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.

Sammi Chekroud

Postdoctoral Researcher

  • Computational Cognitive Neuroscience Lab (O'Reilly Lab)

I am a postdoc in the Computational Cognitive Neuroscience (CCN) lab, headed by Jill O'Reilly, and a Tutor for Statistics on the undergraduate psychology degree.

The world is dynamic and complex, yet we can only bring into focus small amounts of it at any one time. Our perception of the environment around us is part bottom-up sensory input, and part top-down prior knowledge, and we maintain internal representations of recently sampled information to guide our perception and action. Yet to make decisions based on these internal representations, we must evaluate their uncertainty to decide whether or not we rely on them.

I am interested in in the evaluation our internal representations and how we appropriately weight them with prior knowledge to adapt to the world around us. This gives rise to our psychological experience of uncertainty, which shapes how we interact with the world. To understand these processes, i use a combination of psychophysical methods, physiological recordings (eyetracking and EEG), and computational models of behaviour.

I completed my DPhil in 2022  in Oxford working with Kia Nobre and Nils Kolling, looking at how uncertainty and reward shape working-memory performance. I received my BA in Experimental Psychology from Oxford in 2015. Following my undergraduate degree, I worked as a Research Assistant in the Brain and Cognition lab for three years, supporting work on how attention shapes the use of working memories, using psychophysical methods, eye-tracking, EEG and MEG.

I also have a strong interest in the use of large, pre-existing datasets to enhance mental health treatments and care. I worked part-time on a collaboration with researchers at Yale, and industry partners, to further investigate the association between exercise and mental health.

Recent publications

More publications