Prestimulus oscillations enhance psychophysical performance in humans

Abstract

The presence of various ongoing oscillations in the brain is correlated with behavioral states such as restful wakefulness or drowsiness. However, even when subjects aim to maintain a high level of vigilance, ongoing oscillations exhibit large amplitude variability on time scales of hundreds of milliseconds to seconds, suggesting that the functional state of local cortical networks is continuously changing. How this volatility of ongoing oscillations influences the perception of sensory stimuli has remained essentially unknown. We investigated the relationship between prestimulus neuronal oscillations and the subjects' ability to consciously perceive and react to somatosensory stimuli near the threshold of detection. We show that, for prestimulus oscillations at approximately 10, 20, and 40 Hz detected over the sensorimotor cortex, intermediate amplitudes were associated with the highest probability of conscious detection and the shortest reaction times. In contrast, for 10 and 20 Hz prestimulus oscillations detected over the parietal region, the largest amplitudes were associated with the best performance. Our data indicate that the prestimulus oscillatory activity detected over sensorimotor and parietal cortices has a profound effect on the processing of weak stimuli. Furthermore, the results suggest that ongoing oscillations in sensory cortices may optimize the processing of sensory stimuli with the same mechanism as noise sources in intrinsic stochastic resonance.

Figure 1.

Dynamics of ongoing oscillations at 10 Hz. A, The positions of channels that covered the left and right sensorimotor (gray) and parietal (black) regions are shown on a flattened view of the helmet-shaped sensor array. Each rectangle represents the two joint planar gradiometers. B, The amplitude spectral density (ASD) plots of the MEG signals have distinct peaks at ∼10 Hz with local maxima over parietal and left and right sensorimotor regions (insets are computed from all of the 20 min sessions and averaged across the 4 selected channels in each region and across all subjects). Max., Maximum; Min., minimum. C, The amplitude (Amp.) envelope of 10 Hz oscillations from a representative subject and a channel over the right sensorimotor region shows that these oscillations exhibit large amplitude variability on time scales of hundreds of milliseconds to tens of seconds. D, Somatosensory-evoked fields were visible in the grand average of both detected (thin lines) and undetected (thick lines) trials (data from a representative channel over the right sensorimotor region). E, The 10 Hz oscillation amplitude attenuated transiently after stimulation for both detected and undetected trials (the average is across all trials, across selected channels and subjects, and over both hemispheres, giving a total of 7697 detected and 16,355 undetected trials).

Figure 2.

Evidence for linear and parabolic dependences of performance on prestimulus oscillation amplitude. For trials belonging to 10 levels of prestimulus amplitudes of 10 Hz oscillations in a prestimulus window of 1000 msec, we have plotted the change in hit rate (ΔHR) relative to the mean across all trials (see Materials and Methods for details). The best performance is seen at intermediate amplitudes of oscillations over sensorimotor regions (A) and at the largest amplitudes of oscillations over the parietal cortex (B). The difference in reaction time (ΔRT) relative to the mean across all trials also exhibited a parabolic and a linear dependence on the prestimulus amplitudes over sensorimotor (C) and parietal (D) regions, respectively. The data points indicate the grand-average mean ± SEM (n = 14). A least-squares fit to the data of a third-order polynomial is indicated by the solid lines in A and C. The hit-rate change of the first (squares), fifth (dots), and 10th (circles) amplitude bin is plotted as a function of the prestimulus-window size for sensorimotor (E) and parietal (F) channels. The same plots for the reaction time are shown in G and H. The changes in both hit rates and reaction times exhibit clear trends toward a poorer performance for small-amplitude states with increasing prestimulus time scales (squares). Conversely, the large-amplitude states show worse performance with smaller time windows (circles). These dependencies were common to the sensorimotor and parietal regions. Significant linear trends in E-H are marked with an asterisk to the right of the least-squares fitted lines. Amp., Amplitude.

Figure 3.

The dependence of hit rate on oscillations over the sensorimotor and parietal regions. The same plot as in Figure 2 A is shown, but for different frequency bands over the sensorimotor (A-D) and parietal (E-H) regions. ΔHR, Change in hit rate; Amp., amplitude.