The individuality of shape asymmetries of the human cerebral cortex
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Evaluation Summary:
The paper is of interest to scientists who study neuroanatomy or the many behavioural phenotypes that have been proposed to be associated with left-right asymmetry of the human brain. The authors' new tool appears to provide clues to identify individuals based on shape asymmetry.
(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 #2 agreed to share their name with the authors.)
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Abstract
Asymmetries of the cerebral cortex are found across diverse phyla and are particularly pronounced in humans, with important implications for brain function and disease. However, many prior studies have confounded asymmetries due to size with those due to shape. Here, we introduce a novel approach to characterize asymmetries of the whole cortical shape, independent of size, across different spatial frequencies using magnetic resonance imaging data in three independent datasets. We find that cortical shape asymmetry is highly individualized and robust, akin to a cortical fingerprint, and identifies individuals more accurately than size-based descriptors, such as cortical thickness and surface area, or measures of inter-regional functional coupling of brain activity. Individual identifiability is optimal at coarse spatial scales (~37 mm wavelength), and shape asymmetries show scale-specific associations with sex and cognition, but not handedness. While unihemispheric cortical shape shows significant heritability at coarse scales (~65 mm wavelength), shape asymmetries are determined primarily by subject-specific environmental effects. Thus, coarse-scale shape asymmetries are highly personalized, sexually dimorphic, linked to individual differences in cognition, and are primarily driven by stochastic environmental influences.
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Author Response
Reviewer 1 (Public Review):
The paper by Chen et al studies inter-individual differences in the left-right asymmetry of the shape of the cerebral cortex. The authors introduce a novel shape asymmetry measure based on a spectral analysis of cortical geometry, reporting that relatively coarse scales of shape asymmetry are highly specific to individual study participants. Shape asymmetry (SAS) is shown to have associations with cognition and biological sex, but not handedness. Result suggest that shape asymmetry is not highly heritable, and that it is driven primarily by environmental rather than genetic influences.
The paper has many strengths. The problem of investigating directional versus fluctuating asymmetry is clearly stated and biologically important. SAS is based on a sophisticated methodological approach and …
Author Response
Reviewer 1 (Public Review):
The paper by Chen et al studies inter-individual differences in the left-right asymmetry of the shape of the cerebral cortex. The authors introduce a novel shape asymmetry measure based on a spectral analysis of cortical geometry, reporting that relatively coarse scales of shape asymmetry are highly specific to individual study participants. Shape asymmetry (SAS) is shown to have associations with cognition and biological sex, but not handedness. Result suggest that shape asymmetry is not highly heritable, and that it is driven primarily by environmental rather than genetic influences.
The paper has many strengths. The problem of investigating directional versus fluctuating asymmetry is clearly stated and biologically important. SAS is based on a sophisticated methodological approach and rigorously applied. The use of three datasets increases the generalizability of the results, and the comparison to fMRI measures provides important context. Weaknesses include the interpretability of the measure and some specific methodological issues that could be further addressed as discussed below.
We appreciate the positive feedback. As in our responses below, we present new figures and analyses to increase the interpretability of the SAS and address the specific methodological issues.
- The lack of higher identifiability of fine-grained SAS is hard to understand. Given that secondary and tertiary sulci are not likely to change between time point 1 and time point 2, and that it is known that secondary and tertiary sulci vary more than primary sulci between people, this suggests that higher measurement error at finer scales may limit the comparisons between fine and coarse made in the paper.
We appreciate the point. The spatial scale for optimal identifiability in our analysis included secondary sulci but captured limited information about tertiary sulci. While the general location of secondary and tertiary sulci may not change much within an individual over time, subtle changes in regional grey matter volume may alter the shape of surrounding sulci and gyri in such a way that variations at fine spatial scales carry less identifying information. Our shape measures are sensitive to both sulcal and gyral anatomy and other changes in cortical shape.
Higher measurement noise at fine scales may indeed play a role. In our revised manuscript, we now include a demonstration of this effect in Figure 2—figure supplement 2 and have amended Lines 265-269 of the revised manuscript accordingly:
"The reconstruction captures shape variations at a coarse scale, representing major primary and secondary sulci, but with minimal additional details. If we include additional eigenfunctions to capture more fine-scale anatomical variations, inter-session image differences increase, suggesting that finer spatial scales may be capturing dynamic aspects of brain structure that are more susceptible to increased measurement noise (Figure 2—figure supplement 2)."
