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Poster F in Poster Session F: Thursday, August 6, 1:45 – 3:30 pm, Kimmel Center, Shorin & Rosenthal Rooms

Classification of Strategies in Reversal Learning Tasks Using a Mixture Model

Daniel Janko¹, Hans Kirschner¹, Markus Ullsperger¹; ¹Otto von Guericke University Magdeburg

Presenter: Daniel Janko

People employ different strategies for continuous environmental learning, and in the presented study we developed a computational model to disentangle these on the single-subject level. Simulations confirmed the model could correctly identify the generative strategy, though refinement is needed for a more flexible fitting procedure. Initial fitting of a constrained version to choice data showed promising results, identifying different behavioral strategies across participants. Future work will refine the model and examine how these strategies are expressed on the neural level using 7T fMRI.

Topic Area: Memory, Learning & Knowledge Structures