{'fraction_non_alphanumeric': 0.025059665871121718, 'fraction_numerical': 0.003579952267303103, 'mean_word_length': 5.124087591240876, '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}}
Performance of a Leaky-Integrate-and-Fire Model vis-a-vis Measured Response of Diseased Neurons

Information processing in the brain is still not fully understood, and in-depth theoretical and experimental studies are required in this field. An approximate but low-complexity mathematical model on membrane potential [1] is used as a potential candidate to assess model parameters from selected measured data sets available from Allen Institute of Brain Science [2]. Four different cells having epilepsy and tumor have been considered for validating the leaky-integrate- and fire model of [1]. Values of three model parameters and their statistical features are presented in detail. Closer estimates of the model parameters will help in tuning the model and thus generating spike trains closer to what are generated by biological neurons.