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Currently the HRF convolution is applied to the full design matrix that spans all subjects and runs. This means there could theoretically be some bleeding over across different runs and subjects. In practice this is unlikely to matter much given the designs we've been working with, but it needs to be addressed. Recommended approach is to refactor the modeling code so that all design matrix specification and convolution is done on a run-by-run basis, and then processed runs are concatenated into the full dataset just prior to sampling. This will also have the added benefit of making it easier to handle different numbers of volumes/events in each scanning run.
The text was updated successfully, but these errors were encountered:
Currently the HRF convolution is applied to the full design matrix that spans all subjects and runs. This means there could theoretically be some bleeding over across different runs and subjects. In practice this is unlikely to matter much given the designs we've been working with, but it needs to be addressed. Recommended approach is to refactor the modeling code so that all design matrix specification and convolution is done on a run-by-run basis, and then processed runs are concatenated into the full dataset just prior to sampling. This will also have the added benefit of making it easier to handle different numbers of volumes/events in each scanning run.
The text was updated successfully, but these errors were encountered: