I have two physiological signals (discharge rate of a neuron and electrical voltage [EMG] of a muscle). I'd like to determine the cross-correlation between the two signals as a function of time (i.e. if a "relationship" between the two signals exists, how does this "relationship" change over time). I've managed to do this using a MATLAB function called 'cra.m'. It first uses an AR model to "whiten" both signals (in case, one or both signals has some inherent periodicity) and then cross-correlates them to get an 'impulse response function'. So that gives me the relationship as a function of the time lag between the signals. I also break the signal up into smaller sliding windows to see the change in this curve as a function of time. I can figure out for one window what the value of a significant correlation is. However, I'm not sure how to determine significance over the multiple windows. If I have say 100 windows (each 40 bins) should I just say use some sort of Bonferonni correction (i.e. the p for 40 bins / 100)? Thanks. -Tony =========================================================================== This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===========================================================================
