Publication: Journal of Psychopharmacology

Kanen JW, Arntz FE, Yellowlees R, Cardinal RN, Price A, Christmas DM, Sahakian BJ, Apergis-Schoute AM, Robbins TW

18 February 2020

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The involvement of serotonin in responses to negative feedback is well established. Acute serotonin reuptake inhibition has enhanced sensitivity to negative feedback (SNF), modelled by behaviour in probabilistic reversal learning (PRL) paradigms. Whilst experiments employing acute tryptophan depletion (ATD) in humans, to reduce serotonin synthesis, have shown no clear effect on SNF, sample sizes have been small.

The researchers studied a large sample of healthy volunteers, male and female, and found ATD had no effect on core behavioural measures in PRL.

These results indicate that ATD effects can differ from other manipulations of serotonin expected to have a parallel or opposing action.

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Publication: Psychopharmacology

Kanen JW, Ersche KD, Fineberg NA, Robbins TW, Cardinal RN

20 July 2019

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Disorders of compulsivity such as stimulant use disorder (SUD) and obsessive-compulsive disorder (OCD) are characterised by deficits in behavioural flexibility, some of which have been captured using probabilistic reversal learning (PRL) paradigms.

This study used computational modelling to characterise the reinforcement learning processes underlying patterns of PRL behaviour observed in SUD and OCD and to show how the dopamine D2/3 receptor agonist pramipexole and the D2/3 antagonist amisulpride affected these responses.

The researchers applied a hierarchical Bayesian method to PRL data across three groups: individuals with SUD, OCD, and healthy controls. Participants completed three sessions where they received placebo, pramipexole, and amisulpride, in a double-blind placebo-controlled, randomised design.

The researchers compared seven models using a bridge sampling estimate of the marginal likelihood.

The results showed that stimulus-bound perseveration, a measure of the degree to which participants responded to the same stimulus as before irrespective of outcome, was significantly increased in SUD, but decreased in OCD, compared to controls (on placebo).

Individuals with SUD also exhibited reduced reward-driven learning, whilst both the SUD and OCD groups showed increased learning from punishment (nonreward).

Pramipexole and amisulpride had similar effects on the control and OCD groups; both increased punishment-driven learning. These D2/3-modulating drugs affected the SUD group differently, remediating reward-driven learning and reducing aspects of perseverative behaviour, amongst other effects.

The research showed how perseverative tendencies and reward- and punishment-driven learning differentially contribute to PRL in SUD and OCD.

D2/3 agents modulated these processes and remediated deficits in SUD in particular, which may inform therapeutic effects.

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Publication: Psychopharmacology

Alsiö J, Phillips BU, Sala Bayo J, Nilsson SRO, Calafat-Pla TC, Rizwand A, Plumbridge J, López-Cruz L, Dalley JW, Cardinal RN, Mar AC, Robbins TW

19 June 2019

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Dopamine D2-like receptors (D2R) are important drug targets in schizophrenia and Parkinson’s disease, but D2R ligands also cause cognitive inflexibility such as poor reversal learning. The specific role of D2R in reversal learning remains unclear.

Here researchers tested the hypotheses that D2R agonism impairs reversal learning by blocking negative feedback and that antagonism of D1-like receptors (D1R) impairs learning from positive feedback.

Male Lister Hooded rats were trained on a novel visual reversal learning task. Performance on “probe trials”, during which the correct or incorrect stimulus was presented with a third, probabilistically rewarded (50% of trials) and therefore intermediate stimulus, revealed individual learning curves for the processes of positive and negative feedback.

The effects of D2R and D1R agonists and antagonists were evaluated. A separate cohort was tested on a spatial probabilistic reversal learning (PRL) task after D2R agonism.

Computational reinforcement learning modelling was applied to choice data from the PRL task to evaluate the contribution of latent factors.

The team found that D2R agonism with quinpirole dose-dependently impaired both visual reversal and PRL. Analysis of the probe trials on the visual task revealed a complete blockade of learning from negative feedback at the 0.25 mg/kg dose, while learning from positive feedback was intact. Estimated parameters from the model that best described the PRL choice data revealed a steep and selective decrease in learning rate from losses. D1R antagonism had a transient effect on the positive probe trials. They concluded that D2R stimulation impairs reversal learning by blocking the impact of negative feedback.

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Publication: BMC Medical Informatics and Decision Making

Rudolf N Cardinal

26 April 2017

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Electronic medical records contain information of value for research, but contain identifiable and often highly sensitive confidential information.

Patient-identifiable information cannot in general be shared outside clinical care teams without explicit consent, but anonymisation/de-identification allows research uses of clinical data without explicit consent.

This article presents CRATE (Clinical Records Anonymisation and Text Extraction), an open-source software system with separable functions: (1) it anonymises or de-identifies arbitrary relational databases, with sensitivity and precision similar to previous comparable systems; (2) it uses public secure cryptographic methods to map patient identifiers to research identifiers (pseudonyms); (3) it connects relational databases to external tools for natural language processing; (4) it provides a web front end for research and administrative functions; and (5) it supports a specific model through which patients may consent to be contacted about research.

Creation and management of a research database from sensitive clinical records with secure pseudonym generation, full-text indexing, and a consent-to-contact process is possible and practical using entirely free and open-source software.

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