1. Reviewer #2 (Public Review):

    It is well established in diverse sensory modalities that fluctuating excitability of cortical regions is likely reflected in ongoing alpha activity in these respective areas. However, how this oscillatory activity relates to "intensities" of neural (~evoked) responses and perception following supra-threshold stimulation is not well established. Building up and extending also their own previous work in the somatosensory domain (Stephani et al., 2020), this is the main goal of the authors.

    To achieve their goals the authors implement a straight-forward somatosensory discrimination task while recording EEG. The study builds up on very high quality data as well as analysis approaches and along with a decent sample size allows draw conclusions with respect to the aforementioned questions. Using CCA to analyse ongoing and stimulus (single-trial) evoked responses from a (for the non-invasive researcher world) well-circumscribed brain region is a clear strength, when studying the inter-relationships between these brain activity features. The displayed results of the structural equation model (Figure 4) is a great summary of the main effects of the results and an important contribution to the field. In particular, I really appreciate the inclusion of peripheral responses, that convincingly make the case that the non-trivial relationship between stimulus and perceptual intensity on the one hand side and early evoked response (N20) on the other hand side indeed emerges at a brain level.

    However there are also some weaknesses that need to be mentioned:

    • The main weaknesses of the manuscript becomes most apparent with respect to the stated impact that "The widespread belief that a larger brain response corresponds to a stronger percept of a stimulus may need to be revisited.". I am not really sure if there are many cognitive neuroscientists, that would actually subscribe to such a simplistic relationship between evoked responses and perception and that temporal differentiation (early vs late responses) and the biasing influence of prestimulus activity patterns are becoming increasingly recognized. So rather than actually changing a dominant paradigm, this work is an (excellent) contribution to a paradigm shift that is already taking place.

    • Also it should be considered that with regards to the analysis approach using CCA, the claims are mainly restricted to BA3b: i.e. while I also think that this is a strength of the current study, one should refrain from over-interpreting the results in a very generalized manner. The authors do include some "thalamus" and "late" evoked response patterns as well, however that presentation of the results is somewhat changed now as compared to the N20 (e.g. using LMEs rather than comparison of extremes; not using SEMs). The readability of results and especially the comparison of effects would profit from a more coherent approach.

    • I have some concerns whether the relationship between large alpha power and more negative N20s could be driven by more trivial factors rather than the model explanations the authors develop in the discussion. Concretely the question whether phase locking of large alpha power along with >30 Hz high pass filtering could produce a similar finding as shown e.g. in Figure 2c. This is an important issue, as prestimulus alpha influences the N20 amplitudes as well as the perceptual reports.

    • It is important to emphasize that the model develop is a post-hoc one, i.e. the authors do not develop already in the discussion various alternative scenario results based on different model predictions. Therefore there is no strong evidence in support of the specific one advanced in the discussion.

    Read the original source
    Was this evaluation helpful?
  2. Reviewer #1 (Public Review):

    In this study, Stephani et al. addresses the question of how ongoing fluctuations in neuronal excitability, as well as stimulus strength, impact the perception of above-threshold tactile stimuli and the subsequent stimulus-evoked brain activity. Specifically, pre-stimulus alpha oscillation amplitude and the N20 component of the SEP are used as a readout of cortical excitability, while signal detection theory quantities - sensitivity and criterion - derived from participant response are used as the behavioral correlates. The authors find that 1) higher prestimulus alpha amplitude is associated with a higher criterion, i.e., participants tend to rate stimuli as "weaker" regardless of the actual intensity, while there was no effect on sensitivity; 2) larger N20 amplitude (more negative) is associated with stronger stimulus intensity; 3) conditioned on actual stimulus intensity, larger N20 amplitude is associated with a higher criterion, similar to prestim alpha; 4) the above effects are confirmed using a multi-level structural equation model while also accounting for peripheral control measures; and finally 5) that the thalamic response, as measured in very early components, have no association with perceptual response and previous findings on later SEP components (N140) is reproduced in this data. The authors offer a physiological interpretation that explains the seemingly contradictory result by accounting for the recruitment level of cortical neurons and their membrane depolarization in excitable stages.

