We introduce a new method for detecting differences in the latency of blood oxygenation level-dependent (BOLD) responses to brief events within the context of the General Linear Model. Using a first-order Taylor approximation in terms of the temporal derivative of a canonical hemodynamic response function, statistical parametric maps of differential latencies were estimated via the ratio of derivative to canonical parameter estimates. This method was applied to two example datasets: comparison of words versus nonwords in a lexical decision task and initial versus repeated presentations of faces in a fame-judgment task. Tests across subjects revealed both magnitude and latency differences within several brain regions. This approach offers a computationally efficient means of detecting BOLD latency differences over the whole brain. Precise characterization of the hemodynamic latency and its interpretation in terms of underlying neural differences remain problematic, however.