Abstract: Embodiments provide thought classifier devices that convert analog electroencephalogram signals obtained from mental activity of a person to a digital signal bitstream data; identify a portion of the bitstream as a thought chunk representing discrete thought activity in response to matching, via a first artificial neural network comparison, digital signal bitstream thought chunk portion metadata to metadata labeled in association with a thought within a thoughts data set, the first artificial neural network trained on the thoughts data set; identify a user category in response to matching, via a different, second artificial neural network comparison, metadata of the thought chunk portion to labeled metadata within the thoughts data set, the second artificial neural network trained on the thoughts data set; and identify a specific thought of the thoughts data that has metadata that has corresponding metadata.