Frontal cortical regions associated with attention connect more strongly to central than peripheral V1

  1. Sara Sims
  2. Pinar Demirayak
  3. Simone Cedotal
  4. Kristina Visscher

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    Summary: The manuscript is a replication of findings from Griffis et al., 2017, and it seeks to validate those findings using a different modality (diffusion-weighted imaging; DWI). While the questions asked in this manuscript are of considerable interest to the field, the findings' focus and implications are relatively narrow. Further, the study does not reveal new conclusions about brain function or organization. Authors may be cautious about interpreting the findings as representing direct structural connections between the occipital and frontal cortex -- as the reported structural and functional connectivity values may not be strong enough to support such a strong interpretation. The reviewers also agree that the methods are not presented clearly, in a manner that is straightforward to follow and critique.

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Abstract

The functionality of central vision is different from peripheral vision. Central vision is used for fixation and has higher acuity that makes it useful for everyday activities such as reading and object identification. The central and peripheral representations in primary visual cortex (V1) also differ in how higher-order processing areas modulate their responses. For example, attention and expectation are top-down processes (i.e., high-order cognitive functions) that influence visual information processing during behavioral tasks. This top-down control is different for central vs. peripheral vision. Since functional networks can influence visual information processing in different ways, networks (such as the Fronto-Parietal (FPN), Default Mode (DMN), and Cingulo-Opercular (CON)) likely differ in how they connect to representations of the visual field across V1. Prior work indicated the central representing portion of V1 was more functionally connected to regions belonging to the FPN, and the far-peripheral representing portion of V1 was more functionally connected to regions belonging to the DMN.

Our goals were 1) Assess the reproducibility and generalizability of retinotopic effects on functional connections between V1 and functional networks. 2) Extend this work to understand structural connections of central vs. peripheral representations in V1. 3) Examine the overlapping eccentricity differences in functional and structural connections of V1.

We used resting-state BOLD fMRI and DWI to examine whether portions of V1 that represent different visual eccentricities differ in their functional and structural connectivity to functional networks. All data were acquired and minimally preprocessed by the Human Connectome Project. We identified central and far-peripheral representing regions from a retinotopic template. Functional connectivity was measured by correlated activity between V1 and functional networks, and structural connectivity was measured by probabilistic tractography and converted to track probability. In both modalities, differences between V1 eccentricity segment connections were compared by paired, two-tailed t-test. Dice Coefficients were used to determine spatial overlap between modalities.

We found 1) Centrally representing portions of V1 are more strongly functionally connected to frontal regions than are peripherally representing portions of V1, 2) Structural connections also show stronger connections between central V1 and frontal regions, 3) Patterns of structural and functional connections overlaps in the lateral frontal cortex.

In summary, the work’s main contribution is a greater understanding of higher-order functional networks’ connectivity to V1. There are stronger structural connections to central representations in V1, particularly for lateral frontal regions, implying that the functional relationship between central V1 and frontal regions is built upon direct, long-distance connections. Overlapping structural and functional connections reflect differences in V1 eccentricities, with central V1 preferentially connected to attention-associated regions. Understanding how V1 is functionally and structurally connected to higher-order brain areas contributes to our understanding of how the human brain processes visual information and forms a baseline for understanding any modifications in processing that might occur with training or experience.

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  1. eLife

    Reviewer #3:

    This manuscript examines data from the Young Adult Human Connectome Project's 900-subject release to compare both structural and functional connections between iso-eccentricity bands in striate cortex and the fronto-parietal, cingulo-opercular, and default mode networks. The authors find that central vision is most strongly connected to the fronto-parietal network, which is associated with attention, while the far periphery is more strongly connected to the default mode network. The questions asked in this manuscript are of considerable interest to the field, and this study has the potential to be impactful. However, substantial work is needed to make the methods and results sufficiently clear and reproducible to the reader.

    Major Comments:

    A major problem throughout this paper is that the authors have not been very careful in documenting their methods, what they are plotting, or how they are supporting their assertions. This is a major shortcoming of the work. I do not believe there is sufficient detail in this paper as is to reproduce the methods, nor was I able to understand what precisely was calculated in the statistical tests reported.

