Chi I-Jou, Tsai Shih-Jen, Chen Chun-Houh, Yang Albert C
Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan.
Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.
Psychiatry Clin Neurosci. 2025 Mar;79(3):98-107. doi: 10.1111/pcn.13780. Epub 2025 Jan 11.
Autistic traits exhibit neurodiversity with varying behaviors across developmental stages. Brain complexity theory, illustrating the dynamics of neural activity, may elucidate the evolution of autistic traits over time. Our study explored the patterns of brain complexity in autistic individuals from childhood to adulthood.
We analyzed functional magnetic resonance imaging data from 1087 autistic participants and neurotypical controls aged 6 to 30 years within the ABIDE I (Autism Brain Imaging Data Exchange) data set. Sample entropy was calculated to measure brain complexity among 90 brain regions, utilizing an automated anatomical labeling template for voxel parcellation. Participants were grouped using sliding age windows with partial overlaps. We assessed the average brain complexity of the entire brain and brain regions for both groups across age categories. Cluster analysis was conducted using generalized association plots to identify brain regions with similar developmental complexity trajectories. Finally, the relationship between brain region complexity and autistic traits was examined.
Autistic individuals may tend toward higher whole-brain complexity during adolescence and lower complexity during childhood and adulthood, indicating possible distinct developmental trajectories. However, these results do not remain after Bonferroni correction. Two clusters of brain regions were identified, each with unique patterns of complexity changes over time. Correlations between brain region complexity, age, and autistic traits were also identified.
The study revealed brain complexity trajectories in autistic individuals, providing insight into the neurodiversity of autism and suggesting that age-related changes in brain complexity could be a potential neurodevelopmental marker for the dynamic nature of autism.
自闭症特征表现出神经多样性，在不同发育阶段具有不同行为。阐释神经活动动态的大脑复杂性理论，可能有助于阐明自闭症特征随时间的演变。我们的研究探讨了自闭症个体从儿童期到成年期的大脑复杂性模式。
我们分析了自闭症大脑成像数据交换（ABIDE I）数据集中1087名6至30岁的自闭症参与者和神经典型对照者的功能磁共振成像数据。利用自动解剖标记模板进行体素分割，计算90个脑区的样本熵以测量大脑复杂性。参与者使用部分重叠的滑动年龄窗口进行分组。我们评估了两组在不同年龄类别下全脑和脑区的平均大脑复杂性。使用广义关联图进行聚类分析，以识别具有相似发育复杂性轨迹的脑区。最后，研究了脑区复杂性与自闭症特征之间的关系。
自闭症个体在青春期可能倾向于具有更高的全脑复杂性，而在儿童期和成年期则较低，这表明可能存在不同的发育轨迹。然而，经邦费罗尼校正后，这些结果不再成立。识别出两组脑区，每组随时间具有独特的复杂性变化模式。还确定了脑区复杂性、年龄和自闭症特征之间的相关性。
该研究揭示了自闭症个体的大脑复杂性轨迹，为自闭症的神经多样性提供了见解，并表明与年龄相关的大脑复杂性变化可能是自闭症动态本质的潜在神经发育标志物。
