Sequential alpha and theta dynamics resolve competition between rival visual stimuli

Reviewer #1 (Public review):

Summary:

These authors used a binocular rivalry task with flickering stimuli in which subjects had to report the color of the target grating at the end of each trial. Target or distractor cues provided information about the orientation of the respective stimulus prior to each trial. The stated goals of this project include testing the neural mechanisms underlying strategic target and distractor processing. Behavioral enhancement was observed for target cueing, while no cost was noted for distractor cueing. These authors present evidence for reactive suppression, characterized by pronounced frontal theta activity that reduced the sensory gain (SSVEP) of the distractor. Distractor cues also increased alpha activity over parietal areas, which these authors link to attentional gating while pointing out no relationship with sensory gain.

Strengths:

This manuscript clearly reflects thoughtful analysis of the available data. Alongside a simple and effective task design, sophisticated methods provide good support for most of the claims made by these authors.

Weaknesses:

Lack of temporal precision for SSVEP effects. I would like to see how sensory gain is/isn't dynamically modulated in the moments after the initial ERP to see if there could be differences compared to the broader window used presently (1.3 to 3.1 seconds).

These authors indicate that persistence of the neural representation of cued distractor orientations into the rivalry period is evidence against a "search-and-destroy" type mechanism where distractors are enhanced to then be suppressed reactively. This claim relies on an indirect link between the maintenance of information about distractor orientation (i.e., successful orientation decoding) and the processing of sensory representations. This claim would be backed up more substantially if the SSVEP (a measure of sensory processing) could reveal temporal dynamics on a finer scale.

Reviewer #2 (Public review):

Summary:

The findings are conceptually useful - a sequential alpha-then-theta architecture for proactive gating and reactive distractor suppression would be a compelling contribution to the attention control literature - but the evidence is incomplete at best. The central dissociation rests on an inadequate proxy for perceptual dominance, the key alpha-behavior effect is small (d = 0.199) and confined to a single unprotected data quadrant, and the GLMM uses an inadequate random effects structure that inflates false-positive risk.

Strengths:

The SSVEP frequency-tagging + binocular rivalry combination is genuinely inventive for isolating sensory gain signals from the two competing stimuli simultaneously. The finding that distractor cueing enhances sensory processing of the distractor yet fails to impair behavior is a clean result that directly addresses a behavioral paradox in the attentional suppression literature. The non-phase-locked TF analysis and the use of RESS for SSVER extraction are methodologically sound.

Weaknesses:

The most consequential flaw in the paper is the operationalization of "perceptual dominance." The authors explicitly acknowledge in a footnote that trial categorization as "target-dominant" or "distractor-dominant" is based on which eye received the stimulus, not on participants' actual perceptual reports. Because participants were never asked to report which stimulus was dominant (only to reproduce the target's color), the assignment is an anatomical proxy, not a perceptual measure. This matters enormously for the paper's central claims. Specifically: (a) The entire two-mechanism dissociation (theta for target-dominant trials, alpha for distractor-dominant trials) is built on a trial-type categorization that may not reflect subjective perceptual experience on a given trial, and (b) Dominant-eye stimuli do typically win initial rivalry dominance, but dominance alternates, and in a 2-second window (the stimulus duration used), perceptual states likely fluctuate in many trials. The lack of button-press perceptual tracking (e.g., continuous dominance reports) means the authors cannot verify that their neural effects actually correspond to the perceptual states they claim. This is a major structural limitation of the design that can't be retroactively corrected, and it significantly weakens the consciousness/awareness framing of the findings.

Another significant issue is that the parietal alpha effect on behavior is confined to a very specific quadrant of the data: distractor-dominant trials where both target and distractor SSVERs are weak simultaneously. The authors present this as an elegant result - "alpha helps most under high perceptual uncertainty" - but it could equally reflect insufficient statistical power for effects in the other three SSVER-strength cells (target strong/distractor weak; target weak/distractor strong; both strong). The Cohen's d for the alpha effect on target reporting probability is only d = 0.199, which is a very small effect. With N=36 and no correction for the multiple SSVER-strength subgroupings tested, there is a real risk that this specific cell-finding is a false positive, while the null in adjacent cells reflects inadequate power rather than a genuine boundary condition.

A third major limitation is that with a design that includes 6 fixed effects and all their interactions, the random effects structure should include random slopes for at least the key predictors (cueing condition, dominance). Fitting maximal random effects models or justified reduced structures (Barr et al., 2013) is standard in within-subjects EEG research. Using only random intercepts risks inflating Type I error rates for the interaction terms that form the core of the paper's claims. The authors provide a supplementary table (Table S1) but do not describe whether model convergence was verified or alternative random effects structures were tested.

