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Background <p>Duchenne muscular dystrophy (DMD) is associated with cognitive deficits and neural abnormalities, yet how temporal properties of regional brain activity align with structural changes across development remains unclear. We integrated intrinsic neural timescale (INT) with voxel-based morphometry (VBM) to explore whether intrinsic timescales disruptions co-localize with gray matter volume (GMV) alterations and relate to cognition in children with DMD.</p> Methods <p>Thirty-six children with DMD and 30 age-matched healthy controls underwent T1-weighted MRI and resting-state fMRI. INT and VBM analyses were conducted to assess intrinsic timescales and GMV, respectively. Group differences were tested in statistical parametric mapping toolkit using two-sample <i>t</i>-tests with Gaussian random-field correction (voxel-wise <i>P</i> &lt; 0.001; cluster-wise <i>P</i> &lt; 0.05). Global volumetrics were analyzed with ordinary least squares models including group × age interactions. Spearman rank correlations were subsequently computed to assess associations between cognitive scores and the identified neural abnormalities.</p> Results <p>DMD showed cognitive impairment and distinct neurodevelopmental features, including: co-localized shorter INT and lower GMV within limbic–sensorimotor networks; widespread GMV reductions across the visual, default-mode, and dorsal attention networks; and divergent age-related trends in global volumes. Moreover, GMV in multiple abnormal regions correlated positively with working memory and perceptual reasoning scores.</p> Conclusions <p>These findings suggest that dystrophin deficiency induces co-located functional-structural deficits and aberrant neurodevelopmental trends, offering insights into neurodevelopmental abnormalities in children with DMD. The integration of INT and GMV provides a novel framework for decoding hierarchical network dysfunction and morphological plasticity changes in DMD, identifying potential targets for cognitive intervention.</p>

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Cognitive deficits linked to intrinsic timescales and gray matter volume abnormalities in children with Duchenne muscular dystrophy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月29日

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  • Xiaoyu Niu,
  • Qin Hu,
  • Xinyuan Zhang,
  • Suming Zhang,
  • Ke Xu,
  • Rong Xu,
  • Yu Song,
  • Hang Fu,
  • Ziqi Zhou,
  • Ying Ren,
  • Caihan Li,
  • Ting Xu,
  • Shaoqiang Han,
  • Yong Zhang,
  • Huayan Xu,
  • Xiaotang Cai,
  • Bochao Cheng,
  • Yingkun Guo

摘要

Background

Duchenne muscular dystrophy (DMD) is associated with cognitive deficits and neural abnormalities, yet how temporal properties of regional brain activity align with structural changes across development remains unclear. We integrated intrinsic neural timescale (INT) with voxel-based morphometry (VBM) to explore whether intrinsic timescales disruptions co-localize with gray matter volume (GMV) alterations and relate to cognition in children with DMD.

Methods

Thirty-six children with DMD and 30 age-matched healthy controls underwent T1-weighted MRI and resting-state fMRI. INT and VBM analyses were conducted to assess intrinsic timescales and GMV, respectively. Group differences were tested in statistical parametric mapping toolkit using two-sample t-tests with Gaussian random-field correction (voxel-wise P < 0.001; cluster-wise P < 0.05). Global volumetrics were analyzed with ordinary least squares models including group × age interactions. Spearman rank correlations were subsequently computed to assess associations between cognitive scores and the identified neural abnormalities.

Results

DMD showed cognitive impairment and distinct neurodevelopmental features, including: co-localized shorter INT and lower GMV within limbic–sensorimotor networks; widespread GMV reductions across the visual, default-mode, and dorsal attention networks; and divergent age-related trends in global volumes. Moreover, GMV in multiple abnormal regions correlated positively with working memory and perceptual reasoning scores.

Conclusions

These findings suggest that dystrophin deficiency induces co-located functional-structural deficits and aberrant neurodevelopmental trends, offering insights into neurodevelopmental abnormalities in children with DMD. The integration of INT and GMV provides a novel framework for decoding hierarchical network dysfunction and morphological plasticity changes in DMD, identifying potential targets for cognitive intervention.