Neural correlates of spatial orienting in the human superior colliculus

Abstract

A natural visual scene contains more information than the visual system has the capacity to simultaneously process, requiring specific items to be selected for detailed analysis at the expense of others. Such selection and inhibition are fundamental in guiding search behavior, but the neural basis of these mechanisms remains unclear. Abruptly appearing visual items can automatically capture attention, but once attention has been directed away from the salient event, return to that same location is slowed. In non-human primates, signals associated with attentional capture (AC) and subsequent inhibition of return (IOR) have been recorded from the superior colliculus (SC)--a structure known to play a pivotal role in reflexive spatial orienting. Here, we sought to establish whether similar signals could be recorded from the human SC, as well as early retinotopic cortical visual areas, where signals associated with AC and IOR have yet to be investigated with respect to oculomotor responses. Using an optimized oculomotor paradigm together with high-field, high-spatial resolution functional magnetic resonance imaging and high-speed eye tracking, we demonstrate that BOLD signal changes recorded from the human SC correlate strongly with our saccadic measures of AC and IOR. A qualitatively similar pattern of responses was found for V1, but only the inhibitory response associated with IOR persisted through V2 and V3. Although the SC plays a role in mediating these automatic attentional biasing signals, the source of these signals is likely to lie in higher cortical areas.

Fig. 1.

Cue-target oculomotor task. A: participants maintained central fixation for 50–500 ms (jittered onset), then 2 peripheral ring placemarkers appeared either side of fixation for 500 ms, 1 of the rings briefly brightened for 75 ms, followed by an interstimulus interval (ISI) of 0, 50, 200, 300, 400, 500 ms before a target appeared (solid white circle) at either the cued (“SAME”) or the uncued (“OPPOSITE”) location. Participants made a rapid eye movement to fixate the target and returned to central fixation. A variable delay of 425–925 ms then followed (depending on cue-target ISI) to ensure that each trial lasted 2,000 ms (excluding initial jitter). The proportion of “SAME” trials varied across conditions: condition 1 50% SAME trials, condition 2 75% SAME trials, condition 3 25% SAME trials. For each condition, participants performed blocks of 64 trials, with the ISI fixed throughout the block. For the functional magnetic resonance imaging (fMRI) experiment trial timing differed slightly: initial fixation 500 ms, placemarkers 500 ms, cue 75 ms, ISI 0 ms or 400 ms, target 500 ms, final fixation 525 ms or 125 ms (for ISI 0 ms or 400 ms, respectively). Total trial time = 2,100 ms. Saccadic latencies were calculated for all cue-target combinations and are presented graphically as a function of ISI in Figs. 2 and 4. B and C: example eye position traces for 2 representative trials, showing a rightward (upward) and a leftward (downward) saccade, recorded during the behavioral experiment outside the scanner (B, black trace) and during the fMRI experiment inside the scanner (C, black trace). A saccade velocity of >30°/s was used to detect the onset of a saccade (vertical black bar).

Fig. 2.

Saccadic latencies from behavioral experiment outside scanner. A: group mean saccadic latencies were calculated for targets appearing at the same location as the cue (SAME, ●) or at the opposite location to the cue (OPPOSITE, ■). For each of the 3 conditions saccade latencies are plotted as a function of cue-target ISI. Saccadic latencies were shorter for targets appearing at the cued location compared with the opposite location if the ISI was short (<200 ms). This “same-location advantage” quantifies the reflexive attentional capture (AC) by the salient cue. At longer ISIs (>200 ms) saccadic latencies were shorter for targets appearing at the opposite location to the cue compared with the same location as the cue. This “same-location disadvantage” quantifies inhibition of return (IOR). B: effects of AC and IOR are best revealed by calculating the relative difference in saccadic latency for targets appearing at the opposite location compared with the same location as the cue. Positive values signify a “same-location advantage” (AC), and negative values signify a “same-location disadvantage” (IOR). Increasing the proportion of SAME location trials enhanced the “same-location advantage” of AC, whereas increasing the proportion of OPPOSITE trials enhanced the “same-location disadvantage” associated with IOR. Error bars indicate SE.

