Encoding of brain state changes in local field potentials modulated by motor behaviors

摘要: Local field potentials (LFPs) measure aggregate neural activity resulting from the coordinated firing of neurons within a local network. We hypothesized that state parameters associated with underlying brain dynamics may be encoded in LFPs but not directly measurable signal temporal and spectral contents. Using Kalman filter we estimated latent changes recorded monkey motor cortical areas during execution visually instructed reaching task, under different applied force conditions. Prior to estimation, matched filtering was performed decouple behavior-relevant signals (Stamoulis Richardson, J Comput Neurosci, 2009) unrelated background oscillations. State baseline oscillations appeared insignificant. In contrast, LFP components movement were significant. Approximately direction-invariant vectors consistently observed. Their patterns invariant also conditions, peak first 200 ms interval, exponentially decreasing zero approximately onset, time at which velocity reached its peak. Thus, modulated by neither direction nor mechanical environment. Finally, compared using basis functions obtained through Principal Component Analysis. The pattern vector very similar PCA component, further suggesting encode fluctuations behavior.