Sex-dependent effects of early life stress on reinforcement learning and limbic cortico-striatal functional connectivity

Zühlsdorff, Katharina; López-Cruz, Laura; Dutcher, Ethan G.; Jones, Jolyon A.; Pama, Claudia; Sawiak, Stephen J.; Khan, Shahid A.; Milton, Amy; Robbins, Trevor W.; Bullmore, Edward T.; Dalley, Jeffrey W.

doi:10.1016/j.ynstr.2022.100507

Cited by 8 publications

(4 citation statements)

References 107 publications

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“…Additionally, stickiness represents repeated responses, rather than response shifts. In rats, it has been shown that side stickiness (stimulus stickiness was not studied) is correlated with activity in medial PFC and dorsal striatal regions (Zühlsdorff et al 2023). It is therefore possible that side and stimulus stickiness recruit different neural circuits, but this requires further analysis in the same species.…”

Section: Discussionmentioning

confidence: 99%

“…Furthermore, the neural substrates underlying these changes in RL parameters are not clearly defined. In rats, stickiness positively correlated with resting-state fMRI activity between the medial OFC (mOFC), PFC and subcortical structures (Zühlsdorff et al 2023). In humans, the link between RL behavior and neural activity has not yet been established.…”

Section: Introductionmentioning

confidence: 99%

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Computational modeling of reinforcement learning and functional neuroimaging of probabilistic reversal dissociates compulsive behaviors in Gambling and Cocaine Use Disorders

Zühlsdorff

Verdejo‐Román

Clark

et al. 2023

Preprint

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Cognitive flexibility refers to the ability to adjust to changes in the environment and is essential for adaptive behavior. It can be investigated using laboratory tests such as probabilistic reversal learning (PRL). In individuals with both Cocaine Use Disorder (CUD) and Gambling Disorder (GD), overall impairments in PRL flexibility are observed. However, it is poorly understood whether this impairment depends on the same brain mechanisms in cocaine and gambling addictions. Reinforcement learning (RL) is the process by which rewarding or punishing feedback from the environment is used to adjust behavior, to maximise reward and minimise punishment. Using RL models, a deeper mechanistic explanation of the latent processes underlying cognitive flexibility can be gained. Here, we report results from a re-analysis of PRL data from control participants (n=18) and individuals with either GD (n=18) or CUD (n=20) using a hierarchical Bayesian RL approach. We observed significantly reduced stimulus stickiness (i.e., stimulus-bound perseveration) in GD, which may reflect increased exploratory behavior that is insensitive to outcomes. RL parameters were unaffected in CUD. We relate the behavioral findings to their underlying neural substrates through an analysis of task-based fMRI data. We report differences in tracking reward and punishment expected values (EV) in individuals with GD compared to controls, with greater activity during reward EV tracking in the cingulate gyrus and amygdala. In CUD, we observed reduced responses to positive punishment prediction errors (PPE) and increased activity following negative PPEs in the superior frontal gyrus compared to controls. Thus, an RL framework serves to differentiate behavior in a probabilistic learning paradigm in two compulsive disorders, GD and CUD.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Computational modeling of reinforcement learning and functional neuroimaging of probabilistic reversal dissociates compulsive behaviors in Gambling and Cocaine Use Disorders

Zühlsdorff

Verdejo‐Román

Clark

et al. 2023

Preprint

Self Cite

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show abstract

“…In rats, it has been shown that side stickiness (stimulus stickiness was not studied) is correlated with activity in medial PFC and dorsal striatal regions. 20 It is therefore possible that side and stimulus stickiness recruit different neural circuits, but this requires further analysis in the same species.…”

Section: Discussionmentioning

confidence: 99%

“…In rats, stickiness positively correlated with resting-state fMRI activity between the medial OFC (mOFC), PFC and subcortical structures. 20,21 In humans, the link between reinforcement learning behaviour and neural activity in these clinical populations has not yet been established.…”

Section: Neural Substrates Of Reward Processing In Disorders Of Compu...mentioning

confidence: 99%

Computational modelling of reinforcement learning and functional neuroimaging of probabilistic reversal for dissociating compulsive behaviours in gambling and cocaine use disorders

