Unraveling Neural Complexity: Exploring Brain Entropy to Yield Mechanistic Insight in Neuromodulation Therapies for Tobacco Use Disorder

Abstract

Neuromodulation therapies, such as repetitive transcranial magnetic stimulation (rTMS), have shown promise as treatments for tobacco use disorder (TUD). However, the underlying mechanisms of these therapies remain unclear, which may hamper optimization and personalization efforts. In this study, we investigated alteration of brain entropy as a potential mechanism underlying the neural effects of noninvasive brain stimulation by rTMS in people with TUD. We employed sample entropy (SampEn) to quantify the complexity and predictability of brain activity measured using resting-state fMRI data. Our study design included a randomized single-blind study with 42 participants who underwent 2 data collection sessions. During each session, participants received high-frequency (10Hz) stimulation to the dorsolateral prefrontal cortex (dlPFC) or a control region (visual cortex), and resting-state fMRI scans were acquired before and after rTMS. Our findings revealed that individuals who smoke exhibited higher baseline SampEn throughout the brain as compared to previously-published SampEn measurements in control participants. Furthermore, high-frequency rTMS to the dlPFC but not the control region reduced SampEn in the insula and dlPFC, regions implicated in TUD, and also reduced self-reported cigarette craving. These results suggest that brain entropy may serve as a potential biomarker for effects of rTMS, and provide insight into the neural mechanisms underlying rTMS effects on smoking cessation. Our study contributes to the growing understanding of brain-based interventions for TUD by highlighting the relevance of brain entropy in characterizing neural activity patterns associated with smoking. The observed reductions in entropy following dlPFC-targeted rTMS suggest a potential mechanism for the therapeutic effects of this intervention. These findings support the use of neuroimaging techniques to investigate the use of neuromodulation therapies for TUD.

Divergent association between pain intensity and resting‐state fMRI‐based brain entropy in different age groups

“…In addition, altered BEN has been found in several brain diseases, such as smoking, alcohol use, and nicotine dependence (Chang, Zhang, et al., 2018; Jiang et al., 2023; Li et al., 2016), cocaine addiction (Wang et al., 2017), multiple sclerosis (Zhou et al., 2016), Alzheimer's disease (Wang, 2020), major depression disorder (Liu et al., 2020), Schizophrenia (Xue et al., 2019). BEN has shown sensitivity to task activation (Camargo et al., 2024; Lin et al., 2022; Wang et al., 2014), caffeine (Chang, Song, et al., 2018), medication (Liu et al., 2020), and transcranial magnetic stimulation (Chang, Zhang, et al., 2018; Jordan et al., 2024; Song, Chang, Zhang, Peng, et al., 2019). Overall, age‐related BEN increase has been interpreted as a consequence of brain tissues functional and structural deteriorations, while negative associations between BEN and education and fluid intelligence have been proposed to reflect greater general cognitive capability as well as larger capacity of the cognitive reserve (Wang, 2020, 2021).…”