Scientists Reveal Cognitive Mechanisms Involved in Bipolar Disorder
An international team of researchers including scientists from HSE University has experimentally demonstrated that individuals with bipolar disorder tend to perceive the world as more volatile than it actually is, which often leads them to make irrational decisions. The scientists suggest that their findings could lead to the development of more accurate methods for diagnosing and treating bipolar disorder in the future. The article has been published in Translational Psychiatry.
Bipolar disorder (BD) is a chronic affective condition characterised by alternating episodes of extreme elation (mania) and severe depression. According to the WHO, an estimated 40 million people worldwide live with bipolar disorder, but diagnosing the condition can be challenging, as its symptoms are not always apparent.
Studies show that individuals with bipolar disorder, even during remission, exhibit specific behavioural and brain activity patterns that may indicate the condition. In particular, patients with bipolar disorder have been found to exhibit impairments in their decision-making processes. Normally, when making a decision, a person tries to choose the option that offers the greatest reward. If the choice proves to be correct, they are likely to make the same decision again next time. However, circumstances can change, requiring a person to reassess which option offers the greatest benefit. Patients with BD often struggle to recognise when it is necessary to adjust their decision-making strategy.
A group of researchers from HSE University, Sechenov University, the Max Planck Institute, and Goldsmiths, University of London, conducted an experiment to investigate how individuals with bipolar disorder adapt to environmental changes and make decisions.
The study included 22 bipolar patients in remission and 27 healthy volunteers who served as the control group. Participants were instructed to earn as many points as possible by selecting either a blue or red image on a computer screen. Each option had a certain probability of winning, which changed throughout the experiment. For example, initially the blue image won 70% of the time, but later its winning probability dropped to 30%. Throughout the experiment, participants’ neuronal brain activity was monitored using magnetoencephalography (MEG).
Marina Ivanova
'This experimental design mimics real-world conditions, which are also full of uncertainties and require constant decision-making—even in everyday situations. For example: should you pet a cat, or is it better not to? Will it purr or scratch? We try to anticipate the consequences of our choices and make the best decision accordingly,' explains Marina Ivanova, Junior Research Fellow at the HSE Institute for Cognitive Neuroscience and primary author of the study.
The results of the experiment showed that participants with bipolar disorder perceived the environment as more volatile than it actually was, which often led them to make incorrect choices.
'If a person makes a decision and it turns out to be the right one, they will likely repeat that choice next time. However, someone with bipolar disorder may change their strategy even after a successful outcome,' says Ivanova.
The scientists also observed neural differences in brain regions involved in decision-making, specifically the medial prefrontal, orbitofrontal, and anterior cingulate cortices. At the neural level, while healthy individuals exhibited alpha-beta suppression and increased gamma activity during the experiment, participants with bipolar disorder showed dampened effects.
'Our study reveals that even outside of manic or depressive episodes, people with bipolar disorder process information about environmental changes differently. They constantly anticipate changes but struggle to properly learn from them when they occur. As a result, their decisions are more spontaneous and unpredictable than those of the control group,' comments Ivanova. ‘However, it is important to remember that our experiment only simulates real life, so we should be cautious when applying these findings to actual everyday situations.'
The results may be useful for developing models to diagnose bipolar disorder and predict its recurrence. In the future, this approach could be adapted to other mental health conditions involving adaptive learning impairments and may also serve as an important step toward advancing computational psychiatry.
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