Neural networks and chemical messengers: Insights into tobacco addiction

Motivation: Tobacco addiction (TA) is associated with altered brain networks, but the underlying neurobiological mechanisms remain unclear. This study explores resting-state network (RSN) changes in TA and their relationship to neurotransmitter systems. Goal(s): To investigate functional connectivity (FC) changes in RSNs in TA individuals and their connection to neurotransmitter alterations. Approach: Functional MRI and independent component analysis were used to extract RSNs in 90 TA patients and 46 healthy controls. Correlation studies examined the link between FC changes and PET/SPECT-derived neurotransmitter maps. Results: TA patients showed reduced FC in sensorimotor and visual networks, linked to 5-HT1a and kappa opioid receptors. Impact: This study identifies specific brain network alterations in tobacco addiction linked to neurotransmitter systems, offering new targets for therapeutic interventions. These findings may guide personalized treatments and stimulate further research into the molecular mechanisms underlying addiction.