Measures of brain activation (e.g., changes in scalp electrical potentials) have become the most popular method for inferring brain function. However, examining brain disruption (e.g., examining behavior after brain injury) can complement activation studies. Activation techniques identify regions involved with a task, whereas disruption techniques are able to discover which regions are crucial for a task. Voxel-based lesion mapping can be used to determine relationships between behavioral measures and the location of brain injury, revealing the function of brain regions. Lesion mapping can also correlate the effectiveness of neurosurgery with the location of brain resection, identifying optimal surgical targets. Traditionally, voxel-based lesion mapping has employed the chi-square test when the clinical measure is binomial and the Student's t test when measures are continuous. Here we suggest that the Liebermeister approach for binomial data is more sensitive than the chi-square test. We also suggest that a test described by Brunner and Munzel is more appropriate than the t test for nonbinomial data because clinical and neuropsychological data often violate the assumptions of the t test. We test our hypotheses comparing statistical tests using both simulated data and data obtained from a sample of stroke patients with disturbed spatial perception. We also developed software to implement these tests (MRIcron), made freely available to the scientific community.

Spatial normalization reshapes an individual’s brain to match the shape and size of a template image. This is a crucial step required for group-level statistical analyses. The most popular standard templates are derived from MRI scans of young adults. We introduce specialized templates that allow normalization algorithms to be applied to stroke-aged populations. First, we developed a CT template: while this is the dominant modality for many clinical situations, there are no modern CT templates and popular algorithms fail to successfully normalize CT scans. Importantly, our template was based on healthy individuals with ages similar to what is commonly seen in stroke (mean 65 years old). This template allows studies where only CT scans are available. Second, we derived a MRI template that approximately matches the shape of our CT template as well as processing steps that aid the normalization of scans from older individuals (including lesion masking and the ability to generate high quality cortical renderings despite brain injury). The benefit of this strategy is that the resulting templates can be used in studies where mixed modalities are present. We have integrated these templates and processing algorithms into a simple SPM toolbox (http://www.mccauslandcenter.sc.edu/CRNL/tools/spm8-scripts).

Recent technological advances, such as functional imaging techniques, allow neuroscientists to measure and localize brain activity in healthy individuals. These techniques avoid many of the limitations of the traditional method for inferring brain function, which relies on examining patients with brain lesions. This has fueled the zeitgeist that the classical lesion method is an inferior and perhaps obsolescent technique. However, although the lesion method has important weaknesses, we argue that it complements the newer activation methods (and their weaknesses). Furthermore, recent developments can address many of the criticisms of the lesion method. Patients with brain lesions provide a unique window into brain function, and this approach will fill an important niche in future research.