Abhi Banerjee is PI of the Adaptive Decisions Lab and a Professor of Neuroscience at the University of Oxford and Barts and London School of Medicine, UK. His lab is currently working on the flexibility of learning, decision-making and its dysfunctions in neurological disorders. He is also an affiliate at the Institute of Neuroinformatics, ETH-Zürich. Abhi did his undergraduate degree at Presidency College, Calcutta and became interested in Neuroscience while working in Professor Upi Bhalla’s lab at NCBS Bangalore, India. He did his D.Phil. in Physiology at the University of Oxford as a Felix Scholar in the laboratory of Professor Ole Paulsen. Abhi studied spike timing-dependent learning rules and the roles of NMDA receptors in cortical development and plasticity. During his postdoctoral training, Abhi worked as a Simons Foundation Fellow at MIT with Professor Mriganka Sur, focusing on inhibitory mechanisms in cortical plasticity. Furthermore, he investigated cellular and circuit mechanisms of inhibitory dysfunctions in Rett syndrome, a neurodevelopmental disorder in the autism spectrum. He postulated functional mechanistic rescue using recombinant human IGF1, the only drug now approved by the FDA for Rett Syndrome. During his time at MIT, he was also an Instructor at the Department of Biology and a Teaching Fellow in Neurobiology at the Department of Molecular and Cellular Biology, Harvard University. He moved to the University of Zürich as a Marie Skłodowska-Curie Fellow and NARSAD Young Investigator to work with Professor Fritjof Helmchen, where he developed assays to study flexibility of learning and prefrontal-sensory interactions that guide such ability.  

How do we learn new tasks in our everyday life? If you know how to play tennis, what happens when you start playing, say squash, for the first time? How does our brain understand and accommodate new sensorimotor actions (e.g., serve) as well as new ‘rules of the game’ (Merci, Monsieur Renoir)? Understanding how the brain learns a new sensory and cognitive task that allows ‘flexible behaviour’ is a hugely complex challenge. This is partly due to decentralised neural computation in the brain. Learning dynamics shape the properties of microscopic structures in individual neurons and how populations of similar or different types of neurons in different brain areas interact at the mesoscale to influence new learning and decision-making. We are fascinated by such questions.

The research in our Adaptive Decisions Lab entails a combination of parametric behavioural tasks, novel neurotechnology (viral methods, optogenetics, CRISPR), and multi-area imaging methods to reveal the dynamics of micro-and mesoscopic circuits during flexible behaviour. This effort promises substantial new insight into how dysfunction in mechanisms at either spatial scale leads to pathophysiology in autism spectrum disorders. We also merge the field of AI and neuroscience to implement new machine learning algorithms to decipher and better interpret how cognitive variables reorganise during learning. Finally, we are developing analogous cognitive tasks in humans with EEG and fMRI measurements to probe conserved circuit-specific computations in the brain. Dimensional psychiatry is at a crossroads; we need a cross-species neurobiological and computational footing to understand brain disorders.