Decoding of Attentional State Using High-Frequency Local Field Potential Is As Accurate As Using Spikes.

Local field potentials (LFPs) in visual cortex are reliably modulated when the subject's focus of attention is cued into versus out of the receptive field of the recorded sites, similar to modulation of spikes. However, human psychophysics studies have used an additional attention condition, neutral cueing, for decades. The effect of neutral cueing on spikes was examined recently and found to be intermediate between cued and uncued conditions. However, whether LFPs are also precise enough to represent graded states of attention is unknown. We found in rhesus monkeys that LFPs during neutral cueing were also intermediate between cued and uncued conditions. For a single electrode, attention was more discriminable using high frequency (>30 Hz) LFP power than spikes, which is expected because LFP represents a population signal and therefore is expected to be less noisy than spikes. However, previous studies have shown that when multiple electrodes are used, spikes can outperform LFPs. Surprisingly, in our study, spikes did not outperform LFPs when discriminability was computed using multiple electrodes, even though the LFP activity was highly correlated across electrodes compared with spikes. These results constrain the spatial scale over which attention operates and highlight the usefulness of LFPs in studying attention.

Electrocorticogram (ECoG) Is Highly Informative in Primate Visual Cortex.

Neural signals recorded at different scales contain information about environment and behavior and have been used to control Brain Machine Interfaces with varying degrees of success. However, a direct comparison of their efficacy has not been possible due to different recording setups, tasks, species, etc. To address this, we implanted customized arrays having both microelectrodes and electrocorticogram (ECoG) electrodes in the primary visual cortex of 2 female macaque monkeys, and also recorded electroencephalogram (EEG), while they viewed a variety of naturalistic images and parametric gratings. Surprisingly, ECoG had higher information and decodability than all other signals. Combining a few ECoG electrodes allowed more accurate decoding than combining a much larger number of microelectrodes. Control analyses showed that higher decoding accuracy of ECoG compared with local field potential was not because of differences in low-level visual features captured by them but instead because of larger spatial summation of the ECoG. Information was high in the 30-80 Hz range and at lower frequencies. Information in different frequencies and scales was nonredundant. These results have strong implications for Brain Machine Interface applications and for study of population representation of visual stimuli.SIGNIFICANCE STATEMENT Electrophysiological signals captured across scales by different recording electrodes are regularly used for Brain Machine Interfaces, but the information content varies due to electrode size and location. A systematic comparison of their efficiency for Brain Machine Interfaces is important but technically challenging. Here, we recorded simultaneous signals across four scales: spikes, local field potential, electrocorticogram (ECoG), and EEG, and compared their information and decoding accuracy for a large variety of naturalistic stimuli. We found that ECoGs were highly informative and outperformed other signals in information content and decoding accuracy.