Decision letter: Distinct roles of forward and backward alpha-band waves in spatial visual attention

Abstract

Article Figures and data Abstract Editor's evaluation Introduction Results Discussion Methods Data availability References Decision letter Author response Article and author information Metrics Abstract Previous research has associated alpha-band [8–12 Hz] oscillations with inhibitory functions: for instance, several studies showed that visual attention increases alpha-band power in the hemisphere ipsilateral to the attended location. However, other studies demonstrated that alpha oscillations positively correlate with visual perception, hinting at different processes underlying their dynamics. Here, using an approach based on traveling waves, we demonstrate that there are two functionally distinct alpha-band oscillations propagating in different directions. We analyzed EEG recordings from three datasets of human participants performing a covert visual attention task (one new dataset with N = 16, two previously published datasets with N = 16 and N = 31). Participants were instructed to detect a brief target by covertly attending to the screen’s left or right side. Our analysis reveals two distinct processes: allocating attention to one hemifield increases top-down alpha-band waves propagating from frontal to occipital regions ipsilateral to the attended location, both with and without visual stimulation. These top-down oscillatory waves correlate positively with alpha-band power in frontal and occipital regions. Yet, different alpha-band waves propagate from occipital to frontal regions and contralateral to the attended location. Crucially, these forward waves were present only during visual stimulation, suggesting a separate mechanism related to visual processing. Together, these results reveal two distinct processes reflected by different propagation directions, demonstrating the importance of considering oscillations as traveling waves when characterizing their functional role. Editor's evaluation Alamia and colleagues investigate the direction of traveling waves in the α frequency band during visual spatial attention. The authors' novel perspective adopted here is important to understand the functional relevance of α oscillations for spatial attention. The observed pattern of results is consistent with distinct roles for travelling α waves in spatially opposite directions and makes a solid case for considering this new perspective on α rhythms in human cognitive function. https://doi.org/10.7554/eLife.85035.sa0 Decision letter Reviews on Sciety eLife's review process Introduction Brain oscillations are related to several cognitive functions, as they orchestrate neuronal activity at distinct temporal and spatial scales (Buzsáki and Draguhn, 2004; Buzsáki, 2009). Alpha-band oscillations [8–12 Hz] are the most prevailing rhythms in electrophysiological (EEG) recordings, spreading through most cortical regions. Several studies investigated their functional role in various cognitive processes (Palva and Palva, 2007; Palva and Palva, 2011), providing mixed results. On the one hand, some studies showed that alpha-band oscillations might filter sensory information, regulating excitation and inhibition of sensory-specific brain regions (Jensen and Mazaheri, 2010; Mathewson et al., 2011; Klimesch, 2012; Sadaghiani and Kleinschmidt, 2016). Accordingly, researchers interpreted alpha oscillations as a top-down mechanism involved in inhibitory control and timing of cortical processing (Klimesch et al., 2007), as well as modulating cortical excitability (Jensen and Mazaheri, 2010; Mathewson et al., 2011). Experimental studies corroborated this hypothesis, demonstrating how the phase of alpha-band oscillation affects visual perception (Busch et al., 2009; Fakche et al., 2022; but see also Ruzzoli et al., 2019). Another highly replicated result regarding the inhibitory role of alpha oscillations consists in the hemispheric modulation in occipital regions associated with visual attention, having an increase of power ipsilateral to the attended hemifield, and a corresponding decrease contralaterally (Worden et al., 2000; Sauseng et al., 2005; Kelly et al., 2006; Thut et al., 2006; Händel et al., 2011). On the other hand, other experimental studies have related alpha-band oscillations in occipital and parietal regions to perceptual processing and visual memory (Bonnefond and Jensen, 2012; VanRullen, 2016; Pang et al., 2020; Luo et al., 2021). For example, reverse-correlation techniques reveal that the visual system reverberates sensory information in the alpha-band for as long as 1 s, in what has been dubbed ‘perceptual echoes’ (VanRullen and Macdonald, 2012). Importantly, these echoes are a clear signature of sensory processing as they reflect the input’s precise time course, are modulated by attention and have been dissociated from inhibitory alpha power modulation (VanRullen and Macdonald, 