The Adaptive Brain Computation (ABC) theme brings together a diverse group of scientists from across the University with shared interests in decoding how the brain senses, accumulates, maps, and combines present and past information to enable organisms adaptively to operate in their environments. This is a cross cutting theme with relevance for how the brain represents and computes information at different stages of development, instantiates social cognition, and in coordinating reflexive and higher-order behaviours, all of which depend fundamentally on neural circuits and networks, including neuronal-glial interactions. Moreover, elucidating how the brain captures and integrates information is imperative as a starting point to gain a richer mechanistic understanding of the biological and environmental pressures that extend the brain beyond its normal operating limits, ultimately to cause the outward expression of brain disorders such as autism spectrum disorder, schizophrenia, depression, ADHD, OCD, and addiction.
Research in this theme aims to elucidate the brain mechanisms that mediate neuronal plasticity and adaptive behaviour across species and scales. It works towards building a mechanistic understanding of how the brain senses, accumulates, maps, and combines present and past information about the external and internal environments, and uses them for decision-making, learning, and memory. It seeks to characterise the processes giving rise to flexible responses that adapt to changing environments and shifting goals, while maintaining operational stability and overall homeostasis. It also wishes to understand the principles and mechanisms by which evolution moulds brain circuits adaptively to distinct ecological niches and behavioural needs.
Adaptive Brain Computation researchers belong to more than 10 different department and institutes, including the Departments of Psychology, Psychiatry, Engineering, Physiology, Development and Neuroscience, Medicine, the MRC Laboratory of Molecular Biology and the MRC Cognition and Brain Sciences Unit. We work on theory and computation as well as experimental approaches, and aim to cover the full range of scales in neuroscience, from molecules to neurons and networks, to systems, to whole organism and behaviour.
Work in this theme strongly integrates with the “Neurons, Circuits and Networks” and “Brain and Machines” themes, creating further strong synergies between the Schools of Biological Sciences, Clinical Medicine, Physical Sciences, and Technology.
Key priorities include (i) integrating levels of analysis and technologies, (ii) triangulating inference between complementary methodologies, (iii) boosting collaborations and skill-sharing while reducing the administrative burdens, and (iv) increasing the quality of data storage and animal facilities.
Research at the molecular and cellular level aims to uncover the mechanisms of neuronal plasticity which underpin adaptation and learning. Plasticity can recruit epigenetic, biochemical, structural, electrophysiological effectors to modulate form and function of sensory receptors, synapses, and overall neurons. Researchers focus on a huge variety of brain areas, and use multi-method experimental approaches ranging from single cell sequencing to intracellular recordings to understand how neurons respond to altered sensory stimuli from the environment, as well as to different internal states, in order to support change and learning, or stability and homeostasis. Moreover, they investigate how such plasticity can be maladaptive and eventually lead to neuronal dysfunction or death, and/or circuit imbalances between inhibition and excitation which lead to a variety of disorders.
Examples of research in these field include work on hippocampal and cortical synaptic plasticity in rodents and its malfunctioning in Alzheimer’s disease and neurodevelopmental disorders; developmental plasticity and synaptic competition in Drosophila; and linking genes and environmental factors impacting hypothalamic neurons to obesity.
Research at the systems behavioural and computational level seeks to understand the neural and cognitive functions that support the brain’s ability to accumulate, map, and combine present and past information for adaptive decision-making, learning, and memory. Work aims to characterise how this information is embodied in neural activity, how these neural responses adapt to varying internal and external challenges, and they are shaped by evolution to ecological niches and behavioural needs. Work in this theme draws on a huge range of techniques from in vivo electrophysiology with awake behaving animals through a suite of invasive and non-invasive forms of neuroimaging in humans. It targets explanations that scale from understanding the response of single regions to large-scale networks, and from the dynamic responses of neurons over milliseconds to learning that takes place over months or years. It combines approaches from experimental psychology, behaviour, psychophysics, pharmacology, neuro-stimulation, neuroimaging, and computational modelling.
Examples include work on the basis for flexible control of selective attention in the human brain , computational, algorithmic/representational and neurobiological instantiation of learning and memory; genetic, neurodevelopmental and neurobiological bases of individual differences in behaviour including in drug abuse and addiction and in psychiatric disorders such as schizophrenia, ADHD and OCD; how perceptual organization, learning and attention alter the way in which visual stimuli are processed in different brain areas; human intelligence, cognitive control, action selection and selective attention, from behavioural to cellular levels; neuronal plasticity during adulthood and development; using computational models, pharmacology and brain imaging to understand how humans build adaptive expectations about the world around us; how the dynamics of sensory and motor cortices support complex computations such as movement generation; long term memory and its disorders; the structure-function relationship in brain networks in health and disease; the nature of neural representations and computations in goal-directed behaviour; the role of learning in translating sensory experience into complex decisions and adaptive behaviours; corticostriate plasticity processes underlying addiction; and the neurochemical, molecular and intracellular basis of memory reconsolidation.