Your project will entail modelling the dynamics of a network comprising both the inhibitory and excitatory neurones. Understanding the organisational principles
underlying networks in the brain, which appear at different scales – from those involving synapses and gap junctions that connect individual neurones to tracts that link large brain regions – and their potential role in shaping the functional dynamics of the nervous system is one of the most exciting challenges in neuroscience. The human brain is composed of billions of neurones, which are classified as either excitatory or inhibitory. These are connected in intricate arrangements, generating complex collective activity that results from the stimuli they are subject to, as well as, their connection topology. The networks in the brain, in common with those seen in many other complex systems, are seen to have modular organisation. It is a fundamental mezoscopic design principle for networks and is characterised by relatively high density of connections between neurones occurring in the same module and sparse connections between those belonging to different modules. 

While the structural signatures of modular neuronal networks have been studied, little is known about the precise role played by such complex network architecture, e.g., in generating spontaneous, self-sustained network activity. Such persistent activity patterns which are sustained even in the absence of external stimulus, are considered to occur as a result of balancing excitation and inhibition in the network which prevents runaway excitation (due to high excitation) on one hand and quiescence (due to excess inhibition) on the other. Your work will aim at elucidating the dynamic properties of persistent activity arising in networks of neutrons with a certain fraction of inhibitory neurones — the range of the persistent activity observed is considerably enhanced by modular organisation of the connection topology. We expect you —after obtaining required computational and theoretical insights — to provide answers to the fundamental reasons for this observed phenomena. 

You will join the Team dedicated to the discovery of mechanisms, methods and paradigms for the development of computational methods pertaining to making biophysical complexity tractable. By doing your Master of Science/in Engineering project you will contribute to turning scientific vision into tangible solutions for clinicians and patients. You will either engage in fundamental theoretical research with a clear applied facet —or you may prefer to draw from theory in developing methods. Output of your highquality research will be disseminated at A grade conferences and published in peer-reviewed journals. 

If you i) enjoy learning; ii) enjoy science; iii) want to do something meaningful in life, then you are the kind of person we would like to talk to.