Eye movements were monitored to assess memory for scenes indirectly (implicitly). Two eye movement-based memory phenomena were observed: (a) the repetition effect, a decrease in sampling of previously viewed scenes compared with new scenes, reflecting memory for those scenes, and (b) the relational manipulation effect, an increase in viewing of the regions where manipulations of relations among scene elements had occurred. In normal control subjects, the relational manipulation effect was expressed only in the absence of explicit awareness of the scene manipulations. Thus, memory representations of scenes contain information about relations among elements of the scenes, at least some of which is not accessible to verbal report. But amnesic patients with severe memory impairment failed to show the relational manipulation effect. Their failure to show any demonstrable memory for relations among the constituent elements of scenes suggests that amnesia involves a fundamental deficit in relational (declarative) memory processing.

In this article, the authors empirically assess the costs and benefits of designing an adaptive system to follow social conventions regarding the appropriateness of interruptions. Interruption management is one area within the larger topic of automation etiquette. The authors tested these concepts in an outdoor environment using the Communications Scheduler, a wearable adaptive system that classifies users' cognitive state via brain and heart sensors and adapts its interactions. Designed to help dismounted soldiers, it manages communications in much the same way as a good administrative assistant. Depending on a combination of message priority, user workload, and system state, it decides whether to interrupt the user's current tasks. The system supports decision makers in two innovative ways: It reliably measures a mobile user's cognitive workload to adapt its behavior, and it implements rules of etiquette adapted from human-human interactions to improve humancomputer interactions. Results indicate costs and benefits to both interrupting and refraining from interrupting. When users were overloaded, primary task performance was improved by managing interruptions. However, overall situation awareness on secondary tasks suffered. This work empirically quantifies costs and benefits of "appropriate" interruption behaviors, demonstrating the value of designing adaptive agents that follow social conventions for interactions with humans.

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The effectiveness of neurophysiologically triggered adaptive systems hinges on reliable and effective signal processing and cognitive state classification. Although this presents a difficult technical challenge in any context, these concerns are particularly pronounced in a system designed for mobile contexts. This paper describes a neurophysiologically derived cognitive state classification approach designed for ambulatory task contexts. We highlight signal processing and classification components that render the electroencephalogram (EEG) -based cognitive state estimation system robust to noise. Field assessments show classification performance that exceeds 70% for all participants in a context that many have regarded as intractable for cognitive state classification using EEG. ADDRESS CORRESPONDENCE TO: Michael C. Dorneich, Honeywell Laboratories, Human-Centered Systems, 3660 Technology Dr., Minneapolis, MN 55418, 612/951-7488, michael.dorneich@honeywell.com.

Honeywell has designed a joint humancomputer cognitive system to support rapid decision making demands of dismounted soldiers. In highly networked environments the sheer magnitude of communication amid multiple tasks could overwhelm individual soldiers. Key cognitive bottlenecks constrain information flow and the performance of decision-making, especially under stress. The adaptive decision-support system mitigates non-optimal human performance via automation when the system detects a breakdown in the human's cognitive state. The human's cognitive state is assessed in real-time via a suite of neuro-physiological and physiological sensors. Adaptive mitigation strategies can include task management, optimizing information presentation via modality management, task sharing, and task loading. Mitigations are designed with consideration for both the costs and benefits of intermittent augmentation The paper describes the system development and evolution, explorations of usable cognitive mitigation strategies, and four evaluations that show adaptive automaton can effectively, mitigate human decision-making performance at extremes (overload and underload) of workload.

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A conceptual framework for designing humancomputer cognitive systems is proposed. The Cognitive Bottleneck Framework (CBF) identifies four significant "cognitive bottlenecks" that negatively impact the quality and tempo of decision making: (1) Information overload; humans cannot manage the vast amounts of information delivered by their computing environment, (2) Sequential cognitive processing; while information arrives in parallel, humans are essentially serial processors that can only address a single thread or task at a time, (3) Narrow user input capabilities: the system has more sophisticated means of communicating to the human than the human has of communicating to the system, and (4) Function mis-allocation; tasks are allocated to humans by default rather than by design, leaving them with tasks for which they are cognitively ill-suited. The overall purpose of CBF is to "right-size" these bottlenecks, remove constraints that restrict information flow, and better fit information channels to the abilities of either the human or computer.