Psychophysiology has a long tradition within human factors (Boucsein & Backs, 2000) and has especially contributed to the present understanding of mental workload (Gaillard & Kramer, 2000). Mental workload is often considered to reflect the costs associated with a person's expenditure of limited-capacity information-processing resources to keep task performance within specification and thus is a function of both the person's abilities and the task demands on his or her abilities (Gopher & Donchin, 1986). Many methods of assessing mental work-load have been proposed, each with its own advantages and disadvantages (O'Donnell & Eggemeier, 1986; Tsang & Wilson, 1997). Psychophysiological methods have been used to assess mental workload in domains such as aviation because measurement of responses such as heart rate usually does not interfere with task performance and because psychophysiological responses are sometimes more sensitive to task demands than are performance measures (Kramer & Weber, 2000). The present study examined whether a new approach to the analysis and interpretation of cardiac psychophysiological responses that has been useful for assessing mental workload in the aviation domain is also useful for simulated driving.
By far, the most popular cardiac response used by the human factors community is heart rate (Wilson & Eggemeier, 1991). The heart is dually innervated by the sympathetic and parasympathetic branches of the autonomic nervous system (ANS), and these two branches have opposing effects on heart rate: sympathetic activation increases heart rate, whereas parasympathetic activation decreases heart rate. In the classic model of ANS function (e.g., Cannon, 1959), sympathetic and parasympathetic activity are reciprocally coupled--that is, sympathetic activation occurs concomitantly with parasympathetic inhibition and vice versa. According to the classic model, heart rate change in response to varying task demands would always be the result of some unknown combination of reciprocal change in both autonomic branches.
However, Backs (1995) reviewed studies from the aviation domain that used heart rate as an index of pilot mental workload and found many instances in which heart rate did not change in a manner consistent with the classic ANS model. He suggested that a newer model of ANS function proposed by Berntson, Cacioppo, and Quigley (1991, 1995) could better account for the observed heart rate results. The Berntson et al. model of autonomic space subsumes the classic model of ANS function and instead proposes multiple "modes of autonomic control" (1991, p. 459)." The modes of autonomic control can be represented as a two-dimensional "autonomic space" (see Figure 1), which can be illustrated by axes plotting parasympathetic activity on the ordinate and sympathetic activity on the abscissa. Vectors on the positive diagonal represent the classic coupled reciprocal modes of autonomic control (sympathetic activation with parasympathetic inhibition, or the reverse). Vectors on the negative diagonal represent coupled nonreciprocal modes of control (coactivation and coinhibition), in which the sympathetic and parasympathetic branches increase or decrease together. Vectors parallel to one axis represent uncoupled modes of control, in which activity in one branch changes but activity in the other branch does not. Table 1 presents the autonomic control mode taxonomy and the effects of change along each mode of autonomic control on heart rate.
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Backs (1995) described two important limitations in using heart rate to make inferences about mental workload, which are evident in Table 1. Both limitations exist because heart rate alone is uninformative about the psychological-physiological mapping responsible for the response. The first is that sensitivity can be limited because heart rate may not change with varying task demands, even though sympathetic and parasympathetic activity may change greatly. …