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Publications

Computational Psychiatry & Decision-making

Papers, reviews & chapters

    2021

  • doi pdf How representative are neuroimaging samples? Large-scale evidence for trait anxiety differences between MRI and behaviour-only research participants.
  • Charpentier C, Faulkner P, Pool E, Ly V, Tollenaar MS, Kluen LM, Fransen A, Yamamori Y, Lally N, Mkrtchian A, Valton V, Huys QJM, Morrow K, Krenz V, Kalbe F, Cremer A, Zerbes G, Kausche FM, Wanke N, Giarrizzo A, Pulcu E, Murphy A, Kaltenboeck A, Browning M, Paul LK, Cools R, Roelofs K, Pessoa L, Harmer C, Chase HW, Grillon C, Schwabe L, Roiser J, Robinson O and O'Doherty J
  • Soc Cog Aff Neurosci nsab057
  • Over the past three decades, MRI has become a key tool to study how cognitive processes are implemented in the human brain. However, the question of whether participants recruited into MRI studies differ from participants recruited into other study contexts has received little to no attention. This is particularly pertinent when effects fail to generalize across study contexts: for example, if a behavioural effect discovered in a non-imaging context does not replicate in a neuroimaging environment. Here, we tested the hypothesis, motivated by preliminary findings (n=272), that MRI study participants differ from behaviour-only study participants on one fundamental individual difference variable: trait anxiety. Analysing a large-scale dataset drawn from multiple institutions (n=3317) and controlling for possible confounding variables, we found robust support for lower trait anxiety in MRI study participants, consistent with a sampling bias. Distributions of trait anxiety scores differed most markedly when psychiatric screening was minimal. Our findings highlight the need for surveying trait anxiety at recruitment and for appropriate screening procedures, in an attempt to mitigate this bias.
  • doi pdf Neurocomputational mediators in psychotherapy
  • Reiter AMF, Atiya N, Berwian IM and Huys QJM
  • Curr Op Behav Sci (2021) 38: 103-109
  • A classic definition of intrusive thinking is "any distinct, identifiable cognitive event that is unwanted, unintended, and recurrent. It interrupts the flow of thought, interferes in task performance, is associated with negative affect, and is difficult to control" (Clark 2005:4). While easy to understand and applicable to many cases, this definition does not seem to encompass the entire spectrum of intrusions. For example, intrusive thoughts may not always be experienced as unpleasant or unwanted, and may in some situations even be adaptive. This chapter revisits the definition of intrusive thinking, by systematically considering all the circumstances in which intrusions might occur, their manifestations across health and disorders, and develops an alternative, more inclusive definition of intrusions as being "interruptive, salient, experienced mental events." It proposes that clinical intrusive thinking differs from its nonclinical form with regard to frequency, intensity, and maladaptive reappraisal. Further, it discusses the neurocognitive processes underlying intrusive thinking and its control, including memory pro- cesses involved in action control, working memory and long-term memory encoding, retrieval, and suppression. As part of this, current methodologies used to study intrusive thinking are evaluated and areas are highlighted where more research and/or technical innovation is needed. It concludes with a discussion of the theoretical, therapeutic, and sociocultural implications of intrusive thinking and its control.

