Maladaptive context inference as key mechanism underlying impaired control (TRR 265: Project B09)
Project Summary
Addiction can be conceptualized as result of aberrant associative learning and maladaptive action control. Our project aims to develop, test, and apply a comprehensive computational model of addictive behavior integrating both Pavlovian and instrumental mechanisms, as well as cognitive control. Such a formal model of addictive behavior enables rigid empirical tests that will foster our understanding of underlying neuro-cognitive mechanisms, and thus pave the way for novel mechanism-based interventions. The key idea is that apparent habitual behavior and underlying impaired control over substance use is at least partially a consequence of failure to adequately recognize and adapt to contexts. Here, we will refer to the process of recognizing a context as context inference. In this view, goal-directed and habitual control are context-dependent, and Pavlovian cues are a mechanism biasing context inference. This would explain why substance use behavior appears to be habitual but, at the same time, patients with substance use disorders can also be highly goal-directed when it comes to organizing their substance use. In the first funding period we have developed an integrative computational model, that quantitatively describes the balancing of habitual and goal-directed behavior, as well as contextual effects and cognitive control conjointly. At the experimental level, we developed three novel tasks and set off to experimentally test predictions. Main goals for the second funding period are to (1) extend the current model by Pavlovian control (i.e. Pavlovian stimuli bias context inference and thereby selection of action policies), (2) test predictions of the context inference hypothesis with PIT task data from project B03 (collected during first funding period) and a refined task, (3) assessing associations with alcohol- and tobacco use disorders using our novel tasks developed in the first funding period, and (4) identify neural correlates of hypothesized computational/cognitive processes using model-based fMRI.
Project Members
Principle Investigators
Prof. Dr. Stefan Kiebel, Technische Universität Dresden
Prof. Dr. Michael N. Smolka, Technische Universität Dresden
Dr. Sarah Schwöbel, Technische Universität Dresden
Staff
Sascha Frölich (Ph.D student)
Johannes Steffen (Ph.D student)
Sia Hranova (Ph.D. student)
Dr. med. Arvid Pietsch (Physician)
Funding
Key Publications
- Belanger MJ, Chen H, Hentschel A, Garbusow M, Ebrahimi C, Knorr FG, Zech HG, Pilhatsch M, Heinz A & Smolka MN (2022) Development of novel tasks to assess outcome-specific and general Pavlovian-to-Instrumental Transfer in humans. Neuropsychobiology. 81(5):370-86. doi: 10.1159/000526774
- Chen H, Mojtahedzadeh N, Belanger MJ, Nebe S, Kuitunen-Paul S, Sebold M, Garbusow M, Huys QJM, Heinz A, Rapp MA & Smolka MN (2021) Model-based and model-free control predicts alcohol consumption developmental trajectory in young adults: A 3-year prospective study. Biol Psychiatry 89(10):980–989. doi: 10.1016/j.biopsych.2021.01.009
- Chen H, Nebe S, Mojtahedzadeh N, Kuitunen-Paul S, Garbusow M, Schad DJ, Rapp MA, Huys QJM, Heinz A & Smolka MN (2021) Susceptibility to interference between pavlovian and instrumental control is associated with early hazardous alcohol use. Addict Biology 26(4):e12983. doi: 10.1016/j.biopsych.2021.01.009
- Frölich S, Esmeyer M, Endrass T, Smolka MN & Kiebel SJ (2022) Interaction between habits as action sequences and goal-directed behavior under time pressure. Front Neurosci. doi: 10.3389/fnins.2022.996957
- Marković D, Goschke T & Kiebel SJ (2021) Meta-control of the exploration-exploitation dilemma emerges from probabilistic inference over a hierarchy of time scales. Cogn Affect Behav Neurosci 21(3):509–533. doi: 10.3758/s13415-020-00837-x
- Schwöbel S, Marković D, Smolka MN & Kiebel SJ (2021) Balancing control: A Bayesian interpretation of habitual and goal-directed behavior. J Math Psychol 100:102472. doi: 10.1016/j.jmp.2020.102472
- Sebold M, Kiebel SJ, Smolka MN, Heinz A & Deserno L (2022) Computational theories of Alcohol Use Disorder: Mapping learning and choice mechanisms on symptoms. Neuropsychobiology. 81(5):339-56. doi: 10.1159/000527146
Link
FP1 - Domain B: Collaborative Research Centre TRR 265: Losing and Regaining Control over Drug Intake
FP2 - Domain B: Collaborative Research Centre TRR 265: Losing and Regaining Control over Drug Intake