Functional magnetic resonance imaging in real time (FIRE): Sliding-window correlation analysis and reference-vector optimization

New algorithms for correlation analysis are presented that allow the mappin g of brain activity from functional MRI (fMRI) data in real time during the ongoing scan. They combine the computation of the correlation coefficients between measured fMRI time-series data and a reference vector with "detren ding," a technique for the suppression of non-stimulus-related signal compo nents, and the "sliding-window technique." Using this technique, which limi ts the correlation computation to the last N measurement time points, the s ensitivity to changes in brain activity is maintained throughout the whole experiment. For increased sensitivity in activation detection a fast and ro bust optimization of the reference vector is proposed, which takes into acc ount a realistic model of the hemodynamic response function to adapt the pa rameterized reference vector to the measured data. Based on the described c orrelation method, real-time fMRI experiments using visual stimulation para digms have been performed successfully on a clinical MR scanner, which was linked to an external workstation for image analysis. (C) 2000 Wiley-Liss, Inc.