Activity level in left auditory cortex predicts behavioral performance in inhibition tasks in children

  1. Sam van Bijnen
  2. Lauri Parkkonen
  3. Tiina Parviainen

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Abstract

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  1. Version published to 10.1016/j.neuroimage.2022.119371
  2. eLife

    ###Reviewer #3:

    Short-summary:

    Children (wide range) and adults participated in 3 MEG-experiments with auditory oddball paradigms varying in task demands. The focus is on the child N250m. Results show that although the N250m was not attenuated by task differences, increased activation in the left hemisphere (for at least the standard stimulus in the gng-task) was associated with better performances in inhibition tasks. Since the N250m in children was mainly located in the temporal cortices, whereas activation in adults was present in other areas, notable the ACG, this suggests that children differ from adults in the mechanisms required for cognitive control, and rely longer on sensori-motor areas.

    Positive: well-written, great pictures.

    Major comments:

    1. The proposed link between auditory skills and inhibition is poorly explained and requires more elaboration. They want to relate auditory processing to " cognitive skills" (line 22, 77). Yet cognitive skills are a broad construct, encompassing many skills and abilities, including for instance reading, but also executive functions, which includes inhibition (Miyake et al., 2000) . Actually why zoom in on inhibition? Is it as one of the three components of executive function (Miyake et al., 2000) or is it viewed as part of self-regulation (Nigg, 2017)? You refer to cognitive control (46/47)- which suggests the latter explanation - but this remains unclear. It would help the reader to use consistent terminology (e.g., inhibition, cognitive control, executive control, inhibitory control are used now), or to highlight the links between the related concepts. Moreover, there are many paradigms to test inhibition, why did you chose the one you chose (Littman & Takacs, 2017)? And you also examine the behavioral performance sin the inhibition-MEG task (line 303)? Why the additional focus on attention in the results?

    2. Your summary of the two child components (N1m and N250m) predicts different findings with the relationships with inhibition. That is, the link between the child N1m and inhibition should be smaller/non-existent, while it is mainly in the N250m that you expect it. While your results prove evidence towards the latter, your analyses do not concern the first component. It would be stronger if you do.

    3. The logic of having three different auditory-listening tasks, and one behavioral outcome measure was not entirely clear to me. It seems that the paper is addressing various aims (e.g., replicate earlier work showing that the N250m is unaffected by task parameters in children while it is only present in adults for active tasks; another is linking the N250 m across all three tasks, or only for one of the three, if so, which? related to inhibition, but only for children, or also adults?) it would help to be explicit about this. For instance, there is an MEG-inhibition task and a behavioral task. Were you going to relate performances to both?

    4. Why is age a significant predictor in explaining SSRT performance when adding left hemisphere OB-deviant, but not when adding LH GNG-S? Moreover, isn't it surprising that increase in activation yields better SSRT scores when this component disappears in adults?

    5. From an association one cannot infer causal relationships - such limitations need to be discussed in more detail. Results do not allow for concluding that a sustained response ' aid inhibitory performance' (line 624).

  3. eLife

    ###Reviewer #2:

    In this study the authors sought to explore the relationship between a child-specific auditory evoked response (N250) and cognitive control, using a classic auditory oddball paradigm. Here the cognitive control was manipulated by varying the tasks that participants were instructed to do while listening to the oddball tone sequence: (a) ignore all sounds ("passive listening"), (b) respond to the standard tones ("go/no-go") and respond to the deviant tone (which was called "oddball task" in this study).

    Using the combined MEG and EEG as well as MRI, they reported an association between the strength of N250 in the left hemisphere and the behavioural performance in the go/no-go task and a separate inhibition task. Based on this observation as well as the fact that N250 was only visually observed in the children's brain response, the authors claimed that when doing sound involved cognitive tasks, different neural mechanisms were employed by adults and children. Considering the difficulty in operating a MEG and EEG combined experiment on children (6-14 years), the large sample size (n=78) is very, very impressive and the task was carefully embedded in a children-friendly game, which showed that the authors did a lot of work for this project.

    However, it is hard to generalise such a conclusion based on the current paradigm and the results reported here. I also found it's a bit hard to follow the logic in the original manuscript, not because of the language but I think it might need more thorough revision to better explain what exactly the authors hypothesize, why use this specific paradigm, and why analyse the data in these ways.

    Major comments:

    1. While the task "press a button to standard tone" is called go/no-go task, the task "press a button to deviant tone" is called an oddball task. Why is the latter not a go/no-go task? It's definitely ok to have different names for different blocks, and also to analyse the data in these two blocks separately to double check. However, I would not expect fundamental difference in these two blocks. (However, as mentioned later, the authors reported divergence between these two tasks).

    2. The main finding "Left hemisphere auditory responses at 250ms predicts behavioural performance on inhibition tasks" was based on the observation that, the brain activity in the left hemisphere (independent of the task) was negatively correlated with the within-individual variance in RT and the error rate in the go/no-go task (where subjects were instructed to respond to the standard tones) and the reaction time in a separate inhibition task done outside of the scanner. Why smaller within-individual variance in RT means better performance? Someone could be consistently very slow and this should not be a better performer. I found this is confusing, especially that based on Table 3, there was no correlation between RT and the brain response strength.

    3. The scatterplots in Figure 7 shows the correlation reported in Table 3. However, the correlation seems to be largely driven by a few outliers: about 5 subjects whose source amplitude was much more negative than the rest of the population. Why did these subjects have a particularly strong source amplitude? After excluding these five subjects' data, will the correlation remain significant?

