Our everyday view of the world is necessarily biased: we focus our attention on information that is most relevant to our current goals, and ignore behaviourally irrelevant information. Without such bias, we would be lost in a world of information-overload, unable to accomplish even the simplest tasks.
Research in the Attention Group explores how the brain controls these biases to streamline processing for adaptive behaviour. In our experiments, we measure and disrupt human brain activity with high temporal and spatial resolution using magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS). Working with our collaborators in Oxford and further afield, we also explore brain activity recorded directly with intracranial electrodes. By exploiting convergent methodologies, we are better able to overcome specific limitations inherent to any single approach.
The results of our research will provide a richer understanding of the fundamental neural mechanisms of attention, and how they influence perception and decision-making. Our research also explores how these perceptual biases shape memory formation, and conversely, how our memories in turn create new bias patterns. Finally, we are also exploring how individuals differ in their ability to focus attention on behaviourally relevant information, and/or suppress distractions. A clearer understanding of how individuals differ in controlling attention will provide a foundation for further research into how cognitive factors could play a role in neuropsychiatric models of depression and anxiety.
Hot off the Press:
Stokes, Kusunoki, Sigala, Nili, Gaffan and Duncan (2013). Dynamic Coding for Cognitive Control in Prefrontal Cortex. Neuron, 78, 364-375 [here]
Also see coverage: Miller Lab (MIT), Neuron Preview; Brain Box Research Briefing; and project page for more information
Kadohisa, Petrov, Stokes, Sigala, Buckley, Gaffan, Kusunoki & Duncan (in press). Dynamic construction of a coherent attentional state in a prefrontal cell population. Neuron