Taylor Curley

Computational/Mathematical modeler · Air Force Research Laboratory (AFRL) · taylor.curley.ext@afresearchlab.com

I am a Research Psychologst with the Air Force Research Laboratory. I use behavioral and computational methodologies to measure and understand memory and cognition.

Research

Computational Modeling



Fatigue & Vigilant Attention

Adults are unable to hold their attention to demanding cognitive tasks for long periods of time. Sometimes, these increases in fatigue across time-on-task can lead to errors. Along with other researchers at the 711th Human Performance Wing at the Air Force Research Laboratory (AFRL), I use computational models of cognition to understand and develop empirical hypotheses about fatigue and errors in vigilant attention tasks, such as the Psychomotor Vigilance Test (PVT). Our models capture individual differences in vigilant task performance using both behavioral and neural (EEG) data. [M28] [M29]

Metacognition & Hypothesis Generation

Research in cognitive psychology indicates that individuals do not have direct (or "privileged") access to the contents of their own memory. Cues diagnostic of information of interest, however, are available, though these cues may or may not be accessible at the time of inference. Furthermore, inferential cues can be overwhelmed by cues that are not diagnostic of a true memory state, such as fluency of retrieval or item associativeness. In order to understand this "multiple-cue utilization" (MCU) hypothesis of metacognition, the Adult Cognition Lab, along with Drs. Rick Thomas and David Illingworth, modified existing cognitive architectures (MINERVA2 and HyGene) to model how memory decisions are made based on the integration of multiple memory cues. [M24] [M30]

Vowel Category Formation

Infants face great acoustic developmental challenges - not only must they learn to distinguish speech tokens (i.e., individual vowel and consonant sounds), but they must do so while encountering high variability in these tokens between speakers. A large source of speaker invariance, for example, comes from differences between genders, with female speaker tokens registering at higher levels on the acoustic spectrum than male speakers. Despite this lack of invariance, infants readily learn differences between vowel sounds through observing their stochastic properties. Led by Dr. Joe Toscano at Villanova University, we developed a computational model of vowel category learning in infants that both capitalizes on statistical learning and accounts for speaker variability. [M5]

Metacognition



Aging & Metamemory

When we think about aging, we commonly hark upon declines in declarative episodic memory, specifically in explicit recall. While it is true that normally-aging older adults have greater difficulty with explicit recall than do younger adults, they are still able to provide accurate decisions about their memory that allow them to function normally in their daily lives. With Dr. Chris Hertzog and the Adult Cognition Lab (ACL), I study the accuracy of memory judgments across the lifespan and the strategies that can aid individuals in making decisions about their own knowledge, even when specific information cannot be directly recalled. Recently, we have been examining feelings-of-knowing (FOKs), which scale confidence that an individual will be able to recognize an item that they cannot currently recall and, in turn, allows researchers to make inferences about that individual's access to diagnostic information in the absense of explicit memory. [P2]

Judgments & Monitoring

A major focus of the research during my graduate studies was understanding metacognitive monitoring (monitoring the status of the cognitive system) during experimental tasks. Specifically, how well can individuals judge their current level of knowing of to-be-remembered information? How accurate are their predictions of remembering that information in the future? With the Adult Cognition Lab, I use predictive judgments of if an item will be recognized in the event that it cannot be recalled (called feeling-of-knowing [FOK] judgments) to assess metacognitive accuracy in both young and older adults. [P5] [M24] [M30]

Utilization of Monitoring

Although they largely escape our awareness, we use metacognitive monitoring constantly during learning to determine how to study information that needs to be remembered at a later time as well as how much time we should spend studying that information. A large focus of my research on the relationship between monitoring and control is on the decisions that learners make during studying when introduced to certain task manipulations, such as the difficulty of the items being studied or the wording of the instructions that are presented before learning even begins. [P4]

Experience

Computational/Mathematical Modeler

Air Force Research Laboratory

As a Research Psyhologist (DR-02), I integrate behavioral and neural data with computational techniques to understand human performance. I work in the Airmen Systems (RH) directorate within the 711th Human Performance Wing at the Air Force Research Laboratory (AFRL) at Wright-Patterson AFB.

November 2022 - present

Cognitive Modeler

Cubic Corporation | Air Force Research Laboratory

I worked with researchers at the 711th Human Performance Wing at the Air Force Research Laboratory (AFRL) to examine behavioral and computational accounts of human cognition, such as the effects of fatigue during sustained vigilance tasks. I used a wide variety of modeling techniques, such as ACT-R and multilevel modeling, to capture individual differences in memory and attention.

