Different effects of spatial and temporal attention on the integration and segregation of stimuli in time

Abstract

Having expectations about when and where relevant stimuli will appear engenders endogenous temporal and spatial orienting and can provide vital benefits to visual processing. Although more is known about how each of these forms of orienting affects spatial processing, comparatively little is understood about their influences on the temporal integration and segregation of rapid sequential stimuli. A critical question is whether the influence of spatial cueing on temporal processing involves independent spatial and temporal orienting effects or a synergistic spatiotemporal impact. Here we delineated between the temporal and spatial orienting engendered by endogenous cues by using a paradigm with identical visual stimulation when the goal was to integrate or segregate the stimuli, in separate blocks of trials. We found strong effects of spatial orienting on both integration and segregation performance. In contrast, temporal orienting engendered only an invalid cueing cost, and for integration trials only. This clear differentiation between spatial and temporal cueing effects provides constraints to inform arbitration between theories of how attention biases the visual processing stream and influences the organization of visual perception in time.

Binding Mechanisms in Visual Perception and Their Link With Neural Oscillations: A Review of Evidence From tACS

“…Indeed, as previously reported, a better segregation performance is expected with higher alpha frequencies (e.g., IAF + 2 Hz), while an improved integration should be associated with lower alpha frequencies (e.g., IAF -2 Hz) Ronconi et al, 2018). They used an alternative version of the missing-dot task (Eriksen and Collins, 1967), the SegInt task, which measures temporal segregation and integration performance (Wutz et al, 2016(Wutz et al, , 2018Ronconi et al, 2018;Sharp et al, 2019). In this task, two displays are shown in sequence, separated by a blank interval.…”

Testing the effect of tACS over parietal cortex in modulating endogenous alpha rhythm and temporal integration windows in visual perception

“…Each target display (containing the 7 circles and one half-circle) was shown for 1 refresh cycle (10 ms) separated by a blank interval equal to five refresh cycles (50 ms). This value was chosen based on our previous studies (Ronconi et al, 2018;Sharp et al, 2018Sharp et al, , 2019Wutz et al, 2016Wutz et al, , 2018 showing that this time interval was optimal to reach an intermediate accuracy level (across integration/segregation conditions) around 60%-70% (chance level = 6.25%), which gave us reasonable margins to test the eventual performance fluctuations over time caused by tACS. Importantly, a 50 ms time interval fits within the alpha duty cycle (if we consider 10 Hz as the central alpha frequency) (Jensen et al, 2012), and thus is particularly suitable to test variation in performance in relation to variation in the ongoing alpha phase and frequency.…”

“…Finally, one location was left empty in both displays. The stimuli used were similar to those in previous studies measuring temporal integration and segregation (Ronconi et al, 2018;Sharp et al, 2018Sharp et al, , 2019Wutz et al, 2016Wutz et al, , 2018. The experiment was programmed in Matlab, using the Psychtoolbox (Brainard, 1997).…”

“…More recently, Ronconi et al. (2018) showed that sensory entrainment at the individual alpha frequency (IAF) + or −2 Hz was able to modulate both integration and segregation of two stimuli in close temporal proximity using a variant of the missing‐dot task (Eriksen & Collins, 1967; Hogben & Lollo, 1974) called the “SegInt” task (Ronconi et al., 2018, 2020; Sharp et al., 2018, 2019; Wutz et al., 2016, 2018). In this task, also employed in this study (Figure 1b), an identical sequence of two displays was used to measure temporal integration or segregation according to the specific task instruction.…”

“…Here, tACS was used to induce changes in the frequency of endogenous oscillations; EEG was used to verify such changes by comparing peak frequencies between the pre‐ and post‐stimulation resting‐state EEG signal. We used the SegInt task, which tests temporal integration and segregation using identical stimuli (see above; Eriksen & Collins, 1967; Hogben & Lollo, 1974; Ronconi et al., 2018, 2020; Sharp et al., 2018, 2019; Wutz et al., 2016), depending on a specific task instruction. tACS was delivered at the upper and lower boundary frequencies of the individually defined alpha band, by choosing for each participant the two stimulation frequencies based on the IAF peak obtained from the pre‐stimulation resting‐state EEG.…”