{'fraction_non_alphanumeric': 0.018285714285714287, 'fraction_numerical': 0.0, 'mean_word_length': 5.394160583941606, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A True Spatio-Temporal Test Statistic for Activation Detection in FMRI by Parametric Cepstrum

A main purpose of data analysis in functional magnetic resonance imaging (fMRI) is to determine which regions of the brain are activated by pre-specified temporal stimuli. In recent work, under the assumption of known spectra, we developed a detection statistic based on a spatially and temporally correlated noise model. In this paper, we implement the developed test statistic, which includes spatial and temporal whitening operators. For the estimation of spatial and temporal correlations, we use the parametric cepstral modeling, which allows dramatic reduction of computation in the model fitting and very simple methods to obtain spatiotemporal whitening operators. Model comparison and selection are discussed as well. We apply the developed techniques to a human dataset.