Dynamic Friday Tutorials

The goal of the Dynamic Friday Tutorials is to build the DFT community by presenting 'case study' tutorials in an on-line, discussion-oriented, and hands-on environment. The first three case studies will build on three recent papers:

  1. October 7th: Spencer (2020) Current Directions in Psychological Science [3-layer visual working memory model]
  2. November 4th: Spencer, Ross-Sheehy & Eschman (2022) Infancy [IOWA spatial attention model]
  3. December 2nd: Bhat, Spencer & Samuelson (2022) Psychological Review [WOLVES word learning model]

In advance of the meeting, the presenter will pre-record a talk to accompany each of the papers above. Attendees will be expected to listen to the talk and preview the paper in advance. Then, on the day of the event, the presenter will give a brief recap of the talk (e.g., 5-min overview) and open the floor for an on-line discussion. This will be followed by a hands-on tutorial session walking through simulators of the particular model (using, for instance, CEDAR or COSIVINA). The goal is to unpack the model and to help facilitate work with dynamic field models more generally.

Sessions will run from 3:30-5pm UK time (10:30am Eastern Standard Time in the US; 4:30pm in Europe)

Suggested Readings

(available online)

  1. Spencer, J. P. (2020). The development of working memory. Current Directions in Psychological Science, doi/10.1177/0963721420959835.
  2. Spencer, J.P., Ross-Sheehy, S. & Eschman, B. (2022). Testing predictions of a neural process model of visual attention in infancy across competitive and non-competitive contexts. Infancy.
  3. Bhat, A., Spencer, J.P. & Samuelson, L.K. (2021). Word-Object Learning via Visual Exploration in Space (WOLVES): A Neural Process Model of Cross-Situational Word Learning. Psychological Review, https://doi.org/10.1037/rev0000313.

Target Audience

No specific prior knowledge of the mathematics of dynamical systems models or neural networks is required. An interest in formal approaches to cognition and development is an advantage.

To register (on Teams), use the link on this page.