Human electrophysiology and smoking

Abstract

Self-reported motives for smoking include stress reduction and improved concentration. While these self-reports are reliable, they are also rather subjective. We have utilized the electroencephalogram (EEG) to investigate further why people may smoke. EEG is a relatively non-invasive measure of the electrical activity of the brain and can be used in many different ways to answer questions about the change in brain activity after smoking. Three different techniques of analyzing EEG data (frequency band analysis, event-related potentials (ERPs) and measures derived from nonlinear dynamics) each shed light on different aspects of the effects of smoking on brain activity. In resting subjects, smoking produces a pattern of changes in different frequency bands after smoking indicative of cortical activation. In cases where the subject is already alert (such as during a higher-workload mental task) changes appear to be more restricted to a high frequency band that has been associated with anxiolitic effects of benzodiazepines. However, evidence linking self-reports of stress reduction to this change in EEG frequency remains weak. ERPs allow a more fine grained analysis of brain activity following a particular stimulus. In particular, one specific component of the ERP can be used to indicate the relative speed of the perceptual processing of stimuli. After smoking it has been found that faster perceptual processing occurs for visual stimuli but not for auditory stimuli. This may indicate that the reports of better concentration may result from enhanced visual processing after smoking. Nonlinear dynamics provide numerical methods for estimation of the dimensional complexity (DCx) of the EEG. In our findings, there has been a negative correlation between presmoking DCx and the change in DCx produced by smoking. EEG activity may be more optimal for stimulus processing after smoking than before smoking. Drug Dev. Res. 38:299–304. © 1996 Wiley-Liss, Inc.