Scholarlink

<p>Spontaneous brain activity is fundamental to understanding the neural basis of inter-individual differences, making its characterization central to brain-wide association studies. While inter-regional coupling patterns have been extensively studied, intra-regional dynamics remain largely unexplored. Here, analysing data from four neuroimaging cohorts (ages 8–82 years; <i>N</i> = 30,148), we extracted ~5,000 time-series features from resting-state haemodynamic signals across 271 brain regions, offering a comprehensive characterization of intra-regional dynamics. We identified a reliable subset that serves as an individual-specific ‘barcode’, capturing multifaceted dynamic dimensions that stably reflect inter-individual variation across datasets. These barcodes linked nonlinear autocorrelations in unimodal regions to substance use traits and random walk dynamics in higher-order networks to general cognitive abilities. Importantly, these brain–behaviour associations generalized across life stages and populations, with substance use showing age-specific variation and cognition exhibiting consistent patterns across age groups. This work advances large-scale, generalizable brain-wide association studies by highlighting the potential of intra-regional dynamics.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Spontaneous brain regional dynamics contribute to generalizable brain–behaviour associations

  • 期刊论文

  • 发表日期：

    2025年10月30日

查看全文
  • Xiaohan Tian,
  • Yingjie Peng,
  • Shu Liu,
  • Golia Shafiei,
  • Meng Wang,
  • Yuqing Sun,
  • Jing Lou,
  • Junxing Xian,
  • Ke Hu,
  • Yini He,
  • Qi Wang,
  • Chaoyue Ding,
  • Tian Gao,
  • Shangzheng Huang,
  • Kaixin Li,
  • Qi Wang,
  • Xi-Nian Zuo,
  • Zhanjun Zhang,
  • Ang Li,
  • Bing Liu

摘要

Spontaneous brain activity is fundamental to understanding the neural basis of inter-individual differences, making its characterization central to brain-wide association studies. While inter-regional coupling patterns have been extensively studied, intra-regional dynamics remain largely unexplored. Here, analysing data from four neuroimaging cohorts (ages 8–82 years; N = 30,148), we extracted ~5,000 time-series features from resting-state haemodynamic signals across 271 brain regions, offering a comprehensive characterization of intra-regional dynamics. We identified a reliable subset that serves as an individual-specific ‘barcode’, capturing multifaceted dynamic dimensions that stably reflect inter-individual variation across datasets. These barcodes linked nonlinear autocorrelations in unimodal regions to substance use traits and random walk dynamics in higher-order networks to general cognitive abilities. Importantly, these brain–behaviour associations generalized across life stages and populations, with substance use showing age-specific variation and cognition exhibiting consistent patterns across age groups. This work advances large-scale, generalizable brain-wide association studies by highlighting the potential of intra-regional dynamics.