extract from wired magazine article, 19 October 2017, by sian bradley
"Computational psychiatrists have broken new ground in understanding how humans learn, by modelling a software program to behave just behave like us. The study, published in the journal eLife could help explain why people with depression can feel overwhelmed by negative thoughts.
This study shows that maybe people with depression focus on the negative things in the world because they believe that they hold more information, which would make focusing on them the logical thing to do. - Michael Browning
Using a simple shape-choosing task, the study found that humans learn more when events have volatile outcomes. The research was led by Michael Browning from the University of Oxford and his colleague Erdem Pulcu. They investigated whether a tendency to alter how we prioritise the processing of negative and positive events could bias our beliefs. The study is the first to prove that people separately judge how informative good and bad outcomes are. This could mean that people with depression tend to prioritise negative thoughts because they seem more important.
During the study, participants chose between two shapes that flashed up on a screen. Choosing one shape earned them money, the other would take it away. “All you have to do in this task is learn where you think the winner is, so you can win as much money as possible,” Browning explains.
Browning designed the task so either the positive (winning money) or negative (losing money) outcomes were variable. Variable means the outcomes change unexpectedly – for instance getting heads eight times in a row during a coin toss – rather than stably switching between the two."
Read the full article: 'This computer model is unlocking why people suffer from depression', Wired Magazine.
Read more about Professor Michael Browning
Read more about Dr Erdem Pulcu
Read more about the Computational Psychiatry Lab