Exploring the Role of vmPFC in Smoking Behavior: A Functional Connectivity Analysis
Poster No:
644
Submission Type:
Abstract Submission
Authors:
Chen Zheng1, Tianye Jia1
Institutions:
1Fudan University, Shanghai, China
First Author:
Co-Author:
Introduction:
Nicotine addiction is a major public health concern, significantly contributing to global mortality and economic impacts. Our recent study demonstrated that reduction in gray matter volume (GMV) in the left ventromedial prefrontal cortex (vmPFC) may causally influence rule-breaking behavior, leading to smoking initiation, while changes in the right vmPFC's GMV may modulate the hedonic effects of substance use, reinforcing and maintaining future use[1]. The current work delves into the functional mechanisms of the vmPFC in smoking behavior.
Methods:
Data of Caucasian adults (age 24, n=1023) from the IMAGEN project were employed [2]. Smoking behavior was measured by the ESPAD survey. Participants with scores greater than 0 for item 'occasions of lifetime smoking' were considered smokers.The monetary incentive delay (MID) task was adopted [3], from which the big win vs. no win contrast were used for functional connectivity (FC) analysis using the CONN toolbox [4]. Hierarchical clustering were conducted with Ward's method to identify subregions in vmPFC among all participants. Two sample t-test were conducted to investigate the regions with different FC between smokers and non-smokers.
Results:
Analysis of voxel-to-voxel FC within smoking-related areas identified by changes of GMV (Fig.1a-b) suggested the existence of subregions. Employing hierarchical clustering, we delineated 5 subregions (Fig. 1d) arranged from left to right as L1, R1, R2, L2, and R3 in the dendrogram (Fig.1c). L1 exhibited widespread negative FC, while L2 and R3 showed similar, vmPFC-focused patterns.
Our findings highlight a significant inverse relationship between inter-hemispheric FC and the subjects' smoking history. Specifically, the analysis revealed the duration of daily smoking was inversely correlated with FC: between L1 and R1 (r=-0.15, p=0.018, Fig.1e), and between L2 and R3 (r=-0.18, p=0.005, Fig.1f). And the duration of smoking correlated negatively with FC: between L2 and R2 (r=-0.09, p=0.036, Fig.1g) and L2 and R3 (r=-0.08, p=0.049, Fig.1h).
Within the subregions, L1 exhibited pronounced negative FC with key brain regions associated with inhibition control, namely the dorsolateral prefrontal cortex (DLPFC), the anterior cingulate cortex, and the lateral orbitofrontal cortex. Case-control analysis between smokers and non-smokers revealed that L1 in smokers displayed significantly enhanced FC with the right DLPFC (Fig.2a). Notably, this increased FC was positively correlated with smoking frequency (r=0.08, p=0.01, Fig.2b) and the duration of smoking (r=0.07, p=0.034, Fig.2c).
Our findings highlight a significant inverse relationship between inter-hemispheric FC and the subjects' smoking history. Specifically, the analysis revealed the duration of daily smoking was inversely correlated with FC: between L1 and R1 (r=-0.15, p=0.018, Fig.1e), and between L2 and R3 (r=-0.18, p=0.005, Fig.1f). And the duration of smoking correlated negatively with FC: between L2 and R2 (r=-0.09, p=0.036, Fig.1g) and L2 and R3 (r=-0.08, p=0.049, Fig.1h).
Within the subregions, L1 exhibited pronounced negative FC with key brain regions associated with inhibition control, namely the dorsolateral prefrontal cortex (DLPFC), the anterior cingulate cortex, and the lateral orbitofrontal cortex. Case-control analysis between smokers and non-smokers revealed that L1 in smokers displayed significantly enhanced FC with the right DLPFC (Fig.2a). Notably, this increased FC was positively correlated with smoking frequency (r=0.08, p=0.01, Fig.2b) and the duration of smoking (r=0.07, p=0.034, Fig.2c).
Conclusions:
Our study extends previous research on GMV changes in the vmPFC by elucidating its functional mechanisms in relation to smoking behavior. We identified 5 functional subregions within the vmPFC, displaying distinct FC patterns. FC patterns among the subregions are significantly correlated with individuals' smoking histories, underscoring a potential neurobiological link between vmPFC activity and smoking behavior. The delineation of subregions represents a novel contribution to the field, providing a foundation for more nuanced investigations into the role of vmPFC in smoking. Notably, the FC between L1 and the right DLPFC correlated significantly with smoking history, highlighting a potentially critical pathway involving vmPFC, associated with evaluation processes, and the DLPFC, linked to inhibition control, in the context of smoking behavior. The identification of this pathway not only advances our understanding of the neurobiological mechanism of smoking but also opens new avenues for targeted research and interventions aimed at addressing nicotine addiction.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Emotion, Motivation and Social Neuroscience:
Reward and Punishment
Higher Cognitive Functions:
Executive Function, Cognitive Control and Decision Making
Modeling and Analysis Methods:
Connectivity (eg. functional, effective, structural) 2
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Addictions
ADULTS
FUNCTIONAL MRI
Other - Smoking; Functional Connectivity; vmPFC
1|2Indicates the priority used for review
Provide references using author date format
2 Schumann, G. (2010), ‘The IMAGEN Study: Reinforcement-related Behaviour in Normal Brain Function and Psychopathology’, Molecular Psychiatry, vol. 15, no. 12, p. 1128-1139.
3 Knutson, B. (2001), ‘Dissociation of Reward Anticipation and Outcome with Event-related fMRI’, Neuroreport, vol. 12, no. 17, p. 3683-3687.
4 Susan, WG. (2012), ‘CONN: a Functional Connectivity Toolbox for Correlated and Anticorrelated Brain Networks’, Brain Connectivity vol. 2, no. 3, p. 125-141.