A bibliometric analysis of neuroimaging studies on cognitive control in autism spectrum disorder (2000-2025)

This study aims to systematically analyze neuroimaging research on cognitive control in Autism spectrum disorder (ASD) from 2000 to 2025 using bibliometric methods, in order to reveal the evolutionary trajectory, core knowledge base, research hotspots, and future frontiers of the field.

A search was conducted on the Web of Science Core Collection and Scopus databases, resulting in the inclusion of 1,581 relevant articles. VOSviewer and the Bibliometrix package in R were utilized to conduct a comprehensive visualization and quantitative analysis of annual publication volume, country/institution/author collaboration networks, keyword co-occurrence, document co-citation, and thematic evolution.

(1) The volume of research literature showed exponential growth, with an annual growth rate of 21.61%, entering a period of rapid development particularly after 2012, which is closely related to the popularization of functional magnetic resonance imaging (fMRI) technology. (2) "Functional connectivity," "executive function," and "default mode network" were the most central keywords. "Functional connectivity" rapidly became a hub connecting various themes after 2010, marking a paradigm shift from "functional localization" to "brain network dysregulation." (3) The "Triple network model" proposed by Menon was the most cited document, laying the core theoretical foundation for understanding ASD as a disorder of large-scale brain network dysfunction. (4) "Transdiagnostic" research has emerged as a new hotspot, while "multimodal imaging," "machine learning," and "dynamic connectivity" represent highly promising future directions.

Over the past two decades, neuroimaging research on cognitive control in ASD has undergone a profound paradigm shift: from focusing on abnormal activation in isolated brain regions to exploring the static and dynamic dysregulation of large-scale brain networks. The research perspective has also expanded from a single-disorder model to a transdiagnostic framework that includes comparisons with other neurodevelopmental disorders (e.g., ADHD). Future research should focus on the fusion of multimodal data, the application of computational psychiatry methods, and the translation of basic research findings into personalized clinical interventions.