Baseline Features Extraction from Microelectrode Array Recordings in an in vitro model of Acute Seizures using Digital Signal Processing for Electronic Implementation

Microelectrode arrays (MEA) arise as a promising technology enabling detection of local field potentials from multiple locations and permitting the acquisition of more information on brain network electrical activity than conventional electrophysiology techniques. However, whereas most of the electrophysiological studies addressing brain activity have focused on events/patterns analysis, no one has so far addressed the features that might be hidden within the signal baseline. In this paper, I performed an analysis of the Microelectrode Array Signal to study all the features and frequency content of this signal.