Thomas Shultz (PhD Yale, Psychology) is Professor of Psychology and Associate Member of the School of Computer Science at McGill University. He teaches courses in Computational Psychology and Cognitive Science. He is a Fellow of the Canadian Psychological Association, and a founder and current Director of the McGill Cognitive Science Programs. Research interests include cognitive science, cognitive development, evolution and learning, relations between knowledge and learning, decision making, problem solving, memory, neural networks, and agent-based modeling. He has over 390 research publications in these areas.

News:
  • Peter Helfer's paper on a molecular-level model of memory reconsolidation was published in May in PLOS Computational Biology (Helfer & Shultz, 2018). The first submission was positively regarded by all three reviewers. Reviewer #3 concluded: “This is a very elegant paper presenting a computational model of pathways involved in late-LTP to see whether they can create the stability required to generate persistent memories. The key claim is that this long-term stability (longer than protein turnover) can be generated by linking two feedback loops: 1. PMK zeta initiating local translation of PMK zeta mRNA and 2. PMK zeta and GluR2-containing AMPARs preventing each other's removal from the synapse. The model focuses on PKM zeta and the pathways it is involved in. The authors show that the computational model can reproduce a range of known features of L-LTP. This is a beautiful model, providing a valuable addition to the synaptic modelling landscape. The paper is very well written. I am considering making the introduction required reading for all my students!” See the abstract and URL under PUBLICATIONS / Memory.
  • Our paper on Modelling the Spread of Innovation in Wild Birds (Shultz, Montrey, & Aplin, 2017) was published online 28 June 2017 in the Journal of the Royal Society Interface. See RESEARCH HIGHLIGHTS for a brief summary.
  • Our preliminary paper on Converting Cascade-Correlation Neural Nets into Probabilistic Generative Models (Nobandegani & Shultz, 2017) was recently favorably reviewed by Synced: In-Depth AI Technology & Industry Review. They were impressed by our efforts in "bestowing important human-like ... features such as knowledge and imagination to machines." We presented a talk on this work at the July 2017 Cognitive Science annual meeting in London. Our paper received an unusual 5/5 positive reviews from this  highly competitive Cognitive Science conference.
  • Dominique Danco won the best-poster award at the 12 April 2017 McGill Cognitive Science Undergraduate Research Presentation Day. She reported our work on how humanitarianism might compete more successfully with ethnocentrism in the evolution of cooperation. 
  • Our paper providing a novel resolution of Rogers' paradox about the inability of social learning to enhance population fitness appears in the February 2017 issue of Journal of Theoretical Biology. See  RESEARCH HIGHLIGHTS for a quick summary of the major findings.