    The amount of work that has been put into this project's quality control (at minimum, visual inspection and filtering of 900 MR images) is very impressive! This information should really be shared with the broader research community in order to make this manuscript more reproducible and in order to ensure that other researchers can simply use and cite the authors' efforts rather than repeating them. This could be as simple as a supplemental table or text-file that includes the subject IDs of those HCP subjects that were included in all analyses.

    It should be crystal-clear from the Methods section whether the manuscript's data were collected or reanalyzed by the authors. My understanding is that all of this manuscript's analyzed data are from the HCP database. However, had I read only the "Data Acquisition" section I would have been left with the strong impression that the authors collected the data themselves using the same kind of scanner and the same analysis pipelines as the HCP. Unless this is the case, the opening sentence of this section should probably be something like "All data were acquired and preprocessed by the Human Connectome Project (Van Essen et al., 2013)" [10.1016/j.neuroimage.2012.02.018]. It may also be wise to reference the HCP in the Acknowledgements section. Further information: https://www.humanconnectome.org/study/hcp-young-adult/document/hcp-citations. This should apply equally to the data and the preprocessing methods-i.e., if the quality control mentioned in the above comment was performed by the HCP and not the authors, that should have been explicit.

    P3, ❡6. This paragraph is critical to the methods but is not at all clear. In particular, the paragraph eventually describes seven eccentricity segments per subject, yet it does not explain what the eccentricity boundaries of these segments are, nor does Figure 2 show these segments. It isn't clear from the manuscript if these are ever used (rather than the 3 central/mid-peripheral/far-peripheral segments) or exclusively used.

    In looking at Figure 4, my first and strongest impression is that the central connectivity is very similar to the far-peripheral connectivity, and the z-score differences are incredibly small. Additionally, the legend does not make the quantities plotted very clear (these are based on the averaged z-scores across subjects?) so I'm left wondering how to assess any sort of significance. I have a similar reaction to Figure 5. More help is needed to understand these results.

    Given that this paper consists of a large analysis of a large existing dataset, it would be especially nice if the authors would make their source code and intermediate analysis files publicly available. Having access to the source code directly is virtually a requirement of making this kind of study reproducible and would mediate many of my concerns about the ambiguities of the methods.

  2. eLife

    Reviewer #2:

    In this work, Sims and colleagues use resting-state functional connectivity and diffusion tractography in human connectome project data to examine the connectivity of the central and peripheral aspects of the primary visual cortex. They find that central V1 connects more strongly to regions of the prefrontal cortex interpreted as the Fronto-parietal network than does peripheral V1.

    The idea that central V1 may be directly connected to control-related networks is an interesting one, and has fascinating implications for the study of top-down modulation of visual cortex function. However, I must say I am somewhat skeptical of these findings, for several reasons.

    First, I find the a priori anatomical basis for these proposed connections to be dubious. The authors themselves describe how Markov et al. explicitly conducted tract tracing with central V1 and found connections with posterior frontal and parietal cortex, but nothing with areas classically associated with the fronto-parietal cortex. The authors propose that the inferior fronto-occipital fasciculus may connect V1 with lateral prefrontal regions only in humans. However, they provide no evidence for this suggestion. Indeed, my understanding of the iFOF is that it connects to inferior and lateral occipital cortex (see e.g. figures from the Takemura study cited in this work). Can the authors better support the idea that the iFOF might be the route of connection between V1 and frontal cortex?

    Second, I am concerned that both 1) the Central V1 ROI employed in this work and 2) the inferior frontal cortex region showing strong FC with that Central V1 ROI overlap very closely with regions where we have seen poor BOLD signal in our own fMRI data (I would like to attach a figure if possible).

    We are not confident what the source of the poor signal might be in posterior occipital or inferior frontal cortex; we suspect the presence of large veins (possibly the transverse sinus in V1; see Winawer et al., 2010, Journal of Vision). In any case, the data quality is low enough that we believe our data should not be considered to represent actual neural function in those regions. Can the authors demonstrate convincingly that this is not the case in their HCP data?