September 2021 - October 2022

Graduate Student Researcher

School of Psychology | Georgia Institute of Technology

As a graduate student at Georgia Tech, my primary research focus was age differences in episodic memory and memory awareness (metamemory). I helped design, run, and examine the results of behavioral studies that ranged from simple paired-associates learning to large-scale word norms using a number of statistical and computational techniques. Along with my research, I designed a graduate-level statistics lab curriculum that focused on the use of the R programming language.

August 2015 - December 2021

Cognitive Scientist Intern

Charles River Analytics

I researched dynamics of cognitive performance and fatigue in the battlefield and implemented models of soldier performance using Python, R, Clojure, and in-house programming languages. These projects were funded by SBiRs with support from the U.S. Army Natick Soldier Systems Center.

May 2017 - August 2017

Education

Georgia Institute of Technology

Doctor of Philosophy in Psychology
Maior: Cognitive Aging
Minor: Quantitative Methodology

Advisor: Chris Hertzog, PhD
Adult Cognition Lab (ACL)

August 2015 - December 2021

Villanova University

Master of Science in Experimental Psychology

Thesis Advisor: Thomas Toppino, PhD
Memory and Cognition Lab
Word Recognition and Auditory Perception (WRAP) Lab

August 2013 - May 2015

University of North Carolina at Wilmington

Bachelor of Arts in Psychology (Departmental Honors)
Bachelor of Arts in English

Thesis Advisor: Jeffrey Toth, PhD
Aging and Cognitive Training (ACT) Lab

August 2008 - May 2012

    Media

    Publications
    2021
  • Hertzog, C., Curley, T., & Dunlosky, J. (2021). Are age differences in recognition-based retrieval monitoring an epiphenomenon of age differences in memory? Psychology & Aging, 36, 186-199. https://doi.org/10.1037/pag0000595.

  • [P4] Toppino, T., Heslin, K., Curley, T. et al. (2021). Why do learners ignore expected feedback in mkaing metacognitive decisions about retrieval practice? Memory & Cognition, 49, 1-13. https://doi.org/10.3758/s13421-021-01171-4.

  • 2020
  • [P3] Castro, N., Curley, T., & Hertzog, C. (2020). Category norms with a cross-sectional sample of adults in the United States: Consideration of cohort, age, and historical effects on semantic categories. Behavior Research Methods, 53, 898-917. https://doi.org/10.3758/s13428-020-01454-9.

  • 2019
  • [P2] Hertzog, C. & Curley, T. (2019). Metamemory and Cognitive Aging. Book chapter for The Oxford Research Encyclopedia of Psychology, Oxford University Press. https://doi.org/10.1093/acrefore/9780190236557.013.377.

  • [P1] Bauchwitz, B., Curley, T., Kwan, C., Niehaus, J., Pugh, C., & Weyhrauch, P. (2019). Modeling framework used to analyze and describe junctional tourniquet skills. Journal of Military Medicine, 184, 347-360. https://doi.org/10.1093/milmed/usy348 10.1093/milmed/usy348.


  • Presentations and Other Media
    2022
  • [M31] Curley, T., Borghetti, L., & Morris, M. (November, 2022). Local mental effort vs. global compensation: Perspectives from a neurocognitive model of vigilant attention. Upcoming presentation at the 3rd Workshop on Mental Effort at Brown University.

  • [M30] Curley, T. (November, 2022). Exploring the mechanisms of output interference during cued recall using metamemory judgments. Upcoming spoken presentation at the Annual Meeting of the Psychonomic Society.

  • [M29] Curley, T., Borghetti, L. & Morris, M. (July, 2022). Gamma power as an index of sustained attention in simulated vigilance tasks. Conference paper in Proceedings of the 20th Annual Meeting of the International Conference on Cognitive Modeling (ICCM).

  • [M28] Curley, T. & Morris, M. (July, 2022). Modeling short-term fatigue decrements in the successive/simultaneous discrimination task. Conference paper in Proceedings of the 20th Annual Meeting of the International Conference on Cognitive Modeling (ICCM).

  • [M27] Curley, T. (April, 2022). Age equivalence in the effects of output interference during cued recall. Poster presentation at the Cognitive Aging Conference in Atlanta, GA.

  • [M26] Curley, T., Castro, N., & Hertzog, C. (April, 2022). Alternative estimates of category exemplar typicality across adulthood. Poster presentation at the Cognitive Aging Conference in Atlanta, GA.

  • [M25] Curley, T., Dunlosky, J., & Hertzog, C. (April, 2022). Distinctive encoding enhances performance, but not monitoring, during category cued recall for both young and older adults. Poster presentation at the Cognitive Aging Conference in Atlanta, GA.

