Matter of context: Revealing the circuit architecture of internal brain state influence on behaviour

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My aim is to understand how ongoing internal activity patterns within the brain shape the way it processes information and controls behaviour. Human and animal behaviour is not merely a set of 'automatic' reflexes. Rather, the way we respond to sensory inputs such as the sight of food or the sound of a phone ringing depends on multiple contextual factors such as emotional state, time of day and how satiated or alert we are. Modern neuroscience has made important progress towards understanding the brain systems that report these factors. For instance, the dopaminergic and serotonergic systems that signal reward have been extensively studied due to their importance in shaping normal behaviour as well as psychiatric disorders. However, major challenges remain in terms of understanding how multiple brain pathways act together to modulate sensory processing and behaviour. To a large extent this is due to the size and complexity of the brain which precludes simultaneous measurement of the many brain cells involved. By establishing a new research programme in the Department of Neuroscience, Physiology & Pharmacology at UCL, I plan to take a novel approach to tackle this problem. My strategy combines state-of-the-art imaging in an experimentally advantageous model organism - the larval zebrafish - with data-driven biology and computational modelling: key research avenues identified by the BBSRC.Zebrafish larvae are particularly well suited for simultaneously tracking activity in multiple brain structures. This tiny animal (3.5 mm long) is almost perfectly transparent, allowing its small brain to be monitored non-invasively using fluorescent microscopy while the fish performs a range of recognizable behaviours such as hunting and avoidance. Importantly, many of these behaviours are influenced by contextual factors such as hunger or alertness, by virtue of brain circuits fish share with all other vertebrates, including humans. To study how distributed brain networks work together to shape behaviour, I will use cutting-edge "light-sheet microscopy" to individually track the activity of each of the zebrafish's 80,000 neurons. While doing so, I will alter environmental factors to manipulate satiety, alertness and other contextual elements. Deciphering the resulting dataset will be a complex endeavour, comparable to extracting insights into market dynamics by simultaneously listening to each and every one of the 100,000 finance employees in the City of London. The potential for valuable insights is enormous, but so is the challenge in making sense of the massive amount of data and finding the most informative sources. To meet this challenge, I will use recurrent neural networks - a modern machine-learning algorithm akin to the one that powers automated speech recognition. It will enable me to identify neurons that can predict if the animal is likely to respond to a specific visual cue, even before the stimulus is presented. Such cells are good candidates for signalling contextual information and my computational modelling will resolve how they work together to collectively influence behaviour. To test my hypotheses, I will use advanced "optogenetic methods" to directly control brain activity using light and examine the resulting effects on activity elsewhere in the brain and on the behaviour of the fish.Ultimately, these findings will shed new light on how neural activity related to context and experience combine to influence fundamental brain function. Because all vertebrates possess the same basic brain plan, my experimental findings are likely to reveal principles that apply to many species, including humans. Thus, in line with the BBSRC's priority of supporting world-class basic bioscience for health, this project will provide a major advance in our understanding of how the healthy brain produces behaviour. In the longer term, this could underpin greater understanding of how brain function is disrupted during disease.