Participants

A total of twenty-five healthy participants took part in this study (16 females, 9 males, age range: 19–34, average age ± SD = 23.12 ± 4.21). All participants were right handed and had normal or corrected-to normal vision. Before taking part in the experiment, all participants provided written informed consent. Ethics approval was given by the College of Science and Engineering ethics committee of the University of Glasgow.

Apparatus

The experiment was presented using E-Prime 2.0 software (Psychology Software Tools, Pittsburgh, PA) on a CRT monitor (Samsung Sync Master 1100MB, 20inch in diameter, spatial resolution of 1280 x 1024 pixels and refresh rate of 85Hz). A chinrest maintained a constant viewing distance of 35cm to the screen. Eye movements were monitored online using a CCTV camera to ensure participants understood the concept of the task (covert attention shifts without eye movements following the cues).

Stimuli and Task

A visual pre-target motion paradigm was implemented (adapted from [22], initially inspired by [12]). A matrix of 5 x 9 circles (placeholders) and a central fixation cross were presented at all times on the screen (Fig 1A). The placeholders were presented in grey on a black background together with the white fixation cross. Symbolic cues presented on top of the fixation cross were all white (Fig 1B). The diameter of the placeholders was 1.2cm, with a vertical distance of 3cm and a horizontal distance of 3.4cm.

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Fig 1. Schematic representation of the experimental design.

(A) Fixation cross and placeholders. The dashed rectangle and the arrows (here drawn on top of the background screen for illustrative purposes, not part of visual stimulation) highlight respectively the row in which visual motion cues were presented, and the two possible target locations in the left and right visual fields. (B) Endogenous symbolic arrow-cues (left, right or neutral) as presented in the centre of the screen. (C) Each trial began with a fixation cross (1000ms) and was followed by the presentation of a symbolic cue indicating the probable upcoming target location (here: neutral). The symbolic cue stayed on the screen until target presentation and throughout motion cueing. Motion cueing began 1000ms after symbolic cue onset. Spatial trajectory cueing was implemented by successively flashing (for 35.3ms) each adjacent circle in the row below the symbolic endogenous cue from the left or right periphery towards the centre. Temporal cueing was implemented by presenting the motion cues in either a rhythmic or arrhythmic temporal structure. After a fixed ISI of 1294ms from motion cue onset (including 258.8ms after the last motion cue), the target appeared for 11.8ms either in or out of motion trajectory. Participants were asked to engage in endogenous orienting based on the symbolic cues, and to ignore the motion cues because they were task-irrelevant.

https://doi.org/10.1371/journal.pone.0144082.g001

The core of a trial consisted of five placeholders in the row below the fixation cross successively flashing from grey to white (left- or rightward x rhythmic or arrhythmic flashes) (Fig 1C). The flashing of the circles either started with the rightmost circle and ended with the central circle directly underneath the fixation cross, or started with the leftmost circle and ended with the same central circle. This created an apparent motion effect of the circles and was followed by a target presented in one of the adjacent placeholders, left or right from the central circle. Thus, targets appeared either in- or out- of apparent motion direction (for spatial trajectory cueing/ probing spatial extrapolation). Left- and rightward motion direction was equally probable and uninformative of upcoming target position (pointing in 50% of trials towards and in the other 50% away from the target).

In addition, the temporal structure of the apparent motion trajectory was manipulated (for temporal trajectory cueing/ probing temporal extrapolation). To this end, the apparent motion cues (flash = 35.3ms) flickered either rhythmically at 3.9Hz (four fixed ISIs of 258.8 ms) or arrhythmically with four intervals of 117.6, 152.8, 329.4 and 435.2 ms (shuffled and presented in random order per arrhythmic trial). These intervals were chosen because visual stimuli moving in discrete steps at these frequencies are perceived as apparent motion [21]. In order to prevent differential forward masking (see also [15]) between rhythmic and arrhythmic conditions, the last interval between the fifth circle and the visual target was fixed at 258.8ms across all trials. In addition, time from motion cue onset to target presentation was fixed across all trials of both the rhythmic and arrhythmic conditions (1294ms). Hence, rhythmic and arrhythmic trials only differed in rhythmic or arrhythmic trial history, but were not differentially informative as to time of target onset, emphasizing differences in deployed unintentional processes (linked to the rhythmicity of motion) rather than endogenous mechanisms (e.g. linked to time-estimation). Rhythmic and arrhythmic trials were presented in random order. Participants were instructed that motion stimuli were uninformative as to both forthcoming target position and time of appearance and therefore irrelevant to the task.

