Neurons, Circuits and Networks (NCN) unites researchers working with radically different datasets and at distinct scales of investigation – from cellular signalling networks, to neuronal circuits, to large-scale networks of interacting brain regions. There are many research groups in Cambridge whose work is revolutionising our understanding of Neurons, Circuits and Networks across all scales.
This theme focuses on the structure and function of individual neurons, as well as their organisation into circuits and larger-scale networks of neuronal populations. We aim to understand how neuronal circuits give rise to complex behaviours and cognitive processes both in health and in disease. Ultimately, we believe that a mechanistic understanding of circuit function and dysfunction will help drive innovation both in treatments of brain disease and in biologically inspired artificial intelligence.
A major strength of the Neurons, Circuits and Networks community in Cambridge is that it isn’t siloed, either by scale of investigation – from molecules to whole brains – or by conventional divisions between departments. Instead, we bring together a broad range of researchers from Cambridge-based institutes such as the MRC Laboratory of Molecular Biology and the Wellcome Sanger Institute, as well as many different University departments including Genetics, MRC Cognition and Brain Sciences Unit, Pharmacology, Physiology, Development and Neuroscience, Zoology, Medicine, Clinical Neurosciences, Psychiatry, Psychology, Engineering and Applied Mathematics & Theoretical Physics.
Together we investigate questions such as (i) the molecular mechanisms underpinning the function of individual neurons and synapses, (ii) communication between neurons, glia and other cell types, (iii) computational and algorithmic aspects of how neurons represent and manipulate information, (iv) mechanisms of neural network development, degeneration and regeneration – from axon guidance to plasticity, (v) the neuronal circuits underpinning physiological processes such as circadian rhythms or modulation of fertility hormones, and (vi) the neuronal and network mechanisms underpinning cognitive processes – from vision and navigation to attention, learning, decision-making and reward processing.
Many research groups within the theme also focus on how neural circuits and networks differ in health and disease, and how neuronal function can be manipulated for therapeutic benefit. This includes applications to understanding and better treating chronic pain, addiction, obesity, dementias, mood disorders, and other neuropsychiatric disorders such as schizophrenia.
It makes little sense to study the nervous system in isolation. We therefore work closely with the “Beyond the Neuron” theme to study for example how immune cells and cancer cells interact with the nervous system. Our pioneering research in Neuroimmunology focuses on immune mechanisms and related therapeutics for depression and dementia, while our work in Cancer Neuroscience investigates how cancer cells use neural mechanisms, as well as how cancer arises in the brain. We also leverage a network understanding of the brain to develop methods for better-targeted neurosurgery and management of brain injury.
While some of our work focuses on individual neurons, or even neuronal components, we believe many of the questions above can only be tackled by considering the networked nature of the brain or nervous system. The theme therefore brings together laboratories that generate cutting-edge network data (e.g. mapping out the connectivity of the drosophila central nervous system, high-field brain imaging on humans and animals) as well as labs that develop new theoretical tools and methods to understand and model these networks and how they orchestrate complex behaviours.
Cambridge is also a focal point for network science more generally, since the establishment of the Cambridge Networks Network (CNN) – a forum for academics in Cambridge and beyond interested in network science and its various applications in fields as diverse as genetics, computer science and architecture.
Strikingly, the application of network science to a broad spectrum of real-world systems, in neuroscience and beyond, has revealed that many of them share key organisational features. This implies that many insights gleaned from one specific organism will be generalisable, and that there is much to be gained by working collaboratively on network approaches to different systems in neuroscience.
A key question running through almost every research topic within our theme is how the neurons, circuits and networks we observe developed from conception to their adult organisation. In Cambridge our pioneering work in animal models as well as in human cerebral organoids offers a unique opportunity to study and perturb developmental processes – from axon guidance, to plasticity, to the development of larger-scale circuits such as the cortico-striatal circuitry involved in impulsive or compulsive behaviour. This developmental perspective is not only interesting in its own right, but also offers two key advantages:
(i) it enables us to investigate individual differences in behaviour compared to normative developmental trajectories.
(ii) observing which features of structure and function develop in synchrony is often fundamental to understanding structure-function relationships in brain circuits.
Such developmental insights are facilitated by the availability of large longitudinal datasets in both human and animal imaging within Cambridge and are coordinated within the “Lifelong Brain Development” theme with which we have close connections.
Much of our research points to the idea that brain organisation is best understood in terms of an evolutionary trade-off between cost and function – two driving forces which are also key in the field of engineering. As such our work is closely integrated with the “Brains and Machines” theme. We ask what design principles govern the structure and function of neurons and neural circuits? To what extent have energy costs shaped neurons and brain networks during evolution? And what features of network organisation are likely to confer adaptive advantage? Can we identify network strategies for restoring function in damaged networks or enhancing information processing in healthy networks? These questions have the potential both to revolutionise our understanding of the brain and to drive innovations in neurosurgery, biologically inspired artificial intelligence, and the engineering of bionic systems for healthcare applications.
In order to address such a breadth of scientific questions, our work integrates insights from a range of model systems, including neuronal cultures and cerebral organoids (‘mini-brains’) as well as invertebrate and vertebrate animals (from the C. elegans worm, to fruit flies, lampreys, rodents, and marmosets) and of course non-invasive studies of the human brain.
Our theme also naturally encompasses a range of experimental and theoretical methodologies. Theoretical approaches draw on a range of related fields to understand, model and predict the behaviour of neurons and neuronal circuits. We use methods from statistical physics, dynamical systems, control theory and network science, amongst many others. Experimental approaches include genetic manipulations of individual neurons, single-cell transcriptomics, electrophysiology and calcium imaging in cell cultures or acute brain slices in vitro, multi-unit recordings in behaving animals, imaging of the nervous system at synaptic resolution with electron microscopy, targeted neural and neurochemical brain lesions in animal models, MEG, fMRI and structural neuroimaging techniques in humans and animals in vivo, as well as human psychophysical experiments.
Overall, the theme brings together cutting-edge research on neuronal circuits and networks within the Cambridge neuroscience community, breaking down traditional silos between researchers working at different scales, with different species, in different departments, with experimental versus theoretical approaches, and with a basic neuroscience versus clinical focus. Cambridge is therefore uniquely placed to transform our understanding of circuit function and dysfunction in the brain – because it takes a complex network of researchers to understand the complex network of our nervous system.