Nature of intelligence: Bridging animal and artificial intelligence

21 - 22 September 2026 09:00 - 17:00 DoubleTree by Hilton, Bristol Free
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Theo Murphy meeting organised by Dr HaDi MaBouDi, Professor Andrew Barron and Professor Mikko Juusola

Nature of intelligence brings together animal cognition, systems neuroscience, bio-inspired AI and robotics to examine how intelligence emerges in biological systems and how those principles can guide adaptive constructive intelligence. By connecting biologists, neuroscientists, engineers and AI researchers, the meeting will foster interdisciplinary collaboration, identify shared challenges, and accelerate theory, technology and future partnerships across natural and artificial intelligence.

Programme

The programme, including speaker biographies and abstracts, is available below but please note the programme may be subject to change.

Attending this event

Registration update

Please note that the event has reached capacity. All new registrations submitted from this point onwards will be placed on a waiting list. Should places become available, attendees on the waiting list will be offered places in the order their registrations are received.

  • Free to attend and in-person only
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Please note that scientific meetings hosted by the Royal Society do not necessarily represent a Royal Society position or signify an endorsement of the speakers or content presented.

Enquiries: contact the Scientific Programmes team.

Organisers

  • HaDi MaBouDi

    Dr HaDi MaBouDi

    HaDi MaBouDi is an interdisciplinary computational neuroethologist working at the intersection of neuroscience, mathematics, computation, and bio-inspired engineering. His research investigates how compact nervous systems generate robust, flexible and efficient behaviour, with a particular focus on insect vision, decision-making, active sensing and embodied intelligence. Drawing on experience across academic research and the AI and robotics industries, he integrates behavioural experiments and neurophysiology with computational and neuromorphic modelling, machine learning and robotic validation. His work seeks to uncover fundamental principles of neural computation and translate them into more adaptive and autonomous forms of machine intelligence. By bridging mechanistic neuroscience and technological innovation, he advances interdisciplinary research across animal cognition, systems neuroscience and nature-inspired engineering.

  • Mikko Juusola

    Professor Mikko Juusola

    Professor Mikko Juusola is Professor of Systems Neuroscience at the University of Sheffield. He received his MD in General Medicine and PhD in Neurophysiology from the University of Oulu, Finland, in 1993, where he was appointed Docent of Neurophysiology in 1995. His career has included fellowships and research positions at the Universities of Alberta, Dalhousie, Cambridge and Sheffield, including Royal Society University Research Fellow appointments at Cambridge and Sheffield. He was also Visiting Professor and Principal Investigator at the State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, China.

    Professor Juusola studies how animals sense, recall, think and behave, focusing particularly on information processing in the eye and brain circuits of Drosophila. His laboratory combines in vivo electrophysiology, two-photon imaging, genetics, mathematical analysis, biophysical modelling and behavioural studies.

  • Andrew Barron

    Professor Andrew Barron

    Andrew Barron is Director of The Macquarie University Minds and Intelligences Research Centre. Andrew completed his PhD in Zoology at The University of Cambridge in 1999. His lab studies honey bee neurobiology, specialising on understanding the intelligence of bees and how sophisticated social behaviour is possible with such a tiny brain.

Schedule

Chair

Marie-Geneviève Guiraud

Dr Marie-Geneviève Guiraud

Aix-Marseille University, France

09:05-09:30 Title tbc
Professor Josep Call

Professor Josep Call

University of St Andrews, UK

09:30-09:45 Discussion
09:45-10:15 Affective states in invertebrates: Mechanisms, functions, phylogeny and implications for embodied AI

Long regarded as simple reflexive automata, social insects are now recognised as cognitively sophisticated organisms. Although cognitive sophistication does not imply emotional experience, the recognition of social insect intelligence and behavioural flexibility raises a compelling question about whether they express emotional states and to what extent these states are analogous to those of vertebrates. Adopting a functional, multicomponent framework, inferring internal states from synchronised behavioural, physiological, neurochemical, and cognitive changes, provides a robust framework to investigate whether insects possess states functionally analogous to basic emotions without relying on subjective reports. Here, we present multi-scale evidence for fear-like states and affective cognitive biases in social bees. When anticipating aversive events, honeybees exhibit coordinated, negative-valence defensive states characterised by elevated respiration, thoracic heating, altered acoustic buzz, increased thigmotaxis, and elevated brain serotonin and octopamine levels. Beyond defensive reactions, negative emotional states also alter cognitive processing: exposure to simulated predator attacks induces a distinct attentional narrowing in bumblebees, shifting visual processing from global spatial configurations to localised details, a shift driven by dopaminergic signalling. These findings suggest that miniature brains share with vertebrates the fundamental building blocks of affective states, namely valence, persistence, scalability, and global coordination. Furthermore, we bridge these neuroethological insights with artificial intelligence to offer a novel perspective for embodied AI, discussing how affective mechanisms could inform the design of simple, adaptive artificial agents.

