The Memory & Attention Group is a collective of scientists within Psychology and the Centre for Human Brain Health (CHBH) who study attention and memory from a cognitive, neuroscientific and computational perspective. Our mission is to uncover how the human brain creates conscious percepts from the information coming in through the senses, and how our perceptions are then transformed into long-lasting memories.
Much of the work in our group is basic research. In the domain of attention, we study how the human brain extracts the relevant information from a complex and fast-changing external environment, and what pathways this information then has to follow through the brain to ultimately result in a conscious perception. In the memory domain, we investigate how experiences are transformed into short- or long-term memories. We develop new methods that allow us to track memories in patterns of brain activity throughout all stages of their existence: from a memory’s original encoding, via its stabilization during wake and sleep cycles, to its active remembering (reactivation) at a later point in time.
Apart from this basic research, we also translate our findings into applied and clinical contexts. Such contexts include object classification in autism, memory in ageing populations, and intrusive memories in post-traumatic stress disorders, and the effects of environmental pollution on cognition. We believe that pooling our various areas of interest and expertise opens exciting new routes to research with a broad impact.
We study these processes using experimental-behavioural work in humans and rodents. We combine our attention and memory tasks with state-of-the art neuroimaging tools. In humans these tools encompass fMRI, EEG, MEG, intracranial recordings with single neuron precision, sleep recordings, and brain stimulation. In rodents we also use pharmacological and cellular approaches. Many group members are experts in the use of advanced time-frequency analyses to study brain oscillations. These rhythmic brain signals can tell us a lot about how the brain communicates and transmits information on a fast time scale. Our other major area of methods expertise is the use of machine learning and representational similarity techniques. These multivariate techniques are particularly useful for tracking the information flow through the human brain when information is either perceived or reactivated from memory.