2012; VanRullen, 2016; Brüers and VanRullen, 2018; Schwenk et al., 2020). Altogether, these experimental evidences support distinct and contradictory conclusions about alpha-band oscillation’s functional role(s), which remains an open debate. Here, we address this question from a different perspective that interprets alpha-band oscillations as traveling waves (Muller et al., 2018; Alamia and VanRullen, 2019), thus considering their spatial component, and their propagation direction. Considering the case of visual attention, we tested the hypothesis that two functionally distinct alpha-band oscillations propagate along the frontal–occipital line in opposite directions. This compelling hypothesis about the different functional roles of alpha-band traveling waves derives from our previous studies (Alamia and VanRullen, 2019; Pang et al., 2020), in which we showed how visual perception modulates alpha waves, that is forward waves during visual stimulation, backward waves when the stimulus was off. In addition, this hypothesis is in line with previous studies suggesting that distinct alpha-band oscillations are related to specific cognitive processes (Gulbinaite et al., 2017; Deng et al., 2019; Schuhmann et al., 2019; Sokoliuk et al., 2019; Kasten et al., 2020). In this study, we analyzed three datasets, two publicly available (Foster et al., 2017; Feldmann-Wüstefeld and Vogel, 2019, see below), and one collected specifically for this study. In all datasets, participants attended either to the left or the right hemifield, while keeping central fixation. Our results confirmed the hemispheric modulation of alpha-band oscillations in posterior regions (Worden et al., 2000; Sauseng et al., 2005; Kelly et al., 2006; Thut et al., 2006; Händel et al., 2011) and revealed two distinct alpha-band traveling waves propagating in opposite directions. First, visual attention increases top-down alpha-band waves propagating from frontal to occipital regions ipsilateral to the attended location, and such waves correlate positively with alpha power in frontal and occipital regions. Moreover, our analysis demonstrates that visual attention also modulates contralateral forward waves, that is, waves propagating from occipital to frontal areas. Importantly, the attentional modulation of forward waves is crucially dependent on sustained sensory processing, as this modulation disappears in the absence of visual stimulation. In contrast, alpha-band top-down waves are present and modulated by visual attention irrespective of the presence or absence of concurrent sensory stimulation. These results demonstrate two distinct alpha-band oscillatory waves propagating in opposite directions, seemingly underlying different cognitive processes. The well-known lateralization effect observed in alpha-band can be interpreted as top-down traveling waves, and it is most likely related to inhibitory processes, in line with previous studies (Jensen and Mazaheri, 2010; Händel et al., 2011). However, different alpha-band oscillations propagate in a forward direction and are directly related to sensory processing, reconciling previous evidence linking alpha-band oscillations with visual processing (VanRullen and Macdonald, 2012; Lozano-Soldevilla and VanRullen, 2019). Results Traveling waves’ spectral profile The goal of the study was to investigate how visual attention modulates alpha-band traveling waves in the hemisphere contra- and ipsilateral to the attended location. To test this, we considered 11 lines of electrodes running from occipital to frontal regions (Figure 1C), 5 for each hemisphere and 1 midline. It is important to note that the spatial resolution of these lines is not critical for our analysis, as we do not expect significant differences within each hemisphere. However, before testing how visual attention modulates traveling waves, we explored the amount of waves propagating forward (FW) and backward (BW) as a function of their temporal frequency (see Figure 5 and methods for a detailed description of the analysis). Figure 1D shows the spectral profile of FW and BW waves in the midline (along the Oz–Fz axis) and the contra- and ipsilateral lines: confirming previous experimental studies (Alamia and VanRullen, 2019; Pang et al., 2020), we found that alpha-band oscillatory waves propagate in both directions during visual stimulation, whereas theta (4–7 Hz) and high-beta/gamma (24–45 Hz) bands propagate mostly bottom-up from occipital to frontal regions, and low-beta (13–23 Hz) waves flow in the top-down direction. Interestingly, this pattern of results confirms previous studies using different methods, in which higher frequency bands (i.e., high-beta/gamma) have been associated with forward processing, whereas low-beta and alpha frequencies have been related to top-down processing (Bastos et al., 2012; Bastos et al., 2015; van Kerkoerle et al., 2014; Michalareas et al., 2016; but see also Schneider et al., 2021b). Figure 1 