Thirty university students (15 females) performed tasks from the NASA Multiattribute Task Battery, which was used to manipulate the attentional processing resource demands of the tasks. Separate groups performed visual or auditory monitoring tasks singly and in combination with visual-manual tracking while heart period, respiratory sinus arrhythmia (RSA), and pre-ejection period (PEP) were recorded to determine the modes of cardiac control during task performance. The tracking single-task suppressed RSA and was interpreted as eliciting an uncoupled parasympathetic inhibition mode of cardiac control because of its demand upon perceptual and manual processing resources. The monitoring task both suppressed RSA and shortened PEP and was interpreted as eliciting a reciprocally-coupled sympathetic activation and parasympathetic inhibition mode of cardiac control because of its demand for perceptual/central processing resources. Dividing attention elicited uncoupled parasympathetic inhibition that was greater for the visual monitoring and tracking dual-task than for the auditory monitoring and tracking dual-task, which we interpreted as indicating a greater sharing of perceptual/spatial and manual processing resources for these tasks. Practice lengthened PEP in the dual-tasks and was interpreted as eliciting uncoupled sympathetic inhibition that was indicative of improved central processing resource efficiency. The results are evaluated in terms of how knowledge of cardiac control modes may be used to assess mental workload in applications such as adaptive automation.Key words: divided attention, heart period, respiratory sinus arrhythmia, pre-ejection periodMental workload is a construct that is central to the application of attention theory to the problem of optimizing the interaction between people and their tasks. Mental workload has been described by Gopher and Donchin (1986) as the extent to which a person's information processing abilities are actively engaged by tasks that they are motivated to perform. Optimizing the person/task interaction means more than minimizing mental workload for the duration of a task. Ideally, optimization implies that mental workload be dynamically adjusted so that a person is neither over nor under loaded while performing the task. Achieving this ideal person/task interaction will require a system that can allocate functions between the person and other (typically automated) task components, an approach that is integral to applications such as adaptive aiding, adaptive