    Third, I have an issue with the localization of effects in this paper. The paper describes effects in the fronto-parietal network throughout the manuscript, including the title. How surprising, then, that the strongest effects are not in the FP network at all! Figure 4A makes it very clear that the largest effects are in the IFG, which is outside the green outlines describing the extent of the fronto-parietal network, but inside the Default network. Figure 3A also supports this Default-centric localization, with Central V1 effects in posterior lateral parietal, medial parietal, and superior frontal cortex, all outside FP but inside Default. Since the FC effects are not actually primarily in FP, I see no reason why FP should be used as a mask in Figure 5. Indeed, the authors should show the localization of SC effects throughout the cortex, not just in FP. I also see no reason why these V1-Default connections should be characterized in any way as "attention" or "control".

    Fourth, I feel that these FC and SC differences are wildly over-interpreted. From the scale, the actual strength of FC and SC between central V1 and lateral parietal cortex is extremely weak (around Z(r) = .1 for FC and p-track = .1 for SC). Under no circumstances would I believe that either of those values represents any sort of real connection. Cortical regions with direct structural connections have much stronger FC values, as do regions that influence each other indirectly via multi-step connections. Further, very large portions of the brain probably have both stronger FC and SC to central V1 than these FP regions (the authors show this for FC but exclude this info for SC). Most glaringly, I certainly don't believe there is a "direct structural connection" as is claimed in the discussion--a claim based, strangely, on the spatial correspondence between the structural and functional maps, which really has nothing to do with any evidence for a direct connection.

    Finally, the authors must note that p values may not be used for spatial correlations between brain maps. This is because these maps are always highly autocorrelated, which violates the independence assumption of the correlation procedure.

  3. eLife

    Reviewer #1:

    This manuscript extends on prior work by the authors (Griffis et al, 2017), which originally reported eccentricity-dependent differences in resting state connectivity between V1 and regions brain wide. This study builds on that work by expanding the pool of participants, using the HCP dataset, as well as also investigating any eccentricity-dependent effects that may emerge with tractography. Interestingly, both measures find that foveal areas in V1 are more strongly connected to frontoparietal networks. The study is interesting, but I have a few remaining points.

    1. While during the resting state scans, there was, in theory, no 'task', participants were asked to maintain fixation on the cross in the center of the screen throughout the scan. I think it would be important for the authors to note that there is a possibility that the resting state correlations observed wherein foveal areas were more correlated with frontoparietal regions (and far periphery with DMN areas) could be due to attention directed towards the fixation cross, and away from the periphery. While I acknowledge the authors have no way to test this with this data set, it is possible that if participants had been asked to covertly attend to a ring in their far periphery the entire time instead, the correlations might have been flipped, with frontoparietal connectivity highest in the periphery towards the attended eccentricity. The authors should either explain why this is not a concern, or acknowledge it in the manuscript.

    2. Related to the last point, what was the size of the screen used during the connectivity data acquisition? I ask because the far eccentricity bands determined using Benson et al's technique are very eccentric. And if participants had eyes opened and were fixating, was that eccentricity outside the outer edge of the screen? Because then it would be encouraged to be 'unattended', thereby potentially influencing connectivity results.

    3. Was there any attempt at replicating these results in extra striate cortex? Are these patterns still there, both in structural and functional connectivity, for V2 or V3?

  4. eLife

    Summary: The manuscript is a replication of findings from Griffis et al., 2017, and it seeks to validate those findings using a different modality (diffusion-weighted imaging; DWI). While the questions asked in this manuscript are of considerable interest to the field, the findings' focus and implications are relatively narrow. Further, the study does not reveal new conclusions about brain function or organization. Authors may be cautious about interpreting the findings as representing direct structural connections between the occipital and frontal cortex -- as the reported structural and functional connectivity values may not be strong enough to support such a strong interpretation. The reviewers also agree that the methods are not presented clearly, in a manner that is straightforward to follow and critique.

  5. Version published to 10.1101/2020.09.09.281725 on bioRxiv