Download asset Open asset Experimental design and waves’ spectral profile. (A) Each trial lasted 5 s, in which two flickering stimuli were presented to both hemifield. Participants were instructed to attend either the left or the right hemifield, as indicated by a central cue. In some trials, a target or a distractor appeared for 100 ms as a square either in the attended or unattended location. (B) The target and distractor luminance changed over trials due to the QUEST algorithm, which kept participants’ performance around 80%. (C) We quantified traveling waves along 11 electrodes lines, running along the anterior–posterior axis. These lines were located in the contralateral or the ipsilateral hemisphere to the attended location. (D) The amount of waves in dB computed for forward (in blue) and backward (in red) waves in the midline (central subplots, thinner lines represent standard errors of the mean) and in the ipsi- and contralateral hemisphere (left and right panels, respectively). These waves were computed on trials without target or distractors. Positive (negative) values reflect more (less) waves than the chance level (as quantified by the surrogate distribution), whereas values around 0 indicate no difference between the real and the null distribution. (E) Simulated data providing a schematic representation of forward and backward waves in the time domain in a given line of electrodes (from more frontal E1 to more occipital E7). A positive and a negative phase shift characterized forward and backward waves, respectively. Attending to visual stimuli modulates traveling waves In this analysis, we investigated how covert visual attention influences the traveling wave pattern. We focused on trials where neither a target nor a distractor was presented. First, we quantified the amount of traveling waves in the contra- and ipsilateral hemispheres to the attentional allocation. As shown in Figure 2 (left column), we found a strong lateralization effect revealing an increase (respectively, decrease) of contralateral (ipsilateral) forward waves in the alpha-band, and the opposite pattern in waves propagating in the opposite direction. These results were confirmed by a Bayesian analysis of variance (ANOVA), considering as factors DIRECTION (FW or BW), LINES (distance from the midline), and LATERALITY (contra vs. ipsi). The results revealed strong evidence in favor of the interaction between DIRECTION and LATERALITY factors (BF10 = 31.230, estimated error ~1%, η2 = 0.08 as estimated from a classical ANOVA), whereas all other factors and their interactions revealed evidence in favor of the absence of an effect (BFs10 < 0.3). We also found no significant effect in the other frequency bands (as shown in Figure 1D, namely theta, low, and high beta), hence we focused the following analyses on alpha-band oscillatory waves. These results demonstrate that the direction of alpha-band oscillatory traveling waves shows a laterality effect during a task involving covert selective attention. Figure 2 Download asset Open asset Traveling waves block analysis. Each column in the figure represents a different EEG dataset involving experiments with visual stimulation (left and middle columns) and without visual stimulation (right column). In the upper panels, the net amount of forward (blue) and backward (red) waves is represented along different lines of electrodes, normalized to the midline. The left and central panels reveal an increase (decrease) of forward (backward) waves contralateral to the attended location when participants attended to visual stimulation. The right column shows that when participants attended an empty screen (data from Foster et al., 2017), only backward waves were modulated by visual attention, and no effect was observed in the forward waves without visual stimulation. Error bars represent standard errors of the mean. The middle row shows schematic representations of the screen during the tasks: the central panel illustrates the task from Feldmann-Wüstefeld and Vogel, 2019, where D and T stand for Distractor and Target, respectively. In the task from Foster et al., 2017, the screen was empty, as the eight circles were not displayed during the task but here illustrate the stimulus positions (Foster et al., 2017). The lower panels represent the lines of electrodes in all datasets. Backward waves correlate with alpha-band power Previous studies investigating the role of alpha-band oscillations in visual attention reported a lateralization effect in the spectral power of alpha-band oscillations (Worden et al., 2000; Sauseng et al., 2005; Kelly et al., 2006; Thut et al., 2006; Jensen and Mazaheri, 2010; Händel et al., 2011). One may then wonder about the relationship between alpha power and traveling waves. To address this question, we investigated whether the oscillatory activity we observe propagating through the cortex relates to the spectral power in either occipital or frontal regions. We