Response to letter regarding “hemispheric imbalance in mild cognitive impairment: a graph-theoretical analysis of multimodal brain networks”

Thank you for your thoughtful comments on our manuscript, “Hemispheric Imbalance in Mild Cognitive Impairment: A Graph-Theoretical Analysis of Multimodal Brain Networks [1].” We appreciate the opportunity to clarify our methodology and highlight directions for future research. Below are our point-by-point responses.

Point#1: Lateralization methodology

We acknowledge the value of the lateralization index (LI) as a classical metric. However, this study aimed to reveal hemispheric lateralization patterns across different mild cognitive impairment (MCI) subtypes, exploring whether inter-hemispheric differences and their patterns are consistent, rather than merely comparing lateralization degree. Therefore, we adopted a multi-level strategy: separate between-group comparisons for each hemisphere to identify hemisphere-specific abnormalities, followed by within-group paired-tests to describe each group’s lateralization profile. This approach has precedent in the literature [2]. The main reason for not using LI is that it compresses hemispheric information into a single scalar, losing spatial detail and potentially conflating distinct mechanisms (e.g. left-hemisphere damage and altered bilateral coordination may yield similar LI changes) [3]. Our approach enhances transparency and interpretability.

We agree that significant within‑group differences do not directly imply between‑group differences. This principle has been considered in the design and is clarified here: within-group comparisons are descriptive, and the main conclusions are based on combined evidence from both between-group and within-group comparisons. The abstract statement noted by readers is solely a within-group description. Notably, the healthy control group showed no significant lateralization (Figure 3), which does not support the readers’ hypothesis.

The core contribution of this study lies in revealing a spatially specific network pattern and generating hypotheses for future research. In subsequent studies, we will integrate task-based paradigms and methods including LI to further explore the underlying mechanisms.

Point#2: Structure–Function Coupling (SFC) analysis

The global SFC analysis was designed to macroscopically assess hemispheric balance, supporting the exploration of overall network patterns. This metric integrates multi-region information, providing a holistic perspective on hemispheric coordination changes [4]. We acknowledge the possibility that local changes could offset global effects, so it is presented as supplementary evidence, not for inferring region-specific pathology. We agree that node- or network-level analysis is valuable and will be an important direction to refine our work in the future.

Point#3: Clinical translation and neuromodulation

Thank you for your attention to clinical translation. Neuromodulation discussion is framed as hypothesis generation, suggesting future research directions, not for direct clinical applications. We agree that validation requires prospective intervention, as noted in our limitations. The reported correlation (r ∼ 0.3–0.4) explores biological links between brain networks and cognitive function, not diagnosis, and represents a meaningful medium effect [5].

Overall, these suggestions are insightful for future research, though they address different analytical levels and objectives. Within this study’s focus on hemispheric lateralization patterns, the adopted strategy is appropriate and aligned with the goals. We look forward to expanding these findings in larger, longitudinal studies.

Funding Statement

The study received no funding.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Not applicable, as no new data was generated.