Microcomputers in social psychophysiological research: An overview

Abstract

Microcomputer systems have become commonplace in the psychophysiological laboratory during the past 5 years and are currently used in all phases of data acquisition, experimental control, and data analysis. In the past year, however, advances in microprocessor technology and scientific software have greatly extended the capabilities ofthese desk-top systems. Small laboratories now can afford an integrated laboratory microcomputer system and both the high-fidelity data acquisition hardware and the sophisticated analysis capabilities traditionally found in large minicomputers. We briefly describe the demands that social psychophysiological research can place on computer systems, the system presently employed in our laboratory, and a system being installed to overcome limitations on sampling rate, sampling periods, and waveform analysis.Research and theory in social psychology have been based in large part On self-report data to assess the efficacy of the experimental manipulations, the effects of these manipulations On verbal and overt behavior, and the occurrence of postulated intervening processes. In part to avoid the limitations inherent in relying on verbal measures, there has been a growing interest among social psychologists in the potential of chronometric and noninvasive psychophysiological measures to test and refine theories of social interaction and behavior. The purpose of this paper is to briefly review the tasks typically faced in social psychophysiological research and the advances in microcomputers as they relate to observing, measuring, and quantifying social phenomena; to outline the advantages and limitations of employing inexpensive personal computers in this area of research; and to indicate the general issues involved in selecting a microcomputer system with which to automate laboratory functions. 1 GENERAL ISSUESBridging the gap between social psychological concepts (e.g., arousal, interpersonal attraction, and emotion) and the physiological activity subserving social behavior typically requires the collection of multiple response measures in the context of multifactor experimental designs. One reason for this is that physiological systems are responsive to a wide variety of stimuli. For example, a given level of electrodermal activity (EDA) could result from the presentation of a loud noise, a deep breath, emotional imagery, or a run up a flight of stairs. In addition, the mapping from theoretically derived psychological processes into particular bodily responses often involves

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