computed the averaged alpha-band power in frontal and occipital areas, contra- and ipsilaterally to the target presentation, considering the same electrodes used for quantifying the traveling waves (see Figure 3A). Interestingly, we found a significant positive correlation between alpha-band power in both occipital and frontal regions and backward waves, but not with forward waves (Figure 3A and Table 1). Next, we considered the lateralization effect in the alpha-band, as shown in Figure 3B (topographic plot in the right panel) and well replicated in previous studies (Sauseng et al., 2005; Thut et al., 2006; Händel et al., 2011). We wondered whether we could observe a correlation between such lateralization, defined as the difference between alpha-band power when attention is allocated to one side of the screen and to the other side, and the effect we reported in the traveling waves (Figure 2). As shown in Figure 3B (left panels), our results demonstrate a lack of correlation for both backward and forward waves in both frontal and occipital regions (all |r| < 0.1, BF10~ = 0.3). Table 1 Correlation with alpha-band power. The table reports the Pearson’s correlation coefficient and the Bayes Factor (BF10 supporting the alternative hypothesis, that is the presence of a correlation) between frontal and occipital electrodes and forward (FW) and backward (BW) waves, in both contra- and ipsilateral hemispheres. Values in bold reflect Bayes Factors providing strong evidence in favor of the alternative hypothesis. All correlations were computed on trials when neither a target nor a distractor was displayed. Pearsonr (BF₁₀)FWBWCONTRAIPSICONTRAIPSI OCC.CONTRA−0.297 (0.549)−0.350 (0.697)0.720 (28.519)0.698 (19.503)IPSI−0.305 (0.566)−0.342 (0.669)0.786 (116.990)0.746 (47.512) FRONT.CONTRA−0.222 (0.422)−0.252 (0.465)0.772 (84.225)0.712 (24.645)IPSI−0.327 (0.625)−0.354 (0.710)0.747 (48.448)0.705 (21.841) Figure 3 Download asset Open asset Correlation with alpha-band power. (A) Panel A reveals a correlation between backward waves and alpha power (static, standing power, i.e., measured via wavelets transform), in both frontal and occipital areas, in both hemispheres. We did not observe such correlation with forward waves. The plot to the right reveals the topographic distribution of alpha power when participants attended to the right hemifield (we included the ‘left’ condition by flipping the electrodes symmetrically to the midline). The white dots indicate the electrodes used for the correlation. (B) The plots to the left show the correlation between the laterality effect in the alpha power and in the waves (laterality measured as the mean difference between contra- and ipsilateral hemispheres for both alpha power and the waves – for the waves we computed the difference using lines of electrodes symmetrical to the midline). We did not observe any correlation in neither forward nor backward waves, with neither frontal nor occipital alpha power. The topography to the right reveals a lateralization effect in the alpha power (attention to the left minus attention to the right), confirming the presence of alpha power lateralization, in line with previous studies (Sauseng et al., 2005; Thut et al., 2006; Händel et al., 2011). (C) Panel C shows the trial-by-trial correlation coefficients averaged across participants for different conditions (as indicated in the x-axis). Confirming the results in panel A, we found a positive correlation across participants between backward waves and alpha power, specifically in the contralateral hemisphere. We also observed a positive global effect of the laterality condition across participants in the forward waves, even though the combined p values for the trial-by-trial correlation did not reach the significant threshold. Error bars represent standard errors of the mean. To further investigate the relation between alpha-band traveling waves and alpha power, we performed the same analysis focusing on the correlation within each participant. In particular, we correlated trial-by-trial forward and backward waves with alpha-band power for each subject, obtaining correlation coefficients ‘r’ and their respective p values. As in the previous analysis, we correlated forward and backward waves with frontal and occipital electrodes in both contro- and ipsilateral hemispheres. We applied the Fisher method (Fisher, 1992, see Methods for details) to combine all subjects’ p values in every conditions. Overall, we found a significant effect of all combined p values (p < 0.0001), except in the lateralization condition (contra- minus ipsilateral hemisphere), similar to our previous analysis. Additionally, we tested for a consistent positive or negative distribution of the correlation coefficients. As shown in Figure 3C, the results support a significant correlation between backward waves and alpha power in the hemisphere contralateral to the attended location (BF10 = 10.7 and BF10 = 7.4 for