Distinct gradients of cortical architecture capture visual representations and behavior across the lifespan
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eLife Assessment
This study provides a valuable perspective on visual cortex architecture by identifying two cortical gradients that change across the lifespan and have distinct functional and structural features. The first gradient captures well-mapped variations in cortical thickness and myelination markers from early sensory to higher-order cortex, while the second gradient shows divergence in these measures with a more localized structure, notably predicting a previously unknown cluster of visual field maps in the anterior temporal lobe. The large-scale lifespan data are compelling, but the evidence overall is incomplete with key questions around methodical checks and implementation, the standard of evidence for the new visual maps, and how the gradient model relates to sharp tissue boundaries parcellating the cortex.
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Abstract
The microstructure of cells within human cerebral cortex varies across the cortical ribbon, where changes in cytoarchitecture and myeloarchitecture are thought to endow each region of cortex with its unique function. While fine-scale relative to a cell, these changes at population level impact architectural properties of cortex measurable in vivo by noninvasive MRI, such as the thickness and myelin content of cortex. This raises the question of whether or not we can use these in vivo architectural measures to understand cortical organization, function, and development more broadly. Using human visual cortex as a test bed, we demonstrated two architectural gradients, one in which cytoarchitecture and myeloarchitecture converge and another in which they diverge. These two gradients underlie the structural and functional topography of visual cortex, even predicting the presence of new visual field maps. Moreover, the two gradients show distinct visual behavior relevance and lifespan trajectory. These findings provide a more general framework for understanding human cortex, showing that architectural gradients are a measurable fingerprint of functional organization and ontogenetic routines in the human brain.
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eLife Assessment
This study provides a valuable perspective on visual cortex architecture by identifying two cortical gradients that change across the lifespan and have distinct functional and structural features. The first gradient captures well-mapped variations in cortical thickness and myelination markers from early sensory to higher-order cortex, while the second gradient shows divergence in these measures with a more localized structure, notably predicting a previously unknown cluster of visual field maps in the anterior temporal lobe. The large-scale lifespan data are compelling, but the evidence overall is incomplete with key questions around methodical checks and implementation, the standard of evidence for the new visual maps, and how the gradient model relates to sharp tissue boundaries parcellating the cortex.
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Reviewer #1 (Public review):
Summary:
The manuscript uses large-scale existing datasets that span almost the full range of human life (5-100 years) to identify two distinct architectural cortical gradients within the visual cortex. These gradients are distinct: in one, cytoarchitecture and myeloarchitecture converge and in the other, they diverge. The authors tested whether these gradients mapped onto known functional properties of the visual cortex, as well as accounting for visual behaviours that are impacted throughout the lifespan. The manuscript also reports the identification of a hitherto unknown cluster of visual field maps in the anterior temporal lobe.
Strengths:
A major strength of the current manuscript is the use of large-scale measurements of human brain structure throughout the lifespan, courtesy of the Human Connectome …
Reviewer #1 (Public review):
Summary:
The manuscript uses large-scale existing datasets that span almost the full range of human life (5-100 years) to identify two distinct architectural cortical gradients within the visual cortex. These gradients are distinct: in one, cytoarchitecture and myeloarchitecture converge and in the other, they diverge. The authors tested whether these gradients mapped onto known functional properties of the visual cortex, as well as accounting for visual behaviours that are impacted throughout the lifespan. The manuscript also reports the identification of a hitherto unknown cluster of visual field maps in the anterior temporal lobe.
Strengths:
A major strength of the current manuscript is the use of large-scale measurements of human brain structure throughout the lifespan, courtesy of the Human Connectome Project Initiative. The scope of this cross-sectional analysis would be rare, if not impossible to achieve through an individual project.
The approach employed holds promise for assessing the link between large-scale anatomical gradients in the brain and functional/behavioural properties. The current manuscript focuses on the visual cortex but the approach could easily be implemented across the brain in general.
Weaknesses:
While the evidence in favour of the two gradients largely supports the claims, the evidence for a new visual field map cluster in the anterior temporal lobe falls short of the level used historically when identifying visual field maps in the visual cortex and is, at present, not convincing.
More specifically, the progressions of polar angle within the putative anterior lobe cluster are highly variable across subjects. Few subjects have convincing polar angle reversals at either the horizontal or vertical meridians. In other cases, a putative border is shown that spans different polar angles, which does not align with the accepted definitions for visual field maps in the cortex.