    4. This point is related to points (1) and (2). In table 3, left hemisphere response during passive listening was strongly correlated with ICV, ERR and SSRT, but in table 6, there were no more correlations for passive listening. Can the authors explain why there is a difference between two passive listening sessions which in theory should be the same? Again, if there is no difference between "press a button to standard tone" and "press a button to deviant tone" and the correlation observed in table 3 was robust, then we would expect to see the significant correlations in table 6 for ICV, ERR too, but it is not true. These together make the finding less convincing. If there is any misunderstanding, the authors still need to justify these clearly in the manuscript and further analysis would be helpful.

    5. Interpretation of the result: Even if the association between the amplitude of N250 and the behavioural performance is proven robust and true, this doesn't mean that this activity "aid the inhibitory performance in children" (line 624). Correlation does not imply causation. The authors need to provide more direct evidence to support such a claim or consider re-wording.

    6. Design of the task: a. The block order: Why was the task order fixed for all participants? b. It is unclear why the passive listening block has a different number of trials (300) compared to the other two active blocks (360).

    7. Sample size: Although the large sample size used in this study is very impressive, it is unclear how this sample size was determined and why the sample size of two groups (children vs adults) was so different (children n=78, adults n=16). It is crucial to justify this difference in this study because the motivation of this study is based on the hypothesis that N250 is present in children but not in the adult.

    8. The unequal number of samples in statistical analysis: Related to the last two points, it is unclear whether the number of trials/participants was equalised before running the statistical analysis in this study.

    9. Handedness: As the authors themselves mentioned in the discussion, the effect in left hemisphere observed here could be related to the handedness. Then the authors should also report the handedness amongst the participants.

    10. Analysis: It is generally unclear why the children's data were divided into two groups: above or below 10 years old. The authors need to explain their rationale behind this clearly before doing so.

    11. Figure 3: Each sub-figure includes 6 different conditions and makes it very hard to visualise. Please consider plotting the results in pairs for comparison, also show error-bar and run proper time-series statistics on the result. Also, it is unclear which channels are selected based on the black and white cap image at the centre. Please visualise it differently, for example, colours.

  4. eLife

    ###Reviewer #1:

    This study by van Bijnen et al. used MEG/EEG recordings to examine the behavioral relevance of auditory processing in children, with a specific focus on an auditory cortical component around 250 ms, which only occurs in children but not in adults. They demonstrate that this component, particularly in the left auditory regions, covaries with several behavioral measurements in children. They conclude that the results suggest a shift in cognitive control function from sensorimotor regions in children to prefrontal involvements in adults.

    The study addresses an important question in both auditory neuroscience and developmental science and is carefully performed. The modified design for children is interesting. However, I am not quite convinced that the findings constitute a great breakthrough. Moreover, I have major concerns about the correlation analysis that would support the central claim in the paper, that is, the attentional inhibition relevance of the M250 component in the left auditory cortex.

    Major:

    1. The child-specific M250 component occurring in the auditory cortex is interesting, but as mentioned throughout the paper, this is a well established observation. This study provides some evidence for the behavioral correlates of the component, but I am not convinced that the correlations supports the unique function of the component in attentional inhibition and its development trajectory from children to adults. First, the author only focused on the M250 component and calculated its correlation to behavior and thus could not exclude that other components might also be involved in the process. I would suggest the authors to do the correlation throughout the time course to thoroughly seek the behavioral-related components. Second, even for the passive listening conditions when inhibition is not required, the M250 also correlated with some behavioral measurements in certain task (Table 3) ? Third, only the to-be-inhibited sound was analyzed so how could the results support that the component only correlates with attentional inhibition? I understand that the authors might want to avoid the motor confounding factors associated with attended sound, but without comparison or control analysis, the conclusion could not firmly hold. Finally, behavioral relevance analysis was only done on children but not adults.

    2. The authors calculated correlations between the M250 component with a series of behavioral measurements. Is there any way to do multiple comparison correction? Moreover, the results are inconsistent across different comparisons (e.g., Table 3, Table 6). For example, several behavioral indexes correlated with neural component for both PL and GN conditions (Table 3) while only SSRT showed correlation with the component under OB condition. I would suggest a more fair analysis by performing a GLM analysis using all the behavioral measurements (not just select factors that showed significant partial correlation which I think is double dipping to some extent, e.g., table 4, 7) as predictors.

    3. To support the developmental trajectory of the M250 component, the authors could also perform the behavioral correlation for adults and compare it to that for children, even the behavioral-relevant component might be different in time and occur in distinct brain regions.

  5. eLife

    ##Preprint Review

    This preprint was reviewed using eLife’s Preprint Review service, which provides public peer reviews of manuscripts posted on bioRxiv for the benefit of the authors, readers, potential readers, and others interested in our assessment of the work. This review applies only to version 1 of the manuscript.

    ###Summary:

    All the reviewers acknowledged the importance of the question the paper aims to address, the big sample size, and the interesting experimental design for children. The paper is also clear and well written. However, the reviewers raised several critical concerns that question the main conclusions, including the interpretation of the results (i.e., relation to inhibition in cognitive control), inconsistency across experiments (i.e., differences in the results between the two experiments), and analysis details (i.e., behavioral-neural correlations). The paper could also be improved by a reframing in which the hypotheses and rationale behind the experiments are better explained.

  6. Version published to 10.1101/2020.04.30.069906 on bioRxiv