A computational approach to network control in the brain

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The question of how structure relates to function is one of the most rich and enduring themes in neuroscience. The brain is inescapably an intricate and complex network of many interacting components at all levels, from the molecular interactions within the cell, to neurons connected by synapses, to macroscopic regions connected by white matter tracts. Over the past years, ever more detailed maps of these networks have been emerging. Yet, few studies are able to provide quantitative links between structure, function, and behaviour, especially in the human brain. The wiring of the healthy brain must facilitate control: a nervous system is able to continuously control the state of its circuitry, and maintain functional control between its inputs (external stimuli) and outputs (behavioural responses). Mounting evidence, including my own research in C. elegans, is demonstrating the promise of network control to achieve this elusive goal and make experimentally testable predictions. C. elegans, a ~1mm long roundworm, remains one of the only examples of a completely mapped nervous system at the neuronal level. In this network, nodes are neurons which are connected by electrical and chemical synapses. With this proposal, we plan to use tools from network neuroscience and network control theory to develop a truly transdisciplinary description of the structure and function of the C. elegans neuronal network. Our goal is to ascertain a theoretical and algorithmic understanding of how the interactions within a neural system, relying on inputs from multiple sensory systems, achieve and maintain control. Specifically, we seek to understand: (i) How, at the network level, the brain facilitates single behaviours, and whole repertoires of behaviours; (ii) The energetic principles of state transitions in the brain and why specific behaviours are selected in certain circumstances; (iii) How to restore function to a damaged network. These findings will have implications for our understanding of the structure-function mapping in the brain networks of organisms more generally.