Asymmetric Functional Gradients in the Human Subcortex
Curation statements for this article:-
Curated by eLife
Summary: This study investigates asymmetry in functional gradients in human thalamus, striatum and cerebellum. The authors found that the thalamus and the pallidum of the lenticular nucleus have strongly asymmetric principal functional gradients across the two hemispheres. In the case of the caudate and cerebellum, their 2nd and 3rd gradients were asymmetric. In general, the reviewers and editors found the study to be intriguing, but ultimately, felt that the dichotomous model, while interesting, was too speculative with no direct evidence presented. Considering also the lack of results on the functional significance of the asymmetries, the editors and reviewers felt that the study is better suited for a more specialized audience.
This article has been Reviewed by the following groups
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
- Evaluated articles (eLife)
Abstract
A central principle in our understanding of cerebral cortical organization is that homotopic left and right areas are functionally linked to each other, and also connected with structures that share similar functions within each cerebral cortical hemisphere. Here we refer to this concept as interhemispheric functional symmetry (IHFS). While multiple studies have described the distribution and variations of IHFS in the cerebral cortex, descriptions of IHFS in the subcortex are largely absent in the neuroscientific literature. Further, the proposed anatomical basis of IHFS is centered on callosal and other commissural tracts. These commissural fibers are present in virtually all cerebral cortical areas, but almost absent in the subcortex. There is thus an important knowledge gap in our understanding of subcortical IHFS. What is the distribution and variations of subcortical IHFS, and what are the anatomical correlates and physiological implications of this important property in the subcortex? Using fMRI functional gradient analyses in a large dataset (Human Connectome Project, n=1003), here we explored IHFS in human thalamus, lenticular nucleus, cerebellar cortex, and caudate nucleus. Our detailed descriptions provide an empirical foundation upon which to build hypotheses for the anatomical and physiological basis of subcortical IHFS. Our results indicate that direct or driver cerebral cortical afferent connectivity, as opposed to indirect or modulatory cerebral cortical afferent connectivity, is associated with stronger subcortical IHFS in thalamus and lenticular nucleus. In cerebellar cortex and caudate, where there is no variability in terms of either direct vs. indirect or driver vs. modulatory cerebral cortical afferent connections, connectivity to cerebral cortical areas with stronger cerebral cortical IHFS is associated with stronger IHFS in the subcortex. These two observations support a close relationship between subcortical IHFS and connectivity between subcortex and cortex, and generate new testable hypotheses that advance our understanding of subcortical organization.
Article activity feed
-
Reviewer #3:
Thank you for inviting me to review this manuscript by Guell and colleagues, in which the authors conduct an interesting study into the hemispheric symmetry (or lack thereof) between low-dimensional resting state functional connectivity gradients in key structures within the subcortex. In a large cohort of individuals, the authors demonstrate interesting asymmetries in the thalamus and pallidum, along with the cerebellum and striatum. They then survey a broad anatomical literature in search of a parsimonious explanation for their observed results.
Overall, I found the manuscript to be interesting, well-documented and well-reasoned. I have only minor comments that I hope will help the manuscript.
• My only slightly major concern is in the section titled 'Projection of subcortical functional gradients to cerebral cortex'. …
Reviewer #3:
Thank you for inviting me to review this manuscript by Guell and colleagues, in which the authors conduct an interesting study into the hemispheric symmetry (or lack thereof) between low-dimensional resting state functional connectivity gradients in key structures within the subcortex. In a large cohort of individuals, the authors demonstrate interesting asymmetries in the thalamus and pallidum, along with the cerebellum and striatum. They then survey a broad anatomical literature in search of a parsimonious explanation for their observed results.
Overall, I found the manuscript to be interesting, well-documented and well-reasoned. I have only minor comments that I hope will help the manuscript.
• My only slightly major concern is in the section titled 'Projection of subcortical functional gradients to cerebral cortex'. Specifically, I'm worried that multiplying each subcortical voxel by the absolute value of its eigenvalue may remove the effects of interest. For instance, in the raw eigenvalue, there is an interpretable (and important) difference between loadings of +1 and -1, however these two scores would be equivalent when the absolute value is taken. The authors mention that "Absolute functional gradient values were used in order to specifically observe the relationship between subcortical regions with strong IHFaS as indexed by asymmetric functional gradients and cerebral cortical connectivity", but I don't see how this follows.
• Is it perhaps surprising that there is strong IHFaS between first order thalamic regions but not between the cortical regions providing modulatory inputs to those regions?
• Do the authors predict that these patterns will be similar for task-based data analyses?
• The thalamic patterns appear to overlap with Ted Jones' concept of 'core' and 'matrix' thalamic nuclei (doi: 10.1016/s0166-2236(00)01922-6). Although these terms loosely overlap with 'first-order' and 'higher-order' thalamus, they are defined by the mode of thalamic projection to the cerebral cortex (targeted, granular vs. diffuse, supragranular, respectively), rather than the projection from cortex (as in the case of first- and higher-order).
