ePoster

Decoding of fMRI resting-state using task-based MVPA supports the Incentive-Sensitization Theory in smokers

Cindy Lor, David Steyrl, Mengfan Zhang, Feng Zhou, Benjamin Becker, Marcus Herdener, Boris B. Quednow, Amelie Haugg, Frank Scharnowski
FENS Forum 2024(2024)
Messe Wien Exhibition & Congress Center, Vienna, Austria

Conference

FENS Forum 2024

Messe Wien Exhibition & Congress Center, Vienna, Austria

Resources

Authors & Affiliations

Cindy Lor, David Steyrl, Mengfan Zhang, Feng Zhou, Benjamin Becker, Marcus Herdener, Boris B. Quednow, Amelie Haugg, Frank Scharnowski

Abstract

Background The Incentive-Sensitization Theory postulates that addiction is primarily driven by the sensitization of the brain’s reward system to addictive substances, such as nicotine. According to this theory, exposure to such substances leads to an increase in ‘wanting’, while ‘liking’ the experience remains relatively unchanged. Although this candidate mechanism has been well substantiated through animal brain research, its translational validity for humans has only been partially demonstrated so far, with evidence from human neuroscience data being very limited.Methods From fMRI data of N=31 individuals with Nicotine Use Disorder, we created multivoxel patterns capable of capturing wanting and liking-related dimensions from a smoking cue-reactivity task. Using these patterns, we then designed a novel resting-state ‘reading’ method to evaluate how much wanting or liking still persist as a neural trace after watching the cues.Results We found that the persistence of wanting-related brain patterns at rest increases with longer smoking history but this was not the case for liking-related patterns. Interestingly, such behavior has not been observed for non-temporal measures of smoking intensity.Conclusion This study provides basic human neuroscience evidence that the dissociation between liking and wanting escalates over time, further substantiating the Incentive-Sensitization Theory, at least for Nicotine Use Disorder. These results suggest that treatment approaches could be personalized to account for the variability in individuals’ neural adaptation to addiction by considering how individuals differ in the extent to which their incentive salience system is sensitized.

Unique ID: fens-24/decoding-fmri-resting-state-using-task-based-a67a4912