  • 2021
  • [M24] Curley, T. (2021). The effects of output interference on metamemory and cued recall accuracy in young and older adults. (Dissertation). Georgia Institute of Technology.

  • [M23] Curley, T. (February, 2021). Are age differences in recognition-based retrieval monitoring an epiphenomenon of age differences in memory? Talk presented at the Cognitive Aging Brown Bag at the Georgia Institute of Technology.

  • 2020
  • [M22] Curley, T., Castro, N., & Hertzog, C. (November, 2020). Examining the agreement of alternative estimates of category exemplar typicality. Poster at the Annual Meeting of the Psychonomic Society.

  • [M21] Curley, T. (March, 2020). Aging and feelings-of-knowing: Exploring the factors that can help or hinder memory judgment accuracy. Talk presented at the Cognitive Aging Brown Bag at the Georgia Institute of Technology.

  • 2019
  • [M20] Curley, T., Castro, N., Hertzog, C. & Dunlosky, J. (May, 2019). Exploring the effects of encoding and semantic network properties on memory for related items. Poster at the 2019 Context and Episodic Memory Symposium (CEMS) in Philadelphia, PA.

  • [M19] Curley, T., Castro, N., & Hertzog, C. (February, 2019). Cohort, age, and historical effects on semantic categories. Talk presented at the Cognitive Aging Brown Bag at the Georgia Institute of Technology.

  • [M18] Curley, T. (January, 2019). Encoding and semantic network properties affect memory for related items. Spoken presentation at the North Georgia Regional Memory Meeting (NGRAMM).

  • 2018
  • [M17] Castro, N., Hertzog, C., & Curley, T. (November, 2018). Semantic network structure and level of processing: Implicit and explicit representations influence recall and recognition of items studied in the presence of categorically-related words. Poster presentation at the 59th Psychonomic Society Annual Meeting in New Orleans, LA.

  • [M16] Hertzog, C., Curley, T., & Dunlosky, J. (2018). Distinctiveness-based encoding reduces age differences in high-confidence recognition errors. Published abstract in Innovation in Aging, 2, 48. https://doi.org/10.1093/geroni/igy023.177.

  • [M15] Lynn, S., Curley, T., & Weyhrauch, P. (July, 2018). Modeling perceptual judgements in believable agents: A signal detection approach. In I. Juvina, J. Houpt, & C. Myers (Eds.), Proceedings of the 16th International Conference on Cognitive Modeling (pp. 47-48). Madison, WI: University of Wisconsin.

  • [M14] Curley, T., Hertzog, C., & Douglass, S. (April, 2018). The effects of judgment scaling on feeling-of-knowing accuracy in younger and older adults. Poster presentation at the Cognitive Aging Conference in Atlanta, GA.

  • [M13] Curley, T. (March, 2018). Aging and distinctiveness encoding: Implications for metacognitive retrieval monitoring. Talk presented at the Cognitive Aging Brown Bag at the Georgia Institute of Technology.

  • [M12] Curley, T. (January, 2018). Effects of distinctiveness encoding and item typicality on metacognitive retrieval monitoring. Spoken presentation at the North Georgia Regional Memory Meeting (NGRAMM).

  • 2017
  • [M11] Curley, T. & Bauchwitz, B. (December, 2017). Correlated changes in brain functioning and cognitive performance are marked by individual differences. Spoken presentation at the IEEE Data Bank Challenge at Charles River Analytics, Inc. in Cambridge, MA.

  • [M10] Hertzog, C., Curley, T., & Dunlosky, J. (November, 2017). Effects of a distinctiveness manipulation on metacognitive retrieval monitoring. Talk presented at the Cognitive Aging Brown Bag at Georgia Tech.

  • [M9] Hertzog, C., Curley, T., & Dunlosky, J. (November, 2017). Effects of a distinctiveness manipulation on metacognitive retrieval monitoring. Spoken presentation at the Annual Meeting of the Psychonomic Society.

  • [M8] Bauchwitz, B. & Curley, T. (August, 2017). Modeling junctional tourniquet skills from empirical data. Spoken presentation at the Military Health Research Symposium (MHRSRS)

  • 2016
  • [M7] Curley, T. & Hertzog, C. (October, 2016). Aging and feelings-of-knowing. Talk presented at the Cognitive Aging Brown Bag at the Georgia Institute of Technology.

  • [M6] Curley, T. (2016). Effects of framing practice tests as restudy on final recall. (Master’s thesis). Villanova University, Villanova, PA.

