Because of the importance of oxidative energetics for cerebral function, extraction of oxygen consumption (CMR_O2) from blood oxygenation level‐dependent (BOLD) signal using multi‐modal measurements of blood flow (CBF) and volume (CBV) has become an accepted functional magnetic resonance imaging (fMRI) technique. This approach, termed calibrated fMRI, is based on a biophysical model which describes tissue oxygen extraction at steady‐state. A problem encountered for calculating dynamic CMR_O2 relates to concerns whether the conventional BOLD model can be applied transiently. In particular, it is unclear whether calculation of CMR_O2 differs between short and long stimuli. Linearity was experimentally demonstrated between BOLD‐related components and neural activity, thereby making it possible to use calibrated fMRI in a dynamic manner. We used multi‐modal fMRI and electrophysiology, in α‐chloralose anesthetized rats during forepaw stimulation to show that respective transfer functions (of BOLD, CBV, CBF) generated by deconvolution with neural activity are time invariant, for events in the millisecond to minute range. These results allowed extraction of a significant component of the BOLD signal that can be ascribed to CMR_O2 transients. We discuss the importance of minimizing residual signal, represented by the difference between modeled and raw signals, in convolution analysis of multi‐modal signals.