occipital and frontal regions, respectively; all other BF10 were between 1 and 2, providing inconclusive evidence). Interestingly, this analysis also revealed a small but consistent effect in the correlation between lateralization effects, as we reported a consistently positive correlation in the contra- minus ipsilateral difference between forward waves and alpha power (BF10 ~ 5 for both frontal and occipital electrodes). However, it is important to notice that the combined p values obtained using the Fisher method did not reach the significance threshold in the lateralization condition, reducing the relevance of this specific result. Covert attention modulates forward waves only with visual stimuli To confirm our previous results, we replicated the same traveling waves analysis on two publicly available EEG datasets in which participants performed similar attentional tasks (experiment 1 of Foster et al., 2017 and experiment 1 of Feldmann-Wüstefeld and Vogel, 2019). In the first experiment from the Feldmann-Wüstefeld and Vogel dataset, participants were instructed to perform a visual working memory task in which, while keeping a central fixation, they had to memorize a set of items while ignoring a group of distracting stimuli. We focused our analysis on those trials in which the visual items to remember were placed either to the right or the left side of the screen, while the distractors were either in the upper or lower part of the screen (we pulled together the trials with either two or four distractors, as this factor was irrelevant for our analysis). The stimuli were shown for 200 ms, and we computed the amount of forward and backward waves in the 500 ms following stimulus onset. As shown in Figure 2 (central column), the analysis confirmed our previous results, demonstrating a strong interaction between the factors DIRECTION and LATERALITY (BF10 = 667, error ~2%; independently, the factors DIRECTION and LATERALITY had BF10 = 0.2 and BF10 = 0.4, respectively). These results confirmed that spatial attention modulates both forward and backward waves in the presence of visual stimulation. Next, we analyzed another publicly available dataset from Foster et al., 2017. In the first experiment of Foster’s study, participants completed a spatial cueing task, requiring them to identify a digit among distractor letters. After a central cue was displayed for 250 ms, participants attended one of eight locations for 1000 ms before the onset of the target and distractors. As in our design, participants allocated attention to different locations to the left or right of the screen while keeping central fixation. However, unlike in our and in Feldmann-Wüstefeld’s study, no stimulus was displayed while participants were attending one of the possible locations. Here, we assessed the amount of waves in the 1000 ms before the onset of the stimulus during attention allocation, when no visual stimuli were shown on the screen. Remarkably, as shown in Figure 2 (right panel), our analysis demonstrated an effect of the lateralization (LATERALITY: BF10 = 3.571, error ~1%), revealing more waves contralateral to the attended location, but inconclusive results regarding the interaction between DIRECTION and LATERALITY (BF10 = 2.056, error ~1%). However, using a classical ANOVA (i.e., without modeling the slope of the random terms), the interaction between DIRECTION and LATERALITY proved significant (F(1,16) = 9.81, p = 0.003, η2 = 0.13). In addition, when testing LATERALITY separately for forward and backward waves, we observed an effect in the backward waves (BF10 = 3.497, error <0.01%) but not in the forward waves (BF10 = 0.231, error <0.01%, supporting evidence in favor of the absence of an effect). In addition, as analyzed in our dataset, we tested the correlation between backward waves and alpha-band power in occipital (electrodes: PO3 and PO4) and frontal (electrodes: F3 and F4) regions. We found moderate evidence of a positive correlation between contra- and ipsilateral backward waves, and occipital (all Pearson’s r~ = 0.4, all BFs10~ = 3) but inconclusive evidence in the frontal areas (all Pearson’s r~ = 0.3, all BFs10~ = 2). These results supported those from our dataset, despite having a smaller amount of electrodes’ lines, and potentially reduced statistical power (see Figure 2, lower panels). All in all, we could confirm our previous conclusion that covert visual attention modulates top-down oscillatory waves, showing this effect even in the absence of visual stimulation. In addition, we surmised that the lateralization effect we reported in the forward waves in our dataset (absent in the Foster dataset) is related to the steady visual stimulation during the attentional allocation, in line with our previous results demonstrating that oscillatory bottom-up waves reflect sensory processing (Alamia and VanRullen, 2019; Pang et al., 2020). Both detected targets and distractors elicit FW waves, but not