Table 1.

Noise model parameters for motor, sensory, or combined motor and sensory noise sources

Noise Model	Motor noise parameters				Sensory noise parameters					Fit Error
	r m1	n m	α m	r m2	n p	n g	n t	α s	r s
M1	0.0114	588	1.31							395
M2		274	1.87	0.0449						573
M3	0.0098	540	1.35	0.0109						390
S1					5.03 × 10-4	0.0067	8037	1.26		150
S2					4.99 × 10-4	0.0063	9573	1.22	0.0130	136
S3					5.07 × 10-4	0.0039	7033	1.28	0.00346	146
S1M1	1.63 × 10-6	0.148	3.64		6.09 × 10-4	0.0067	2727	1.21		115
S1M2		0.445	3.58	0.0143	5.44 × 10-4	0.0061	0	1.27		128
aS1M3	1.45 × 10-6	0.157	3.67	0.0163	6.01 × 10-4	0.0063	1850	1.20		102
aS2M1	2.19 × 10-6	0.0487	3.61		5.84 × 10-4	0.0072	10225	1.07	0.0140	101
S2M2		0.409	3.60	0	5.60 × 10-4	0.0061	112	1.26	0.0126	126
aS2M3	6.44 × 10-7	0.0344	3.88	0	5.89 × 10-4	0.0064	5182	1.17	0.0130	98
S3M1	9.99 × 10-7	0.142	3.75		6.29 × 10-4	0.0059	322	1.25	8.20x10-4	116
S3M2		0.959	3.38	0.0147	5.23 × 10-4	0.0044	0	1.25	0.0025	128
aS3M3	3.93 × 10-6	0.558	3.43	0.0166	6.03 × 10-4	0.0064	45	1.17	0	103

^aindicates the noise models that had low and comparable fit errors values

The functional form of the various sensory and motor noise models are given in Methods. The fit error is defined as the value of the loss function J ₂ (see Methods)