Cognitive Workload and the Motor Component of Visual Attention

Cognitive Workload and the Motor Component of Visual Attention Jason Ralph, Wayne D. Gray, & Michael J. Schoelles Rensselaer Polytechnic Institute Abstract Outside the laboratory, the ability to control visual input dur- ing multiple task performance by controlling where the eyes look and when is an obvious component of multiple task performance. However, inside the laboratory researchers ei- ther obviate the control of the eyes by presenting information from one task at a time or are oblivious to the need for just-in- time control of the motor component of visual attention. We investigate the effects of cognitive workload on eye move- ments in a paradigm that controls the demand on the eyes as an input channel while increasing workload by increas- ing the demand on working memory. Despite constant visual demands, we find that fixations become more scattered with increasing working memory load. Keywords: dual mechanisms of control, cognitive control, cognitive workload Introduction Our ability to switch among multiple tasks has been the subject of extensive research for many decades (Allport, Styles, & Hsieh, 1994; Altmann & Gray, 2008; Broadbent, 1952; Cherry, 1953). People generally exhibit a multitask ef- fect in which they are slower and commit more errors when performing multiple concurrent tasks than a sequential series of the same tasks. Most theories of multitasking propose a re- source capacity explanation for this multi-task effect. These theories, including Wicken’s multiple resource theory (MRT) (Wickens, 2002; Wickens & Colcombe, 2007), and Salvucci and Taatgen’s threaded cognition (Salvucci & Taatgen, 2008; Salvucci & Taatgen, 2011), propose a variety of resources which must be shared by concurrent tasks. They argue that when the capacity of one of these resources is exhausted, the cognitive system must wait for the bottleneck to clear, which causes slower task execution. MRT identifies input modalities (visual or auditory), re- sponse modalities (motor, vocal), and cognition as resources responsible for multi-task effects (Wickens, 2002; Wickens, 1992; Wickens, Goh, Helleberg, Horrey, & Talleur, 2003). For instance, if two tasks require visual processing, perfor- mance will be slower because the capacity of the visual pro- cessor is limited. MRT has not been instantiated in computa- tional form but its assumptions appear compatible with other capacity theories such that multiple tasks can be performed without interference until some capacity limit is reached (e.g., see Just, Carpenter, & Hemphill, 1996a, 1996b). Threaded cognition is a model based procedural theory of task switching, which is implemented within the ACT-R cognitive architecture (Anderson et al., 2004). In this theory, “concurrent multitasking emerges from the interaction of au- tonomous process threads in conjunction with a straightfor- ward mechanism for resource acquisition and conflict reso- lution,” (Salvucci & Taatgen, 2008, p. 102). Although we see Threaded Cognition as a major advance in the modeling of complex cognition, at present it focuses on the control of task switching per se, not on the control of tasks. As detailed by the Dual Mechanisms of Control (DMC) theory (Braver, Gray, & Burgess, 2007; Braver, 2012), the brain’s ability to prepare ahead of time (proactive control) is limited. Proactive control requires that the strategy and in- formation for a task be kept active. Hence, proactive control places strategies such as the verbal-articulatory loop (Bad- deley, 2012) and updating, shifting, and inhibition (Miyake et al., 2000) under control of the PFC and subject to lim- its in PFC processing. The importance of proactive control depends on the nature of the task being performed. In situ- ations with a limited number of stimuli and responses (i.e., most experimental psychology tasks), then proactive control seems best. However, in tasks that require the subject to re- spond to one of a number of different stimuli in a number of different ways (e.g., driving on the freeway during rush hour) then reactive processing seems required. Cognitive control is recruited by a mix of proactive and reactive influences, and understanding how this mix changes based on task demands is key to understanding performance of multiple tasks. We hypothesize that differences between single-task and multi-task performance depend on how the brain manages the demands on proactive control. A major limiting factor in multitasking is our ability to distribute our attention to per- form multiple concurrent tasks. In visual tasks, the capac- ity of the eyes to focus on one part of the visual scene at a time is a factor constraining our performance. Many tasks require the ability to control eye movements to capture re- quired information from the world, or to maintain sustained focal attention. The ability to control our eyes during task performance is an overlooked but critical variety of control. Unless we assume that pointing-the-eyes at potentially informative ar- eas of visual interest is somehow both automatic and effort- less, then the need to control gaze to optimize task perfor- mance adds yet another burden to our control mechanisms. Hence, it may be possible to determine when a switch in