About this Research Topic
Many workplace settings are characterized as complex, uncertain and where performance is limited by one’s available cognitive resources, like those in military, aviation and medical fields. Tasks in these settings often require sustained attention where momentary lapses can cause errors. However, advances in modern technology have further increased the amount of information available and simultaneously decreased processing time for decision making – putting a significant strain on the cognitive demands and stress management of operators. This combination of task requirements and strained cognitive load have increased the risk for hazardous work environments due to attentional drift, transient or persistent shifts in attention away from the primary task. Although human attention will naturally ebb and flow, attentional drift can result in catastrophic errors due to neglected critical signals, skipped or duplicated sequences in a procedure, increased time to complete tasks and impaired learning of new material.
The goal of this Research Topic is to investigate the wax and wane of attention to provide a better understanding of human performance and prevent errors due to attentional drift. Traditional measures of performance and workload, like self-report indices, lack the temporal resolution needed to capture these shifts in attention, and accuracy and response latency often suffer from data loss due to the use of only accurate trials restricting their ability to identify the underlying mechanisms of performance. Unlike these methods, neurophysiological measures (e.g., eye tracking, electroencephalography (EEG), galvanic skin conductance), offer an ability to continuously capture changes in physiology that can be tied to neurological states (e.g., calm vs. stressed) to offer a more comprehensive view of human performance. The implications for the findings are broad including identifying the sources of individual differences attentional drift, characterizing attentional stages and patterns, and improved human performance through the use of decision support systems and other forms of automation aids that can use these tools to capture an individual’s attentional state and redirect attention back to the primary task when attention has drifted away.
This research topic will consider research papers, theories, models and applications that leverage neurophysiological measures or computational models that capture transient shifts in attention in an attempt to discern engaged on-task behaviors from off-task processes. We are interested in research that seeks to improve our scientific understanding of the underlying mechanisms at play as well as aspects of attention that are likely impacted. Thus, we welcome manuscripts that address but are not limited to the following:
• The role of cognitive control and individual differences in maintaining internal goals in the face of distraction – specifically, the interplay between cognitive control and attentional drift and how that may vary across individuals
• An improved understanding of how attention supports the maintenance and execution future-oriented goals
• An improved understanding of the susceptibility of human performance to the vigilance decrement
• The impacts of and interaction between task environment (e.g., uncertainty of cues and task difficulty) and an individual’s internal states (e.g., mood, fatigue, arousal, etc.) on the ebb and flow of attention toward a primary task
• Design interventions to improve task performance and mitigate the effects of attentional drift that cause human errors
The goal of this Research Topic is to investigate the wax and wane of attention to provide a better understanding of human performance and prevent errors due to attentional drift. Traditional measures of performance and workload, like self-report indices, lack the temporal resolution needed to capture these shifts in attention, and accuracy and response latency often suffer from data loss due to the use of only accurate trials restricting their ability to identify the underlying mechanisms of performance. Unlike these methods, neurophysiological measures (e.g., eye tracking, electroencephalography (EEG), galvanic skin conductance), offer an ability to continuously capture changes in physiology that can be tied to neurological states (e.g., calm vs. stressed) to offer a more comprehensive view of human performance. The implications for the findings are broad including identifying the sources of individual differences attentional drift, characterizing attentional stages and patterns, and improved human performance through the use of decision support systems and other forms of automation aids that can use these tools to capture an individual’s attentional state and redirect attention back to the primary task when attention has drifted away.
This research topic will consider research papers, theories, models and applications that leverage neurophysiological measures or computational models that capture transient shifts in attention in an attempt to discern engaged on-task behaviors from off-task processes. We are interested in research that seeks to improve our scientific understanding of the underlying mechanisms at play as well as aspects of attention that are likely impacted. Thus, we welcome manuscripts that address but are not limited to the following:
• The role of cognitive control and individual differences in maintaining internal goals in the face of distraction – specifically, the interplay between cognitive control and attentional drift and how that may vary across individuals
• An improved understanding of how attention supports the maintenance and execution future-oriented goals
• An improved understanding of the susceptibility of human performance to the vigilance decrement
• The impacts of and interaction between task environment (e.g., uncertainty of cues and task difficulty) and an individual’s internal states (e.g., mood, fatigue, arousal, etc.) on the ebb and flow of attention toward a primary task
• Design interventions to improve task performance and mitigate the effects of attentional drift that cause human errors
Keywords: neurophysiology, eye tracking, computational models, cognitive control, sustained attention, attentional drift
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