Dr Luigi Baciadonna

Dr Luigi Baciadonna

University of Turing, Italy

10:15-10:30 Discussion
10:30-11:00 Break
11:00-11:30 Title tbc
Dr Julia Haas

Dr Julia Haas

Google DeepMind, UK

11:30-11:45 Discussion
11:45-12:15 Corvid cognition in context: Social and ecological drivers of flexible behaviour

In recent decades, corvids, such as crows, ravens, jays, and magpies, have become a key model group in animal cognition research. Their success across a wide range of ecological niches and social contexts has prompted research into the mechanisms and evolutionary pressures underlying their cognitive abilities. Corvids inhabit a vast range of environments, from arid deserts to urban landscapes, and exhibit diverse social structures, from territorial pairs to large, dynamic flocks. This talk synthesizes current findings on corvid cognition, focusing on how socio-ecological factors shape their remarkable learning and problem-solving abilities. Some species, such as New Caledonian crows, use and manufacture tools; others display innovative foraging strategies and exploit anthropogenic food sources. Importantly, corvids exhibit strong executive control, including delay of gratification, allowing them to plan, adapt, and navigate complex challenges. Vocal communication plays a central role in coordinating social interactions. As open-ended vocal learners, corvids can acquire and modify vocalisations throughout life, engage in vocal mimicry, and flexibly adjust their calls according to social and ecological context. These abilities facilitate the maintenance of social relationships, the transmission of information, and the coordination of group activities. In addition to species-level traits, corvids show substantial individual variation in cognitive performance. Studying these differences offers a powerful approach to understanding the evolutionary pressures acting on cognition. Together, these insights position corvids as a crucial comparative model for investigating the evolution of cognition across biological systems.

Dr Claudia Wascher

Dr Claudia Wascher

Anglia Ruskin University, UK

12:15-12:30 Discussion

Chair

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Dr Ali Asgar Bohra

University of Sheffield, UK

13:30-14:00 Synaptic high-frequency jumping

For centuries, from Robert Hooke’s Micrographia to the ideas of Charles Darwin and Sigmund Exner, insect compound eyes have been viewed as fundamentally limited by their fixed, faceted structure, producing a coarse, pixel-like representation of the world. Our new work challenges this long-standing assumption. We show that insect vision is not static, but dynamically shaped by movement: both the animal’s rapid saccadic turns and microscopic movements within the eye itself actively enhance what is seen.

When insects move, their eyes do not simply record images; they actively sample the world in bursts. These rapid shifts, combined with the physics of light detection in thousands of tiny photoreceptive units, generate especially strong and precisely timed signals. At the first synapse in the visual system, this gives rise to a striking effect that we term synaptic high-frequency jumping: the neural signal is reshaped to carry much faster fluctuations than previously thought possible, effectively boosting temporal resolution while minimising delay. In essence, motion transforms the visual system into a high-speed encoder.

This mechanism helps explain how insects achieve hyperacute vision, resolving fine detail far beyond what their eye structure alone would predict, while reacting on millisecond timescales during flight. More broadly, these findings point to a new principle of neural computation: perception emerges from tightly coupled dynamics between behaviour and neural processing. Rather than passively filtering inputs, the brain actively structures them in time, suggesting new ways to think about both biological and artificial vision.

Professor Mikko Juusola

Professor Mikko Juusola

University of Sheffield, UK

14:00-14:15 Discussion
14:15-14:45 Learning about learning through the worm

Understanding how intelligence emerges from biological systems requires linking neural architecture to molecular networks and behaviour. The nematode Caenorhabditis elegans provides a powerful platform to do this: its complete connectome is known, it offers exceptional genetic tractability, and its transparency enables whole-animal, high-resolution optical methods, including optogenetics and calcium imaging. I will describe how these features support studies of behavioural plasticity through three examples.

First, we examined how neuromodulatory signalling interacts with synaptic connectivity to shape behavioural states. Using behaviour tracking, optogenetics, and calcium imaging, we identified a two-step neuropeptide pathway linking mechanosensation to arousal and nociceptor sensitisation, showing how extrasynaptic signals expand circuit function.

Second, we showed that sexually dimorphic behaviours arise by repurposing shared transmitters. Sex-specific expression of the neuropeptide LURY-1 tunes prioritisation between feeding and reproduction in males and hermaphrodite sexes, illustrating state-dependent modulation of behaviour.

Finally, our recent work innovated on a proximity-labelling strategy to map protein-level changes during learning within neurons. Our approach captured conserved signalling pathways alongside novel regulators, supporting the idea that memory emerges from a minimal, evolutionarily conserved molecular network. Our next studies seek to profile these protein-level changes at the level of defined neurons and subcellular localisations.

Together, these studies illustrate how C. elegans enables the interrogation of multiple layers of systems neuroscience within the same model – from molecules to circuits to behaviour – dissecting causality and revealing principles of adaptive intelligence that may be relevant to both biological and artificial systems.

