Plots ERDS maps based on either FFTs or wavelets. This function calculates time-frequency maps (ERDS maps) using either wavelets or FFT analysis. The result is stored in the output variable, which can be used by other functions to plot the map, for example. Usage: erds = erdsmap(X, frames, tlimits, Fs); Input parameters: X ... Single channel data vector <1 x frames*ntrials> frames ... Frames per trial tlimits ... Epoch time limits (ms) [mintime maxtime] Fs ... Sampling rate (Hz) cycles ... =0: Use FFTs (with constant window length) >0: Number of cycles in each analysis wavelet Optional input parameters: 'detret' ... Detrend data in time ['on'|'off'] 'detrep' ... Detrend data across trials ['on'|'off'] 'winsize' ... If cycles = 0: Data subwindow length If cycles > 0: Longest window length to use, determines the lowest output frequency {frames/8} 'timesout' ... Number of output times {200} 'padratio' ... FFT length/winframes (2^k) {2} Multiplies the number of output frequencies by dividing their spacing; when cycles = 0, frequency spacing is (low_freq/padratio) 'maxfreq' ... Maximum frequency (Hz) to plot {40} 'baseline' ... Spectral baseline window center end-time (in ms) {0} 'powbase' ... Baseline power spectrum to normalize the data. 'alpha' ... If non-zero, compute bootstrap significance level {0.05} 'naccu' ... Number of bootstrap replications to accumulate {200} Output parameter: erds ... Structure containing information about the ERDS map

- dftfilt dftfilt() - discrete Fourier filter

- calcErdsMap Calculates time-frequency (ERDS) maps.

Generated on Sat 16-May-2009 00:04:49 by