Correlative evidence provides support for the idea that brain oscillations underpin neural computations. Recent work using rhythmic stimulation techniques in humans provide causal evidence but the interactions of these external signals with intrinsic rhythmicity remain unclear. Here, we show that sensorimotor cortex follows externally applied rhythmic TMS (rTMS) stimulation in the beta-band but that the elicited responses are strongest at the intrinsic individual beta peak frequency. While these entrainment effects are of short duration, even subthreshold rTMS pulses propagate through the network and elicit significant cortico-spinal coupling, particularly when stimulated at the individual beta-frequency.Our results show that externally enforced rhythmicity interacts with intrinsic brain rhythms such that the individual peak frequency determines the effect of rTMS. The observed downstream spinal effect at the resonance frequency provides evidence for the causal role of brain rhythms for signal propagation.

In ERP and other large multidimensional neuroscience data sets, researchers often select regions of interest (ROIs) for analysis. The method of ROI selection can critically affect the conclusions of a study by causing the researcher to miss effects in the data or to detect spurious effects. In practice, to avoid inflating Type I error rate (i.e., false positives), ROIs are often based on a priori hypotheses or independent information. However, this can be insensitive to experiment-specific variations in effect location (e.g., latency shifts) reducing power to detect effects. Data-driven ROI selection, in contrast, is nonindependent and uses the data under analysis to determine ROI positions. Therefore, it has potential to select ROIs based on experiment-specific information and increase power for detecting effects. However, data-driven methods have been criticized because they can substantially inflate Type I error rate. Here, we demonstrate, using simulations of simple ERP experiments, that data-driven ROI selection can indeed be more powerful than a priori hypotheses or independent information. Furthermore, we show that data-driven ROI selection using the aggregate grand average from trials (AGAT), despite being based on the data at hand, can be safely used for ROI selection under many circumstances. However, when there is a noise difference between conditions, using the AGAT can inflate Type I error and should be avoided. We identify critical assumptions for use of the AGAT and provide a basis for researchers to use, and reviewers to assess, data-driven methods of ROI localization in ERP and other studies.

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Increased computer use in clinical settings offers an opportunity to develop new neuropsychological tests that exploit the control computers have over stimulus dimensions and timing. However, before adopting new tools, empirical validation is necessary. In the current study, our aims were twofold: to describe a computerized adaptive procedure with broad potential for neuropsychological investigations, and to demonstrate its implementation in testing for visual hemispatial neglect. Visual search results from adaptive psychophysical procedures are reported from 12 healthy individuals and 23 individuals with unilateral brain injury. Healthy individuals reveal spatially symmetric performance on adaptive search measures. In patients, psychophysical outcomes (as well as those from standard paper-and-pencil search tasks) reveal visual hemispatial neglect. Consistent with previous empirical studies of hemispatial neglect, lateralized impairments in adaptive conjunction search are greater than in adaptive feature search tasks. Furthermore, those with right hemisphere damage show greater lateralized deficits in conjunction search than do those with left hemisphere damage. We argue that adaptive tests, which automatically adjust to each individual's performance level, are efficient methods for both clinical evaluations and neuropsychological investigations and have the potential to detect subtle deficits even in chronic stages, when flagrant clinical signs have frequently resolved. (JINS, 2008, 14, 243-256.)