  • doi pdf Model-based and model-free control predicts alcohol consumption developmental trajectory in young adults - a three-year prospective study
  • Chen H, Belanger MJ, Mojtahedzadeh N, Nebe S, Kuitunen-Paul S, Sebold M, Garbusow M, Huys QJM, Heinz A, Rapp MA and Smolka MN
  • Biological Psychiatry (2021) 89(10): 980-989
  • Background: A shift from goal-directed toward habitual control has been associated with alcohol dependence. Whether such a shift predisposes pathological drinking is not yet clear. We investigated how goal-directed and habitual control at age 18 predict alcohol use trajectories over the course of three years. Methods: Goal-directed and habitual control, as informed by model-based and model-free learning, were assessed with a two-step sequential decision-making task during fMRI in 146 healthy 18-year-old male adults. Two key drinking variables were used to model the three-year alcohol use developmental trajectory: a consumption score from the Alcohol Use Disorders Identification Test (AUDIT-C; assessed every six months) and a binge drinking score (gram alcohol/occasion; assessed every year). We applied a latent growth curve model to examine how model-based and model-free control predicted the drinking trajectory. Results: The drinking behavior was best characterized by a linear trajectory. The model-based behavioral control was negatively associated with the development of the binge drinking score; the model-free reward prediction error (RPE) BOLD signals in the ventromedial prefrontal cortex and the ventral striatum predicted a higher starting point and steeper increase of the consumption score over time, respectively. Conclusions: We found that model-based behavioral control was associated with the binge drinking trajectory, while the model-free RPE signal was closely linked to the consumption score development. These findings support the idea that a shift from model-based to model-free control might be an important individual vulnerability in predisposing hazardous drinking behavior.
  • doi pdf A Comparison of 'Pruning' During Multi-Step Planning in Depressed and Healthy Individuals
  • Faulkner P, Huys QJM, Renz D, Eshel N, Pilling S, Dayan P and Roiser JP
  • Psychological Medicine 1-9.
  • Humans routinely formulate plans in domains so complex that even the most powerful computers are taxed. To do so, they seem to avail themselves of many strategies and heuristics that efficiently simplify, approximate, and hierarchically decompose hard tasks into simpler subtasks. Theoretical and cognitive research has revealed several such strategies; however, little is known about their establishment, interaction, and efficiency. Here, we use model-based behavioral analysis to provide a detailed examination of the performance of human subjects in a moderately deep planning task. We find that subjects exploit the structure of the domain to establish subgoals in a way that achieves a nearly maximal reduction in the cost of computing values of choices, but then combine partial searches with greedy local steps to solve subtasks, and maladaptively prune the decision trees of subtasks in a reflexive manner upon encountering salient losses. Subjects come idiosyncratically to favor particular sequences of actions to achieve subgoals, creating novel complex actions or "options."
  • 2020

