Cross-correlation technique to identify activated pixels in a three-condition fMRI task

Most fMRI studies are conducted with a stimulus “on” and a stimulus “off” or control state to delineate pixels activated during a two-condition presentation. We have developed a multiple reference function based novel cross-correlation technique that is not restricted to two conditions but could be applied to delineate pixels activated in multi-condition tasks. A logic-based analysis to form functional images, where each pixel is uniquely assigned to an image based on which reference function produced the highest correlation-coefficient for that pixel, has also been developed. Both steady-state and event-related fMRI studies have been conducted. Using steady-state motor stimulation as an example with right and left hand movements representing conditions 1 and 2, and no movement representing condition 3, results of images generated through a three-condition processing technique are in good agreement with those generated through two separate two-condition experiments. Similarly, the results of right and left finger flexions in a multi-condition event-related study show that the logic based correlation coefficient approach provides unique information about the activation characteristics of individual pixels