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Project leader: Dr Thomas Parr, Academic Clinical Fellow

Thomas’ research uses methods from theoretical neurobiology to understand symptoms and signs of neurological disease – particularly cognitive disorders seen in neurodegenerative conditions. This builds upon his previous work using a framework known as Active Inference (Parr et al., 2022) to model disorders of decision-making and movement (Parr & Friston, 2018).

Much of Thomas’ PhD focused upon modelling the contribution of action to visual perception. This involved modelling saccadic sampling patterns, disorders of which one might observe in visual neglect syndromes (Parr & Friston, 2017). He used a combination of functional imaging and eye tracking to test hypotheses about brain connectivity arising from this modelling (Parr et al., 2019).

Ongoing research themes

An ongoing theme of Thomas' work is the interaction between decision-making and the execution of those decisions (Parr et al., 2021). Key to this is the brain’s ability to segment time into a series of events, so that we can select between different sequences of actions. Thomas recently investigated how we might understand arrhythmokinesis, that emerges in Parkinson’s disease during repetitive movements, as a breakdown in the brain’s internal clock (Parr et al., 2025).

A second theme Thomas is interested in is phenotyping of patients in heterogenous diagnostic groups for a personalised understanding of individual patients’ conditions. He is involved in an international collaborative project looking to use this sort of computational phenotyping to answer questions about effortful decision-making (Parr et al., 2023).

Ultimately, Thomas’ research seeks to contribute to our understanding of the pathologies of neuronal computation that underwrite neurological disease.

 

June 2025

computational anatomy

Illustration of the computational anatomy that takes us from decision-making to movement:

Computational anatomy

Spinal and brainstem reflex arcs acting to fulfil descending predictions about the proprioceptive data our brains anticipate receiving from our muscles (in Parr et al., 2025). These predictions, which have spatial and temporal components, depend upon:

  • supratentorial structures (including the cerebral cortex and basal ganglia) that weigh up alternative courses of action, and
  • infratentorial structures (like the cerebellum) that may play a role in estimating the precision with which sensory data are generated.

Many neurological and psychiatric diagnoses have been proposed to follow from mismatches between the way in which our brains model our world and the sensory data we elicit when interacting with it.

 

Image reproduced, unchanged, from Parr et al., 2025, under a Creative Commons CC BY 4.0 license