Using a cognitive architecture with a physiological substrate to represent effects of a psychological stressor on cognition

Christopher L. Dancy, Frank E. Ritter, Keith A. Berry, Laura C. Klein

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Adding a physiological representation to a cognitive architecture offers an attractive approach to modeling the effects of stress on cognition. We introduce ACT-R/Φ, an extended version of the ACT-R cognitive architecture that includes an integrative model of physiology. The extension allows the representation of how physiology and cognition interact. This substrate was used to represent potential effects of a startle response and task-based stress during a mental arithmetic (subtraction) task. We compare predictions from two models loaded into the new hybrid architecture to models previously developed within ACT-R. General behavior differed between models in that the ACT-R/Φ models had dynamic declarative memory noise over the course of the task based on varying epinephrine levels. They attempted more subtractions but were less accurate; this more closely matched human performance than the previous ACT-R models. Using ACT-R/Φ allows a more tractable integration of current physiological and cognitive perspectives on stress. ACT-R/Φ also permits further exploration of the interaction between cognition and physiology, and the emergent effects on behavior caused by the interaction among physiological subsystems. This extension is useful for anyone exploring how the human mind can occur in and be influenced by the physical universe.

Original languageEnglish (US)
Pages (from-to)90-114
Number of pages25
JournalComputational and Mathematical Organization Theory
Volume21
Issue number1
DOIs
StatePublished - Jan 1 2015

Fingerprint

Cognitive Architecture
Cognition
Substrate
Physiology
Substrates
Subtraction
Mental arithmetic
Model
Human Performance
Dynamic models
Interaction
Stressors
Psychological
Subsystem
Data storage equipment
Prediction
Modeling

All Science Journal Classification (ASJC) codes

  • Decision Sciences(all)
  • Computer Science(all)
  • Modeling and Simulation
  • Computational Mathematics
  • Applied Mathematics

Cite this

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