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
The field that taught machines to learn
Behavior analysis, artificial intelligence, and the cost of not building. Reinforcement learning traces back to Thorndike and Skinner. The people building modern AI know this. Behavior analysis has not made that lineage central to its own account of AI — and outsiders are building the measurement layer around autism care without it.
Context and persistence
The AI you used on Tuesday does not remember you on Thursday. What we call persistence is really scheduled context loading — someone decides what gets loaded into the model's window each session. Every improvement in "the AI's performance" is really an improvement in the system around it: better files, better instructions, better decisions about what to carry forward.
AI in ABA: Conceptual foundations and ethical challenges
Earlier framing of the question the paper above takes at length: what happens when a field built on measurement, replication, and observable outcomes meets systems that produce confident output from opaque mechanisms. Presented at Best of ABA, Cagnes-sur-Mer, 2024; later accepted as a broader EABA panel in Brno.
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