Cognitive control processes and their interaction

Richard P. Cooper (with Eddy J. Davelaar) is exploring the computational basis of cognitive control. We are primarily concerned with two questions. First, assuming that cognitive control can be understood as a set of distinct processes, how does a single process (e.g., response inhibition) operate in different tasks? Second, how do such processes interact in the control of tasks of moderate complexity? We are very open to the possibility that phenomena associated with specific control processes (again, response inhibition is a good example) may emerge from the interaction of lower-level processes. Our computational work on this project is supported by associated empirical studies.

Selected Relevant Publications:

  • Cooper, R. P. (submitted). Cognitive control in the generation of random sequences: A computational study of secondary task effects
  • Cooper, R. P. (2010): Cognitive control: Componential or emergent? Topics in Cognitive Science, 2, 598-613.
  • Cooper, R. P. & Davelaar, E. J. (2010): Modelling the correlation between two putative inhibition tasks: A simulation approach. In Salvucci, D. & Gunzelmann, G. (eds.), Proceedings of the 10th International Conference of Cognitive Modelling. pp. 31-36. Drexel University: Philadelphia, PA, USA.
  • Davelaar, E. J. & Cooper, R. P. (2010): Modelling the correlation between two putative inhibition tasks: An analytic approach. In Catrambone, R. & Ohlsson, S. (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. pp. 937-942. Cognitive Science Society Incorporated: Portland, OR, USA.
  • Cooper, R. P. (2009): Extending the contention scheduling model of routine action selection: The Wisconsin Card Sorting Task and frontal dysfunction. In Howes, A., Peebles, D., & Cooper, R. P. (eds.), Proceedings of the Ninth International Conference on Cognitive Modelling. Manchester, UK. pp. 198-203. April.

Mechanisms of statistical learning

Denis Mareschal (in collaboration with Robert French in Dijon) is exploring possible mechanisms of statistical learning that underlie performance in adults, children and infants. In particular, they have been exploring the idea that a connectionist based memory model best captures the data across all three age groups, suggesting that participants are learning to recognise sequence chunks rather than learning global sequence statistics.

Multisensory cue integration

Denis Mareschal (in collaboration with Marko Nardini at Durhma and Natasha Kirkham at Birkebck) is exploring how well Bayesian optimal cue integration models account for children's developing use of multisensory cues when navigating and learning in the real world.

Imitation and social learning

Richard P. Cooper (with Cecilia Heyes) is using computational modellingto help understand the processes related to social learning and imitation. This ongoing project aims to understand whether social learning differs from other forms of learning. A longer term goal is to explore the development of "mirror neurons" and hence the significance and role of the "mirror neuron system".

Selected Relevant Publications:

  • Cooper, R. P. & Heyes, C. (2013), Are automatic and spatial compatibility mediated by different processes?

Embodied time perception

In collaboration with Robert French and Elizabeth Thomas (at Dijon) Denis Mareschal is exploring how the sense of time and ability to judge the duration of events in the world relates to memory decay processes, and is calibrated during early infant cyclical actions.