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. 2023 Jul 28;7(1):47-59.
doi: 10.5334/cpsy.96. eCollection 2023.

Electrophysiological Markers of Aberrant Cue-Specific Exploration in Hazardous Drinkers

Ethan M Campbell  1 , Garima Singh  1 , Eric D Claus  2 , Katie Witkiewitz  1 , Vincent D Costa  3 , Jeremy Hogeveen  1 , James F Cavanagh  1
Affiliations

Electrophysiological Markers of Aberrant Cue-Specific Exploration in Hazardous Drinkers

Ethan M Campbell et al. Comput Psychiatr. .

Abstract

Background: Hazardous drinking is associated with maladaptive alcohol-related decision-making. Existing studies have often focused on how participants learn to exploit familiar cues based on prior reinforcement, but little is known about the mechanisms that drive hazardous drinkers to explore novel alcohol cues when their value is not known.

Methods: We investigated exploration of novel alcohol and non-alcohol cues in hazardous drinkers (N = 27) and control participants (N = 26) during electroencephalography (EEG). A normative computational model with two free parameters was fit to estimate participants' weighting of the future value of exploration and immediate value of exploitation.

Results: Hazardous drinkers demonstrated increased exploration of novel alcohol cues, and conversely, increased probability of exploiting familiar alternatives instead of exploring novel non-alcohol cues. The motivation to explore novel alcohol stimuli in hazardous drinkers was driven by an elevated relative future valuation of uncertain alcohol cues. P3a predicted more exploratory decision policies driven by an enhanced relative future valuation of novel alcohol cues. P3b did not predict choice behavior, but computational parameter estimates suggested that hazardous drinkers with enhanced P3b to alcohol cues were likely to learn to exploit their immediate expected value.

Conclusions: Hazardous drinkers did not display atypical choice behavior, different P3a/P3b amplitudes, or computational estimates to novel non-alcohol cues-diverging from previous studies in addiction showing atypical generalized explore-exploit decisions with non-drug-related cues. These findings reveal that cue-specific neural computations may drive aberrant alcohol-related decision-making in hazardous drinkers-highlighting the importance of drug-relevant cues in studies of decision-making in addiction.

Keywords: P3a; POMDP; addiction; alcohol; explore-exploit.

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Conflict of interest statement

The authors have no competing interests to disclose.

Figures

Bandit task schematic and P300 time windows
Figure 1
(A) Three-armed alcohol novelty bandit task schematic. Displays reward and non-reward presentations as well as the novel insertion of an alcohol cue. (B) P3a and P3b averaged across all participants and cue types with highlighted time windows of analysis prior to (pre-insertion) and one trial after novel insertions (post-insertion) with error bars +/– SEM.
(A) Choice behavior averaged across both stimulus types between groups over trials since a novel insertion for the novel, best alternative, and worst alternative stimuli. Note the increase in exploratory behavior on trial 1 after a novel insertion. (B) Probability of selecting the novel stimulus (exploration) minus probability of selecting the best alternative (exploitation) on the post-insertion trial. Hazardous drinkers explored alcohol stimuli more often than controls, and controls explored non-alcohol stimuli more often than hazardous drinkers. (C) BONUS estimates with hazardous drinkers having higher BONUS values for alcohol cues than controls. (D) IEV estimates with no significant differences between groups or cue types
Figure 2
(A) Choice behavior averaged across both stimulus types between groups over trials since a novel insertion for the novel, best alternative, and worst alternative stimuli. Note the increase in exploratory behavior on trial 1 after a novel insertion. (B) Probability of selecting the novel stimulus (exploration) minus probability of selecting the best alternative (exploitation) on the post-insertion trial. Hazardous drinkers explored alcohol stimuli more often than controls, and controls explored non-alcohol stimuli more often than hazardous drinkers. (C) BONUS estimates with hazardous drinkers having higher BONUS values for alcohol cues than controls. (D) IEV estimates with no significant differences between groups or cue types.
Relationship between choice behavior and P3a
Figure 3
Probability of explore minus exploit behavior by P3a, contrasted by group and cue type with significant paired comparison marked. For hazardous drinkers but not controls, an increase in the P3a is associated with an increase in the exploration of alcohol cues relative to non-alcohol cues.
Relationship between POMDP and P3a
Figure 4
BONUS and IEV parameters by P3a amplitude split by group and cue type with significant paired comparisons marked. For hazardous drinkers but not controls, an increase in the P3a is associated with the BONUS values for alcohol cues relative to non-alcohol cues. Additionally in hazardous drinkers but not controls, the P3a decreases as the IEV of alcohol cues increases relative to non-alcohol cues.
Relationship between POMDP and P3b
Figure 5
BONUS and IEV parameters by P3b amplitude split by group and cue type with significant paired comparison marked. The IEV of alcohol cues increases with P3b amplitude in hazardous drinkers relative to controls.
See this image and copyright information in PMC

References

    1. Addicott, M. A., Pearson, J. M., Sweitzer, M. M., Barack, D. L., & Platt, M. L. (2017). A Primer on Foraging and the Explore/Exploit Trade-Off for Psychiatry Research. Neuropsychopharmacology: Official Publication of the American College of Neuropsychopharmacology, 42(10), 1931–1939. DOI: 10.1038/npp.2017.108 - DOI - PMC - PubMed
    1. Al-Khalil, K., Vakamudi, K., Witkiewitz, K., & Claus, E. D. (2021). Neural correlates of alcohol use disorder severity among nontreatment-seeking heavy drinkers: An examination of the incentive salience and negative emotionality domains of the alcohol and addiction research domain criteria. Alcoholism, Clinical and Experimental Research, 45(6), 1200–1214. DOI: 10.1111/acer.14614 - DOI - PubMed
    1. Aloi, J., Crum, K. I., Blair, K. S., Zhang, R., Bashford-Largo, J., Bajaj, S., Schwartz, A., Carollo, E., Hwang, S., Leiker, E., Filbey, F. M., Averbeck, B. B., Dobbertin, M., & Blair, R. J. R. (2021). Individual associations of adolescent alcohol use disorder versus cannabis use disorder symptoms in neural prediction error signaling and the response to novelty. In Developmental Cognitive Neuroscience (Vol. 48, p. 100944). DOI: 10.1016/j.dcn.2021.100944 - DOI - PMC - PubMed
    1. Averbeck, B. B. (2015). Theory of choice in bandit, information sampling and foraging tasks. PLoS Computational Biology, 11(3), e1004164. DOI: 10.1371/journal.pcbi.1004164 - DOI - PMC - PubMed
    1. Beck, A. T., Steer, R. A., & Carbin, M. G. (1988). Psychometric properties of the Beck Depression Inventory: Twenty-five years of evaluation. Clinical Psychology Review, 8(1), 77–100. DOI: 10.1016/0272-7358(88)90050-5 - DOI

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