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PhD Studentship: From Relaxation to Cognition: Mapping the Neurophysiology of GABAergic Modulation

University of Exeter - HLS

Qualification Type: PhD
Location: Exeter
Funding for: UK Students
Funding amount: UK tuition fees and an annual tax-free stipend of at least £20780 per year
Hours: Full Time
Placed On: 3rd June 2025
Closes: 8th July 2025
Reference: 5552

The University of Exeter’s Department of Psychology is inviting applications for a PhD studentship funded by GABA Labs and University of Exeter to commence on 22 September 2025 or as soon as possible thereafter. For eligible students the studentship will cover Home or International tuition fees plus an annual tax-free stipend of at least £20,780 for 3.5 years full-time, or pro rata for part-time study. The student would be based in the Washington Singer Building in the Faculty of Health and Life Sciences.

GABA (gamma-aminobutyric acid) is the brain’s principal inhibitory neurotransmitter, playing a vital role in regulating neural excitability, cognition, mood, and social behaviour. Alcohol is well known for its ability to enhance GABAergic function—contributing to its relaxing, anxiolytic and social effects. However, the downsides of alcohol, including sedation, cognitive impairment, and dependency risk, are increasingly motivating the search for safer, more targeted alternatives.

In recent years, there has been growing interest in natural interventions—ranging from botanical extracts to functional drinks—that aim to modulate GABA activity without the risks associated with alcohol. These include novel non-alcoholic beverages like Sentia, developed as sophisticated alternatives designed to engage the brain’s GABA system. Despite widespread curiosity and promising user reports, the effects of such interventions on the brain and behaviour remain poorly understood. This PhD project will explore the neurophysiological and behavioural impact of GABA-enhancing, non-alcoholic interventions. Using high-density electroencephalography (EEG), behavioural tasks, and computational modelling, the student will examine how these interventions influence brain dynamics, cognition, and subjective experience.

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