Python rf toolbox7/5/2023 ![]() ![]() Third is a scaler which represents the sample rate of the contrast signalĪnd EEG data (128 Hz). Of a normalised sequence of numbers that indicate the contrast of aĬheckerboard that was presented during the EEG at a rate of 60 Hz. When using mtrf_multicrossval, the trials in each of the three sensoryĬonditions should correspond to the stimuli in STIM.When using mtrf_crossval, the trials do not have to be the same length,īut using trials of the same length will optimise performance.When using mtrf_predict, always enter the model in its originalģ-dimensional form, i.e., do not remove any singleton dimensions.This is the same for both forward and backward mapping - theĬode will automatically reverse the lags for backward mapping. Lags for post-stimulus mapping and negative lags for pre-stimulus Enter the start and finish time lags in milliseconds.Stabalise regularisation across trials and enable a smaller parameter Normalise all data, e.g., between or or z-score.To reduce running time, e.g., 128 Hz or 64 Hz. Downsample the data when conducting large-scale multivariate analyses.Ensure that the stimulus and response data have the same sample rate.See examples/examples.ipynb for more detailed use of the different functions. simulate_test_data.py: Used to simulate test cases for precision tests (Python and MATLAB instances of the Toolbox).mtrf_test_set.m: Legacy, used to validate pymtrf against mTRF Toolbox. ![]()
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