We have also amended Lines 435 to 439:
"It is perhaps surprising that individual differences in cortical shape are most strongly expressed at coarse scales, given the known variability of fine-grained anatomical features such as the presence and trajectories of tertiary sulci. It is possible that local subtle changes in grey matter volume affect fine-scale geometry in such a way that it carries less identifying information, or that such fine scales carry too much measurement noise to be used for the purpose of identification."
- From a neuroanatomical perspective, it is not clear what individuals with different asymmetries of shape at different scales actually look like, which limits the interpretability of the measure.
To improve the interpretability of the SAS, we have added one supplementary figure, which we refer to in Lines 171 to 173 of the revised manuscript:
"In general, a brain with a higher degree of shape asymmetry has SAS values that more strongly depart from zero (Figure 1—figure supplement 1)."2
- The possibility that image quality could affect measures of shape asymmetry is not addressed.
Thank you for raising this important issue. The images of each dataset used in this study −OASIS-3, ADNI, HCP− all underwent correction of FreeSurfer segmentations and passed quality control procedures for each dataset. Indeed, the HCP dataset is widely accepted to include some of the best quality images among all open-source data. Therefore, our data are not uncharacteristically noisy. As indicated in our response to Comment 1, increased noise at fine-grained resolutions may affect identifiability at these scales. To further address this issue, we have added further details in Lines 674 to 681 of the revised manuscript about the correlation between the Euler number from FreeSurfer (1) and the SAS:
"To further check the possible influence of image quality on the SAS, we first took the mean of the Euler number of the left and right hemispheres using FreeSurfer, which is widely used as an index of image quality (1-3), and then calculated the Pearson’s correlation between the mean Euler number and the SAS across the first 200 eigenvalues. For the HCP s1200 dataset, the correlations were all below 0.07 (PFDR > 0.05). For the OASIS-3, the correlations were all below 0.18 (PFDR > 0.05) at either time 1 or time 2 MRI session. These results indicate that image quality does not strongly influence the SAS, which is in line with past findings that the eigenvalues and eigenfunctions of the Laplace-Beltrami Operator are robust to image noise (4)."
- The paper does not address that different way of measuring of handedness could theoretically have different associations with asymmetry measures.
Thank you for this comment. In our original analysis, we used the handedness measured by the Edinburgh Handedness Inventory (EHI) as a continuous variable from -100 to 100, with values closer to 100 representing stronger right-handedness. There are different cut-off scores to categorize handedness, but these thresholds are still arbitrary, and thus applying the EHI score as a continuous variable is a widely used approach (5, 6). Here, we tested two thresholds to categorize the handedness. First, right-handed (EHI: 71-100), left-handed (EHI: -100 to-71), and ambidextrous (EHI: -70 to 70) (7-9); second, right-handed (EHI: 50 to 100), left-handed (EHI: -100 to-50), and ambidextrous (EHI: -49 to 49) (10, 11). The categorized handedness variable, regardless of the threshold, was still unrelated to the SAS (2 to 144 eigenvalues). We have amended Lines 818 to 828 of the revised manuscript to better clarify how handedness was measured:
"The HCP dataset provides the handedness preference measured by the Edinburgh Handedness Inventory (EHI) (12). EHI is the most widely used handedness inventory (10, 13), with resulting scores range from -100 (complete left-handedness) to 100 (complete right-handedness) (12). Handedness preference is not a bimodal phenomenon (8), and cut-off scores to categorize the handedness are still arbitrary. We therefore used the EHI score as a continuous variable in our main analysis, which is a widely used approach (5, 6). To further confirm the robustness of the relationship between handedness and the SAS, we tested two thresholds to categorize handedness. First, right-handed (EHI: 71-100), left-handed (EHI: -100 to-71), and ambidextrous (EHI: -70 to 70) (7-9); second, right-handed (EHI: 50 to 100), left-handed (EHI: -100 to-50), and ambidextrous (EHI: -49 to 49) (10, 11). Regardless of the threshold, the categorized handedness variable was still unrelated to the SAS (2 to 144 eigenvalues)."
Reviewer #2 (Public Review):
Being a paleoanthropologist, I am not a real specialist of the neuroscientific field. For this reason, my understanding of the methods, and particularly of the mathematics behind, may be partial. However, I am used to studies of bilateral variation of the brain. For these reasons, my comments mostly concern the theorical framework of the study, the way the data are analysed and exploited and the interpretations. The authors propose with this paper a new approach to characterize the main asymmetries of the whole cortical shape. This new tool is interesting and provides an original perspective on a longstanding question. Thanks to this approach, the authors identify interesting individual characteristics as individual's shape asymmetry appear to be a good parameter to identify each individual. I have more concerns about the application of this new tool in the context of earlier studies of human brain asymmetries, particularly when the authors contextualise their own researcher and results within the existing knowledge on the topic. From a methodological point of view, I would be interest in having more information about the identified bilateral variation for individuals and samples and a clearer characterization of different parameters for bilateral variation.
