Spectral Encoding of Seen and Attended Object Categories in the Human Brain.

Local field potentials (LFPs) encode visual information via variations in power at many frequencies. These variations are complex and depend on stimulus and cognitive state in ways that have yet to be fully characterized. Specifically, the frequencies (or combinations of frequencies) that most robustly encode specific types of visual information are not fully known. To address this knowledge gap, we used intracranial EEG to record LFPs at 858 widely distributed recording sites as human subjects (six males, five females) indicated whether briefly presented natural scenes depicted one of three attended object categories. Principal component analysis applied to power spectra of the LFPs near stimulus onset revealed a broadband component (1-100 Hz) and two narrowband components (1-8 and 8-30 Hz, respectively) that encoded information about both seen and attended categories. Interestingly, we found that seen and attended categories were not encoded with the same fidelity by these distinct spectral components. Model-based tuning and decoding analyses revealed that power variations along the broadband component were most sharply tuned and offered more accurate decoding for seen than for attended categories. Power along the narrowband delta-theta (1-8 Hz) component robustly decoded information about both seen and attended categories, while the alpha-beta (8-30 Hz) component was specialized for attention. We conclude that, when viewing natural scenes, information about the seen category is encoded via broadband and sub-gamma (<30 Hz) power variations, while the attended category is most robustly encoded in the sub-gamma range. More generally, these results suggest that power variation along different spectral components can encode qualitatively different kinds of visual information. In this article, we characterize how changes in visual stimuli depicting specific objects (cars, faces, and buildings) and changes in attention to those objects affect the frequency content of local field potentials in the human brain. In contrast to many previous studies that have investigated encoding by variations in power at high (>30 Hz) frequencies, we find that the most important variation patterns are broadband (i.e., distributed across multiple frequencies) and narrowband, but in lower frequencies (<30 Hz). Interestingly, we find that seen and attended categories are not encoded with the same fidelity by these distinct spectral encoding patterns, suggesting that power at different frequencies can encode qualitatively different kinds of information.