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Papers

Lines of work across behavior, methods, neuroscience, and AI.

This page is less a complete academic archive than a map of the main threads running through the work: applied behavior analysis and measurement, decision-making, neuroscience and motor control, and more recent thinking about AI in ABA. Some of the papers are practical methods pieces. Others are experimental. The common interest is how people and systems behave under real constraints, and how that behavior can be measured clearly enough to make better decisions.

AI in practice

Writing, presentations, and operating questions on AI

Context and Persistence

The AI you used on Tuesday does not remember you on Thursday. What we call persistence is really scheduled context loading — and understanding that changes how you use AI more than any prompt trick ever will.

Inevitable: Opportunities and ethical challenges of AI in ABA

What happens when a field built on measurement, replicability, and observable outcomes meets a technology that produces confident output from opaque mechanisms? Presented at the Best of ABA Conference, Cagnes-sur-Mer, France, 2024.

AI in ABA: Conceptual foundations, ethical dilemmas, and practical applications

A planned panel extending the conceptual and ethical line into a broader discussion format — governance, adoption risk, and where the field's own methodological discipline could become an advantage. Accepted at the 11th Conference of the European Association for Behaviour Analysis, Brno, 2024. Cancelled due to illness.

Neuroscience and decision-making

How the nervous system prepares and inhibits action under pressure

Probing the nervous system to understand high-speed decision-making: how the brain prepares, inhibits, and reorganizes action when conditions change faster than conscious deliberation allows.

  • Motor preparation for compensatory reach-to-grasp responses when viewing a wall-mounted safety handle. Measuring brain activity while participants are unexpectedly released from a support cable and must recover their balance — testing how the nervous system prepares protective responses before a threat actually arrives. Bolton, D. A. E., Cole, D. M., Butler, B., Mansour, M., Schwartz, S., McDannald, D. W., and Rydalch, G. (2019). Cortex, 117, 135-146. https://doi.org/10.1016/j.cortex.2019.03.001 Article Data set
  • Staying upright by shutting down? Evidence that the brain globally suppresses the motor system during reactive balance recovery — shutting down competing actions so the protective response can execute cleanly. Goode, C., Cole, D. M., & Bolton, D. A. E. (2019). Gait & Posture, 70, 260-263. https://doi.org/10.1016/j.gaitpost.2019.03.018 Article
  • Neuronal response variability as a product of divisive normalization. A theoretical neuroscience paper proposing that trial-to-trial variability in neural firing follows from normalization mechanisms, with implications for how variability is modeled at population scales. Ruddy, K. L., Cole, D. M., Simon, C., & Bächinger, M. (2020). HRB Open Research, 3(34). https://doi.org/10.12688/hrbopenres.13062.1 Article

Measurement and validity

Tools, assessment integrity, and translational methods

Early software work and research on the integrity of the tools people use to make decisions in applied settings.

  • Assessing susceptibility of a temporal discounting task to faking. Temporal discounting measures how people choose between smaller immediate rewards and larger delayed ones — a widely used clinical and research tool. This study tested whether participants could deliberately fake their results, with direct implications for whether the measure holds up when translated from the lab to real-world clinical applications. Cole, D. M., Rung, J. M., & Madden, G. J. (2019). Journal of Clinical Psychology, 75(10), 1959-1974. https://doi.org/10.1002/jclp.22831 Article Data set
  • Formative graphing with a Microsoft Excel 2013 template. An early software project — building a free graphing tool for single-case data that was later adopted by university ABA programs. The companion paper covers the design rationale and measurement infrastructure. Cole, D. M., & Witts, B. N. (2015). Behavior Analysis: Research and Practice, 15(3-4), 171-186. https://doi.org/10.1037/bar0000021 Article Project page
  • Adding genetically modified mice to the armamentarium of behavior analysis. Part of a symposium on alternative model organisms — from alcoholic bees to robotic zebrafish — exploring where genetic, behavioral, and engineering methods intersect. Cole, D. M. (2018). Paper presented at the 44th Annual Convention of the Association for Behavior Analysis International, San Diego, CA. Abstract