    Overall, I find this study to be very nicely done, well-written, and with informative figures. My expertise in signal detection theory and awareness of the SEP literature are limited, and the following comments will probably reflect that. Considering that, the introduction was very concise yet informative regarding the state of the field, and nicely motivates why suprathreshold stimulation is an interesting question to investigate, and was overall just a pleasure to read. The data and analyses seem convincing in supporting the authors' conclusions. The results are indeed puzzling (in an interesting way), and while the authors provide a nicely parsimonious explanation rooted in the underlying neurophysiology, I think this study has the potential to further motivate many lines of investigation, especially considering that the majority of works done in this field looks at the effect of ongoing neural activity on the detection of near-threshold sensory stimuli (as far as I know). I have some major concerns broadly regarding the interplay between alpha oscillation and the N20 (detailed below), the rest are mostly clarifying comments/questions that I believe may help the authors improve this paper, as well as other interesting points to consider in the discussion to relate to the broader literature.

    N20 and alpha oscillation

    My main technical concern lies in the choice of decomposition filter for SEP and alpha oscillations, and the conclusions the authors draw from that. Specifically, a CCA spatial filter is optimized here for the N20 component, which is then identically applied to isolate for alpha sources, with the logic being that this procedure extracts the alpha oscillation from the same sources (e.g., L359). I have no issues (or expertise) with using the CCA filter for the SEP, but if my understanding of the authors' intent is correct, then I don't agree with the logic that using the same filter isolate for alpha as well. The prestimulus alpha oscillation can have arbitrary source configurations that are different from the SEP sources, which may hypothetically have a different association with the behavioral responses when it's optimally isolated. In other words, just because one uses the same spatial filter, it does not imply that one is isolating alpha from the same source as the SEP, but rather simply projecting down to the same subspace - looking at a shadow on the same wall, if you will. To show that they are from the same sources, alpha should be isolated independently of the SEP (using CCA, ICA, or other methods), and compared against the SEP topology. If the topology is similar, then it would strengthen the authors' current claims, but ideally the same analyses (e.g., using the 1st and 5th quintile of alpha amplitude to partition the responses) is repeated using alpha derived from this procedure. Also, have the authors considered using individualized alpha filters given that alpha frequency vary across individuals? Why or why not?

    In the same vein, both alpha and N20 amplitude relate to perceptual judgement, and to each other. I believe this is nicely accounted for in the multivariate analysis using the SEM, but the analysis that partitions the behavioral responses using the 20% and 80% are done separately, which means that different behavioral trials are used to compute the effect of N20 and alpha on sensitivity and criterion. While this is not necessarily an issue given that there IS a multivariate analysis, I would like to know how many of those trials overlap between the two analyses.

    At multiple points, the authors comment that the covariation of N20 and alpha amplitude in the same direction is counterintuitive (e.g., L123-125), and it wasn't clear to me why that should be the case until much later on in the paper. My naive expectation (perhaps again being unfamiliar with the field) is that alpha amplitude SHOULD be positively correlated with SEP amplitude, due to the brain being in a general state of higher variability. It was explained later in the manuscript that lower alpha amplitude and higher SEP amplitude are associated with excitability, and hence should have the opposite directions. This could be explicitly stated earlier in the introduction, as well as the expected relationship between alpha amplitude and behavior.

    Furthermore, I have a concern with the interpretation here that's rooted in the same issue as the assumption that they are from the same sources: the authors' physiological interpretation makes sense if alpha and N20 originated from the same sources, but that is not necessarily the case. In fact, the population driving the alpha oscillation could hypothetically have a modulatory effect on the (separate) population that eventually encodes the sensory representation of the stimulus, in which case the explanation the authors provide would not be wrong per se, just not applicable. A comment on this would be appreciated in the revision.

    In addition, given how closely related the investigation of these two quantities are in this specific study, I think it would be relevant to discuss the perspective that SEPs are potentially oscillation phase resets. Even though the SEP is extracted using an entirely different filter range, it could nevertheless be possible that when averaged over many trials, small alpha residues (or other low freq components) do have a contribution in the SEP. If the authors are motivated enough, a simulation study could be done to check this, but is not necessary from my point of view if there is an adequate discussion on this point.

    Read the original source
    Was this evaluation helpful?
  3. Evaluation Summary:

    Stephani et al. address the question of how ongoing fluctuations in neuronal excitability, as well as stimulus strength, impact the perception of above-threshold tactile stimuli and the subsequent stimulus-evoked brain activity. The results are puzzling in an interesting way, and while the authors provide a nicely parsimonious explanation rooted in the underlying neurophysiology, editors and reviewers think this study has the potential to further motivate many lines of investigation. This manuscript will be of interest mainly to researchers using electrophysiological methods (EEG, MEG, ECoG etc.), as the authors have produced a very high-quality EEG data-set (including uncommon peripheral measurements).

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their names with the authors.)

    Read the original source
    Was this evaluation helpful?