Cortical activation, signal-to-noise ratio and stochastic resonance duringinformation processing in man

Objectives: The goal of this study was to determine the relation between EE G, event-related potentials and information processing as measured by an ac oustical choice reaction time task. In particular, we wanted to find out to what extent reaction-time performance is related to the pre-stimulus EEG a ctivity (frequency domain) and the magnitude of signal power as well as noi se power (stimulus-uncorrelated activity) after the tones (time domain). Materials and methods: For parametrization, EEG-activity was factorized acr oss pre-defined frequency bands and 19 electrode positions, applying spectr al power and coherence analysis. Signal power was estimated by calculating the mean power of the evoked single sweeps. Noise power was computed by sub tracting the latter minus the power of the average evoked potential. We inv estigated 254 healthy subjects who had to perform an acoustical choice reac tion task during running EEG. Results: In the frequency domain, it was found that high frontally pronounc ed delta-power in the pre-stimulus EEG correlates with fast reaction-time p erformance, which was regarded as the expression of a readiness potential i n the frequency domain, reflecting increased cortical activation. In the ti me domain, fast reaction times were found to be correlated with the amplitu de of the event-related potential N100 as well as with the signal power and signal-to-noise ratio of the evoked activity. This result pointed to the f requently described relation between evoked signals and information process ing. In accordance with the theory of stochastic resonance, we also found a positive correlation between the magnitude of noise power after the stimul us and reaction-time performance. Besides, noise power was found to be posi tively correlated with pre-stimulus cortical activation (mainly in the delt a and alphal frequency band), whereas no relation was found between pre-sti mulus EEG and the signal power of the event-related activity, except for a weak relation to the alpha2 power. Conclusion: Our findings support the notion that information processing is not only dependent on signal strength but also on a certain amount of basic noise, reflecting the overall energy state of the brain. (C) 1999 Elsevier Science Ireland Ltd. All rights reserved.