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Reviewer #2 (Public review):
Summary:
The authors used large MRI data sets of the Human Connectome Project (HCP) and also conducted additional pRF analyses to describe the structural architecture of the human visual cortex in reference to its functional features. By conducting a PCA, they identify 2 components that explain around 50% of the variance, the driven by a positive co-variance between cortical thickness and T1/T2 ratio, the second by their negative co-variance. The first PC spans most early visual cortex and hence shows a relation to pRF size when taking both early and late visual areas into account. The second is more variable in location and does not relate to pRF size or visual hierarchy. The relationship between these two gradients to cell body density using the BigBrain is explored.
Strengths:
The authors make an attempt …
Reviewer #2 (Public review):
Summary:
The authors used large MRI data sets of the Human Connectome Project (HCP) and also conducted additional pRF analyses to describe the structural architecture of the human visual cortex in reference to its functional features. By conducting a PCA, they identify 2 components that explain around 50% of the variance, the driven by a positive co-variance between cortical thickness and T1/T2 ratio, the second by their negative co-variance. The first PC spans most early visual cortex and hence shows a relation to pRF size when taking both early and late visual areas into account. The second is more variable in location and does not relate to pRF size or visual hierarchy. The relationship between these two gradients to cell body density using the BigBrain is explored.
Strengths:
The authors make an attempt to describe the overall architectural features of the cortex and link it to features of functional representations, and the underlying histology, using different sets of datasets and methods, including histology. They highlight that investigating the structural architecture of the cortex provides important information on their intrinsic organization and common features.
Weaknesses:
The neurobiological model does not take into consideration present knowledge about the microstructural organization of the visual system. This limits the way the results are interpreted correctly. Critical information on the layer-specific myeloarchitecture and cytoarchitecture (and their relation to cortical thickness), as explored for example by Sereno et al. 2013 Cereb Cortex, is missing. There is no information given with respect to how different visual areas differ in their microstructural profile. It is also not mentioned that cortical parcellation is indeed characterized by sharp boundaries between areas, rather than structural gradients, so it remains unclear why focusing on a gradient is of interest. The authors cite the parcellation atlas by Glasser et al. 2016, but do not discuss the rationale of this publication, which was not the definition of gradients, but the definition of sharp boundaries for cortex parcellation. Indeed (as explained below), the results of the authors seem to a large extent to be driven by cortex parcellation, but instead of acknowledging this fact, the authors write (line 179) that "we hypothesize that these local deviations from the canonical thickness and density of cortex underlie the finer-scale division of visual cortex into categorically distinct regions. That is, does the realization of the cortex into distinct regions involve these regions becoming more distinct from a prototypical cortical sheet (i.e., gradient 1)?" - While the first sentence is reasonable, the second sentence is pure speculation ignoring present knowledge on cortical parcellation of this area according to which there is no "prototypical cortical sheet", but each area has its distinct microstructural profile.
Instead of building on present, detailed knowledge of brain anatomy and in-vivo cortex parcellation of the visual system and its known relation to visual maps, the authors focus on two metrics of cortex architecture (mean T1/T1 over depth and cortical thickness), and conduct a PCA to explore their shared variance. It needs to be clarified if the PCA was conducted correctly. There is no mention of standardizing the variables, which could bias the results. In addition, in a PCA, all possible features are categorized as vector components, and those are scanned through the samples, hence, one such analysis per vertex. But the authors write "in which participants are features and cortical vertices are samples" and "the thickness and tissue density maps were concatenated". This needs clarification. The architecture of the PCA should be visualized better.
Because the PCA only contains two features, PC1 is driven by the positive relationship between cortical thickness and mean T1/T2, whereas PC2 is driven by their negative relationship. Because in the early visual cortex, cortical thickness and mean T1/T2 correlate positively, it naturally follows that PC1 relates to pRF size (but mediated by the actual cortex parcellation). However, it is unclear why this insight is interesting. I also do not share the view that "these findings demonstrate that gradient 1 acts as a global gradient enveloping the entire visual cortex (...) while gradient 2 acts as a local gradient specific to individual visual streams". I think this relationship between cortical thickness and T1/T2 ratio does not have much to do with local and global gradients. But if so, stronger arguments as to why this should be the case should be presented.
What the authors make of this result (particularly the discussion starting line 366) is not clear to me. I cannot follow the line of argumentation, which in my view is too far away from the data.
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