Test of No E⁄ect H$_{0}$ Fractional Increase A$_{Z}$= E e T$_{Z}$ Deviate Point Estimate 95% CI Filtered k=2 10.974 0.099 0.084 k=5 12.528 0.271 0.235 k=10 11.103 0.445 0.379 Table 4: Comparison of STN activity with robust covariance adjustment for head move- ment. adjustment. Table 4 applies the method of Table 2 to residuals of STN levels after adjustment for six covariates describing translation and rotation of the head as estimated from three-dimensional images of each session, the residuals being obtaining using the default settings of the R function rlm which implements HuberGLYPH<146>s m-estimation. Table 4 is generally similar to Table 2, so covariance adjustment for head motion did not greatly alter the results. 5 A Simulation of the Size and Power of Competing Tests in the Presence of Interference Between Units 5.1 Description of the simulation Tables 5 and 6 report a simulation study of power with and without interference between units. Both tables refer to a completely randomized experiment; that is, there is a single block, B = 1 . In Table 5, there are N = 250 trials, whereas in Table 6 there are N = 1000 trials. Each trial is randomly assigned to be a treated trial or a control trial with probability 1 $_{2}$. As in the actual experiment in §1.3, only some treated trials elicit the intended cognitive activity and brain response. In Table 5, GLYPH<21> = 50% of treated trials are successful, whereas in Table 6, GLYPH<21> = 10% of treated trials are successful. A control trial yields a response drawn from a distribution F ( GLYPH<1> ) , and in Tables 5 and 6 this distribution F ( GLYPH<1> ) is either the 27