• I couldn't find any information about whether the resting state fMRI data were filtered prior to the calculation of voxelwise cosine similarity. It could be interesting to determine whether the observed patterns are associated with broad-band patterns or more specific frequencies.
• The large sample size is a strength of the approach, but I did not see this leveraged anywhere in the manuscript. For instance, was there strong split-half reliability, or were some patterns more variable across subjects?
-
Reviewer #2:
General assessment:
Using rsfMRI data, the authors showed that unlike the cortex, cerebellum, and caudate, the thalamus and the pallidum of the lenticular nucleus have strongly asymmetric principal functional gradients across the two hemispheres. Using a laterality metric and confirmed with seed-based rsfMRI, they showed that these thalamic and lenticular asymmetries correspond with hemispheric laterality. They report that the cerebellum and caudate have asymmetric secondary and tertiary gradients. Finally, by summing cortical connectivity maps weighted by the functional gradients, the authors show that the asymmetric functional gradients of the cerebellum and caudate are associated with the default network, while those of the thalamus and lenticular nucleus are associated with the ventral attention network. The Discussion …
Reviewer #2:
General assessment:
Using rsfMRI data, the authors showed that unlike the cortex, cerebellum, and caudate, the thalamus and the pallidum of the lenticular nucleus have strongly asymmetric principal functional gradients across the two hemispheres. Using a laterality metric and confirmed with seed-based rsfMRI, they showed that these thalamic and lenticular asymmetries correspond with hemispheric laterality. They report that the cerebellum and caudate have asymmetric secondary and tertiary gradients. Finally, by summing cortical connectivity maps weighted by the functional gradients, the authors show that the asymmetric functional gradients of the cerebellum and caudate are associated with the default network, while those of the thalamus and lenticular nucleus are associated with the ventral attention network. The Discussion argues for an anatomy-informed model explaining these results.
These observations and the posited model are very interesting, but I have a serious concern with grouping the putamen with the pallidum as the lenticular nucleus, and drawing conclusions based on this. Also, more work needs to be done to rule out technical artifacts and improve the writing.
List of substantive concerns:
Why did you group the putamen and globus pallidus together into the lenticular nucleus? The globus pallidus is equally connected to the caudate as to the putamen. There's nothing special functionally between the putamen and pallidum-they were called lenticular nuclei by early anatomists based on their lens-like shape. In fact, I would have grouped the caudate and putamen together as the striatum, and considered the pallidum separately. Grouping the putamen and pallidum together creates a false sense of variability in the lenticular nucleus (Table 1). Based on that, the inferences resting on observations with the lenticular nucleus do not hold in the Discussion. The manuscript should be re-written to address the results of the pallidum specifically, rather than lenticular nucleus. Critically, how would this change the authors' interpretations and dichotomous model in the Discussion?
Another problem with the pallidum is that this is adjacent to the thalamus and may suffer from signal bleeding. Work needs to be done, perhaps by regressing out each signal from the other, to show that the pallidal results are not due to signal bleeding from the thalamus.
As the authors state, a known asymmetry in the brain is the lateralization of certain heteromodal cortical networks, yet these "positive controls" appear highly symmetric (Supp Fig. 1A), at least in comparison to the asymmetry of the thalamus and pallidum. Is this surprising to the authors?
My first order interpretation of the results-that there's greater functional asymmetry/lateralization for the pallidum and thalamus than other brain structures-would be that these structures simply have preferentially ipsilateral connections. The pallidum in particular is a middle link in cortico-basal ganglia-thalamic circuits-it could simply have asymmetry because its connections are mostly with the ipsi basal ganglia and thalamus. A simpler explanation is to see whether these results correspond to anatomical connectivity strength. What are the ispi versus contra connections of these thalamic nuclei to cortical regions?
What does it mean that the asymmetric (sensorimotor?) parts of thalamus are associated with the ventral attention cortical network?
In the Discussion, my first order prediction of the rsfMRI reflections of indirect/direct and driver/modulatory connections would be that direct or driver connections lead to a stronger "influence" of the cortex's properties to the downstream subcortical region. Thus, regions receiving direct or driver connections would be symmetric or asymmetric in a manner consistent with the cortical regions they are connected to. Wouldn't you expect the "influence" of the cortex to be stronger for the regions receiving driver versus modulatory or direct versus indirect inputs?
What other connectional differences explaining these results did you consider and rule out (and for what reason), in addition to cortical inputs?
The dichotomous model interpretation is very interesting, but as there is no direct evidence presented by this paper, I would state these interpretations more speculatively in the Abstract and throughout the paper.