  • doi pdf The relationship between resting-state functional connectivity, antidepressant discontinuation and depression relapse
  • Berwian IM, Wenzel J, Kuehn L, Schnuerer I, Kasper L, Veer IM, Seifritz E, Stephan KE, Walter H, Huys QJM
  • Scientific reports (2020) 10:22346
  • The risk of relapsing into depression after stopping antidepressants is high, but no established predictors exist. Resting-state functional magnetic resonance imaging (rsfMRI) measures may help predict relapse and identify the mechanisms by which relapses occur. rsfMRI data were acquired from healthy controls and from patients with remitted major depressive disorder on antidepressants. Patients were assessed a second time either before or after discontinuation of the antidepressant, and followed up for six months to assess relapse. A seed-based functional connectivity analysis was conducted focusing on the left subgenual anterior cingulate cortex and left posterior cingulate cortex. Seeds in the amygdala and dorsolateral prefrontal cortex were explored. 44 healthy controls (age: 33.8 (10.5), 73% female) and 84 patients (age: 34.23 (10.8), 80% female) were included in the analysis. 29 patients went on to relapse and 38 remained well. The seed-based analysis showed that discontinuation resulted in an increased functional connectivity between the right dorsolateral prefrontal cortex and the parietal cortex in non-relapsers. In an exploratory analysis, this functional connectivity predicted relapse risk with a balanced accuracy of 0.86. Further seed-based analyses, however, failed to reveal differences in functional connectivity between patients and controls, between relapsers and non-relapsers before discontinuation and changes due to discontinuation independent of relapse. In conclusion, changes in the connectivity between the dorsolateral prefrontal cortex and the posterior default mode network were associated with and predictive of relapse after open-label antidepressant discontinuation. This finding requires replication in a larger dataset.
  • pdf The association of the OPRM1 A118G polymorphism and Pavlovian-to-instrumental transfer: clinical relevance for alcohol dependence
  • Sebold M, Garbusow M, Cerci D, Chen K, Sommer C, Huys QJM, Nebe S, Rapp M, Veer IM, Zimmermann US, Smolka MN, Walter H, Heinz A, Friedel E
  • J Psychopharmacology (2020) in press
  • Background: Pavlovian-to-instrumental transfer (PIT) quantifies the extent to which a stimulus that has been associated with reward or punishment alters operant behavior. In alcohol dependence (AD), the PIT effect serves as a paradigmatic model of cue-induced relapse. Preclinical studies have suggested a critical role of the opioid system in modulating Pavlovian-instrumental interactions. The A118G polymorphism of the OPRM1 gene affects opioid receptor availability and function. Furthermore, this polymorphism interacts with cue-induced approach behavior and is a potential biomarker for pharmacological treatment response in AD. Here, we test whether the OPRM1 polymorphism is associated with the PIT effect and relapse in AD. Methods: Using a Pavlovian-to-instrumental transfer task, we examined three independent samples including young healthy subjects (n=161), detoxified alcohol-dependent patients (n=186) and age-matched healthy controls (n=105). We used data of a larger study designed to assess the role of learning mechanisms in the development and maintenance of AD. Subjects were genotyped for the A118G (rs1799971) polymorphism of the OPRM1 gene. Relapse was assessed after three months. Results: In all three samples, participants with the minor OPRM1 G-Allele (G+-carriers) showed increased expression of the PIT effect in the absence of learning differences. Relapse was not associated with the OPRM1 polymorphism. Instead, G+ carriers displaying increased PIT effects were particularly prone to relapse. Conclusion: These results support a role for the opioid system in incentive salience motivation. Furthermore, they inform a mechanistic model of aberrant salience processing and are in line with the pharmacological potential of opioid receptor targets in the treatment of AD.
  • doi pdf Susceptibility to interference between Pavlovian and instrumental control is associated with early hazardous alcohol use
  • Hao C, Nebe S, Mojtahedzadeh N, Kuitunen-Pauls S, Garbusow M, Schad D, Rapp M, Huys QJ, Heinz A, Smolka M
  • Addiction Biology (2020) e12983
  • Pavlovian-to-instrumental transfer (PIT) tasks examine the influence of Pavlovian stimuli on ongoing instrumental behaviour. Previous studies reported associations between a strong PIT effect, high-risk drinking, and alcohol use disorder. This study investigated whether susceptibility to interference between Pavlovian and instrumental control is linked to risky alcohol use in a community sample of 18-year-old male adults. Participants (N=191) were instructed to "collect good shells" and "leave bad shells" during the presentation of appetitive (monetary reward), aversive (monetary loss), or neutral Pavlovian stimuli. We compared instrumental error rates (ER) and fMRI brain responses between the congruent and incongruent conditions, as well as among high-risk and low-risk drinking groups. On average, individuals showed a substantial PIT effect, i.e. increased ER when Pavlovian cues and instrumental stimuli were in conflict compared to congruent trials. Neural PIT correlates were found in the ventral striatum and the dorsomedial and lateral prefrontal cortices (lPFC). Importantly, high-risk drinking was associated with a stronger behavioural PIT effect, a decreased lPFC response, and an increased neural response in the ventral striatum on the trend level. Moreover, high-risk drinkers showed weaker connectivity from the ventral striatum to the lPFC during incongruent trials. Our study links interference during PIT to drinking behaviour in healthy, young adults. High-risk drinkers showed higher susceptibility to Pavlovian cues, especially when they conflicted with instrumental behaviour, indicating lower interference control abilities. Increased activity in the ventral striatum (bottom-up), decreased lPFC response (top-down), along with their altered interplay may contribute to poor interference control in the high-risk drinkers.
  • preprint pdf Explaining distortions in metacognition with an attractor network model of decision uncertainty
  • Atiya N, Huys QJM, Dolan RJ, Fleming S
  • bioRxiv
  • Metacognition is the ability to reflect on, and evaluate, our cognition and behaviour. Distortions in metacognition are common in mental health disorders, though the neural underpinnings of such dysfunction are unknown. One reason for this is that models of key components of metacognition, such as decision confidence, are generally specified at an algorithmic or process level. While such models can be used to relate brain function to psychopathology, they are difficult to map to a neurobiological mechanism. Here, we develop a biologically-plausible model of decision uncertainty in an attempt to bridge this gap. We first relate the model's uncertainty in perceptual decisions to standard metrics of metacognition, namely mean confidence level (bias) and the accuracy of metacognitive judgments (sensitivity). We show that dissociable shifts in metacognition are associated with isolated disturbances at higher-order levels of a circuit associated with self-monitoring, akin to neuropsychological findings that highlight the detrimental effect of prefrontal brain lesions on metacognitive performance. In contrast to existing theoretical work, we account for empirical confidence judgements by fitting our biophysical model solely to first-order performance data, specifically choice and response times. Lastly, in a reanalysis of existing data we show that self-reported mental health symptoms relate to disturbances in an uncertainty-monitoring component of the network. By bridging a gap between a biologically-plausible model of confidence formation and observed disturbances of metacognition in mental health disorders we provide a first step towards mapping theoretical constructs of metacognition onto dynamical models of decision uncertainty. In doing so, we provide a computational framework for modelling metacognitive performance in settings where access to explicit confidence reports is not possible.

