Mapping Sensorimotor Cortex With Slow Cortical Potential Resting-State Networks While Awake and Under Anesthesia

BACKGROUND: The emerging insight into resting-state cortical networks has been important in our understanding of the fundamental architecture of brain organization. These networks, which were originally identified with functional magnetic resonance imaging, are also seen in the correlation topography of the infraslow rhythms of local field potentials. Because of the fundamental nature of these networks and their independence from task-related activations, we posit that, in addition to their neuroscientific relevance, these slow cortical potential networks could play an important role in clinical brain mapping. OBJECTIVE: To assess whether these networks would be useful in identifying eloquent cortex such as sensorimotor cortex in patients both awake and under anesthesia. METHODS: This study included 9 subjects undergoing surgical treatment for intractable epilepsy. Slow cortical potentials were recorded from the cortical surface in patients while awake and under propofol anesthesia. To test brain-mapping utility, slow cortical potential networks were identified with data-driven (seed-independent) and anatomy-driven (seed-based) approaches. With electrocortical stimulation used as the gold standard for comparison, the sensitivity and specificity of these networks for identifying sensorimotor cortex were calculated. RESULTS: Networks identified with a data-driven approach in patients under anesthesia and awake were 90% and 93% sensitive and 58% and 55% specific for sensorimotor cortex, respectively. Networks identified with systematic seed selection in patients under anesthesia and awake were 78% and 83% sensitive and 67% and 60% specific, respectively. CONCLUSION: Resting-state networks may be useful for tailoring stimulation mapping and could provide a means of identifying eloquent regions in patients while under anesthesia.