MASSIVE Research Stories: Exploring the Patterns of Brain Connectivity
Professor Michael Breakspear, a psychiatrist and researcher, looks for unifying models to fit the complex neurophysiology of the brain and reveal how the brain works in time and space.
Michael’s research covers wide-ranging aspects of brain function and neural connectivity networks - the so-called ‘brain connectome’. Such knowledge could form the basis of a greater understanding of what can go wrong when the networks do not function properly, for example in schizophrenia, bipolar disorder, depression and dementia.
The handling and analysis of the large data sets generated by his research is ‘computationally intensive’, which is where MASSIVE comes in.
Michael’s team designs brain imaging experiments capable of identifying signature patterns of connectivity across the population and how these changes might impact our ‘normal’ brain function. The models used take into account the relationships between brain structure, dynamics and cognitive function.
To validate some of the findings concerning the connectome, Michael and collaborators have shown by functional Magnetic Resonance Imaging (fMRI) that certain areas of the brain differ between depressed and non-depressed people. They conducted fMRI on people who watched movie clips featuring that elicit emotions, for example, footage of a stand-up comedian.
The oxygen level in blood is a marker of metabolic activity and measurement of activity-related oxygen is a powerful tool in brain imaging. Functional MRI detects regions of the brain that ‘light up’ when they become more active due to changes in the proportion of oxygenated to deoxygenated haemoglobin in the local blood vessels. So fMRI can provide information about active neural networks.
While subjects viewed a movie, brain regions involved in higher order functions were shown by fMRI to become synchronised, allowing comparison of the brain function and connectome between different people.
Michael’s finding that the connectome varied between different groups could lead to changes in diagnosis and treatment of brain disorders in the future. Importantly, such imaging could improve our understanding of the complexities of normal brain function.
Professor Michael Breakspear and his team are using MASSIVE to formulate models that take into account the relationships between brain structure, dynamics and cognitive function. van den Heuvel et al. (2011) J. Neuroscience, Harriger et al (2012) PLoS ONE
Among the many interests of Michael and colleagues is the relationship between physical wellbeing and mental health and gaining knowledge of the connectome to explore that relationship.
Normally, sitting people tend to stay seated and moving people tend to keep moving, which is more efficient than randomly switching between the two.
To measure patterns of movements and associated impact on the connectome and brain function, the researchers are collecting data from an ‘accelerometer’ belt that people wear while going about their daily lives.
The resources and know-how of MASSIVE have been enlisted to analyse a vast amount of data against seven different models to find the best fit to the data collected from the belts.
In an unusual approach, the analyses involved applying to humans the type of approach used by physicists to study molecules, atoms and electrons.
Depending on the findings of this first study, Michael envisages adapting the design of the experiments to the use of smart phones instead of accelerometer belts and extending the study groups.
"There are parallels between our behaviour and an atom stuck in an electric field that jumps between low- and high-energy states. Sitting can be viewed as the low-energy state and standing and walking represents the transition to the high-energy state".