Spatio-temporal identification of hemodynamics in fMRI: A data-driven approach

This paper presents a new data-driven method to identify the spatial and temporal characteristics of the cerebral hemodynamics in functional magnetic resonance imaging (fMRI). The experiments are in block design paradigm and the scans in task blocks are investigated in a sequential manner. Spatial evolvement of the activated regions along with the time-course are demonstrated. The time series of each region is predicated as the convolution of the stimuli with the hemodynamic response function (HRF) formulated as the sum of two gamma, functions. The predicted time series is fitted to the actual one by using a nonlinear least-squares procedure to estimate the HRF parameters. Analyses on empirical fMRI datasets exhibit obviously the spatial and temporal dispersion of hemodynamics