  • pdf Neuropsychological Mechanisms of Intrusive Thinking
  • Visser RM, Anderson MC, Aron A, Banich MT, Brady KT, Huys QJM, Monfils MH, Schiller D, Schlagenhauf F, Schooler J and Robbins TW
  • In: Intrusive Thinking: From Molecules to Free Will, edited by Kalivas, P and Paulus, M. Strüngmann Forum Reports, vol. 30, J. Lupp, series editor. Cambridge, MA: MIT Press
  • A classic definition of intrusive thinking is "any distinct, identifiable cognitive event that is unwanted, unintended, and recurrent. It interrupts the flow of thought, interferes in task performance, is associated with negative affect, and is difficult to control" (Clark 2005:4). While easy to understand and applicable to many cases, this definition does not seem to encompass the entire spectrum of intrusions. For example, intrusive thoughts may not always be experienced as unpleasant or unwanted, and may in some situations even be adaptive. This chapter revisits the definition of intrusive thinking, by systematically considering all the circumstances in which intrusions might occur, their manifestations across health and disorders, and develops an alternative, more inclusive definition of intrusions as being "interruptive, salient, experienced mental events." It proposes that clinical intrusive thinking differs from its nonclinical form with regard to frequency, intensity, and maladaptive reappraisal. Further, it discusses the neurocognitive processes underlying intrusive thinking and its control, including memory pro- cesses involved in action control, working memory and long-term memory encoding, retrieval, and suppression. As part of this, current methodologies used to study intrusive thinking are evaluated and areas are highlighted where more research and/or technical innovation is needed. It concludes with a discussion of the theoretical, therapeutic, and sociocultural implications of intrusive thinking and its control.

  • doi preprint pdf Advances in the computational understanding of mental illness
  • Huys QJM, Browning MB, Paulus MP and Frank MJ
  • Neuropsychopharmacology In Press
  • Computational psychiatry is a rapidly growing field attempting to translate advances in computational neuroscience and machine learning into improved outcomes for patients suffering from mental illness. It encompasses both data-driven and theory-driven efforts. Here, recent advances in theory-driven work are reviewed. We argue that the brain is a computational organ. As such, an understanding of the illnesses arising from it will require a computational framework. The review divides work up into three theoretical approaches that have deep mathematical connections: dynamical systems, Bayesian inference and reinforcement learning. We discuss both general and specific challenges for the field, and suggest ways forward.


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