{'fraction_non_alphanumeric': 0.007204610951008645, 'fraction_numerical': 0.0, 'mean_word_length': 5.435185185185185, '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}}
Literature review of fMRI image processing techniques

Functional Magnetic Resonance imaging is an aid in identifying the brain activated regions by certain stimuli and tasks. It can be used to identify the psychological or other disease states resulting from various neurological impairments and also to make implication on brain connectivity. Several techniques are used for the functional analysis of fMRI neuroimaging data. Here our endeavor is to make a review of various computational methodologies used by fMRI data analysis, which includes various preprocessing methods used for removing noise and enhancing quality in fMRI as well as various statistical methods of fMRI image analysis.