©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
World J Psychiatry. Mar 19, 2026; 16(3): 113487
Published online Mar 19, 2026. doi: 10.5498/wjp.v16.i3.113487
Published online Mar 19, 2026. doi: 10.5498/wjp.v16.i3.113487
Decoding auditory hallucinations with brain blood flow patterns?
Haewon Byeon, Worker’s Care and Digital Health Lab, Department of Future Technology, Korea University of Technology and Education, Cheonan 31253, South Korea
Author contributions: Byeon H contributed to this paper and designed the study, and was involved in data interpretation and writing the article.
Supported by Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education, No. NRF-RS-2023-00237287.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Haewon Byeon, DSc, PhD, Associate Professor, Director, Worker’s Care and Digital Health Lab, Department of Future Technology, Korea University of Techno logy and Education, 1600, Chungjeol-ro, Cheonan 31253, South Korea. bhwpuma@naver.com
Received: August 27, 2025
Revised: September 12, 2025
Accepted: December 11, 2025
Published online: March 19, 2026
Processing time: 184 Days and 20.6 Hours
Revised: September 12, 2025
Accepted: December 11, 2025
Published online: March 19, 2026
Processing time: 184 Days and 20.6 Hours
Core Tip
Core Tip: This letter highlights the groundbreaking study by Cai et al, which uses an accessible tool to differentiate the causes of auditory verbal hallucinations. The researchers employed transcranial Doppler to find distinct brain blood flow patterns (hemodynamic signatures) in auditory verbal hallucinations across schizophrenia, post-traumatic stress disorder, and depression. While this is a promising proof-of-concept, the findings are preliminary due to the study’s retrospective, single-center design and the potential for medication-related confounding. For widespread clinical use, the models must be vali
