Neil R Bramley

Neil Bramley

I am a cognitive scientist and Moore-Sloan post-doctoral associate in Todd Gureckis' computation and cognition lab at New York University. I use interactive online experiments and games combined with computational modelling to better understand how people learn, represent, and reason about the world.

In particular, my research explores the idea that internal representations—or "causal mental models"— underlie many of the core cognitive competencies that characterise intelligence. These include the ability to imagine alternatives, simulate the future, predict and explain events and invent creative solutions to problems. I show that interventional and temporal cues, along with top-down hierarchical constraints, can inform the evolution and adaptation of increasingly rich causal models over extended experience.

I am also exploring the bidirectional relationship between people's beliefs and their active information gathering behaviour. In general I find that people exhibit a range of active causal learning strategies from the more heuristic exploration characteristic of children's play to informal experiments, that control for confounds while manipulating variables to distinguish hypotheses. A better understanding of how people learn and exploit causal models can help explain reasoning fallacies and pathologies like superstition, hallucinations and depression, and well as informing machine-learning research on active and unsupervised structure learning.

Publications

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Forthcoming

Coenen, A., Ruggeri, A., Bramley, N. R. & Gureckis, T. M. (in prep). Beliefs about sparsity affect causal experimentation.

Bramley, N. R., Gerstenberg, T., Mayrhofer, R. & Lagnado, D. A. (submitted). The role of time in causal learning.

2017

Bramley, N. R., Dayan, P., Griffiths, T. L. & Lagnado, D. A. (2017). Formalizing Neurath's ship: Approximate algorithms for online causal learning. Psychological Review, Vol 124 (3), 301-338.
pdf, supplementary materials, figure 7d (corrected), figure 11d (corrected)

Bramley, N. R., Mayrhofer, R., Gerstenberg, T. & Lagnado, D. A. (2017). Causal learning from interventions and dynamics in continuous time. In Proceedings of the 39th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Coenen, A., Bramley, N. R., Ruggeri, A. & Gureckis, T. M. (2017). Beliefs about sparsity affect causal experimentation. In Proceedings of the 39th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

Schulz, E., Klenske, E. D., Bramley, N. R. & Speekenbrink, M. (2017). Strategic exploration in human adaptive control. In Proceedings of the 39th Annual Meeting of the Cognitive Science Society. Austin, TX: Cognitive Science Society.

2016

Bramley, N. R., Gerstenberg, T. & Tenenbaum, J. B. (2016). Natural Science: Active learning in dynamic physical microworlds. In Papafragou, A., Grodner, D., Mirman, D., & Trueswell, J.C. (Eds.) Proceedings of the 38th Annual Meeting of the Cognitive Science Society (pp. 2567 - 2572). Austin, TX: Cognitive Science Society.
pdf, supplementary materials

McCormack, T., Bramley, N. R., Frosch, C., Patrick, F. & Lagnado, D. A. (2016). Children's Use of Interventions to Learn Causal Structure. Journal of Experimental Child Psychology. 141, 1-22.\
pdf

2015

Bramley, N. R., Dayan, P. & Lagnado, D. A. (2015). Staying afloat on Neurath's boat: Heuristics for sequential causal learning. In Noelle, D. C. et al (Eds.) Proceedings of the 37th Annual Meeting of the Cognitive Science Society (pp. 262-267). Austin, TX: Cognitive Science Society.
pdf, exp 1, exp 2

Bramley, N. R., Lagnado, D. A. & Speekenbrink, M. (2015). Conservative forgetful scholars: How people learn causal structure through interventions. Journal of Experimental Psychology: Learning, Memory & Cognition, Vol 41(3), 708-731.
pdf, exp 1, exp 2, data

2014

Bramley, N. R., Gerstenberg, T. & Lagnado, D. A (2014). The order of things: Inferring causal structure from temporal patterns. In P. Bello, M. Guarini, M. McShane, & B. Scassellati (Eds.), Proceedings of the 36th Annual Meeting of the Cognitive Science Society (pp. 236-242). Austin, TX: Cognitive Science Society.
pdf, demo, data

Theses

Bramley, N. R. (2017). Constructing the world: Active causal learning in cognition. PhD thesis, Experimental Psychology, UCL, London.
pdf, supplement

Bramley, N. R. (2013). Modelling active causal learning. MRes thesis, Computer science, UCL, London.

Bramley, N. R. (2011). Mechanisms of active causal learning. MSc thesis, Cognitive, Perceptual & Brain Sciences, UCL, London.

Bramley, N. R. (2009). Does physicalism entail panexperientialism? MA thesis, Philosophy, University of Glasgow.

Posters

Bramley, N. R., Nelson, J. D., Speekenbrink, M. Crupi, V., Lagnado, D. A. (2014). What should an active causal learner value? Poster presented at The Psychonomic Society Annual Meeting, Long Beach, California, USA.
pdf

Bramley, N. R., Lagnado, D. A. & Speekenbrink, M. (2013). Mechanisms of active causal learning. Poster presented at The 35th Annual Meeting of the Cogntive Science Society, Berlin, Germany.
pdf

Book reviews

Future-Minded: The Psychology of Agency and Control by Magda Osman.
link

Talk series

I host NYU ConCats, a semi-weekly informal discussion group for research related to psychology of concepts and categories. Fridays 1:00-2:30pm in Meyer 851, 6 Washington Place, NYU, New York, NY, 10003.
schedule

Until recently I hosted the London Judgment and Decision Making (LJDM) group seminar series. Wednesdays 17:00-18:30, 313, 26 Bedford Way, UCL, London, WC1H 0AP, UK.
schedule

Lectures

Active learning. For PSYCGD04: Knowledge, Learning & Inference, Experimental Psychology, UCL.
2014, 2016

Integrated information theory of consciousness. For PSYCGD01: Philosophy of Cognitive Science, Experimental Psychology, UCL.
2015a, 2015b

Causal learning in an imperfect world. For PSYC1103: Introduction to Psychological Experimentation, Experimental Psychology, UCL.
2014