Spatiotemporal analysis of prepyriform, visual, auditory, and somesthetic surface EEGs in trained rabbits

1. Spatial ensemble averages were computed for 64 traces of electroencephalograms (EEGs) simultaneously recorded from 8 x 8 arrays over the epidural surfaces of the prepyriform cortex (PPC) and visual, somatic, and auditory cortices. They revealed a common waveform across each array. Examination of the spatial amplitude modulation (AM) of the waveform revealed classifiable spatial pattern in short time segments. The AM patterns varied within trials after presentation of identical conditioned stimuli, and also between trials with differing stimuli. 2. PPC EEGs revealed strong correlates with the respiratory rhythm; neocortical EEGs did not. 3. Time ensemble averaging of the PPC EEG attenuated the oscillatory bursts, indicating that olfactory gamma oscillations (20-80 Hz) were not phase-locked to the times of stimulus delivery but instead to inhalations. Time ensemble averages of neocortical recordings across trials revealed average evoked potentials starting 30-50 ms after the arrival of the stimulus. 4. Average temporal fast Fourier transform (FFT) power spectral densities (PSDs) from pre- and poststimulus PPC EEG segments revealed a peak of gamma activity in olfactory bursts. 5. The logarithm of the average temporal FFT PSDs from pre- and poststimulus neocortical EEG segments, when plotted against log frequency, revealed 1/f-type spectra in both pre- and poststimulus segments for negative/aversive conditioned stimuli (CS-) and positive/rewarding conditioned stimuli (CS+). The alpha'- and beta'-coefficients from the regression of Eq. 2 onto the average PSDs were significantly different between pre- and poststimulus segments, owing to the evoked potentials, but not between CS- and CS+ stimulus segments. 6. Spatiotemporal patterns were invariant over all frequency bins in the 1/f domain (20-100 Hz). Spatiotemporal patterns in the 2- to 20-Hz domain progressively differed from the invariant patterns with decreasing frequency. 7. In the spatial frequency domain, the logarithm of the average spatial FFT power spectra from pre- and poststimulus neocortical EEG segments, when plotted against the log spatial frequency, fell monotonically from the maximum at the lowest spatial frequency, downwardly curving to a linear 1/f spectral domain. This curve in the 1/f spectral domain extended from 0.133 to 0.880 cycles/mm in the PPC and from 0.095 to 0.624 cycles/mm in the neocortices. 8. Methods of FFT and principal component analysis (PCA) EEG decomposition were used to extract the broad-spectrum waveform common to all 64 EEGs from an array. AM patterns for the FFT and PCA components were derived by regression. They were shown by cross-correlation to yield spatial patterns that were equivalent to each other and to AM patterns from calculation of the 64 root-mean-square amplitudes of the segments. 9. Each spatial AM pattern was expressed by a 1 x 64 column vector and a point in 64-space. Similar patterns formed clusters, and dissimilar patterns gave multiple clusters. A statistical test was devised to evaluate dissimilarity by a Euclidean distance metric in 64-space. 10. Significant spatial pattern classification of CS- versus CS+ trials (below the 1% confidence limit for 20 of each) was found in discrete temporal segments of poststimulus data after digital temporal and spatial filter optimization. 11. Varying the analysis window duration from 10 to 500 ms yielded a window length of 120 ms as optimal for pattern classification. A 120-ms window was subsequently stepped across each record in overlapping intervals of 20 ms. Windows in which episodic, significant CS+/CS- differences occurred lasted 50-200 ms and were separated by 100-200 ms in the poststimulus period. 12. Neocortical spatial patterns changed under reinforcement contingency reversal, showing a lack of invariance in respect to stimuli and a dependence on context and learning, as previously found for the olfactory bulb and PPC.