TOPOGRAPHY OF ALPHA-OSCILLATORY AND THETA-OSCILLATORY RESPONSES UPON AUDITORY AND VISUAL-STIMULI IN HUMANS

Brain resonance phenomena and induced rhythms in the brain recently gained importance in electroencephalographic, magnetoencephalographic and cellular studies (Basar and Bullock 1992). It was hypothesized that evoked potentials are superpositions of induced rhythms caused by resonance phenomena in neural populations (Basar et al. 1992). According to Basar (1972), such resonance phenomena are reflected in the main peaks of the amplitude frequency characteristics computed from EEG responses. The present study is based on a frequency domain approach for the evaluation of topography- and modality-dependent properties of oscillatory brain responses. EEG and evoked potentials were recorded from vertex, parietal and occipital scalp locations in 24 volunteers. Two combined methods were applied: (1) amplitude frequency characteristics were computed from the transient evoked responses, and (2) frequency components of the transient responses were obtained by adaptive digital filtering. Our main goal was to investigate theta (4-7 Hz) and alpha (8-15 Hz) response components. (1) Amplitude frequency characteristics. Auditory stimuli elicited theta-alpha compound responses in the 4-11 Hz frequency band (e.g. typical peaking frequency around 7 Hz for vertex recordings). Visual stimuli elicited alpha responses (e.g. typical peaking frequency for vertex recordings around 9-12 Hz). Frequency maxima for visual stimuli thus had main peaks at higher frequency values than frequency maxima for auditory stimuli. (2) Digital filtering confirmed these results: for vertex recordings, theta vs. alpha response amplitudes were 9 mu V vs 6 mu V for auditory stimuli and 5 mu V vs 5 mu V for visual stimuli, thus confirming a shift towards higher frequencies, i.e. a more prominent contribution of the alpha range, in the case of visual stimulation. We hypothesize that these properties might reflect site- and modality-specific features of stimulus encoding in the brain in which resonance properties of neuron populations are involved. Furthermore we emphasize the utility of the systems theory approach for a better understanding of brain function by means of EPs.