The quantification of brain activity has been one of the main goals of neuroimaging since the earliest applications. In functional magnetic resonance imaging (fMRI) such an aim has been pursued indirectly by studying changes of the blood oxygenation dependent signal triggered by alterations in blood flow following changes in energy metabolism. Such approach is limited because of the complex relationship between the vascular and neural systems in brain tissue. Therefore methods have been proposed to assess oxygen metabolism, which directly underlies energy supply to brain tissue and therefore brain activity. Investigating existing and novel MRI methods, the thesis aims to improve the assessment of oxygen metabolism for a fully quantitative measurement of this biomarker. A simulation study has been carried out to optimise one of the mathematical (fMRI calibration) models used to relate the measured signal to the underlying physiology. As a result we are able to define a new model, less complex and more accurate for estimation of oxygen extraction fraction. Following this, an estimation approach recently developed in our centre is applied to carbon dioxide and oxygen calibrated fMRI data in an experimental setting firstly for a repeatability study and then for a drug study looking at the acute effects of caffeine on brain metabolism and haemodynamics. The precision of the novel approach shows values consistent with previous methods, but with much higher spatial resolution. Exploiting this, acute caffeine effects are characterized with a voxel-wise level of detail, showing results consistent with literature electrophysiological findings. Finally, an innovative method for estimating oxygen extraction fraction, based on velocity spectral imaging and estimation of transverse relaxation time, is introduced and tested at a proof-of-concept level. The performance and limits are examined through simulation and experimentation, suggesting that it might be a viable alternative to the calibration techniques previously introduced.