Hemodynamic-based neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) sense hemoglobin concentration in cerebral tissue. The local concentration of hemoglobin, which is differentiated into oxy- and deoxy-hemoglobin by NIRS, features spontaneous oscillations over time scales of 10-100 s in response to a number of local and systemic physiological processes. If one of such processes becomes the dominant source of cerebral hemodynamics, there is a high coherence between this process and the associated hemodynamics. In this work, we report a method to identify such conditions of coherent hemodynamics, which may be exploited to study and quantify microvasculature and microcirculation properties. We discuss how a critical value of significant coherence may depend on the specific data collection scheme (for example, the total acquisition time) and the nature of the hemodynamic data (in particular, oxy- and deoxy-hemoglobin concentrations measured with NIRS show an intrinsic level of correlation that must be taken into account). A frequency-resolved study of coherent hemodynamics is the basis for the new technique of coherent hemodynamics spectroscopy (CHS), which aims to provide measures of cerebral blood flow and cerebral autoregulation. While these concepts apply in principle to both fMRI and NIRS data, in this article we focus on NIRS data.