Application of Mathematical Modelling as a Tool to Analyze the EEG Signals in Rat Model of Focal Cerebral Ischemia

Abstract

The present paper envisages the application of mathematical modelling with the autoregressive (AR) model method as a tool to analyze electroencephalogram data in rat subjects of transient focal cerebral ischemia. This modelling method was used to determine the frequencies and characteristic changes in brain waveforms which occur as a result of disorders or fluctuating physiological states. This method of analysis was utilized to ensure actual correlation of the different mathematical paradigms. The EEG data was obtained from different regions of the rat brain and was modelled by AR method in a MATLAB platform. AR modelling was utilized to study the long-term functional outcomes of a stroke and also is preferable for EEG signal analysis because the signals consist of discrete frequency intervals. Modern spectral analysis, namely AR spectrum analysis, was used to correlate the conditional and prevalent changes in brain function in response to a stroke. © 2014, The Institution of Engineers (India).