How the functional architecture of the working brain is shaped by oscillatory brain activity
08 / 2010 - 08 / 2015
The human brain is composed of multiple regions that need to be flexibly engaged and disengaged depending on the cognitive task performed. A fundamental question in cognitive neuroscience is how the functional architecture of the working brain is shaped. It can only be achieved by fast dynamical processes which do not rely on changes in synaptic connectivity. We propose a new framework in which the functional architecture is determined to a large degree by the inhibition of task-irrelevant regions. Hence the flow of information is directed by blocking regions not required for the task. This leaves the relevant regions to process. Recent findings suggest that disengagement of task-irrelevant regions is achieved by oscillatory neuronal activity in the alpha band (8-13 Hz). Engagement is reflected by gamma activity (30-100 Hz) underlying neuronal processing. We hypothesize that the brain network can be uncovered by studying the alpha/gamma cross-frequency interactions. We will investigate this framework in the context of cognitive experiments on covert attention influencing perception. Importantly, the functional architecture can be set up in anticipation of a given task ? thus we will investigate pre-stimulus as well as post-stimulus brain activity. This will be done using magnetoencephalography (MEG) which allows us to identify and localize oscillatory activity. By further combining electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) we will identify the brain areas controlling the oscillatory brain states. Using transcranial magnetic stimulation (TMS) and neurofeedback we will manipulate the oscillatory brain activity and characterize the causal effects on behavior. Using a brain-computer interface that characterizes the oscillatory brain state online we hope to manipulate perception by presenting information only when the subject is most liable to process it. The main innovation of the project is to provide a new framework for understanding the brain as a network. This will be achieved by studying cross-frequency interactions reflecting functional engagement and disengagement.