The sensory experience of transcranial magnetic stimulation (TMS) evokes cortical responses measured in electroencephalography (EEG) that confound interpretation of TMS-evoked potentials (TEPs). Methods for sensory masking have been proposed to minimize sensory contributions to the TEP, but the most effective combination for suprathreshold TMS to dorsolateral prefrontal cortex (dlPFC) is unknown. We applied sensory suppression techniques and quantified electrophysiology and perception from suprathreshold dlPFC TMS to identify the best combination to minimize the sensory TEP. In 21 healthy adults, we applied single pulse TMS at 120% resting motor threshold (rMT) to the left dlPFC and compared EEG vertex N100-P200 and perception. Conditions included three protocols: No masking (no auditory masking, no foam, and jittered interstimulus interval [ISI]), Standard masking (auditory noise, foam, and jittered ISI), and our ATTENUATE protocol (auditory noise, foam, over-the-ear protection, and unjittered ISI). ATTENUATE reduced vertex N100-P200 by 56%, "click" loudness perception by 50%, and scalp sensation by 36%. We show that sensory prediction, induced with predictable ISI, has a suppressive effect on vertex N100-P200, and that combining standard suppression protocols with sensory prediction provides the best N100-P200 suppression. ATTENUATE was more effective than Standard masking, which only reduced vertex N100-P200 by 22%, loudness by 27%, and scalp sensation by 24%. We introduce a sensory suppression protocol superior to Standard masking and demonstrate that using an unjittered ISI can contribute to minimizing sensory confounds. ATTENUATE provides superior sensory suppression to increase TEP signal-to-noise and contributes to a growing understanding of TMS-EEG sensory neuroscience.

Background: Repetitive transcranial magnetic stimulation (rTMS) to the dorsolateral prefrontal cortex (dlPFC) is an effective treatment for depression, but the neural response to rTMS remains unclear. TMS with electroencephalography (TMS-EEG) can probe these neural effects, but variation in TMS-evoked potentials (TEPs) across the dlPFC are not well characterized and often obscured by muscle artifact. Mapping TEPs and artifacts across dlPFC targets is needed to identify high fidelity subregions that can be used for rTMS treatment monitoring. Objective: To characterize ′early TEPs′ anatomically and temporally close (20-50 ms) to the TMS pulse and associated muscle artifacts (<20 ms) across the dlPFC. We hypothesized that TMS location and angle would affect these early TEPs and that TEP size would be inversely related to muscle artifact. We sought to identify an optimal TMS target / angle for the group and asked if individualization would be beneficial. Methods: In 16 healthy participants, we applied single-pulse TMS to six targets within the dlPFC at two coil angles and measured EEG responses. Results: Early TEPs were sensitive to stimulation location, with posterior and medial targets yielding larger early TEPs. Regions with high early TEP amplitude had less muscle artifact, and vice versa. The best group-level target yielded 102% larger TEP responses compared to other standard targets. Optimal TMS target differed across subjects, suggesting that a personalized targeting approach could boost the early TEP by additional 36%. Conclusions: The early TEPs can be probed without significant muscle-related confounds in posterior-medial regions of the dlPFC. A personalized targeting approach may further enhance the signal quality of the early TEP.

Purpose: Despite optimal local therapy, tumor cell invasion into normal brain parenchyma frequently results in recurrence in patients with solid tumors. The aim of this study was to determine whether microvascular inflammation can be targeted to better delineate the tumor-brain interface through vascular cell adhesion molecule-1 (VCAM-1)-targeted MRI. Experimental Design: Intracerebral xenograft rat models of MDA231Br-GFP (breast cancer) brain metastasis and U87MG (glioblastoma) were used to histologically examine the tumor-brain interface and to test the efficacy of VCAM-1–targeted MRI in detecting this region. Human biopsy samples of the brain metastasis and glioblastoma margins were examined for endothelial VCAM-1 expression. Results: The interface between tumor and surrounding normal brain tissue exhibited elevated endothelial VCAM-1 expression and increased microvessel density. Tumor proliferation and stemness markers were also significantly upregulated at the tumor rim in the brain metastasis model. T2*-weighted MRI, following intravenous administration of VCAM-MPIO, highlighted the tumor-brain interface of both tumor models more extensively than gadolinium-DTPA–enhanced T1-weighted MRI. Sites of VCAM-MPIO binding, evident as hypointense signals on MR images, correlated spatially with endothelial VCAM-1 upregulation and bound VCAM-MPIO beads detected histologically. These findings were further validated in an orthotopic medulloblastoma model. Finally, the tumor-brain interface in human brain metastasis and glioblastoma samples was similarly characterized by microvascular inflammation, extending beyond the region detectable using conventional MRI. Conclusions: This work illustrates the potential of VCAM-1–targeted MRI for improved delineation of the tumor-brain interface in both primary and secondary brain tumors.