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

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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.

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Notes

  1. Here, by biomathematical models, we mean mathematical models that provide a quantitative representation of how some biological process affects the state of a cognitive system, in this case, the model represents alertness (see Gunzelmann et al. 2009, for further discussion).

  2. As implied by Ritter et al. (2007) and explicitly discussed by Ritter et al. (2012).

  3. A newer version of the architecture has been developed to also include a representation of affect/emotion (Dancy, 2013). A version with just the physio module was used for this work.

  4. More information on that model and project is located at http://acs.ist.psu.edu/ACT-R_AC/.

  5. The aversive speech sound is presented at the 2 min point in every block.

  6. Reviews are available on the underlying physiology of the stress response (e.g., Charmandari et al. 2005; Joëls and Baram, 2009) and the underlying physiology of internal (e.g., Kemeny and Shestyuk 2008) and external (e.g., Öhman 2008) causes and effects of the stress response.

  7. This is a simple approximation to an appraisal mechanism.

  8. Our models (Eqs. 1 and 2) had a standard error of the mean (SEM) of 0.708 and 0.920 (respectively). While these SEMs are higher than that reported as an example in Ritter et al. (2011), our much higher run cost (~2*real-time) modified our SEM threshold.

  9. This time interval was chosen because this is how often physiological values were updated in ACT-RΦ (the :phys-delay parameter). Thus, :ans values automatically changed the moment physiology changed.

  10. The syllable-rate parameter controls the time it takes the model to articulate each syllable in a text string.

  11. Base-level constant is a parameter used during the ACT-R memory retrieval process.

  12. As a reminder, this model has a varying declarative memory noise value due to physiological modulation.

  13. See Byrne et al. (2004) and Gunzelmann et al. (2011) for counterexamples.

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Acknowledgments

The views expressed in this paper are those of the authors and do not reflect the official policy or position of the Department of Defense or the U.S. Government. The authors thank Sue Kase for providing the original ACT-R serial subtraction model and Robert Hester for useful discussions related to the HumMod simulation system. The authors also thank Kuo-Chuan (Martin) Yeh, Alex Ororbia, and several anonymous reviewers for many very useful comments. This work was partially funded by the Bunton-Waller Fellowship Program.

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Authors and Affiliations

  1. USAISEC-NCRED, 9325 Gunston Road Building 1466, Fort Belvoir, VA, 22060, USA

    Christopher L. Dancy

  2. The College of Information Sciences and Technology, The Pennsylvania State University, 316G IST Building, University Park, PA, 16802, USA

    Frank E. Ritter

  3. Medical Corps, US Army Reserves and The Bioengineering Department, The Pennsylvania State University, Hershey, PA, 17033, USA

    Keith A. Berry

  4. Biobehavioral Health Research, 105 Biobehavioral Health Building, University Park, PA, 16802, USA

    Laura C. Klein

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  1. Christopher L. Dancy
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Correspondence to Christopher L. Dancy.

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Dancy, C.L., Ritter, F.E., Berry, K.A. et al. Using a cognitive architecture with a physiological substrate to represent effects of a psychological stressor on cognition. Comput Math Organ Theory 21, 90–114 (2015). https://doi.org/10.1007/s10588-014-9178-1

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