Table 2 Model parameters.

From: The visual geometry of a tool modulates generalization during adaptation

Model M13

α 1

α 2

β 1

β 2

\({c}_{E}^{1}={c}_{E}^{2}\)

\({c}_{A}^{1}={c}_{A}^{2}\)

0.8794

0.9897

0.1891

0.0453

0.3070

0.1193

Model M14

α 1

α 2

β 1

β 2

\({c}_{E}^{1}\)

\({c}_{A}^{1}\)

\({c}_{E}^{2}={c}_{A}^{2}\)

0.8809

0.9898

0.1873

0.0445

0.3546

0.0678

0.2146

  1. The best fit parameter values for M13 and M14. In M13, the coupling factor equally affects the fast and slow processes (the superscripts 1 and 2, respectively) and is separately fit to the Explicit (subscript E) and Ambiguous (subscript A) groups. In M14, coupling is separate for each group for the fast process (superscript 1), while shared between the groups for the slow process (superscript 2).