Although motion trajectory were non-predictive as to forthcoming target location and participants were not required to engage with the flicker, participants may still process the apparent motion cues intentionally to extrapolate upcoming events. Thus, to prevent voluntary orienting to the motion cues, participants were asked to engage in a concurrent, symbolically cued endogenous attention orienting task, in anticipation of the upcoming, to-be-discriminated targets: Informative, symbolic arrow-cues were presented at the beginning of the trial, in the centre of the screen (Fig 1), indicating the location of the upcoming target (i.e., left- or rightward arrows, 75% cue-validity) or indicating a neutral trial (bi-directional arrow which was non-predictive (50:50) of target location). Participants were asked to covertly shift attention towards the indicated target position upon presentation of a left- or rightward pointing arrow, or to maintain attention at the fixation cross in neutral trials (and to keep their fixation at the central fixation cross in all cases), while the uninformative motion cues flickered either rhythmically or arrhythmically across the screen (in the background). Targets consisted of a ‘+’ or ‘x’ which needed to be discriminated as fast and accurate as possible by button press.

Procedure

The experiment took place in two sessions (1 hr per session) on two different days to avoid participants’ fatigue. A training phase familiarized participants with the task. The first training block consisted of intermixed endogenous neutral-, left- or right-cues only (100% validity, number of trials: 24). Participants then completed a second training block, including motion (trajectory cues) in a rhythmic or arrhythmic pattern (50% validity), in addition to the 100% valid endogenous cues (number of trials: 32). This was followed by target titration, which served to individually adjust target luminance contrast to approximately 80% discrimination performance to avoid floor or ceiling effects. Overall, the experiment consisted of three symbolic cues (neutral, left and right), two motion directions (left to right and right to left) and two temporal structures (rhythmic or arrhythmic). All conditions were presented in an intermixed order in five blocks with breaks approximately every 6.5 minutes, resulting in a total number of 960 trials (80 trials per condition) per participant.

Statistical analysis

We subjected both discrimination accuracy (proportion correct) and reaction times (correct responses only) to two separate fully within-subjects design (repeated-measure) analysis of variances (ANOVAs). The factors of these 3x2x2x2 ANOVAs consisted of Symbolic Spatial Cueing (neutral vs. left vs. right), Spatial Trajectory Cueing (leftward vs rightward motion), Temporal Trajectory Cueing (rhythmic vs. arrhythmic) and Target Location (left vs. right). Significant main effects or interactions were followed up with simple effect tests. Calculation of the effect sizes for simple tests (Cohen’s d) was based on correlated sample comparisons (within-subjects) [31] and we report their magnitude (not the sign).

Endogenous cueing benefit on target discrimination

In line with the participants following the instructions and engaging in the task (endogenous shifts of attention in response to the symbolic cues), we found both discrimination accuracy (Fig 2A) and reaction time (Fig 2B) to be influenced by endogenous cueing direction (left, neutral, right symbolic cues) as a function of target position (left visual field vs right visual field), which showed in a significant 2-way interaction of Endogenous Spatial Cueing x Target Location both for accuracy (F(2,48) = 13.32, p = .00003, ηp² = .36) and reaction time (F(2, 48) = 83.08, p < .00001, ηp² = .78). Follow-up simple tests showed significantly better performance levels (higher accuracy, faster RTs) for validly than invalidly cued targets in both the left visual field (accuracy L- vs R-cue: F(1,24) = 21.79, p = .00001, Cohen’s d = .93; RT L- vs R-cue: F(1,24) = 80.18, p < .00001, Cohen’s d = 1.79), and the right visual field (accuracy R- vs. L-cue: F(1,24) = 5.05, p = .034, Cohen’s d = .45; RT R- vs. L-cue: F(1,24) = 66.56, p < .00001, Cohen’s d = 1.63).

