hyperemia or ischemia. One of the primary mechanisms in which the neurons communicate with the cerebral blood vessels to increase local blood flow to the region in need is termed as neurovascular coupling. Disordered neurovascular coupling has been observed in several brain pathologies such as hypertension, stroke and Alzheimer’s disease. It is likely that the disruption of the interactions between neurons and the cerebral vasculature contributes to the initiation and progression of brain dysfunction. Hence understanding this coupling mechanism is of vital importance. Experimental exploration suggests that there are more than one factor controlling the vessel dilation during neural activation. Based on the observation that there are different vasoactive ions in different brain regions of the brain, researchers suggested that neurovascular coupling is brain region dependent. Another recent experiment illustrated that it is not just brain region dependent but also specific to the functions in a certain region of the brain as the same region can be connected to many other regions. This suggests that neurovascular coupling has to be explored based on the function that induces the vascular response. We have not yet arrived at a quantitative relationship of the cellular structures controlling neurovascular coupling primarily due to the complexity of the parameters involved and the difficulty of measuring them in the highly heterogeneous brain. Hence, developing mathematical models simultaneously based on experimental data which can be validated with repetitive experiments may help establish a quantitative relationship of the neurovascular coupling mechanism. To test the model built based on a hypothesis , the model must also be related to well established and accessible experimental technique. fMRI BOLD technique is one of the widely available non invasive experimental technique used to map the active regions in the brain. Even though it is used to study the functions of the brain, the method employed primarily utilizes the neurovascular response. So modelling the fMRI BOLD response based on the neurovascular reponse will enable to simulate an output that can be compared with the experimental data. The aim of this study is to model a certain hypothesis of neurovascular coupling based on experimental data and use it to model the fMRI BOLD response and compare it to experimental data. A mathematical model was created based on different existing models to simulate the experimentally well supported K+ signalling mechanism of neurovascular coupling and its associated fMRI BOLD response. Our model predicts the variations of the BOLD response such as initial dip, positive and negative BOLD signals, post stimulus undershoot arising due to the neurovascular and neurometabolic responses. These responses were simulated for different kinds of neural activities such as continuous spiking, bursting and cortical spreading depression. We compared the simulated BOLD response to experimental BOLD signals observed in the hippocampus and cortex under different conditions and it showed reasonably good agreement. While the results of the model suggests that potassium ions released during neural activity could act as the main mediator in neurovascular coupling, along with cytosolic calcium in the smooth muscle cell it certainly does not rule out the possibility of other mechanisms that can coexist and increase blood flow, such as the nitric oxide signalling mechanism or the archidonic acid to EET pathway. The discrepancy in the comparison between simulated and experimental data from the cortex indicates coexistence of other vasoactive factors. This approach of combined quantitative modelling of neurovascular coupling response and its BOLD response will enable more specific assessment of a brain region and could possibly enhance the understanding of the mechanism.