This is the rhythm of your eyes: the phase of ongoing electroencephalogram oscillations modulates saccadic reaction time

Abstract

Motor reaction times in humans are highly variable from one trial to the next, even for simple and automatic tasks, such as shifting your gaze to a suddenly appearing target. Although classic models of reaction time generation consider this variability to reflect intrinsic noise, some portion of it could also be attributed to ongoing neuronal processes. For example, variations of alpha rhythm frequency (8-12 Hz) across individuals, or alpha amplitude across trials, have been related previously to manual reaction time variability. Here we investigate the trial-by-trial influence of oscillatory phase, a dynamic marker of ongoing activity, on saccadic reaction time in three paradigms of increasing cognitive demand (simple reaction time, choice reaction time, and visual discrimination tasks). The phase of ongoing prestimulus activity in the high alpha/low beta range (11-17 Hz) at frontocentral locations was strongly associated with saccadic response latencies. This relation, present in all three paradigms, peaked for phases recorded ∼50 ms before fixation point offset and 250 ms before target onset. Reaction times in the most demanding discrimination task fell into two distinct modes reflecting a fast but inaccurate strategy or a slow and efficient one. The phase effect was markedly stronger in the group of subjects using the faster strategy. We conclude that periodic fluctuations of electrical activity attributable to neuronal oscillations can modulate the efficiency of the oculomotor system on a rapid timescale; however, this relation may be obscured when cognitive load also adds a significant contribution to response time variability.

Figures

Figure 1.

Task design and corresponding RT distributions. Left column, Illustration of the three task paradigms used to record saccadic responses (size not to scale). The easy task involved the detection of the onset of a dot that alternated predictably (but with random intertrial intervals) between the left and right sides of the screen. The medium task required the localization of a single target dot that could appear randomly on either side of the screen. The difficult task implied the discrimination of two simultaneously presented shapes, the target being defined as the one with a gap oriented upward. In all three tasks, participants were instructed to make an eye movement, as quickly and accurately as possible, to the location of the target. Right column, Saccadic RT histograms of all trials, normalized for each subject and then pooled across subjects. The blue bars denote correct trials, and the red bars denote incorrect trials. Note the pronounced bimodality in task 3; the dashed black line at 282 ms represents the boundary criterion for fast versus slow subjects. SO, Stimulus onset.

Figure 2.

Illustration of our experimental approach with simulated data. Within the first two rows, the phase is represented by the rotational angle and the associated response time by radius (see top left item). The top row illustrates different selections of trial subsets. On the left, a complete selection encompasses all trials. On the right, five successive RT quintiles are shown. For each quintile, the red annulus indicates the range of RTs selected. The middle row displays hypothetical data with a spiral structure: each point corresponds to one trial with a particular phase value (at a given time point and frequency of interest) and an associated RT. The trials selected for each RT quintile are highlighted in red. The bottom row shows the polar phase histograms corresponding to each subset of trials. Phase is represented by the rotational angle and trial number in each bin by the corresponding radius. No apparent phase locking or ITC is expected on the left side when computed across all trials. However, each individual RT quintile shows strong phase locking (right). Within this context, our analysis relied on a statistical comparison between ITC values calculated for the left versus the right histograms. (For statistical consistency, 100 random selections of 20% of all trials were applied to the left-hand side data, and the resulting ITCs were averaged before comparison with the quintile-specific ITC values on the right).

Figure 3.

Main results of the bootstrapping ITC analysis on RT quintiles. A, The p value resulting from a comparison between ITC in RT quintiles and ITC over the same number of randomly selected trials is shown as a function of time point and EEG frequency at which the phase value was determined. ITC values for this analysis were pooled across participants, experimental tasks, RT quintiles, and electrodes. Black outlines designate areas deemed significant after correction for multiple comparisons using the FDR procedure (threshold 0.001). The white dashed line marks the time of the gap onset (fixation offset), and the continuous white line marks the time of stimulus onset (SO). B, Topographic mapping of the p values of the pre-gap effect shown in A, highlighted by box “B” (11–17 Hz, 290–190 ms before stimulus onset). The 12 electrodes of interest are highlighted in white: all additional analyses were performed on this subset of electrodes. C, Topographic mapping of peak post-gap effects shown in A, highlighted by box “C” (50–150 ms after stimulus onset, 2–70 Hz range).

Figure 4.

Results for the three individual tasks. p values resulting from the bootstrapping ITC analysis (as in Fig. 3A) are shown separately for each of the three tasks. In all three tasks, significant effects can be seen within a similar time–frequency region (11–17 Hz, 0–100 ms before gap onset). Black outlines highlight regions above FDR threshold. Small insets show topography of activity in the region of interest defined in Figure 3B. SO, Stimulus onset.

Figure 5.

Difficult task: separation of participants based on response strategy. Twelve of the 13 subjects were assigned into fast (A) and slow (B) groups (n = 6 each) according to their median latencies. The corresponding time–frequency maps of p values (C, D) indicate a significant effect of prestimulus phase on saccadic RT only for the fast subject group (conventions as in Figs. 3, 4). SO, Stimulus onset.

Figure 6.

Global phase progression. Top, Latency histogram across all subjects, experimental tasks, and trials. The vertical black dashed lines delimit quintiles, and the blue dashed lines traversing the top and middle graphs mark the median RT of the respective quintiles. A sliding window containing 20% of trials was moved progressively across the RT histogram, starting with the first quintile, shifting at each step by one trial until reaching the last quintile. Middle graph, Phase progression in moving window. The black line represents the mean phase in the subset of trials (unwrapped for increased readability), and the red line represents the concentration parameter (both mean phase and concentration parameters were derived using a Von Mises fit). Three red horizontal lines specify equivalent p levels of the concentration parameter of p < 0.05, p < 0.01, and p < 0.001. The inset illustrates this phase progression in polar coordinates (phase represented by angle and RT by radius): a spiral shape emerges. Bottom row, Phase histograms of all trials in the moving window, at time points corresponding to the five disjoint quintiles used in previous analyses. The red arrow indicates the mean phase angle, and the red circle illustrates the corresponding Von Mises fit. Results of Rayleigh tests of the significance of the mean direction in a circular distribution are reported below. For increased visibility (and for display purposes only), a fixed trial number was subtracted from each phase bin.