Zühlsdorff,

Verdejo-Román,

Clark

et al. 2023

BJPsych open

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Background Individuals with cocaine use disorder or gambling disorder demonstrate impairments in cognitive flexibility: the ability to adapt to changes in the environment. Flexibility is commonly assessed in a laboratory setting using probabilistic reversal learning, which involves reinforcement learning, the process by which feedback from the environment is used to adjust behavior. Aims It is poorly understood whether impairments in flexibility differ between individuals with cocaine use and gambling disorders, and how this is instantiated by the brain. We applied computational modelling methods to gain a deeper mechanistic explanation of the latent processes underlying cognitive flexibility across two disorders of compulsivity. Method We present a re-analysis of probabilistic reversal data from individuals with either gambling disorder (n = 18) or cocaine use disorder (n = 20) and control participants (n = 18), using a hierarchical Bayesian approach. Furthermore, we relate behavioural findings to their underlying neural substrates through an analysis of task-based functional magnetic resonanceimaging (fMRI) data. Results We observed lower ‘stimulus stickiness’ in gambling disorder, and report differences in tracking expected values in individuals with gambling disorder compared to controls, with greater activity during reward expected value tracking in the cingulate gyrus and amygdala. In cocaine use disorder, we observed lower responses to positive punishment prediction errors and greater activity following negative punishment prediction errors in the superior frontal gyrus compared to controls. Conclusions Using a computational approach, we show that individuals with gambling disorder and cocaine use disorder differed in their perseverative tendencies and in how they tracked value neurally, which has implications for psychiatric classification.

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5-HT 2A and 5-HT 2C receptor antagonism differentially modulate reinforcement learning and cognitive flexibility: behavioural and computational evidence

Hervig,

Zühlsdorff,

Olesen

et al. 2024

Psychopharmacology

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Rationale Cognitive flexibility, the ability to adapt behaviour in response to a changing environment, is disrupted in several neuropsychiatric disorders, including obsessive–compulsive disorder and major depressive disorder. Evidence suggests that flexibility, which can be operationalised using reversal learning tasks, is modulated by serotonergic transmission. However, how exactly flexible behaviour and associated reinforcement learning (RL) processes are modulated by 5-HT action on specific receptors is unknown. Objectives We investigated the effects of 5-HT2A receptor (5-HT2AR) and 5-HT2C receptor (5-HT2CR) antagonism on flexibility and underlying RL mechanisms. Methods Thirty-six male Lister hooded rats were trained on a touchscreen visual discrimination and reversal task. We evaluated the effects of systemic treatments with the 5-HT2AR and 5-HT2CR antagonists M100907 and SB-242084, respectively, on reversal learning and performance on probe trials where correct and incorrect stimuli were presented with a third, probabilistically rewarded, stimulus. Computational models were fitted to task choice data to extract RL parameters, including a novel model designed specifically for this task. Results 5-HT2AR antagonism impaired reversal learning only after an initial perseverative phase, during a period of random choice and then new learning. 5-HT2CR antagonism, on the other hand, impaired learning from positive feedback. RL models further differentiated these effects. 5-HT2AR antagonism decreased punishment learning rate (i.e. negative feedback) at high and low doses. The low dose also decreased reinforcement sensitivity (beta) and increased stimulus and side stickiness (i.e., the tendency to repeat a choice regardless of outcome). 5-HT2CR antagonism also decreased beta, but reduced side stickiness. Conclusions These data indicate that 5-HT2A and 5-HT2CRs both modulate different aspects of flexibility, with 5-HT2ARs modulating learning from negative feedback as measured using RL parameters and 5-HT2CRs for learning from positive feedback assessed through conventional measures.

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Sex-dependent effects of early life stress on reinforcement learning and limbic cortico-striatal functional connectivity

Cited by 8 publications

References 107 publications

Computational modeling of reinforcement learning and functional neuroimaging of probabilistic reversal dissociates compulsive behaviors in Gambling and Cocaine Use Disorders

Computational modeling of reinforcement learning and functional neuroimaging of probabilistic reversal dissociates compulsive behaviors in Gambling and Cocaine Use Disorders

Computational modelling of reinforcement learning and functional neuroimaging of probabilistic reversal for dissociating compulsive behaviours in gambling and cocaine use disorders

5-HT 2A and 5-HT 2C receptor antagonism differentially modulate reinforcement learning and cognitive flexibility: behavioural and computational evidence

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