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The 2024 UCL NeuroAI Annual Conference was held on Wednesday 17 July 2024 at the UCL Great Ormond Street Institute of Child Health drawing together machine learning and neuroscience researchers. The conference included talks by speakers from academia and industry, ranging from PhD students to professors, as well as poster sessions for researchers to display and discuss research.
Topics spanned the full scope of NeuroAI from Large Language Models to mouse behaviour and included keynote talks as well as quickfire lightning talks. The conference aimed to inspire attendees by demonstrating the potential of this field for future scientific advancements and novel applications.
Keynote Talks
Dr Rui Ponte Costa
University of Oxford
Back to the present: self-supervised learning in cortical layers
Dr Erin Grant
Gatsby Computational Neuroscience Unit and Sainsbury Wellcome Centre
Nonlinear dynamics of localization in neural receptive fields
Dr Kevin Miller
Google DeepMind, UCL Institute of Ophthalmology and Sainsbury Wellcome Centre
Data-driven discovery of cognitive model
Dr Anthony Zador
Cold Spring Harbor Laboratory
Brain wiring through the genomic bottleneck
Professor Maneesh Sahani
Gatsby Computational Neuroscience Unit, UCL
Neural circuits, distributional representations, and recognition-parametrised learning: principles for building models of the sensory world
Panel discussion
Dr Rui Ponte Costa, Dr Erin Grant, Dr Kevin Miller and Professor Maneesh Sahani
Lightning Talks
Marco Abrate, PhD Student, Cell and Developmental Biology, UCL
An artificial neural network model of cognitive map development
Yang Chu, PhD Student, HiPEDS – EPSRC Centre for Doctoral Training, Imperial College London
Bootstrapping the auditory space map via an innate circuit
Dr Kira Düsterwald, PhD Student, Gatsby Computational Neuroscience Unit, UCL
Unsupervised ground metric learning with tree Wasserstein distance
Dr Marcus Ghosh, AI in Science Postdoctoral Research Fellow, Imperial College London
Non-feedforward architectures enable diverse multisensory computations
Zonglun Li, PhD Student, Mathematics, UCL
When reservoir computing meets information theory: the tendency of entropy change through spike timing-dependent plasticity
Gabriel Ocana Santero, PhD Student, Department of Physiology, Anatomy and Genetics, University of Oxford
Understanding serotonin: gated Deep Neural Networks reveal a unified model across its role in learning, neurodevelopment and psychedelics
Dr Alice Plebe, Research Fellow, Department of Computer Science, UCL
Autonomous vehicles inspired by human brain and cognition
Dilip Rajeswari, Co-founder and CTO, XYZ
Predicting sex using resting-state electroencephalogram and deep learningbased convolutional transformer
Dr Nathan Skene, UK Dementia Research Institute Group Leader, Lecturer and UKRI Future Leaders Fellow, Imperial College London
Predicting cell type-specific epigenomic profiles accounting for distal genetic effects
Dr Michał Wójcik, Research Scientist, Department of Physiology, Anatomy and Genetics, University of Oxford
Learning dynamics in the PFC can be explained by an external controller
Weihao Xia, PhD Student, Department of Statistical Science, UCL
UMBRAE: Unified multimodal brain decoding