Importantly, there was no evidence for motion to affect any of the above endogenous cueing benefits at attended locations (no 3 way interaction of Symbolic Spatial Cueing x Target Location with neither Spatial Trajectory Cueing nor Temporal Trajectory Cueing, for any of the two measures (accuracy and RT) (both 3-way interactions non-significant: F(2,48) < 0.44, p > .646, ηp² < .02). This speaks in favour of the participants maintaining endogenous attention throughout all conditions independently of the presence of simultaneous motion cues, i.e. for participants not dividing endogenous attention between the symbolic endogenous and the motion cues. Or in other words, this shows that participants effectively ignored the motion cues, as desired by instructions and design (motion flicker task-irrelevant and non-predictive as to forthcoming target location). As a consequence, any benefit from spatial or temporal trajectory cueing can be considered to reflect automatic anticipation.

Finally but tangential to the questions of this study, the overall ANOVAs revealed a main effect of Endogenous Cueing for both performance accuracy (F(2,48) = 5.92, p = .005, ηp² = .20) and reaction time (F(2, 48) = 13.88, p = .00002, ηp² = .37).

Automatic spatial extrapolation in response to the motion trajectory: Benefits of motion direction on target discrimination

Despite being task-irrelevant and non-predictive, the direction of motion trajectory (leftward vs. rightward motion) significantly affected both target discrimination accuracy (Fig 3A) and reaction time (Fig 4A) as a function of target location (LVF vs. RVF), as revealed by significant 2-way interactions of Spatial Trajectory Cueing (i.e. motion direction) x Target Location (accuracy: F(1,24) = 10.14, p = .004, ηp² = .30; RT F(1, 24) = 50.93, p < .00001, ηp² = .68). Follow-up simple tests revealed significantly (or near-significantly) better performance levels (higher accuracy, faster RTs) for validly as compared to invalidly cued targets for both the right visual field (accuracy right- vs. leftward motion: F(1,24) = 6.80, p = .015, Cohen’s d = .52/ RT right- vs. leftward motion: F(1,24) = 10.18, p = .004, Cohen’s d = .64) and the left visual field (accuracy left vs. rightward motion: F(1,24) = 3.94, p = .059, Cohen’s d = .40; RT left vs. rightward motion: F(1,24) = 31.22, p = .00001, Cohen’s d = 1.12). Thus, motion direction clearly benefitted target discrimination at motion-cued locations, with higher performance accuracy and faster reaction times for targets appearing in as compared to out of motion trajectory. This is evidence for motion trajectory automatically driving spatial anticipation. Interestingly, this effect was independent of temporal trajectory cueing (rhythmicity) for both accuracy (F(1,24) = .18, p = .67, ηp² = .008) and reaction time (F(1, 24) = .26, p = .62, ηp² = .01) (see Figs 3B and 4B).

Finally and again tangential to our question, there was a main effect of target location, with faster responses for targets in the right visual field relative to the left visual field (difference of 24.46 ms) (F(1,24) = 12.38, p = .002, ηp² = .34).