We appreciate the feedback. As per our response to Comment 2 of Reviewer 1’s Public Review, our revised manuscript now includes a new Figure 2—figure supplement 2, which provides examples of how cortical shape asymmetries appear at different spatial scales for different values of the SAS.
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Evaluation Summary:
The paper is of interest to scientists who study neuroanatomy or the many behavioural phenotypes that have been proposed to be associated with left-right asymmetry of the human brain. The authors' new tool appears to provide clues to identify individuals based on shape asymmetry.
(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 #2 agreed to share their name with the authors.)
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Reviewer #1 (Public Review):
The paper by Chen et al studies inter-individual differences in the left-right asymmetry of the shape of the cerebral cortex. The authors introduce a novel shape asymmetry measure based on a spectral analysis of cortical geometry, reporting that relatively coarse scales of shape asymmetry are highly specific to individual study participants. Shape asymmetry (SAS) is shown to have associations with cognition and biological sex, but not handedness. Result suggest that shape asymmetry is not highly heritable, and that it is driven primarily by environmental rather than genetic influences.
The paper has many strengths. The problem of investigating directional versus fluctuating asymmetry is clearly stated and biologically important. SAS is based on a sophisticated methodological approach and rigorously applied. …
Reviewer #1 (Public Review):
The paper by Chen et al studies inter-individual differences in the left-right asymmetry of the shape of the cerebral cortex. The authors introduce a novel shape asymmetry measure based on a spectral analysis of cortical geometry, reporting that relatively coarse scales of shape asymmetry are highly specific to individual study participants. Shape asymmetry (SAS) is shown to have associations with cognition and biological sex, but not handedness. Result suggest that shape asymmetry is not highly heritable, and that it is driven primarily by environmental rather than genetic influences.
The paper has many strengths. The problem of investigating directional versus fluctuating asymmetry is clearly stated and biologically important. SAS is based on a sophisticated methodological approach and rigorously applied. The use of three datasets increases the generalizability of the results, and the comparison to fMRI measures provides important context. Weaknesses include the interpretability of the measure and some specific methodological issues that could be further addressed as discussed below.
1. The lack of higher identifiability of fine-grained SAS is hard to understand. Given that secondary and tertiary sulci are not likely to change between time point 1 and time point 2, and that it is known that secondary and tertiary sulci vary more than primary sulci between people, this suggests that higher measurement error at finer scales may limit the comparisons between fine and coarse made in the paper.
2. From a neuroanatomical perspective, it is not clear what individuals with different asymmetries of shape at different scales actually look like, which limits the interpretability of the measure.
3. The possibility that image quality could affect measures of shape asymmetry is not addressed.
4. The paper does not address that different way of measuring of handedness could theoretically have different associations with asymmetry measures.
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Reviewer #2 (Public Review):
Being a paleoanthropologist, I am not a real specialist of the neuroscientific field. For this reason, my understanding of the methods, and particularly of the mathematics behind, may be partial. However, I am used to studies of bilateral variation of the brain. For these reasons, my comments mostly concern the theorical framework of the study, the way the data are analysed and exploited and the interpretations. The authors propose with this paper a new approach to characterize the main asymmetries of the whole cortical shape. This new tool is interesting and provides an original perspective on a longstanding question. Thanks to this approach, the authors identify interesting individual characteristics as individual's shape asymmetry appear to be a good parameter to identify each individual. I have more …
Reviewer #2 (Public Review):
Being a paleoanthropologist, I am not a real specialist of the neuroscientific field. For this reason, my understanding of the methods, and particularly of the mathematics behind, may be partial. However, I am used to studies of bilateral variation of the brain. For these reasons, my comments mostly concern the theorical framework of the study, the way the data are analysed and exploited and the interpretations. The authors propose with this paper a new approach to characterize the main asymmetries of the whole cortical shape. This new tool is interesting and provides an original perspective on a longstanding question. Thanks to this approach, the authors identify interesting individual characteristics as individual's shape asymmetry appear to be a good parameter to identify each individual. I have more concerns about the application of this new tool in the context of earlier studies of human brain asymmetries, particularly when the authors contextualise their own researcher and results within the existing knowledge on the topic. From a methodological point of view, I would be interest in having more information about the identified bilateral variation for individuals and samples and a clearer characterization of different parameters for bilateral variation.
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