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Agenda

Speakers

? Duncan Astle

Department of Psychiatry, School of Medicine, University of Cambridge; Cognition and Brain Sciences Unit, Medical Research Council, University of Cambridge

Duncan is the Gnodde Goldman Sachs Professor of Neuroinformatics at the Department of Psychiatry, a Programme Leader at the Medical Research Council’s Cognition and Brain Sciences Unit, and a Fellow of Robinson College. He heads the ‘4D Lab’ (https://www.astlelab.com/). They use a series of analytical tools – sometimes called neuroinformatics – to address crucial clinical and fundamental questions about childhood development and its disorders. Their work has been supported by the Royal Society, the British Academy, the Medical Research Council, the Economic and Social Research Council and various charitable foundations. In recent years Duncan won the Early Career Prize by the British Association of Cognition Neuroscience (2017), the Salvesen Prize (2020), the Vice-Chancellor’s Engagement and Impact Award (2020), and a National Celebrating Neurodiversity Award (2022).

Title: Development, diversity and data science: a transdiagnostic approach to understanding neurodevelopment

Abstract: Macroscopic brain organisation emerges early in life, even prenatally, and continues to change through adolescence and into early adulthood. The emergence and continual refinement of large-scale brain networks, connecting neuronal populations across anatomical distance, allows for increasing functional integration and specialisation. But this gradual process of network emergence is incredibly variable across individuals, and it is not clear why the diversity exists, what consequences it holds for cognition, or what factors might shape it over time. This talk will showcase the application of different AI-inspired computational models to address three crucial challenges that developmental scientists face. Firstly, how do we capture the incredible heterogeneity that exists across childhood and adolescents, and do these differences map to established diagnostic categories? Secondly, can we build developmental models that formalise simple biological principles in order to capture complex developmental phenomena? Thirdly, can we use these models to bridge scales and species to establish fundamental and causal mechanisms that shape development? The take home message? Whilst certain modelling techniques might appear new, in reality they offer us a formal way of addressing some of the most long-standing questions at the heart of developmental science.

? Qiang Luo

Centre for Computational Psychiatry, Institute of Science and Technology for Brain-inspired Intelligence, Fudan University

Qiang Luo, PhD, is a Principal Investigator at ISTBI. He got his PhD on Systems Science in 2010. After his post-doc research in the Shanghai Center for Mathematical Sciences, he has joined Fudan University as a Young Associate Principal Investigator since 2015. He was a Senior Visiting Lecturer at King’s College London for 3 years and had been elected as a Visiting Fellow at Clare Hall, Cambridge in 2018. His research takes a multidisciplinary approach to investigate adolescent brain development, advance the understanding of neuropsychiatric disorders, and design personalized treatments using artificial intelligence. He is the principal investigator of 4 grants from the National Natural Science Foundation of China. He has published papers in top journals in this field, including JAMA Psychiatry, NeuroImage and Neuropsychopharmacology. His research has won the Diversity in Research Award issued by the Human Brain Project of the Europe, and has also been covered by a Spotlight Article in Nature. He has joined the Editorial Board of Psychological Medicine since 2021, and served as an Associated Editor for the Frontiers in Neuroimaging.

Title: Computational behavioural modelling of the stop-signal task and its association with substance use in adolescents

Abstract: The Stop Signal Task (SST) has been used as a definitive assessment for inhibitory control in neuroimaging and neurophysiological research, and has been widely used to detect the deficit of response inhibition in substance users, ADHD patients, etc. In this test, the stop signal reaction time (SSRT), which is used as a measure of response inhibition, can be inferred on the basis of the distribution of reaction times on trials without a stop-signal, and the probability of inhibition. However, the action cancellation in this test seems to have different contributors, especially including processing speed (or attention) and response inhibition. By the computational modelling using two coupled stochastic diffusion processes, we are going to show that SSRT is actually a combination of multiple mechanistic parameters in the model. The preliminary results of the behavioural and neuroimaging characterizations of these model parameters indicate that the response inhibition can be better isolated and assessed by the diffusion rate of the brake process in our model. Furthermore, adolescent smoking seems to be more related to attention while adolescent cannabis use is more related to inhibition.

? Emmanuel Stamatakis

Division of Anaesthesia, School of Medicine, University of Cambridge

Dr Stamatakis leads the Cognition and Consciousness Imaging Group (https://sites.google.com/site/ccigcambridge) in the Division of Anaesthesia, University of Cambridge. His research seeks to determine how cognitive function/dysfunction arises from the topographical organisation and complex dynamics in the brain. His current work focuses on understanding the neural mechanisms underlying a broad spectrum of altered states of awareness/consciousness in healthy volunteers (induced by anaesthetic or psychedelic drugs), and patients who have sustained brain injuries that result in disorders of consciousness (e.g. minimally conscious state). This work is underpinned by fundamental neuroscience questions on the role of the default mode network in complex cognition, as well as broader cognitive architecture questions.  Dr Stamatakis’ recent work was funded by two large collaborative European Research projects (CENTER-TBI and BIOCOG - Framework Programme 7) as well as the Canadian Institute for Advanced Research. The work has been published in high-impact journals such as Nature Neuroscience, Nature Communications, Brain, Lancet Neurology, PNAS, The Neuroscientist, Cerebral Cortex, Communications Biology, Human Brain Mapping, Neuroimage and Journal of Neuroscience.

Title: The neural mechanisms underlying conscious processing