-
Reviewer #1:
This study investigates asymmetry in functional gradients in human subcortical structures (thalamus, striatum and cerebellum). The authors found that the 1st principal gradient of thalamus and palladium are asymmetric, while that's not the case for caudate, putamen and the cerebellum. In the case of the caudate and cerebellum, their 2nd and 3rd gradients were asymmetric. Further analyses suggest that these differences arise based on connectivity between subcortical structures and the cerebral cortex. In the case of the thalamus and lenticular nuclei, asymmetry is stronger in regions with no direct or driver cerebral cortical afferent connections. In the case of the cerebellum and caudate, asymmetry is stronger in regions linked to cortical regions with higher inter-hemispheric asymmetry. The writing style of this paper is …
Reviewer #1:
This study investigates asymmetry in functional gradients in human subcortical structures (thalamus, striatum and cerebellum). The authors found that the 1st principal gradient of thalamus and palladium are asymmetric, while that's not the case for caudate, putamen and the cerebellum. In the case of the caudate and cerebellum, their 2nd and 3rd gradients were asymmetric. Further analyses suggest that these differences arise based on connectivity between subcortical structures and the cerebral cortex. In the case of the thalamus and lenticular nuclei, asymmetry is stronger in regions with no direct or driver cerebral cortical afferent connections. In the case of the cerebellum and caudate, asymmetry is stronger in regions linked to cortical regions with higher inter-hemispheric asymmetry. The writing style of this paper is quite different from the usual papers. I actually quite enjoy this conversational/didactic style. Please see my major and minor concerns below.
The computation of the laterality index is not clear to me. In the methods section, it's defined as "(left_score - right_score) / (left_score + right_score), where left_score and right_score correspond to the sum of all functional connectivity values for each left and right structure (for example, in the case of thalamus, functional connectivity values in left and right thalamus)". This sounded like they were averaging across all voxels within for example across all thalamic voxels. But in Figure 2, I assume each dot represents a thalamic voxel. So what are the authors averaging over? Indeed, in the results section, the authors said "We then computed a laterality index that quantified the degree of asymmetry in each functional connectivity map from each seed (see methods), and plotted laterality index scores for each voxel in thalami and lenticular nuclei against their corresponding functional gradient value." So for each thalamic voxel, the authors computed the correlation of the voxel's time course to all brain voxels or something else? This was also not clear. After obtaining the correlation map for a thalamic voxel, how do the authors then compress the correlation map of the thalamic voxel into either "left_score" or "right_score". That was not really explained. Furthermore, in order to compute the laterality index, the authors need to define a homologous thalamic voxel on the other hemisphere. How was this done? Did the authors use a symmetric MNI template? Which one? This was also not explained.
"Projection of subcortical functional gradients to cerebral cortex" does not quite make sense to me. According to the authors, basically FC maps of voxels are weighted by the absolute gradient values of the voxels. Essentially this means that voxels with extreme gradient values are weighted more. In the case of the thalamus, lenticular nuclei and caudate, voxels with extreme gradient values are indeed voxels with high inter-hemispheric functional asymmetry (IHFaS), so this is ok. However, in the case of the cerebellum, motor regions in lobules I-IV have extreme gradient values as well. As such, these regions would also be weighted more. Thus the resulting projected subcortical gradients might not simply reflect gradient asymmetry. Perhaps it would make more sense to compute a laterality index based on the gradient scores (i.e., left score and right scores are gradient values), and then use the absolute value of the laterality index as the weight rather than the absolute gradient values.
The analysis level in Figure 5 is too coarse. By performing a weighted average of thalamic voxels' FC maps (or caudate or lenticular or cerebellum), the authors are ignoring variation in functional connectivity patterns across thalamic (or cerebellar or caudate or lenticular) voxels. A more direct test of the authors' hypothesis should be as follows. According to the authors' hypothesis, cerebellar/caudate voxels that exhibited greater gradient asymmetry should be more strongly correlated with cortical vertices with strong absolute laterality index. Then there should be strong positive correlations between the absolute laterality index of cerebellar/caudate voxels and the absolute laterality index of the cortical locations mostly strongly correlated with the corresponding cerebellar/caudate voxels. On the other hand, there should be weak correlations for thalamic and lenticular nuclei.
The authors suggest that no p value is necessary with a 1000-subject dataset. That might be true for certain things like functional connectivity maps, but a number of analyses, such as Figures 2, 4 and 5 do require supportive inferential statistics.
"IHFaS is more prominent in first order nuclei (compared to higher-order nuclei)" is not really quantified. The authors should specify in Figure S2, which nuclei are first order nuclei and which are non-first order nuclei. Perhaps the labels on the x-axis could be colored differently for first order and non-first order nuclei.
-
Summary: This study investigates asymmetry in functional gradients in human thalamus, striatum and cerebellum. The authors found that the thalamus and the pallidum of the lenticular nucleus have strongly asymmetric principal functional gradients across the two hemispheres. In the case of the caudate and cerebellum, their 2nd and 3rd gradients were asymmetric. In general, the reviewers and editors found the study to be intriguing, but ultimately, felt that the dichotomous model, while interesting, was too speculative with no direct evidence presented. Considering also the lack of results on the functional significance of the asymmetries, the editors and reviewers felt that the study is better suited for a more specialized audience.
-
