Optimizing Signal Detection: A Parametric Approach to Assessment and Training
Abstract
Can inaccuracies in a person s subjective "cognitive model" of the operational environment be identified and corrected, to improve decision making? In prior research we developed a signal detection theory (SDT) framework to define and manipulate environmental parameters in a social threat perception task and to measure individual differences predictive of threat detection abilities. Here, we propose to extend that work, developing means to quantitatively assess perceivers cognitive model of the environment, provide individually tailored training targeting a person s environmental parameter "misestimate," and describe neurophysiological (EEG) correlates of parameter estimation and training effectiveness. In a one-year project, 100 participants will complete a baseline social-threat perception test. Results will determine individual vulnerabilities to misestimating three environmental parameters known from SDT to control threat detection effectiveness. Subsequently, participants will receive a training protocol and a retest. We hypothesize that participants who receive training specific to their misestimated parameter will show greater improvement than participants who receive training on an accurately estimated parameter. We will assess how executive function and personality traits may modulate the efficacy of neurophysiological measures as putative markers of parameter estimation and training effectiveness. We will address questions concerning: the assessment of learning processes and learner status to tailor training individually, the linking of constructs of adaptability to job performance, and the neurophysiological individual differences related to core military skills, such as perceptual judgement and decision making. If successful this project could transition to applications relevant to Army objectives in learning in formal & informal environments, personnel testing & performance, and psychophysiology of individual differences.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 12, 2017
- Source ID
- W911NF1610192
Entities
People
- Spencer Lynn
Organizations
- Army Contracting Command
- Northeastern University
- United States Army