{'fraction_non_alphanumeric': 0.026519337016574586, 'fraction_numerical': 0.0022099447513812156, 'mean_word_length': 5.661764705882353, '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}}
Fractal analysis of spontaneous fluctuations of the BOLD signal in the human brain networks

To investigate what extent brain regions are continuously interacting during resting‐state, independent component analyses (ICA) was applied to analyze resting‐state functional MRI (RS‐fMRI) data. According to the analyzed results, it was surprisingly found that low frequency fluctuations (LFFs), which belong to the 1/f signal (a signal with power spectrum whose power spectral density is inversely proportional to the frequency), have been classified into groups using ICA; furthermore, the spatial distributions of these groups within the brain were found to resemble the spatial distributions of different networks, which manifests that the signal characteristics of RS LFFs are distinct across networks. In our work, we applied the 1/f model in the fractal analyses to further investigate this distinction.