We are pioneering a novel mixed method, cross-disciplinary approach at the interface of experiments and computational modelling to explore and generate new insights on the function of neuromodulators in brain computation. Neuromodulators, the master switches of the brain, regulate shifts between behavioural states such as learning and prediction, attention and distraction, exploration and exploitation by controlling the electrical oscillations in neural networks. Neural oscillations, which are thought to reflect behavioural states, are rhythmic or repetitive patterns of activity occurring at different frequencies and can be driven either by mechanisms within individual neurons or by interactions between neurons. Among these, high frequency “gamma” oscillations are directly related to cognitive functions such as attention, learning and memory. 

We are, specifically, interested in studying the role of histamine in learning and memory in the rodent visual cortex. Recent evidence demonstrates that gamma oscillations are associated with an increase in the release of histamine in the hippocampus. The role of histamine in modulating the immune response and inflammation is well known. However, it constitutes an entirely separate neuromodulatory system within the brain, which is thought to govern cognitive functions such as learning and memory, as well as sleep. While the sleep-inducing effects of antihistamines are well known and that altered release of brain histamine marks the onset of seizure-like network activity, its effects on the building blocks of the neocortex and how these collectively shape the emergence of neural oscillations, learning and behaviour are completely unknown. 

The ambition of our research programme, therefore, is to 1) Systematically dissect the multi-scale effects of neuromodulators on the building blocks of the neocortex – cells, synapses, microcircuits to shape neural oscillations leading to learning and behaviour 2) Implement biological organizing principles to develop “neuromodulation-aware” artificial neural networks (ANNs) and predict how the neocortex learns and represents information.