Brain modular connectivity interactions can predict proactive inhibition in smokers when facing smoking cues

Area of Science:

• Neuroscience
• Addiction Research
• Cognitive Psychology

Background:

• Proactive inhibition is vital for smokers aiming to reduce or quit nicotine use.
• Understanding how smoking cues affect proactive inhibition and brain networks in withdrawal is limited.

Purpose of the Study:

• To investigate the impact of salient smoking cues on behavioral and neural aspects of proactive inhibition in smokers.
• To analyze the dynamic interactions within and between brain networks during proactive inhibition tasks under different cue conditions.

Main Methods:

• 26 smokers completed a stop-signal anticipatory task (SSAT) in neutral and smoking cue conditions.
• Graph-based modularity analysis was used to examine brain network structures and functional connectivity.
• Behavioral performance was correlated with neural network dynamics.

Main Results:

• Three stable brain modules (sensorimotor network, cognitive control network, default-mode network) were identified.
• Increased task demands altered functional connectivity within and between these networks.
• Smoking cues disrupted dynamic interactions, and these disruptions predicted behavioral performance.

Conclusions:

• Brain network dynamics play a significant role in proactive inhibition for smokers.
• Salient smoking cues impair the neural mechanisms supporting proactive inhibition.
• Findings offer insights for developing targeted interventions for smoking cessation.