Coherence estimation of the hippocampal EEG through fast multichannel orthogonal projection

Hippocampal EEGs at subfields CA1 and the dentate gyrus (DG) are modeled as stationary, multi-channel autoregressive (MAR) process. This work discusses the development of a new MAR modeling algorithm that can efficiently compute MAR coefficient matrices through progressive multichannel orthogonal projection. The resultant MAR coefficients are least square (LS) optimal and utilized to compute the power spectra and the coherence function of hippocampal EEG at CA1 and DG during REM sleep for animals of 15 and 90 days of age. The results show that the new method is easy to implement and provides consistent and smooth spectral and coherence estimates for hippocampal EEG epochs with varying data length.