Table 2. Parameters, their ranges and values, in the different models.

The presence of a parameter in a model is indicated by either a check mark (when it can be fit on its own), a ratio (when it can be fit as a ratio with another parameter), or = 1 when it takes the value 1.

Parameter and range	Path Integration	Kalman Filter	Cue Combination	Hybrid
Velocity gain, γd 0 ≤ γd ≤ 4	= 1	✓	✓	✓
Variance of velocity noise, ${\sigma }_d^2$ 0 ≤ σd ≤ 20	σd/γd	✓	✓	✓
Target gain, γA 0 ≤ γA ≤ 2	γA/γd	✓	✓	✓
Target bias, βA −180 ≤ βA ≤ +180	βA/γd	✓	✓	✓
Variance of target noise, ${\sigma }_A^2$ 0 ≤ σA ≤ 20	σA/γd	✓	✓	✓
Participant’s initial uncertainty, $s_0^2$ 0 ≤ s0 ≤ 20		s0/sf	✓	✓
Participant’s velocity noise variance, $s_d^2$ 0 ≤ sd ≤ 20		sd/sf	✓	✓
Participant’s feedback noise variance, $s_f^2$ 0 ≤ sf ≤ 50		= 1	✓	✓
Participant’s prior on true feedback, r 0 ≤ r ≤ 1			✓	✓