Complex Dopamine Signalling in a Minimal Neural Network

How nervous systems organise and process signals to generate behaviour is a central question in neuroscience. The human brain consists of over 3 billion neurons which communicate via chemical neurotransmitters that turn partner neurons on or off with fast or slow dynamics. Traditionally it has been thought that complex behaviours arise as the size of the brain and number of neurons increases. However, animals with anatomically small networks, like the nematode worm C. elegans, nevertheless perform complex behaviours such as learning and maze navigation. Work by ourselves and others has uncovered a surprising level of complexity in neurotransmission in the worm nervous system which is achieved through an expanded set of neurotransmitter chemicals operating via a vast array of fast and slow receptors. One consequence is that excitatory ‘on’ and inhibitory ‘off’ signalling may be mediated by the same chemical neurotransmitter and even in the same neuron, a phenomenon not seen in mammalian nervous systems. We hypothesise that this expansion of signalling modalities represents a yet uncharacterised evolutionary strategy to generate complex behaviour. To address this hypothesis, we will focus on the use of dopamine in the C. elegans brain, which like in humans, is only released from a small number of neurons but has wide reaching effects on behaviour. However, unlike humans, worms have both fast and slow dopamine receptors and dopamine can act via both excitatory and inhibitory signalling. Making it a smaller more manageable example of this phenomenon of a physically small but complicated nervous system. First, we will build the first truly functional map of dopamine signalling in the worm brain by mapping the distribution of its receptors. This map will not only contain information about which neurons talk to each other but also whether these connections are excitatory or inhibitory, and if they act on fast or slow timescales. Using this map, we will then generate a computer model of the dopamine nervous system and make predictions of what happens to behaviour when we alter or challenge the system. By harnessing the power of this tiny worm, we can also characterise the behavioural importance of all components of the dopamine system as well as test our computer model predictions by carrying out behavioural analyses. By understanding how the small nervous system of the nematode worm can organise and harness opposing and complex signalling modalities we will be contributing to understanding the rules of life, not just those that govern humans but also those that underpin animals more broadly. We will also expand our knowledge of an important class of proteins that are currently used as major drug targets for anti-parasitic medicines, insecticides and for a range of medical applications including anti-psychotics and anaesthetics, which could pave the way for the development of novel therapies in the future. Discoveries made here will have impacts not only for people interested neuroscience and drug discovery, but this alternative strategy of having fewer neurons but doing more with each one could be a blueprint for designing more computationally efficient AI models. These investigations will address the fundamental question of how neurons manage a range of complex signalling patterns and pave the way for understanding these processes in larger animal brains.