Nate Wright

Nate's research aims to combine the latest advancements in machine learning with methods from the comparative science of magic to model how potential networks of information processing and prediction in the brain might result in observable behaviours present in biological organisms.

Unlocking the information pathways of the brain using machine-based modelling (and a little bit of a magic)

UKRI Project Page: Unlocking the information pathways of the brain using machine-based modelling (and a little bit of a magic)

Unlocking the secrets of the brain is often considered one of the grand scientific challenges of our time. One aspect of this challenge is uncovering how the brain processes the vast quantities of sensorimotor information endemic to embodiment to inform cognition and produce appropriate reactions to dynamic environmental conditions (Friston, 2010). Leading theories postulate that significant "shortcuts" are used to facilitate such processing, through which predictions relating to the changing environment are formed using prior experiences and updated through sensorimotor feedback (Friston 2010; Yon and Frith, 2021). It is believed that many neuropsychiatric and neurodevelopmental disorders may result from errors in the formation of these elegant pathways, such as OCD, schizophrenia and dyslexia (Harding et al., 2024; Sterzer et al., 2018; Sigurdardottir et al., 2017). However, such pathways remain a cognitive "black box", limiting potential treatment options.

The comparative psychology and biology of magic have recently offered early insights into the role of embodied information in perceptions and expectations surrounding physical actions performed by dexterous agents, using cognitive illusions as a powerful violation-of-expectation paradigm (Garcia-Pelegrin et al., 2021, 2023, 2024). These investigations have explored cross-species differences in prediction errors relating to manual action expectations in primate species with varying hand morphologies using sleight of hand magic tricks that rely on distinct biomechanical processes. This offers an exciting insight into sensorimotor processing and prediction, with significant scope for further investigation.

Today, we can build more sophisticated machine-learning systems than ever before (Piloto et al., 2022; Gemini Team Google, 2023). These systems have the capacity to act as a test-bed through which to empirically explore the role of sensorimotor representations of environmental information, upon behaviour. Using machine-learning models, we can approximate subunits of biological learning in an artificial context and measure the impact of different information acquisition and transmission pathways on artificial agents' behaviours (e.g., Bell and Lawrence, 2022). As these artificial agents are trainable and modifiable by design, their use presents the opportunity to examine the role of different information streams upon behavioural outputs with a granularity and specificity which is near impossible to achieve in the biological context without extensive invasive neurobiological investigations – for example, lesioning studies to prevent information transfer between brain regions. Subsequently, the proposed methods offer an exciting new avenue through which to shed light on the brain's most mysterious information processing pathways.

By replicating cognitive illusions in artificial agents, we hope to reveal the information-processing systems responsible for their presence in biological agents and, in doing so, begin to map the heuristics that govern biological agents' cognitive processes.

Recent Publications

Farndale Wright, N. R., & Clayton, N. S. (2025). On bodies, brains, and behaviour (and a little bit of magic). Behavioral and Brain Sciences, 48, e97. https://doi.org/10.1017/S0140525X25100666 [Repository version available here: https://doi.org/10.17863/CAM.118146]

Schnell, A. K., Farndale Wright, N. R., & Clayton, N. S. (2023). The inner lives of cephalopods. Integrative and Comparative Biology, 63(6), 1298-1306. https://doi.org/10.1093/icb/icad122

News Articles

DTP Researcher Exploring How Magic Can Illuminate the Brain’s Hidden Processes