Strategy inference during learning via cognitive activity-based credit assignment models


  • Moongathottathil James Ashwin
  • Reynaud-Bouret Patricia
  • Mezzadri Giulia
  • Sargolini Francesca
  • Bethus Ingrid
  • Muzy Alexandre


  • Learning strategies model selection chunking

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We develop a method for selecting meaningful learning strategies based solely on the behavioral data of a single individual in a learning experiment. We use simple Activity-based Credit Assignment algorithms to model the different strategies and couple them with a novel hold-out statistical selection method. Application on rat behavioral data in a continuous T-maze task reveals a particular learning strategy that consists in chunking the paths used by the animal. Neuronal data collected in the dorsomedial striatum confirm this strategy.

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