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Research interests

The beneficial effects of drug treatment for psychiatric disorders often vary substantially between patients – a given medicine might alleviate symptoms in some patients but not in others. Meanwhile, some symptoms are resistant to current drug treatments; examples include the cognitive symptoms (e.g. cognitive inflexibility, impaired attention) and to a large extent the negative symptoms (e.g. low mood, lack of motivation) associated with schizophrenia. At the same time, many of the currently prescribed drugs are linked to frequent and sometimes severe adverse effects, making the pharmacological intervention in psychiatric disorders a balancing act between positive and negative outcomes. In my research group, we are interested in shifting this balance towards the positive, by studying the mechanisms underlying both therapeutic and adverse effects of drugs and perhaps identify drugs that produce less adverse effects while the therapeutic effects are maintained or even refined. This will ultimately improve the treatment of psychiatric disorders.

We approach this using translationally relevant behavioural tasks for cognition (e.g. reversal learning for cognitive flexibility and a sustained attention task) as well as motivation (effort discounting and progressive ratio). We combine such tasks with neural measurements using fibre photometry to gain further understanding of e.g. neurotransmitter dynamics and how this is impacted by drug treatment. In collaboration with Prof. Eamonn Kelly also at the School of Physiology, Pharmacology, and Neuroscience, we use BRET to further understand the mechanisms involved in receptor pharmacology, with a particular emphasis on chemicals that display a functional bias, that is preferentially blocks one intracellular signalling pathway (e.g. β-arrestin signalling) while stimulating another (e.g. G proteins).

Keywords

  • Psychopharmacology
  • Pharmacology
  • Schizophrenia
  • Dopamine
  • Serotonin
  • Basal ganglia
  • Corticostriatal
  • Cognition
  • Brain and behaviour
  • Reinforcement Learning

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