Snyder AC, Smith MA. Stimulus-dependent spiking relationships with the EEG. J Neurophysiol 114: 1468 -1482. First published June 24, 2015 doi:10.1152/jn.00427.2015The development and refinement of noninvasive techniques for imaging neural activity is of paramount importance for human neuroscience. Currently, the most accessible and popular technique is electroencephalography (EEG). However, nearly all of what we know about the neural events that underlie EEG signals is based on inference, because of the dearth of studies that have simultaneously paired EEG recordings with direct recordings of single neurons. From the perspective of electrophysiologists there is growing interest in understanding how spiking activity coordinates with large-scale cortical networks. Evidence from recordings at both scales highlights that sensory neurons operate in very distinct states during spontaneous and visually evoked activity, which appear to form extremes in a continuum of coordination in neural networks. We hypothesized that individual neurons have idiosyncratic relationships to large-scale network activity indexed by EEG signals, owing to the neurons' distinct computational roles within the local circuitry. We tested this by recording neuronal populations in visual area V4 of rhesus macaques while we simultaneously recorded EEG. We found substantial heterogeneity in the timing and strength of spike-EEG relationships and that these relationships became more diverse during visual stimulation compared with the spontaneous state. The visual stimulus apparently shifts V4 neurons from a state in which they are relatively uniformly embedded in large-scale network activity to a state in which their distinct roles within the local population are more prominent, suggesting that the specific way in which individual neurons relate to EEG signals may hold clues regarding their computational roles. EEG; local field potential; spiking activity ELECTROENCEPHALOGRAPHY (EEG) has been a boon to human neuroscience. Because EEG is noninvasive, it is one of the few methods that can be used to measure human brain activity in both health and disease. Moreover, EEG has advantages over other neuroimaging methods. The cost is relatively low, compared with approaches such as functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG); there is no ionizing radiation, as with positron emission tomography (PET); the materials are portable (even usable with actively moving subjects; De Sanctis et al. 2012;Makeig et al. 2009), unlike nearly all alternatives; and the temporal resolution is exquisitely fine, unlike functional near-infrared spectroscopy (fNIRS) and fMRI. EEG covers a wide range of neurophysiological applications, from diagnosis of brain stem lesions to basic research on complex cognition.The principal limitation of EEG is spatial resolution. Typically, EEG is useful for implicating activity in parts of the brain on the order of a cubic centimeter (Sejnowski et al. 2014). The computational machinations of the neurons within ...