Decoding stimulus-reward pairing from local field potentials recorded from monkey visual cortex.

Single-trial decoding of brain recordings is a real challenge, since it pushes the signal-to-noise ratio issue to the limit. In this paper, we concentrate on the single-trial decoding of stimulus-reward pairing from local field potentials (LFPs) recorded chronically in the visual cortical area V4 of monkeys during a perceptual conditioning task. We developed a set of physiologically meaningful features that can classify and monitor the monkey's training performance. One of these features is based on the recently discovered propagation of waves of LFPs in the visual cortex. Time-frequency features together with spatial features (phase synchrony and wave propagation) yield, after applying a feature selection procedure, an exceptionally good single-trial classification performance, even when using a linear classifier.