PCOMPBIOL-D-26-01166

A synthetic 3D human cerebrovascular model informed by histology for simulating the cortical depth-dependent BOLD fMRI signal

PLOS Computational Biology

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Additional Editor Comments (if provided):

The manuscript demonstrates clear merit. However, certain methodological details require additional clarification to improve overall readability. Please revise the text as suggested.

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1) Please ensure that the CRediT author contributions listed for every co-author are completed accurately and in full.

At this stage, the following Authors/Authors require contributions: Mario Gilberto Baez-Yanez, Jeroen C.W. Siero, Matthias J.P. van Osch, and Natalia Petridou. Please ensure that the full contributions of each author are acknowledged in the "Add/Edit/Remove Authors" section of our submission form.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: This is a resubmission of a previously rejected manuscript about a simulation framework referred to as “3D VAMOS” to study blood oxygenation level-dependent (BOLD) signal changes in (task-based) functional magnetic resonance imaging (fMRI). It has undergone substantial revision, largely by expanding the Discussion section are well as clarifying/justifying specific assumptions in the developed model.

As already stated in my initial evaluation, an efficient simulation tool that allows meaningful studies and can thus achieve a better understanding of relationships of the local vascular architecture and hemodynamic response is likely to be of relevant reader interest. I acknowledge that the authors have carefully and sufficiently addressed my earlier critique points. I have no further comments.

Reviewer #2: Báez-Yáñez et al. present a modelling framework for brain vasculature and functional MRI signals based on empirical measurements of brain vascular properties.

Unfortunately, the mentioned github repository was not publicly accessible at the time I tried it, so I can’t comment on any aspects regarding the implementation and it’s user-friendliness. Overall, the paper provides a comprehensive overview of their modelling framework and would benefit from a more thorough description of the computational aspects and a more comprehensive comparison with other approaches.

In detail, can the authors comment on the required computational resources and run-times required for these simulations.

Further, given that a large number of empirically defined parameters enter the simulations, but the ‘final’ output is the depth-dependent percent signal change, a sensitivity analysis would be very insightful, assessing, for example, the impact of artery-to-vein ration, vessel radius, CBV, Grubb constant, etc.

There exist a few other modelling frameworks to simulate depth-dependent BOLD signal changes (Chaussé et al., 2025; Markuerkiaga et al., 2016), but also (Hartung et al., 2025) (admittedly a pre-print) as well as work from the authors themselves (Báez-Yáñez et al., 2025). Can the authors provide more details about the commonalities and differences between these different tools, and what makes the current approach unique.

It would be helpful for the reader to connect the experiments described in the methods sections with the results/figures. For example, where are the results for the different SO2 levels in veins (l886ff)?

Last, in Figure 2E, I could not see any difference between the vessels with tortuosity 1.2 and 1.5 in the zoomed-in patch. Maybe a different visualisation might be more suitable?

Báez-Yáñez, M.G., Siero, J.C.W., Curcic, V., van Osch, M.J.P., Petridou, N., 2025. Impact of vascular architecture, oxygen saturation, and hematocrit on human cortical depth-dependent GE- and SE-BOLD fMRI signals: A simulation approach using realistic 3D vascular networks. Imaging Neurosci. 3, imag_a_00573. https://doi.org/10.1162/imag_a_00573

Chaussé, J., Berman, A.J.L., Chen, J.J., 2025. BOLDsωimsuite: A new software suite for forward modeling of the BOLD fMRI signal. Imaging Neurosci. 3, imag_a_00519. https://doi.org/10.1162/imag_a_00519

Hartung, G., Berman, A.J.L., Sakadžić, S., Linninger, A., Boas, D.A., Polimeni, J.R., 2025. Biophysical simulations of fMRI responses using realistic microvascular models: insights into distinct hemodynamics in humans and mice. https://doi.org/10.1101/2025.10.08.680976

Markuerkiaga, I., Barth, M., Norris, D.G., 2016. A cortical vascular model for examining the specificity of the laminar BOLD signal. Neuroimage 132, 491–8. https://doi.org/10.1016/j.neuroimage.2016.02.073

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Reviewer #1: Yes

Reviewer #2: No:  The mentioned github repository was not accessible at the time I tried.

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Reviewer #1: No

Reviewer #2: Yes:  Saskia Bollmann

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Dear Dr. Baez-Yanez,

We are pleased to inform you that your manuscript 'A synthetic 3D human cerebrovascular model informed by histology for simulating the cortical depth-dependent BOLD fMRI signal' has been provisionally accepted for publication in PLOS Computational Biology.

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Best regards,

Jian Liu

Academic Editor

PLOS Computational Biology

Daniele Marinazzo

Section Editor

PLOS Computational Biology

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The authors have revised the manuscript thoroughly and addressed all reviewer concerns. It is now ready for publication.