Automatic temporal anticipation in response to the motion trajectory: Benefits from the temporal structure of motion stimuli

Overall responses to rhythmic cueing were slightly faster relative to arrhythmic motion cues (difference of 5.3 ms) (F(1, 24) = 4.72, p = .034, ηp² = .16). More importantly temporal cueing (rhythmicity) influenced target discrimination but differently from spatial trajectory cueing. We expected that the benefit from automatically driving spatial anticipation by motion (as revealed above in the 2-way interaction Spatial Trajectory Cueing x Target Location) would be enhanced by temporal cueing (rhythmic vs arrhythmic condition), which was however not the case (no 3-way interaction of Temporal Cueing x Spatial Trajectory Cueing x Target Location, see above). Instead, temporal trajectory cueing benefits were limited to discrimination accuracy and depended on motion direction (significant 2-way interaction of Temporal Trajectory Cueing x Spatial Trajectory Cueing (F(1,24) = 16.16, p = .0005, ηp² = .40)(Fig 3C). This effect was absent for reaction times (Fig 4C). Follow-up simple tests on performance accuracy showed a trend for better performance when exposed to rhythmic as compared to arrhythmic rightward motion (F(1,24) = 3.53, p = .073, Cohen’s d = .38) and a significant advantage for arrhythmic as compared to rhythmic leftward motion (F(1,24) = 10.01, p = .004, Cohen’s d = .63). This finding indicates asymmetric effects of temporal trajectory cueing (rhythmic vs. arrhythmic) for cueing towards the right vs. left visual fields.

Spatial extrapolation automatically driven by apparent motion stimuli

We found that perceptual processing was clearly enhanced when targets appeared at spatially extrapolated locations in the motion direction, despite the fact that the apparent motion cues were task-irrelevant and non-predictive. This extends prior studies showing perceptual benefits when employing apparent motion stimuli (and also with attentive and/or passive object tracking paradigms), in which the observers traced (covertly) an object while perception of a target was probed in or out of the object’s motion path (e.g., [12,16,17,22]). These perceptual benefits are likely conveyed through mechanisms for maintaining and updating the representation of a moving object along an apparent motion trajectory, serving motion extrapolation [16] and interpolation [16,17,21]. In apparent motion this occurs even outside of the voluntary attentional focus [16]. As an explanatory mechanism for the perceptual benefits, smooth shifts in the attentional focus along the motion path have been suggested, tracking the moving object and predicting future target locations [17,21,35]. This could either be mediated by conscious prediction or an internal model [21], updating the motion path intentionally or automatically. Alternatively, low-level motion processing could explain motion prediction mechanisms. As proposed by Nijhawan [36,37], early visual structures may compensate for neuronal processing delays through extrapolation, attempting to predict future locations of a moving object. Our present findings of spatial motion trajectory facilitating perception provide support for automatic prediction mechanisms. This is also in line with prior findings showing that contrast sensitivity to moving objects is enhanced towards the end of the motion trajectory, interpreted to reflect automatic attention capture and prediction mechanisms [38], and that motion induces a forward prediction signal [39].

Temporal anticipation automatically driven by rhythmic (versus arrhythmic) apparent motion stimuli is partially independent from spatial extrapolation

We found perception to be modulated by temporal trajectory cueing. Interestingly however, effects of temporal cueing were independent of spatial cueing, i.e. we did not find any synergy/additive effects of temporal (rhythmic) cueing on the spatial cueing benefit with our design. Instead, temporal cueing showed an unexpected pattern (not observed with spatial cueing): it depended on motion direction. That is, rhythmic cueing tended to benefit perceptual processing with rightward motion (relative to arrhythmic cueing), while arrhythmic cueing was associated with better performance in response to leftward motion (as compared to rhythmic cueing). This asymmetrical perceptual benefit driven by temporal cueing may suggest that distinct mechanisms are at play for spatial and temporal prediction. Importantly, their independence implies that these mechanisms do not interact in our design, i.e. at a purely unintentional/ automatic level (when endogenous spatial attention is saturated).