Fourth, the paper's title and central claim are that alpha and theta dynamics operate sequentially. However, the temporal ordering (preparatory alpha -> rivalry-phase theta) is primarily shown by examining each oscillation in its respective analysis window, not by a single analysis testing whether the sequence itself predicts behavior better than either mechanism alone. A path analysis or cross-lagged model linking trial-level alpha to subsequent theta, and both to behavior, would directly substantiate the "relay" framing. Without this, the sequential architecture is more of an interpretation than a demonstrated property.

Finally, the frontal theta cluster identified by permutation testing spans 3 to 16 Hz - a range that extends well into the alpha band. Calling this a "theta" effect while simultaneously discussing alpha as a separate mechanism is difficult to reconcile. At minimum, this frequency boundary issue warrants explicit discussion.

Reviewer #3 (Public review):

Summary:

Interest was especially focused on how foreknowledge of the orientation of either the target or the distractor could be used to resolve the competition between these stimuli and properly report the target color. The target or distractor was pre-cued by a solid or dashed orientation cue. They were displayed with slightly different presentation frequencies, which allowed for examining their sensory processing with steady-state visual evoked responses (SSVERs). Furthermore, orientation decoding was performed, which revealed that orientation cues selectively affected processing after stimulus onset related to the dominant but not the non-dominant eye. EEG analyses additionally focused on parietal alpha activity and frontal theta, both during the anticipatory phase and the stimulus-processing phase. Cueing the distractor vs. the target induced increased right parietal alpha power during the anticipatory phase, but this did not result in direct inhibition of distractor features. During the stimulus-processing phase, cueing the distractor resulted in increased theta activity. Finally, a generalized linear model was employed wherein trial-by-trial behavior (precision in target color report) was predicted by target and distractor SSVERs, type of pre-cued stimulus (target/distractor), preparatory parietal alpha power, stimulus processing-related frontal theta power, eye dominance, and all their interactions. Performance in the case of reduced sensory processing of the target (based on SSVER) showed more deviations when sensory processing of the distractor was high, but no such effect was observed when sensory processing of the target was high. The latter effects were modulated by eye dominance and cue. Increased theta reduced distractor sensory processing but not target sensory processing. Increased alpha was only beneficial when sensory evidence for both target and distractor was low. Results were interpreted as favoring sensory gating before stimulus onset, reflected by increased parietal alpha (i.e., pro-active control), while theta activity especially seemed relevant to suppress distractor activity (i.e., reactive control) thereby favoring target-related performance.

Strengths:

The authors convincingly show that EEG can provide crucial information about how the human brain deals with the conflict between a target and distractor in a binocular rivalry paradigm with pre-cues signaling either the target or the distractor orientation. An important aspect of the study is the focus on precision of target color report, in combination with the possibility to assess SSVERs to the target and distractor. The strength of this study may actually also be its weakness; the question is whether the presented ideas on proactive and reactive mechanisms can be generalized to paradigms that do not employ binocular rivalry. Separation of target and distractor processing by selectively presenting them to the left/right eye increases the conflict when the target is presented at the non-dominant eye, but what happens in the absence of binocular rivalry concerning the target-distractor conflict?

Weaknesses:

An important aspect of the study relates to the cue manipulation. In many studies, cues are often informative but not mandatory. Couldn't one argue that in this study task performance crucially depends on cue processing, as without the cue, it becomes difficult to tell apart the target from the distractor. It could be argued that participants are able to do this based on the slight difference in flickering frequency, but I doubt whether this is possible at all. However, if this were the case, then they might use this as an alternative cue and ignore the orientation cue. What do participants experience while performing this task? As the cue can be considered to be mandatory, the question may be raised what strategy the participants actually employed. If the target was cued, they simply may have prepared for this orienting and could ignore the distractor. However, if the distractor was cued, they could use two strategies: search for the stimulus without the cued orientation, or first detect the distractor, and then orient towards the other stimulus. The ideas and results on parietal alpha and frontal theta in combination with the other findings are certainly very interesting, but recently, it has also been argued that frontal theta may be more related to action control (e.g., see Panek et al., https://doi.org/10.1093/cercor/bhaf276) and also pro-active control (Cooper et al., 2017). So, it might be that increased theta reflects suppression of the response related to the distractor, which feeds back on its sensory processing. This raises the question whether there is possibly also some evidence on functional connectivity between frontal and posterior regions that varies depending on the precise condition. Are the results also shining a new light on the relation between attentional orienting and eye dominance (e.g., see Schintu et al., 2020)?