Brain dynamics & entropy
Developing brain entropy as a window into the complexity and information capacity of spontaneous neural activity.
- Nonlinear dynamics
- Resting-state fMRI
- Brain network organization
Cognitive neuroscience · Neuroimaging
Postdoctoral Researcher · Department of Psychology
University of Science and Technology of China
I study how the brain’s complex functions emerge from its structure and dynamics—combining multimodal MRI, brain entropy, and non-invasive neuromodulation.
01 · About
I am a postdoctoral researcher in the Department of Psychology at the University of Science and Technology of China (USTC), working at the intersection of cognitive neuroscience, neuroimaging, and neuromodulation.
I received my PhD in Cognitive Neuroscience from the State Key Laboratory of Cognitive Neuroscience and Learning at Beijing Normal University in 2025. Previously, I worked as a Research Fellow and Postdoctoral Fellow at the University of Maryland School of Medicine.
My work develops and applies measures of brain entropy (BEN) to understand functional brain organization, intervention-induced plasticity, and mechanisms of neuropsychiatric conditions. I also investigate the functional architecture of the ventromedial prefrontal cortex using multimodal imaging and connectomics.
02 · Research interests
My research links measurement, mechanism, and intervention across healthy cognition and brain disorders.
Developing brain entropy as a window into the complexity and information capacity of spontaneous neural activity.
Integrating structural MRI, task and resting-state fMRI, perfusion, myelination, and connectomics.
Examining how TMS, neurofeedback, pharmacological intervention, and psychotherapy reshape brain dynamics.
03 · Publications
Recent work appears across journals in systems neuroscience, neuroimaging, and neuromodulation.
Song, D.#, Chen, G.#, Fu, M., Li, S., Zhang, M., Cui, Z., et al. · bioRxiv
Combining multimodal imaging, connectomics, and cross-dataset prediction, this work identifies three VMPFC subdivisions aligned with social cognition, value, and emotion.
Lu, J.#, Song, D.#*, Chang, D., Zhang, X., Ma, X.*, & Wang, Z.* · Neural Plasticity
Across three MRI scanners, rumination showed reproducible increases in posterior midline BEN and decreases in visual cortex, supporting a robust dynamic signature of internally directed thought.
Song, D.*, Deng, X. P., Chang, D., & Wang, Z.* · Cerebral Cortex, 35(7)
Low-frequency rTMS and cTBS produced distinct, target-specific BEN changes across prefrontal, temporoparietal, and occipital stimulation sites, extending BEN as a marker of neuromodulation.
Song, D.*, & Wang, Z.* · NeuroImage, 312, 121226
The study links progesterone to lower frontoparietal and limbic BEN and suggests that DLPFC brain dynamics mediate the relationship between progesterone and impulsivity.
Song, D.*, & Wang, Z.* · Behavioural Brain Research, 115985
In a randomized, double-blind, placebo-controlled study, intranasal oxytocin increased left TPJ entropy in younger adults but decreased it in older adults, revealing an age-dependent neural response.
Liu, P., Song, D.*, Deng, X., Shang, Y., Ge, Q., Wang, Z.*, & Zhang, H.* · Neurotherapeutics, 22(3), e00556
Stimulation intensity reversed the direction of striatal BEN change: subthreshold iTBS reduced entropy, whereas suprathreshold iTBS increased it, highlighting intensity as a key therapeutic parameter.
Song, D.*, Jann, K., & Wang, D. J. · Frontiers in Neurology, 15, 1387356
This editorial frames how nonlinear dynamic methods can complement conventional neuroimaging measures and introduces work spanning methodology, brain states, aging, and clinical applications.
# Equal contribution · * Corresponding author
04 · Current projects
Ongoing program
A systematic research program investigating how BEN relates to network organization, stimulation, neurochemical signaling, and clinical phenotypes.
Recent preprint
Mapping anterior-to-posterior social, value, and affective subdivisions using multimodal imaging and cross-dataset predictive modeling.
View preprintLab research
Contributing neuroimaging and brain-dynamics methods to research at USTC’s Sleep Neuroscience and Brain–Computer Interface Laboratory.
Institutional profile05 · Academic activities
Conference contributions verified against my Google Scholar record and official meeting programs.
Montréal · Canada
Virtual · originally scheduled for Seoul
Hohhot · China
Virtual conference
Shenzhen · China
Singapore
Seoul · South Korea
Workshop · Beijing, China
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University · 25 December 2021
View workshop materials ↗06 · Contact
I welcome conversations about collaborations, methods, open science, and research opportunities.
donghuisong@ustc.edu.cnDepartment of Psychology
University of Science and Technology of China
Hefei, Anhui, China