In contrast to our results, a recent series of studies that concurrently manipulated spatial and temporal attention have shown that temporal attention on its own is not effective in modulating visual performance [13] nor in modulating early visual evoked potentials typically associated with spatial attention [12]. Instead, these studies provide evidence for synergistic effects of temporal on spatial attention, i.e. for the need of spatial processes to be engaged so that temporal advantages can be expressed [12,13]. However, these results are not directly comparable to our findings because of differences in experimental design. Rohenkohl et al. [13] manipulated temporal and spatial expectations in the endogenous dimension. Doherty et al. [12] used apparent motion with an intrinsic, spatially and temporally predictive structure but did not control for intentional deployment of attention to these cues. As a consequence, participants may have engaged in endogenous anticipatory processes to deliberately use the apparent motion information for intentionally predicting the forthcoming events. Hence, synergistic interaction between these systems may require endogenous control to be expressed. Similar to our results, Jones [14] found temporal and spatial cueing to convey independent attentional benefits. However, Jones [14] studied the interaction between endogenous spatial attention and exogenous temporal expectations using symbolic spatial and central flicker cues, i.e. crossing the endogenous/ exogenous divide, again limiting comparison to our results. The discrepancy between our own and previous findings hence suggests that anticipatory processes in the spatial and temporal dimension may differ as to whether the cue is rhythmic or symbolic, as previously suggested [11,13,18,23,40,41], as well as whether the processes reflect intentional versus automatic mechanisms, as suggested here.

Possible neuronal substrates of dissociated automatic spatial and temporal anticipation with apparent motion stimuli

It is well established that the left hemisphere is dominant for processing temporal information, whereas the right hemisphere is more specialized in processing spatial information [42–45]. In line with this view, previous studies have associated temporal attention with left hemispheric activity [11,12]. Coull and Nobre [11], for example, observed left intraparietal and premotor cortex activity for temporal orienting (i.e. in areas engaged in motor planning and attention; [46]) versus right intraparietal activity for spatial orienting. Doherty et al. [12], who found temporal attention to be associated with motor response-related EEG components, again interpreted this to reflect the engagement of left hemispheric resources with temporal attention deployment (in line with [11]). Our finding of a left-right asymmetry showing that perception tends to be enhanced by rhythmic (as compared to arrhythmic) motion but only for the rightward motion cues may hence suggest for the first time that hemispheric (left lateralized) differences may also come into play for automatic temporal anticipatory mechanisms. By extension, our finding that perception was enhanced for arrhythmic (as compared to rhythmic) leftward motion may suggest a right hemispheric process. However, these findings on asymmetry should be interpreted with caution given that they were unexpected. In this light, it is of interest to note that most previous studies reporting perceptual benefits from temporal cueing with pre-target motion paradigms only employed rightward motion (albeit for testing more endogenous attention) [12,23,47]. One exception is De Graaf et al. [22], who used a symmetric design (including left and rightward motion) but did not report an asymmetrical benefit in favour of rhythmic rightward motion (note that no arrhythmic condition was tested). However, the results of De Graaf et al [22] are likely to be confounded by intentional prediction mechanisms, which were not controlled for by design in contrast to the present study. Hence, comparisons to prior studies are limited and follow-up experiments are needed to confirm the hemifield asymmetry we found.

For a possible explanation of the observed hemifield asymmetry, we speculate that the entrainment of the attention focus to rhythmic cues may draw on similar resources as entrainment to rhythmic (and therefore predictive) speech signals (for review see [8]), for which a left hemispheric dominance, albeit not exclusively, can be assumed [48,49]. Alternatively, directional preferences for rightward motion stimuli [50, 51], or a larger rightward shift of attention for rightward (but not leftward) motion [52], may be due to internalized/learned reading habits and thus preferential visual rightward scanning. However, such a bias should be observed not only for temporal but also spatial processes, which was not the case here. Indeed, research on participants with native languages read/written from left to right (e.g. English) has shown that their perceptual span is asymmetrically shifted to the right around the fixation point [53], while this effect is reversed for participants with native languages read/written from right to left [54,55]. Thus, a bias from reading habits is unlikely to explain the dissociation we observe here between temporal and spatial anticipatory processes.