Many neurophysiological mechanisms are governed by neurotransmitter activity. Yet, current analysis methods focus on measuring either electrical signals from neurons or specific neurotransmitters. A major shortcoming of such approaches is the lack of a comprehensive dataset that enables us to infer mechanisms that impact neuropathologies. In this paper, we investigate the transduction of neurotransmitter profiles to complex electronic signals and the subsequent differentiation of these signals using an 'intelligent' array of multiple electrodes to characterize neurophysiological information. The electrodes are coated with bioelectronic films (such as biopolymer chitosan) that differently react with the neurotransmitters, generating complex electrochemical signatures that are analyzed using machine learning algorithms. We show the use of the film-modified multi-electrode arrays to rapidly probe neurotransmitters in biofluids without pretreatment steps (in situ) in two modes of detection: (1) direct detection of neurotransmitter dopamine despite the masking signals generated by the interfering species uric acid, and (2) simultaneous detection of dopamine and norepinephrine using the film-modified 'intelligent' multi-electrode array. The presented work will have a major impact on neurobiology by providing a neurophysiological information, that is not yet available, and will shed light on the underlying neurological mechanisms that are hallmarks of dysfunction in the nervous system.