Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Adaptive behaviour relies on the brain’s ability to navigate uncertainty. Not all uncertainty is the same: it can be expected or unexpected. Expected uncertainty arises from known variability in outcomes within a stable environment. This variability can relate to timing, effort, value, or probability of outcomes. For example, rolling a die always produces a number between 1 and 6, or a vending machine may dispense snacks according to a fixed probability. Here, uncertainty stems from the range of possible outcomes, but the underlying rules remain consistent. In contrast, unexpected uncertainty emerges from sudden, unpredictable changes that violate previously learned rules—so-called structural knowledge of the environment. Examples include a traffic pattern shifting when a road closes without notice, a restaurant unexpectedly changing its menu, or a software update that radically alters a familiar interface. Unlike expected uncertainty, unexpected uncertainty reflects a change in the environment itself, invalidating prior expectations and requiring rapid behavioural adaptation. Differentiating these two types of uncertainty is critical for understanding learning, decision-making, and behavioural flexibility. By studying how the brain responds to expected versus unexpected uncertainty, we can uncover the neural mechanisms that support adaptive strategies in dynamic environments. The Neurobehavior Lab has developed a task in which freely moving mice and humans build structural knowledge of their environment while also experiencing unexpected uncertainty. This framework allows us to model and explain behavioural variability in how strategies are chosen under each form of uncertainty. To uncover the underlying neural mechanisms, we will combine advanced methods in freely moving mice—including miniaturized two-photon microscopy, Neuropixels recordings, fibre photometry, and targeted manipulations with optogenetics and chemogenetics. In collaboration with other groups, the project may also expand to explore the corresponding neural mechanisms in humans.

For further details, please feel free to contact Mehran Ahmadlou (mehran.ahmadlou@dpag.ox.ac.uk).

Primary supervisor

Ahmadlou Group