Models & Metrics of Human Executive Control

a subprogram of

Cognitive Models and Metrics

POC

Roger Remington, Ph.D, NASA AFH N-262 Rm. 238, (650) 604-6243 (voice), (650) 604-3323 (fax).
James Johnston, Ph.D, NASA AFH N-262 Rm. 240, (650) 604-5686 (voice), (650) 604-3323 (fax).

BACKGROUND

The allocation of attention and executive control is at the center of our understanding of how information is selected from the world. This in turn determines the knowledge of the user with respect to the state of the world at any point in time. Here we address the issue of how external stressors influence the allocation of executive control. In particular we focus on the role of time pressure in determining how operators sequence between tasks and information sources.

OBJECTIVES

Extend and validate the APEX computational model of executive control by specifying the role of executive control in cognitive processing and how control failure leads to human error in complex task environments.

APPROACH

Research will test the hypothesis that time pressure leads to a truncating of normal processing, leading to a first-come-first-served task allocation strategy. We pursue this by both empirical testing, by modeling, and by direct observation of brain activity. The existing APEX model of executive control developed in the Cognition Laboratory at NASA Ames will be refined and used as the basis of modeling.

LEVEL 3 MILESTONES

FY98 - Analysis of Time-Pressure Effects on Human Errors in an ATC-like Task
FY98 - Complete Test of 3-stage Information Processing Models by Measuring Brain Activity (FMRI)
FY99 - Analysis of time-pressure effects on monitoring task
FY99 - Identify multiple loci information bottlenecks by recording brain activity
FY00 - Examine Brain Activity Correlates of Time-Induced Omission Errors
FY00 - Analysis of Spatial Display Effects on Distribution and Allocation of Attention
FY01 - General Model of Executive Control
FY02 - Develop/Test Workload Metric Integrating Empirical Testing, Eye Movements, and Brain Recording
FY03 - Validate Workload Metric in Full-Mission Simulation