Fig. 3.

Optimizing signal recording from the superior colliculus (SC). Physiological noise significantly disrupts BOLD signal responses recorded from the upper brain stem region. Axial (A) and coronal (B) views of maximum intensity projections (MIPs) highlight those voxels maximally correlated (dark areas) with cardiac-induced noise (thresholded at P = 0.005). Seventeen regressors were generated for each participant, for each experimental scan run, representing physiological fluctuations associated with breathing rate, breathing volume, and cardiac pulse. These regressors were included as confounds in the first-level analysis for each participant. Voxels showing the greatest correlation with these effects are clearly distributed along the major vascular pathways, such as the circle of Willis and the middle cerebral arteries bilaterally. C, left: enlarged sagittal view of the upper brain stem for 1 participant, with BOLD signal responses superimposed representing the F-contrast for the experimental conditions of interest and the cardiac regressors (P = 0.005). Right: same sagittal section with activity correlated with the cardiac regressors removed, leaving only activity associated with our experimental conditions of interest. Removing the physiologically induced noise significantly improves signal detection related to our experimental conditions of interest. D: localizing the SC. The left SC is predominantly activated by stimuli in the right hemifield and the right SC by stimuli in the left hemifield. In a block design paradigm, participants fixated centrally while passively viewing black and white checkerboard stimuli (reversing at 8 Hz) that stimulated the right or left hemifield. To identify the right and left SCs, voxels in the upper brain stem that showed greater activity to contralateral hemifield stimulation compared with fixation baseline were identified with a threshold for significance of P = 0.05 uncorrected. A 4-mm-radius sphere centered over the participant's SC (using anatomic markers for guidance) was used to restrict activated voxels to within the SC. Both cluster and spherical region of interest (ROI) mask volume images were then created for the right and left SC on a per-participant basis. Parameter estimates were averaged across all voxels within the masks, for each condition of interest. E: raw time course data showing changes in BOLD signal (normalized to the overall mean) for 1 scan run for 1 participant, using a functionally defined cluster ROI. For clarity, colored bars indicate blocks of eye movements (blue or green) alternating with rest (white). The horizontal red dotted lines indicate mean activity for the block. The greatest activity occurred for condition A (75% “SAME” trials at ISI 0 ms, dark blue) and the least for condition C (75% “SAME” trials at ISI 400 ms, dark green).

Fig. 4.

Saccadic latencies from the fMRI experiment. Similar to the behavioral experiment, group mean saccadic latencies were calculated for targets appearing at the same location as the cue (SAME, ♦) or at the opposite location to the cue (OPPOSITE, ■) for each of the 2 block proportions and plotted as a function of cue-target ISI. The pattern of responses replicated that of the behavioral experiment, with enhanced AC for proportion 1 at short ISI and enhanced IOR for proportion 2. Error bars indicate SE.

Fig. 5.

BOLD responses from the human SC. BOLD signal responses evoked by each of our 4 experimental conditions, compared with fixation baseline, were averaged across all voxels within each participant's SC and are presented here as a group mean response. Data for the functionally defined cluster ROIs are shown. Consistent with our predictions, BOLD signals showed a strong correlation with our behavioral measure (saccadic latency) of AC and IOR, as evidenced by a significant increase in activity associated with block type A compared with B [t(8) = 3.259, P = 0.012] and a significant decrease in activity associated with block type C compared with D [t(8) = −2.558, P = 0.034]. Analysis of variance confirmed a significant interaction between trial proportion and ISI [F(1,8) = 14.576, P = 0.005]. Error bars indicate SE.

Fig. 6.

BOLD responses from V1–V3. BOLD signal responses evoked by each of our 4 experimental conditions, compared with fixation baseline, for V1–V3, thresholded at P = 0.001 uncorrected, are shown. BOLD signal responses in V1 showed the pattern of activity most similar to that in the SC, although the interaction between condition and ISI remained significant for all areas. The increase in activity associated with AC was only evident in V1, whereas the decrease in activity associated with IOR persisted for V1–V3. Error bars indicate SE.