Building a Computational Model of Auditory Hallucinations

Psychotic disorders, including schizophrenia and bipolar disorder with psychotic features, are severe mental health conditions that significantly diminish quality of life and place a substantial economic burden on society. In England, the total societal cost of schizophrenia is estimated at £11.8 billion per year, with the public sector bearing approximately £7.2 billion of this cost. People with lived experience of psychosis (PWLEP) may experience a range of symptoms, including positive symptoms such as hallucinations and delusions, negative symptoms such as affective flattening, and cognitive impairments, including difficulties with attention, memory and executive function. Auditory hallucinations, a common and disruptive symptom of psychotic disorders, are typically experienced as hearing voices and occur in approximately 75% of PWLEP. These voices are often intrusive and may be critical, threatening, or commanding, and can be associated with an increased risk of suicide. Whilst antipsychotic treatments, which primarily act through dopamine receptor antagonism, can be effective, they are often associated with significant side effects, and the response to antipsychotic treatment is insufficient in around 40% of patients. There is therefore an urgent need to better understand the mechanisms underlying auditory hallucinations to identify more effective treatment targets and develop novel therapies that act through mechanisms other than dopamine receptor antagonism. A key avenue for understanding auditory hallucinations is examining disruptions in excitatory-inhibitory (E/I) balance, a fundamental mechanism in neural processing. Post-mortem and in vivo electrophysiological studies implicate dysregulated cortical microcircuits in psychosis, where excitatory pyramidal cells (signalling using glutamate) and inhibitory interneurons (signalling using gamma-aminobutyric acid or 'GABA') regulate neural activity. Interactions between these cells generate synchronised neural oscillations across different frequency bands, from low (delta, theta, alpha) to high (beta, gamma) frequencies. These oscillations, which are crucial for coordinating neural activity and supporting cognitive and perceptual function, can also serve as a measure of E/I balance and be assessed in humans using electroencephalography (EEG). Previous studies have shown that resting-state cortical theta and gamma oscillations are increased, whilst beta oscillations and evoked gamma are reduced in people with psychosis, indicating altered E/I balance in the cortex. Dynamic causal modelling (DCM) is a validated computational technique for inferring E/I imbalance in both rodent models and humans, allowing a more precise estimate of E/I balance in the human brain to be obtained. Applying DCM to EEG and functional magnetic resonance imaging (fMRI) paradigms-including resting-state recordings, mismatch negativity (MMN), and the 40-Hz auditory steady-state response (ASSR)-has previously shown that pyramidal neuron disinhibition in the auditory cortex (primary auditory cortex and related regions) was associated with auditory perceptual symptoms, serving as a measure of hallucinations. These findings have been demonstrated in those with chronic psychosis. The investigators now propose to measure E/I early in the presentation of a psychotic disorder to show whether this pathophysiology is related to symptoms demonstrated close to the onset of illness. The aim of this study is to create a computational model of auditory hallucinations using cortical E/I balance in individuals with a psychotic disorder. Primary Objective: The principal research objective is to understand differences in brain signalling, specifically in E/I balance in those with auditory hallucinations using a computational model based on EEG measures such as ASSR relative to healthy volunteers without auditory hallucinations, and whether such measures predict changes in auditory hallucination over time. Secondary Objectives: The secondary research objectives include testing if levels of brain and blood substances and genetics are related to brain E/I balance in those with auditory hallucinations and healthy controls.