Current Research

There remains significant pressure on the NHS and their wait times for an autism diagnosis. This strain has a huge cost on the resources and well-being of those involved. This project aims to provide new methods of diagnostic assistance to tackle these wait times. This initiative uses next-generation tools for testing neurodevelopmental conditions in everyday settings. The project utilizes neuroscience methods, such as functional Near Infrared Spectroscopy (fNIRS) to measure brainwaves, voice analysis, sleep measures, and AI approaches to identify reliable biological and behavioural markers of autism. The central goal is to move diagnostic and monitoring technologies beyond clinical settings to a more affordable, efficient, and inclusive alternative. From analogue to digital! Co-designing this process with autistic community groups, clinicians, and data scientists will help produce tools that are scientifically valid, ethically sound, and genuinely beneficial for both the NHS and wider community. Our outreach for focus groups of autistic people, those awaiting diagnosis, and clinicians involved in the process is still ongoing. If you fall into these categories and wish to get involved, please email me at Robert.harlow@plymouth.ac.uk

This ongoing project aims to investigate how autistic and non-autistic people process and predict the actions of others, and whether knowing the neurotype of the person being observed impacts predictive mechanisms of social perception. We are using electroencephalogram (EEG) recordings to measure brain waves, touch-screen computer responses, and autism questionnaires to explore how social framing and shared neurotype influence perception. This project is still recruiting. If you are interested, please email me at Robert.harlow@plymouth.ac.uk

My PhD - Predictive Perception in Autism

PDF: Here

My thesis investigated how predictive perception, motor coordination, and neurotype differences influence social perception in autism. It explored how these mechanisms contribute to social difficulties faced by autistic people, through the lens of the double empathy problem and second-person neuroscience.

Firstly, I investigated how spoken intentions and visual evidence guide predictive social perception. Across four experiments, results supported a dual-process model whereby top-down expectations shape early perception but are overridden by visual input once motion begins. This led to the ‘kinematic dominance hypothesis’, suggesting motion cues dominate perception once movement begins due to their higher precision in predictive social perception.

Secondly, I used high-resolution active motion capture to analyse autistic motor coordination. Autistic participants showed differences in speed and amplitude of motion during complex tasks when compared to non-autistic participants. These differences correlated with communication and camouflaging traits, suggesting motor differences may influence how autistic actions are interpreted in everyday contexts, with emphasis on differences in movement in achieving task goals, not 'deficits in ability'.

Finally, I tested the double empathy problem through predictive perception and diagnostic framing. Non-autistic participants altered perception when told the actor was autistic, despite identical kinematics. Autistic participants showed stable perception regardless of actor neurotype. These findings bridge predictive perception and the double empathy problem, highlighting that difficulties experienced in autism may stem from environmental and relational factors, including assumptions of autistic behaviour by non-autistic observers, rather than measures of ability.