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UCL NeuroAI
About NeuroAI
The last decade has seen phenomenal advances in the fields of machine learning (e.g. deep learning, reinforcement learning, and AI). While these changes have already had considerable impact on most areas of science they hold a particular resonance for neuroscience.
Crucially, AI shares a common lineage with neuroscience and fundamentally machine learning and the brain employ similar computations to process and compress information. For these reasons AI provides a means to emulate neural functions and the circuits supporting them, providing insights to aid our understanding of the brain and cognition.
Equally, AI tools provide a means to discover, segment, and track distinct neural and behavioural states - yielding more efficient experiments and accelerating the pace of discovery. In turn, this understanding feeds back into the design of more effective AI architectures and models.
Essentially, AI problems posed in neuroscience both require and inspire further advances in AI.
Upcoming Talks:
May 2024 | Katja Hoffman
Talk title: TBC
Speaker: Katja Hoffman, Microsoft Research
Date: Wednesday 1 May 2024
Previous talks
- 2020
July 2020 | Dr Irina Higgins
Talk title: "Unsupervised deep learning identifies semantic disentanglement in single inferotemporal neurons"
Speaker: Dr Irina Higgins, Google Deepmind
Date: Wednesday 15 July 2020September 2020 | Professor Michael Bronstein
Talk title: "Geometric deep learning on graphs and manifolds"
Speaker: Professor Michael Bronstein, Imperial College London
Date: Wednesday 16 September 2020October 2020 | Dr Aldo Faisal
Talk title: "Brains as human-in-the-loop AI systems"
Speaker: Dr Aldo Faisal, Imperial College London
Date: Wednesday 14 October 2020November 2020 | Professor Netta Cohen
Talk title: "The brain map of a worm: A multiscale connectome derived from whole-brain volumetric reconstructions"
Speaker: Professor Netta Cohen, University of Leeds
Date: Wednesday 11 November 2020- 2021
January 2021 | Benigno Uria
Talk title: "The Spatial Memory Pipeline: a deep learning model of egocentric to allocentric understanding in mammalian brains"
Speaker: Benigno Uria, DeepMind
Date: Wednesday 13 January 2021February 2021 | Daniel Yamins
Talk title: "Self-Supervised Learning for Neuroscience and Artificial Intelligence"
Speaker: Daniel Yamins, Stanford University
Date: Wednesday 17 February 2021March 2021 | Kimberly Stachenfeld
Talk title: "Graph Representation Learning and the Hippocampal-Entorhinal Circuit"
Speaker: Kimberly Stachenfeld, DeepMind
Date: Wednesday 17 March 2021June 2021 | Dr Ida Momennejad
Talk title: "Toward Human-like RL"
Speaker: Dr Ida Momennejad, Microsoft Research NYC
Date: Wednesday 9 June 2021July 2021 | Alexander Terenin
Talk title: "Physically Structured Neural Networks for Smooth and Contact Dynamics"
Speaker: Alexander Terenin, Imperial College London
Date: Wednesday 14 July 2021September 2021 | Professor Michael Milford
Talk title: "Spatial and Perceptual Neuroscience Questions a Roboticist Would Love to Have Answered"
Speaker: Professor Michael Milford, Queensland University of Technology
Date: Wednesday 15 September 2021October 2021 | Dr Rebecca Jackson
Talk title: "Reverse-Engineering the Cortical Architecture for Controlled Semantic Cognition"
Speaker: Dr Rebecca Jackson, University of Cambridge
Date: Wednesday 13 October 2021November 2021 | Dr Will de Cothi
Talk title: "Learning predictive maps in the brain for spatial navigation"
Speaker: Dr Will de Cothi, University College London
Date: Wednesday 17 November 2021- 2022
February 2022 | Dr Kelsey Allen
Talk title: "Towards a recipe for physical reasoning in humans and machines"
Speaker: Dr Kelsey Allen, DeepMind
Date: Wednesday 16 February 2022April 2022 | Professor Nathaniel Daw
Talk title: "Tractable, compositional linear approximations to planning in the brain"
Speaker: Nathaniel Daw, Princeton University
Date: Wednesday 20 April 2022June 2022 | Dr Grace Lindsay
Talk title: "Attention in Psychology, Neuroscience, and Machine Learning"
Speaker: Dr Grace Lindsay, New York University
Date: Wednesday 15 June 2022October 2022 | Dr Athena Akrami
Talk title: "Exploiting sensory statistics in decision making"
Speaker: Dr Athena Akrami, Sainsbury Wellcome Centre
Date: Wednesday 12 October 2022November 2022 | Professor Sam Gershman
Talk title: "Amortized inference in mind and brain"
Speaker: Professor Sam Gershman, Harvard University
Date: Wednesday 9 November 2022December 2022 | Dr Jane Wang
Talk title: The power of structured representations (and how to learn them)
Speaker: Dr Jane Wang, DeepMind
Date: Wednesday 14th December 2022- 2023
January 2023 | Dr Carsen Stringer
Talk title: "Making sense of large-scale neural and behavioral data"
Speaker: Dr Carsen Stringer, Howard Hughes Medical Institute Janelia Research Campus
Date: Wednesday 11th January 2023February 2023 | Professor Malcolm MacIver
Talk title: Does terrestriality advantage planning in vertebrates?
