New Functional MRI Experiments Based on Fractional Diffusion Representation Show Independent and Complementary Contrast to Diffusion-Weighted and Blood-Oxygen-Level-Dependent Functional MRI

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Overall Assessment

This manuscript explores the potential of the γ parameter in fractional diffusion representation for functional MRI (fMRI), positing it as a complementary measure to conventional diffusion-weighted (DW) and blood-oxygen-level-dependent (BOLD) fMRI. The study builds upon prior findings in non-Gaussian diffusion MRI and applies an advanced diffusion model to improve spatial specificity in mapping brain activity.

A notable concern is the substantial overlap with previous work, particularly the authors' 2014 study, "fMRI using non-Gaussian γ-stretched exponential maps" (Palombo et al.). While the present study extends the methodology by incorporating fractional diffusion representation and further validating the γ parameter, the level of novelty requires clearer articulation. The authors should explicitly differentiate the contributions of this work from their prior findings and provide a deeper discussion of the incremental advancements.

Major Comments

1. Novelty and Differentiation from Prior Work

   • The study shares methodological and conceptual similarities with the 2014 work. While it introduces fractional diffusion representation, the manuscript does not sufficiently highlight what new insights are gained beyond what was already demonstrated in the previous study.

   • A comparative discussion summarizing how the new findings expand upon or differ from the earlier work should be added, ideally in the Introduction and Discussion sections.

2. Validation and Experimental Justification

   • The study claims that γ provides superior spatial specificity and sensitivity compared to ADC and BOLD. However, the sample size (n=5) is limited. The authors should discuss the statistical robustness of their findings and, if possible, provide an estimate of effect sizes.

   • The activation paradigm is well-explained, but the justification for the chosen b-values (especially in relation to prior studies) could be elaborated further.

3. Potential Confounds and Alternative Explanations

   • Given the ongoing debate regarding whether DW-fMRI signals at high b-values reflect neuronal rather than vascular effects, the authors should critically engage with counterarguments, such as those presented by Pampel et al. (2010) and Miller et al. (2007).

   • Simulations suggest γ is sensitive to both vascular and microstructural changes, but disentangling these effects remains a challenge. A clearer methodological approach to isolating these contributions should be discussed.

Minor Comments

1. Clarity and Terminology

   • The manuscript includes technical jargon that may not be immediately accessible to a broad neuroscience audience. Adding brief explanations for key terms (e.g., "fractional order derivatives" in diffusion MRI) would improve accessibility.

   • Define γ parameter more explicitly in the Introduction for readers unfamiliar with fractional diffusion models.

2. Figure and Data Presentation

   • Figures 2 and 3 are informative, but their captions should include a brief interpretation of the data to enhance readability.

   • The statistical significance of the observed trends should be clearly indicated in the figures where applicable.

3. Reference to Supporting Literature

   • While the manuscript provides a solid theoretical foundation, additional references discussing counterpoints to diffusion MRI as a direct neuronal marker (e.g., Bai et al., 2016) should be incorporated.

Conclusion and Recommendation

This study presents an interesting advancement in diffusion MRI for functional neuroimaging, with the potential to enhance spatial localization of brain activation. However, the manuscript should better articulate its novelty in comparison to the authors' previous work, provide additional discussion on the validation and robustness of results, and address potential confounds more thoroughly.

 

Author Response

Please see the attached file

 

 

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Strengths:

1. Innovative Approach: The study presents an original method using fractional diffusion representation to enhance functional MRI (fMRI) by addressing the limitations of traditional BOLD and diffusion-weighted imaging (DWI). The introduction of the γ parameter as a potential imaging biomarker is a notable advancement in the field.
2. Scientific Rigor: The research is well-grounded in theoretical principles and includes experimental validation through both simulations and human subject trials. The inclusion of Monte Carlo simulations to understand the γ parameter's behavior adds depth to the study.
3. Clear Methodology: The study provides a well-defined experimental design, including MRI acquisition parameters, data processing steps, and a structured stimulus paradigm, ensuring reproducibility.

Weaknesses:

1. Limited Sample Size: The study only involves five subjects, which significantly limits the statistical power and generalizability of the findings. A larger sample size is necessary to validate the effectiveness of the γ parameter in functional neuroimaging.
2. Lack of Direct Comparison with Alternative Methods: While the study claims improved spatial specificity, it does not provide direct quantitative comparisons between γ-maps and other advanced diffusion models, such as diffusion kurtosis imaging (DKI) or neurite orientation dispersion and density imaging (NODDI).
3. Unclear Clinical Relevance: Although the γ parameter shows promise in detecting microstructural changes, its potential applications in clinical neuroscience (e.g., neurological disorders) are not well-explored. Further studies are needed to assess whether this method can be useful for clinical diagnostics.
4. Potential Confounding Factors: The study acknowledges that γ is influenced by both local magnetic susceptibility differences and tissue compartmentalization, but it does not fully separate these contributions in vivo. Future studies should incorporate experimental controls to isolate these effects.

Author Response

Please see the attached file

 

 

Author Response File: Author Response.pdf