Three-parameter model (σ, σ_{m}_{e, rewarded}, σ_{e, unrewarded}) | Two-parameter model (σ, σ_{m})_{e} | One-parameter model (σ)_{e} | |
---|---|---|---|

Experiment 1 | 0 | 1735 | 392 |

Experiment 2 | 0 | 389 | 272 |

Cerebellar | 184 | 0 | 1232 |

Our model comprised three parameters: the SDs of the Gaussian distributions of motor noise (σ

) and exploration following rewarded (σ_{m}_{e}_{, rewarded}) and unrewarded (σ_{e}_{, unrewarded}) trials. To examine the relative importance of each model parameter, we compared the full model to two reduced models: one where exploration variability does not depend on reward history (two-parameter model: σand σ_{m}) and one that does not include motor noise (one-parameter model: σ_{e}). Model comparisons using BIC show the three-parameter model best fit the data from experiments 1 and 2, and the two-parameter model best fit data from the group with cerebellar damage. For each experiment, we show the difference in BIC relative to the best model (i.e., the one with 0)._{e}