  • 2015
  • [M5] Toscano, J. & Curley, T. (November, 2015). Statistical learning of vowel categories: a computational approach. Poster presentation at the Annual Meeting of the Psychonomic Society.

  • 2014
  • [M4] Heslin, K.A., Curley, T.M., Jackiewicz, M.K., Flowers, C.S., Phelan, H.A., & Toppino, T.C. (November, 2014). Influence of feedback on metacognitive decisions about spacing practice tests: A framing effect? Poster presentation at the Annual Meeting of the Psychonomic Society.

  • 2013
  • [M3] Northcutt, C.A., Toth, J.P., Daniels, K.A., & Curley, T.M. (February, 2013). I’ve never been too good with names but I remember faces: Memory for faces and names. Poster presentation at the North Carolina Cognitive Conference, Raleigh, NC

  • 2012
  • [M2] Metacognitive accuracy for face-name pairs using a dual-process approach to judgments of learning. (Undergraduate thesis). University of North Carolina Wilmington, Wilmington, NC.

  • [M1] Curley, T. & Toth, J. (March, 2012). Metacognitive accuracy for face-name pairs using a dual-process approach to judgments of learning. Poster presentation at the Colonial Academic Alliance Undergraduate Research Conference, Norfolk, VA.


  • Tutorials
  • T-tests in R
  • One-way ANOVAs in R
  • Two-way ANOVAs in R
  • Goodman-Kruskal gamma correlations in R


  • Grant Money & Awards
  • Outstanding Graduate Student Instructor, School of Psychology, Georgia Institute of Technology (2020-2021)
  • Ruth L. Kirschstein National Research Service Award Institutional Research Training Grant Recipient (T32; 2017-2021)
  • Travel Award Recipient ($1,500) - Arthur M. Sackler Colloquium (Irvine, CA), National Academy of Sciences (NAS) (2019)
  • Microsoft Azure Research Award - March-December 2018 ($2,000)
  • IEEE Data Bank Competition 2017 (Cambridge, MA) - 3rd Place ($200)
  • Graduate Travel Award ($1,500) – The International Conference on Cognitive Modeling (2016)
  • Graduate Travel Award ($1,000) – The Psychonomic Society (2015)
  • Graduate Studies Student Service Award, Villanova University (2013-2014 & 2014-2015)
  • Graduate Studies Travel Award ($1,500), Villanova University (2014)



  • Content and Work in the Media
  • Psychonomic Society Content: "Modeling the genius of babies: Guidelines for simulations of basic rule learning"
  • Psychonomic Society Content: "Why we don’t serve 'cheese and macaroni': Investigating directionality of relationships between words"
  • Psychonomic Society Content: "Context is everything—but what is context? Disentangling the 'what' from the 'when'"
  • Psychonomic Society Featurette: "Older Adults Monitor Their Memory More Than Young Adults"
  • Psychonomic Society Featurette: "What Can the Science of Word Networks Tell Us About Dementia?"
  • Psychonomic Society Featurette: "Worried About Your Memory? Consider Attentional Refreshing"
  • Psychonomic Society Featurette: "Forgetting Isn't Always Curvilinear"
  • Psychonomic Society Featurette: "In Science, Missing the Target Is Okay"
  • Psychonomic Society Featurette: "Annoying Drug Advertisements Are More Helpful Than You Think"
  • Psychonomic Society Featurette: "A Roadmap for Misinformation and Perceived Truth"
  • Psychonomic Society Featurette: "Can the Content of Our Emails Hinder Future Memory?"
  • Psychonomic Society Featurette: "Adversarial Collaborations: Turning Disagreements Into Collaborations"
  • Phys.org: "What's a Mind Without a Body?"
  • CRA Press Release: "Tourniquet Master Training"
  • CRA Publication: "Modeling Junctional Tourniquet Skills from Empirical Data"


Skills

Programming Languages & Tools
  • Julia
  • Python
  • R
  • MATLAB
  • Mathematica
  • SAS
  • LATEX
  • MPlus
  • EQS
  • Visual Basic
  • SPSS
  • HTML/CSS

Specialized Methodology
  • Behavioral Statistics & Experimental Design
  • Cognitive Computational Modeling
  • Bayesian Inference
  • Multivariate Statistics
  • Structural Equation Modeling
  • Longitudinal Data Analysis
  • Multilevel Modeling
  • Dynamical System Analysis

Interests

When I am not working, I enjoy spending my free time outside playing tennis. I also enjoy hiking in the Appalachian Mountains and competing in adventure races with my brother.

In the rare moments in which I'm neither working nor playing tennis, I enjoy reading, learning about new data analysis/programming technologies, watching Netflix, and (unsuccessfully) modifying simple robots.