Dr Yee Lian Chew

Dr Yee Lian Chew

Flinders Health and Medical Research Institute, Australia

14:45-15:00 Discussion
15:00-15:30 Break
15:30-16:00 Convergence of Brain-World and Brain-Brain perception

How do abstract ideas interact with neuronal processes? We distinguish two complementary domains of cognition: brain-world (BW), describing the brain's physical interactions with its environment, and brain-brain (BB), describing interactions mediated through socially shared ideas. BW interactions are analog, continuous in time and value, whereas BB interactions operate through digital conventions that enable reliable, though information-limited, communication through categorisation. We propose that cascades of neural loops transform analog BW dynamics into digital BB tokens and vice versa. These reciprocal transformations preserve the distinct identities of the two domains rather than reducing one to the other, providing a new perspective on the mind-brain relationship. The resulting framework views perception as an ongoing interaction between BW and BB. Temporary steady states in BW dynamics become categorised as discrete BB tokens, while BB tokens guide and constrain BW dynamics. Thus, every act of perception continuously integrates physical interactions with socially shared meanings.

Professor Ehud Ahissar

Professor Ehud Ahissar

Weizmann Institute, Israel

16:00-16:15 Discussion
16:15-16:45 Title tbc
16:45-17:00 Discussion
17:00-18:15 Poster session and drinks reception

Chair

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Dr Cara Williamson

Opteran, UK

09:00-09:30 Title tbc
Professor James Marshall

Professor James Marshall

The University of Sheffield, UK

09:30-09:45 Discussion
09:45-10:15 Applications of bioinspired vision sensors

Biological visual systems excel where conventional machine vision struggles: high dynamic range, ultra-low latency, low power consumption, sparse data representation, and robust motion estimation in dynamic environments. Neuromorphic engineering seeks to instantiate these properties directly in silicon, producing event-driven, asynchronous sensors that reflect the computational character of biological neural circuits.

This talk surveys applications built around bioinspired vision sensors developed at the International Centre for Neuromorphic Systems at Western Sydney University and the University of Manchester and commercialised by Optera. Applications span ground and aerial robotics, satellite attitude determination, and space domain awareness.

Professor André van Schaik

Professor André van Schaik

University of Manchester, UK

10:15-10:30 Discussion
10:30-11:00 Break
11:00-11:30 Minimal vision for robotics

Insects such as flies and bees exhibit remarkable flight agility and navigation capabilities despite relying on compact and energy-efficient nervous systems. Advances in neuroethology have revealed how their visual systems enable robust perception and control using surprisingly simple visual cues. Inspired by these mechanisms, we develop bio-inspired vision systems for autonomous robotics based on two fundamental sources of information: optic flow, i.e., the motion of images across the visual field, and visual panorama.

This talk will present several robotic platforms that exploit these principles for navigation and control. We show how aerial robots can estimate and regulate their attitude without accelerometers, relying solely on visual processing inspired by insect vision. We also demonstrate navigation strategies based on learned visual panoramas, allowing robots to follow routes using minimal sensory information. Beyond individual navigation, we also investigate collective behaviours emerging from minimal visual processing.

These results highlight how simple bio-inspired visual principles can lead to robust, efficient, and increasingly scalable solutions for autonomous robots.

Professor Franck Ruffier

Professor Franck Ruffier

Lab-STICC, CNRS, IP Paris, France

11:30-11:45 Discussion
11:45-12:15 Biohybrid robotics for living systems

Biohybrid robotics creates new opportunities for robots to monitor and interact with living systems over extended periods. This talk presents robotic technologies developed for continuous observation and controlled interaction in honeybee colonies. The systems combine imaging, sensing, robotic positioning and automated data collection to operate inside the constrained and dynamic environment of a hive. These developments illustrate how robotic hardware can support the long-term study of and interaction with complex biological systems.

Professor Farshad Arvin

Professor Farshad Arvin

Durham University, UK

12:15-12:30 Discussion

Chair

Dr Nuhu Osman Attah

Dr Nuhu Osman Attah

Australian National University, Australia

13:30-14:00 Title tbc
Professor Aurel Lazar

Professor Aurel Lazar

Columbia University, US

14:00-14:15 Discussion
14:15-14:45 Title tbc
Dr Elisa Donati

Dr Elisa Donati

Institute of Neuroinformatics, Switzerland

14:30-14:45 Discussion
15:00-15:30 Break
15:30-16:00 Reverse engineering insect behaviours

It is hard not to be impressed by the competence of animals compared to state-of-the-art robots in real-world tasks. For example, an individual ant is able to emerge for the first time from her nest into an unknown environment, rapidly learn the surrounding cues, traverse hundreds of metres of rough terrain, identify, manipulate and grasp a suitable food item, and carry it directly back to the nest, which, by the way, she has cooperatively constructed. Compared to current AI approaches, an individual insect has been ‘trained’ (evolved) through millions of instances, over millions of generations, interacting with a dynamic world to satisfy a complex value function. This suggests that reverse engineering insect solutions - which often seem to require minimal computation - might be a valuable shortcut to improve AI systems, particularly for interaction with the world in tasks that should not require language. I will discuss some examples of this approach applied to insect navigation, learning, grasping and manipulation.

Professor Barbara Webb

Professor Barbara Webb

University of Edinburgh, UK

16:00-16:15 Discussion
16:15-17:00 Panel discussion/overview (future directions)