Monash University

Restricted Access

Reason: Access restricted by the author. A copy can be requested for private research and study by contacting your institution's library service. This copy cannot be republished

Schizophrenia and Electrovestibulography

posted on 2017-01-16, 22:38 authored by Haghgooie, Saman
Schizophrenia is a complex and serious mental illness characterised by the pres-ence of a range of symptoms like psychosis, apathy, social withdrawal, and cognitive symptoms that deteriorate functionality in personal and social life. Schizophrenia affects about 1% of the populations, with similar rates across na-tions, sexes and cultures. A large body of knowledge regarding the pathophysiology of schizophrenia has been accumulated from postmortem, histological, neurochemical, pharmacologi-cal, functional and structural neuroimaging, and genetic studies. However, identifying the underlying neuropathological processes in schizophrenia has been a major challenge in the field. Converging evidence from different studies sug-gests several neurotransmitter systems are clearly involved in pathophysiology of schizophrenia Since the underlying disease processes are predominantly unknown, it is not yet possible to objectively diagnose the disease and measure the severity of its symptoms. Indeed many abnormalities reported in schizophrenia subjects are non-specific in nature and have overlap with the healthy population, therefore, they are not diagnostically useful. There are currently no definitive laboratory tests or biomarkers associated with the core pathology of the disease or definitive diagno-sis. The vestibular system is responsible for maintaining the body balance and pos-ture as well as coordinating head and eye movements. It also provides sense of balance and information on the motion and position of the head in space. The balance information is relayed to neurons in the vestibular nucleus and other in-tegrative neural centres within the central nervous system via the afferent fibres. The vestibular system in-turn receives extensive innervations from cortical, cere-bellar, and other brainstem structures including emotion processing centres. These structures could compromise the vestibular activity performance as seen in anxiety related vestibular dysfunctions (dizziness). Electrovestibulography (EVestG) is a new recording technique which can record signals from vestibular system driven by whole body motions. A Neural Event Extraction Routine (NEER) was used to distinguish vestibular events from noise and produce averaged responses. Different types of biomarkers were extracted from EVestG signals, which presumably reflect the electrical activity of the vesti-bular afferents and central relays. These biomarkers were hypothesised to be helpful as an assistive tool to diagnose and monitor schizophrenia disorder. In order to test such hypothesis, the EVestG biomarkers from twenty one schizo-phrenia patients were compared with twenty healthy subjects with no history of hearing, balance, vestibular, neurological conditions or drug and alcohol depend-ence/abuse. A 60s recording was conducted before, during, and after each motion stimulus. The recordings were divided into different time-segments to study different ves-tibular response profiles including background, steady state, transient,excitatory, and inhibitory vestibular activity. A number of significant diagnostic differences were observed in schizophrenia and healthy population means. Gen-erally speaking, waveform angles were wider and amplitudes were smaller on average in schizophrenia subjects. Biomarkers which related to the time inter-vals between successive vestibular events were statistically more robust in separating patients from healthy subjects. On average, detected vestibular events were spaced further from each other (or had a lower firing frequency) when com-pared with control subjects. Analysing of correlations between interval histogram data suggests that pattern of interval histograms is significantly different be-tween schizophrenia and control subjects. Some significant changes due to interaction effect of diagnosis and time-segment factors were also identified. In other words, some biomarkers such as (waveform angles) were significantly different between groups during stationary time seg-ments whereas others (especially interval biomarkers) were significantly different during dynamic segments. In order to assess reproducibility characteristics of EVestG biomarker, two par-ticipants were repeatedly tested at three different times a day, for three different days. Responses to different vestibular stimuli were recorded and analysed as de-scribed in previous chapters. The reproducibility test results for biomarkers which were significantly different between the two diagnostic groups showed that biomarkers from interval group were most repeatable whereas waveform angle measurements were highly variable across trials. Clinical correlates of the EVestG biomarkers were also investigated and a num-ber of significant correlations were also identified between the EVestG markers and schizophrenia symptoms acquired using positive and negative syndrome scale (PANSS). Another observation was that EVestG biomarkers can be influ-enced by age. Based on these results, we speculate that observed differences in the EVestG biomarkers are mediated by disruptions in emotion processing centres linked with the central or even peripheral parts of the vestibular system. Furthermore, observed variations in recordings might be due to different factors such as human or equipment inconsistencies, fatigue, and/or vestibular adaptation to repetitive stimuli. As discussed in final chapter, once these results are verified in a larger study sample size, the EVestG biomarkers may be used as an assistive tool for diagnosis, monitoring the symptoms of patients, and/or their response to medica-tion/treatment.


Campus location


Principal supervisor

Brian John Lithgow

Year of Award


Department, School or Centre

Monash University. Faculty of Engineering. Department of Electrical and Computer Systems Engineering


Doctor of Philosophy

Degree Type



Faculty of Engineering