Completed Mental Health Psychology & Behaviour

Information-seeking in health and disease

In plain English

AI plain-English summary

Every day, people decide whether to read the news, check their phone, or ask a question—and those decisions may go awry in depression and anxiety. Psychiatrists have long suspected that patients with these conditions seek or avoid information in unusual ways, but no one has precisely measured what drives those choices or how they break down in illness. This project aims to change that. The researcher has designed tasks that isolate three specific drivers of information-seeking: whether the information is good or bad (valence), how uncertain the person is, and whether the information helps them make a useful decision. By testing healthy volunteers and people diagnosed with affective disorders, the team will determine which of these drivers is over- or under-expressed in mental illness. They will also use brain imaging and drugs that alter dopamine—a chemical that malfunctions in several psychiatric conditions—to identify the neural circuits behind these altered choices. If successful, the work could produce a quantitative behavioural test for diagnosing subtypes of depression or anxiety, and for predicting which treatment might work for a given patient. This is fundamental science: it will not immediately change clinical practice. But understanding the precise computational mechanisms that drive maladaptive information-seeking could eventually lead to targeted therapies that correct those specific biases, rather than treating symptoms broadly.

View original technical description
People spend a substantial amount of time seeking out information (e.g., reading, asking questions, internet browsing). It is theorized that common psychiatric conditions, including depression and anxiety, are characterized by abnormal information-seeking patterns. These patterns could potentially be measured and used to facilitate diagnosis and treatment selection. However, the precise links between information-seeking and psychopathology are unknown. In fact, we know little about how to quantify information-seeking or the mechanisms that control it. My aim is to understand (i) how people decide to seek or avoid information and (ii) how those decisions relate to mental health. I have developed tasks to quantify key drivers of information-seeking (including valence of information, uncertainty, instrumental utility). I will test participants to assess whether psychopathology symptoms are linked to abnormal influence of these drivers on information-seeking. I will also combine pharmacological manipulation with neuroimaging to examine whether the influence of these drivers is dependent on dopamine – a neuromodulator that malfunctions in several conditions in which information-seeking is theorized to be altered- and identify the neural computations involved. I will assess whether these drivers are over/under expressed in individuals diagnosed with affective disorders, and conduct experiments to determine how these alterations impact well-being.

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Researchers

Tali Sharot (EPMC Awardee)

Related Research

Grants with similar aims, by meaning.

Neurocomputational mechanisms of seeking information about oneself and other people
Information Bias in Depression
Neural and behavioural patterns of avoidance; an fMRI analysis and online study approach
Developing an information-theoretic predictive factor analysis method with application to transdiagnostic psychometric and neurocognitive data
Clinical Psychopharmacology of Depression

Original classification

Senior Research Fellowship

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