missed targets In our previous analysis, based on a subset of trials in which neither a target nor a distractor occurred, we demonstrated that sustained attention to one hemifield generates oscillatory alpha-band waves propagating forward in the contralateral hemisphere and backward in the ipsilateral one. We now assess whether the occurrence of a specific event, such as the onset of a target or a distractor stimulus, could induce the generation of transient oscillatory waves. For this reason, we replicated the same analysis on those trials including either a target or a distractor (on average, each participant performed 146.25 trials in each condition), to quantify the amount of waves locked to the onset of these events. The upper panels of Figure 4A reveal the amount of forward and backward waves contralateral to the stimulus. Note that the targets and distractors appeared in the attended and unattended locations, respectively. A Bayesian ANOVA reveals no difference between targets and distractors (EVENT: BF10 = 0.206, error ~1%), or their interaction (DIRECTION × EVENT: BF10 = 0.423, error ~5%), as shown in the top-right panel of Figure 4. This result reveals that both target and distractor elicit forward waves propagating contralateral to the hemifield where they occur. Next, we investigated whether the waves in the hemisphere contralateral to the attended hemifield correlate with the participant’s performance in detecting the target (a QUEST algorithm kept the accuracy throughout the experiment around 80%). Remarkably, we found an effect concerning the ‘hit’ and ‘miss’ target, as revealed by a significant interaction of the DIRECTION and EVENT factors (DIRECTION × EVENT: BF10 = 4.085, error ~2%), as shown in the bottom-right panel of Figure 4A. Interestingly, Figure 4B reveals the amount of waves 400 ms before and after the onset of the stimulus, showing how a missed target is related to a decrease (increase) in forward (backward) waves contralateral (ipsilateral) to the attended location, possibly due to attentional fluctuations during each trial. Figure 4 Download asset Open asset Event analysis. (A) The figure shows the amount of forward (in blue) and backward (in red) contralateral waves around the onset of the target/distractor (left) or hit and missed targets (right panel). Error bars are standard error of the mean. We found an interaction effect when we analyzed the hit versus missed target. (B) The 2D maps represent the amount of waves in the 11 lines of electrodes (x-axis) and around the onset time (y-axis) for forward and backward waves, and for hits and missed targets separately. The opposite pattern for hits versus misses, already visible before the target onset, suggests that missed targets are due to a failure of attentional allocation rather than sensory processing; and consequently, that proper attentional allocation is characterized by contralateral forward waves and ipsilateral backward waves. Discussion Previous studies demonstrated that selective attention modulates alpha-band oscillations in occipital and parietal regions (Worden et al., 2000; Sauseng et al., 2005; Kelly et al., 2006; Thut et al., 2006; Händel et al., 2011), supposedly indicating their involvement in top-down, inhibitory functions. Here, we took a novel perspective on these results by interpreting oscillations as traveling waves (Muller et al., 2018), thus considering their spatial component on top of the temporal one. Our results revealed two distinct alpha-band waves propagating in opposite directions: attention modulates oscillations traveling from occipital to frontal regions only in the presence of visual stimulation, thus relating forward waves to visual processing (Lozano-Soldevilla and VanRullen, 2019; Pang et al., 2020); whereas oscillations propagating in the opposite, top-down direction were modulated by attention irrespective of the presence or absence of concurrent visual stimulation; as in standard studies of alpha power lateralization (Worden et al., 2000; Sauseng et al., 2005; Kelly et al., 2006; Thut et al., 2006; Händel et al., 2011), this attentional modulation involved both an decrease of alpha waves contralateral to the attended location, and an ipsilateral increase. In line with previous studies (Gulbinaite et al., 2017; Deng et al., 2019; Schuhmann et al., 2019; Sokoliuk et al., 2019; Kasten et al., 2020), our results support the thesis that distinct alpha-band oscillations are involved in separate cognitive processes. A recent study from Sokoliuk et al., 2019 demonstrated two different sources of alpha-band oscillations during a multisensory task: one, located in visual areas, reflects the ‘spotlight of attention’ and decreases linearly with increasing attention, whereas another one indicates attentional efforts and occurs in parietal regions. Gulbinaite et al. also demonstrated that parietal, but not occipital alpha-band oscillations are responsible for the oscillatory reverbe