Development of new medications for mental health conditions is a pressing need given the high proportion of people not responding to available treatments. We hope that presenting ebselen to a wider audience will inspire further studies on this promising agent with a benign side-effects profile. Laboratory research, animal research and human studies suggest that ebselen shares many features with the mood stabilising drug lithium, creating a promise of a drug that would have a similar clinical effect but without lithium’s troublesome side-effect profile and toxicity. Both drugs have a common biological target, inositol monophosphatase, whose inhibition is thought key to lithium’s therapeutic effect. Both drugs have neuroprotective action and reduce oxidative stress. In animal studies, ebselen affected neurotransmitters involved in the development of mental health symptoms, and in particular, produced effects of serotonin function very similar to lithium. Both ebselen and lithium share behavioural effects: antidepressant-like effects in rodent models of depression and decrease in behavioural impulsivity, a property associated with lithium's anti-suicidal action. Human neuropsychological studies support an antidepressant profile for ebselen based on its positive impact on emotional processing and reward seeking. Our group currently is exploring ebselen’s effects in patients with mood disorders. A completed ‘add-on’ clinical trial in mania showed ebselen’s superiority over placebo after three weeks of treatment. Our ongoing experimental research explores ebselen’s antidepressant profile in patients with treatment resistant depression. If successful, this will lead to a clinical trial of ebselen as an antidepressant augmentation agent, similar to lithium.

A single person can be the source of billions of data points, whether these are generated from everyday internet use, healthcare records, wearable sensors or participation in experimental research. This vast amount of data can be used to make predictions about people and systems: what is the probability this person will develop diabetes in the next year? Will commit a crime? Will be a good employee? Is of a particular ethnicity? Predictions are simply represented by a number, produced by an algorithm. A single number in itself is not biased. How that number was generated, interpreted and subsequently used are all processes deeply susceptible to human bias and prejudices. This session will explore a philosophical perspective of data ethics and discuss practical steps to reducing statistical bias. There will be opportunity in the last section of the session for attendees to discuss and troubleshoot ethical questions from their own analyses in a ‘Data Clinic’.

Classic economists proposed that economic choices rely on the computation and comparison of subjective values. This hypothesis continues to inform economic theory and experimental research, but behavioral measures are ultimately not sufficient to prove the proposal. Consistent with the hypothesis, when agents make choices, neurons in the orbitofrontal cortex (OFC) encode the subjective value of offered and chosen goods. Moreover, neuronal activity in this area suggests the formation of a decision. However, it is unclear whether these neural processes are causally related to choices. More generally, the evidence linking choices to value signals in the brain remains correlational. In my talk, I will present recent results showing that neuronal activity in OFC are causal to economic choices.