The 28th Bartlett Memorial Lecture. Causal learning: an associative analysis.

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Getting formal with dopamine and reward. (2002, unknown): “…that prediction errors, rather than simple stimulus-reinforcer pairings, play a crucial role in learning situations such as animal conditioning (Kamin, 1969), human conditioning (Martin and Levey, 1991), causal learning (Dickinson, 2001), and artificial network learning (Sutton and Barto, 1990).”
Knowledge mediates the timeframe of covariation assessment in human causal induction (2002, background): “Be that as it may, associative learning theory as applied to causal judgement (see, e.g., Dickinson, 2001; Shanks & Dickinson, 1987) seems to be incapable of accounting for the instructional effects we found on the assessment of delayed contingencies.”
States versus Rewards: Dissociable neural prediction error signals underlying model-based and model-free reinforcement learning (2010, background): “Prediction errors have been proposed as a putative mechanism for guiding learning of such causal associations (Dickinson, 2001), All peaks are corrected for the entire brain volume at p 0.05 unless stated otherwise.”