Speaker: Professor Malcolm MacIver (Northwestern University)
Date: Wednesday 15th February 2023March 2023 | Professor Jakob Macke
Talk title: " Bridging machine learning and mechanistic modelling"
Speaker: Professor Jakob Macke (University of Tübingen)
Date: Wednesday 15th March 2023June 2023 | Professor Neil Burgees
Talk title: "Understanding our memory system as a generative model"
Speaker: Professor Neil Burgess (UCL)
Date: Wednesday 14th June 2023
Previous annual events
- May 2021
Date: Wednesday 12 May 2021
UCL's Annual NeuroAI event featured speakers working across the spectrum of machine learning and neuroscience. This event fostered further collaboration and discussion.
Speakers: Professor Alexander Mathis (Swiss Federal Institute of Technology, EPFL), Professor Claudia Clopath (Bioengineering Department, Imperial College London), Professor Daniel Alexander (UCL Department of Computer Science), Dr Jennifer Collinger (Department of Physical Medicine and Rehabilitation, University of Pittsburgh)
Full programme available here.
- July 2022
Date: Monday 11 July 2022
UCL's Annual NeuroAI event featured speakers working across the spectrum of machine learning and neuroscience. This event fostered further collaboration and discussion.
Speakers: Professor Peter Latham (Gatsby Computational Neuroscience Unit, UCL), Dr Raia Hadsell (DeepMind), Professor Blake Richards (McGill University), Dr Kim Stachenfeld (DeepMind)
Event programme:
1.00pm – Welcome
1.05pm – 2.35pm – Session one
Kim Stachenfeld (DeepMind) "Predictions and Relations for Biological and Artificial Reasoning"
Peter Latham (UCL) "Why Dale’s law?"
Blake Richards (McGill University) "Contrastive introspection to rapidly identify contingencies in the environment"
2.35pm - 2.55pm – Comfort break
2.55pm – 3.55pm – Session two
Raia Hadsell (DeepMind) "Embodied AGI and The Future of Robotics"
Panel discussion
3.55pm - 4.00pm – Closing remarks
4.00pm - 5.00pm – Drinks reception
- November 2023
Date: Tuesday 28 November 2023
UCL's Annual NeuroAI event was held at the Sainsbury Wellcome Centre and featured speakers working across the spectrum of machine learning and neuroscience. This event fostered further collaboration and discussion.
Speakers: Professor Murray Shanahan (Imperial College London), Dr Maria Eckstein (DeepMind), Dr Ann Duan (Sainsbury Wellcome Centre), Professor Christopher Summerfield (University of Oxford), Professor Ila Fiete (Massachusetts Institute of Technology), Professor Timothy Behrens (University of Oxford), Dr Alexandra Keinath (University of Illinois Chicago).
Avaliable Talks:
Professor Murray Shanahan, Professor in Cognitive Robotics, Imperial College London
Role Play with Large Language Models
Dr Maria Eckstein, Research Scientist, DeepMind
Predictive and Interpretable: Using Classic Cognitive Models and Artificial Neural Networks to Understand Human Learning and Decision Making
Dr Ann Duan, Senior Research Fellow and Group Leader, Sainsbury Wellcome Centre
Mice Dynamically Adapt to Opponents in Multiplayer Games
Professor Christopher Summerfield, Professor of Cognitive Neurosci-ence, University of Oxford
Learning Content and Structure in a Dual-Streams Neural Network
Lightning Talks
Ms Lauren Bennett, PhD student, Cell and Developmental Biology, UCL
Building a Biologically-Plausible Model of Subiculum Activity
Professor Rhodri Cusack, Trinity College Institute of Neuroscience
Human Infants are Learning a Foundation Model
Dr George Dimitriadis, Senior Research Fellow, SWC/Gatsby
Curriculum Learning in Animals and Animats
Mr William Dorrell, PhD student, Gatsby Unit
Actionable Neural Representations: Normative Theories of Neural Internal Models
Mr Tom George, PhD Student, Sainsbury Wellcome Centre
Is the Hippocampus a Helmholtz Machine: Bioplausible Substrates for the Wake-sleep Algorithm and Hippocampal Structure Learning
Dr Marcus Ghosh, Postdoctoral Research Fellow, I-X, Imperial College London
Multimodal Units Fuse-Then-Accumulate Evidence Across Channels
Mr Ed Li, Masters Student, Nuffield Department of Clinical Neurosci-ences, University of Oxford
A Tractable Solution to Imperfect Observation Models: Cut-Posteriors and their Application in Multisensory Integration
Mr Samuel Liebana Garcia, PhD Student, Department of Physiology, Anatomy and Genetics, University of Oxford
Striatal Dopamine Reflects Individual Long-term Learning Trajectories
Dr Kryzystof Potempa, Founder and CEO, BRAINCURES
An LTP-gene Powered Biological Intelligence Approach to De-Risked and Acceler-ated Drug Development
Elizaveta Tennant, PhD Student, Computer Science
Modeling Moral Choices in Social Dilemmas with Multi-Agent Reinforcement Learning