Author response table 1. Bayes Factor Analysis on Orientation Discrimination data.

Table 1a and 1b reports the results of the BF analysis that tested the two models, null and Stimulation Condition (Condition). P(M) indicates the prior probabilities of each model to be equal (prior model odds). P(M|data) reports the updated probabilities having taken into consideration the data (posterior model probabilities); BFM indicates how much the data have changed the prior model odds. BF10 indicates the Bayes factors for each model (the BF10 for stimulation condition indicates how many times data are more likely to fall under the stimulation model, rather than the null model). Error % indicates the sensitivity to numerical fluctuations. Table 1c reports the results of the post-hoc Tests BF analysis. The posterior odds have been corrected for multiple testing by fixing to 0.5 the prior probability that the null hypothesis holds across all comparisons (Westfall et al. 1997). Individual comparisons are based on the default t-test with a Cauchy (0, r = 1/sqrt(2)) prior. The "U" in the Bayes factor denotes that it is uncorrected.

Table 1a
Bayesian Repeated Measures ANOVA
Data Input: OD pre, and post-stimulation performance
Model Comparison
Models	P(M)	P(MIdata)	BF m	BF 10	Error %
Null model (inc. subject)	0.200	0.011	0.046	1.000
RM Factor + Condition + RM * Condition	0.200	0.945	69.335	83.962	2.528
RM Factor	0.200	0.031	0.126	2.713	6.920
RM Factor + Condition	0.200	0.009	0.038	0.834	2.510
Condition	0.200	0.003	0.013	0.297	0.664
Note. All models include subject
Table 1b
Bayesian ANOVA
Data Input: OD performance changes
Model Comparison
Models	P(M)	P(MIdata)	BF m	BF 10	error %
Null model	0.500	0.010	0.010	1.00
Condition	0.500	0.990	99.956	99.956	5.865e -4
Table 1c
Bayesian ANOVA
Post Hoc Comparison – Cond
Models	Prior Odds	Posterior Odds	BF 10,u	error %
Parietal vs Sham	0.587	18.103	30.818	2.505e -4
Parietal vs hMT	0.587	11.304	19.243	8.095e 4
Sham vs hMT	0.587	0.299	0.510	6.066e -4