weights multiplied by the fMRI measurements. If a region of a subjectGLYPH<146>s brain has become unusually active, we expect this weighted average to become unusually large. Figure 2 is a pair of boxplots of this weighted average for the one session and one subject in Figure 1. In Figure 2, there is some indication that the responses in the stop or treated trials in Figure 1 are elevated. Although the analysis uses the responses in Figure 2 weighted by the hrf ( x ) function, the method is applicable with any method of scoring the trials that produces one number per trial. For instance, a response that is sometimes used is the correlation between the hrf ( x ) function and the sequence of responses that immediately follow a trial. 1.4 Outline Section 2 reviews notation from Rosenbaum (2007a) for treatment e⁄ects when interference may be present. In §3.1, a nonlinear rank statistic T$_{Z}$ is proposed for a randomized block design with blocks of unequal block sizes; in particular, T$_{Z}$ is intended to perform well when not all treated trials are successful in eliciting the intended cognitive activity. Under the null hypothesis of no treatment e⁄ect there is, of necessity, no interference among the treatment e⁄ects, and §3.2 uses ideas from Orban and Wolfe (1982) to obtain the null randomization distribution of the test statistic T$_{Z}$ . A conGLYPH<133>dence statement about the magnitude of e⁄ect with interference is then obtained by a pivotal argument in §3.3: it measures the magnitude of the di⁄erence between the actual trial and the uniformity trial. In §4, the method of §3.3 is applied to activation of the subthalamic nucleus in §1.3. A simulation in §5 evaluates the power of T$_{Z}$ in experiments with interference using a mixture model in which not all trials elicit the intended cognitive activity. 10