Using Magnetoencephalography to Investigate Aberrant Neural Synchrony in Prodromal Schizophrenia: A Translational Biomarker Approach

Schizophrenia is a common mental disorder which is associated with a range of complaints, including voice-hearing (hallucinations) and strange thoughts (delusions) as well as pronounced impairments in memory and attention. Because these symptoms lead to a breakdown of thought-processes, people who are diagnosed with the disorder often cannot live independently and no effective cure currently exists.

Schizophrenia is typically diagnosed during the transition from puberty to early adulthood, a period critical for social and occupational development. Accordingly, one important goal of current research is to identify individuals who have an elevated risk of developing schizophrenia prior to the full outbreak of the disorder. If possible, this could reduce or even prevent the profound and long-lasting disruptions that occur to people's lives.

One important prerequisite for early intervention are diagnostic techniques which allow reliable prediction of those individuals who may have a particularly high chance of developing the disorder. In the current study, we will use a brain imaging technique, so-called Magnetoencephalograph or MEG, which is a machine that allows the measurement of brain activity with excellent temporal resolution, to develop a novel diagnostic test. In particular, we are interested in finding out whether changes in rhythms of neural activity that the brain generates, so-called "oscillations", may be impaired prior to the outbreak of the disorder and whether those can be useful for predicting the risk of developing schizophrenia.

Brain oscillations have been shown to occur during normal brain functioning and are closely linked to the ability to perceive, memorize and attend to information. Moreover, we know from previous studies that patients with established schizophrenia show prominent impairments in the generation of these oscillations which could be one reason for their cognitive difficulties as well as for their hallucinations and delusions. Thus, it appears that brain oscillations could be a key to understanding the causes of the disorder.

For the proposed project, we will recruit a large sample of individuals from psychiatric services in Edinburgh and Glasgow who show already behavioural and psychological problems and conduct detailed interviews. If their mental state shows certain signs which could be indicative of schizophrenia but do not meet yet the full diagnostic criteria, we will perform a MEG-measurement as well as a magnetic resonance imaging scan. The latter will also allow us to assess the presence of two neurotransmitters in the brain which are important for proper brain functioning.

After the initial brain imaging, we will follow-up these participants for a period of up to two years to assess whether their mental state has changed. If individuals during this period experience a deterioration in their mental health, we will assess them again with an extended interview. In addition to participants at risk for the development of schizophrenia, we will also recruit a group of individuals from the general populations in order to compare their patterns of brain activity with those who may be at-risk for schizophrenia.

Through our research, we hope to find a way of diagnosing schizophrenia with brain imaging techniques earlier which could represent an important step to prevent the occurrence of the profound deficits in behavior and brain functioning. Moreover, through our measurements of brain oscillations and associated neurochemicals, we hope to gain in insight into the underlying causes which could be important for the development of novel therapies.

In this project, we will apply state-of-the-art magnetoencephalography (MEG) towards examining neural synchrony in participants at ultra-high-risk (UHR) for the development of schizophrenia (ScZ) with the aim of establishing a diagnostic index. Specifically, we will recruit 100 participants meeting UHR-criteria over a two year period from psychiatric services in Glasgow and Edinburgh as well as from the data base of the Edinburgh High Risk study. Following the initial assessment of UHR-status, monthly mental-state monitoring for the first six-months will be implemented to detect transition to psychosis. After this period, UHR-subjects will receive monitoring assessments every 3 months up to a total of 2 years.
MEG-activity will be obtained during a visuo-spatial WM-paradigm as well as during a perceptual task which requires participants to detect a sine-wave grating. In addition, resting-state activity will be measured. Time-frequency representations will be estimated at the sensor and source-level. Moreover, time course of oscillatory activity within a specified frequency band will be investigated for source-connectivity based on a Partial Directed Coherence (PDC) approach and cross-frequency coupling.
In addition to MEG-data, we will obtain estimates of GABA and Glutamate levels through proton magnetic resonance spectroscopy (MRS) to examine relationship between neural synchrony and excitatory-inhibition (E/I) balance parameters. MEG, MRS and MRI-measurements will be complimented by detailed psychopathological (CAARMS, SPI-A) and neuropsychological testing.
To develop a diagnostic index, we will employ a multivariate machine learning technique towards the development of a biomarker which compares controls, converted and non-converted UHR-participants. This will be informed by our Information theoretic analysis of the different MEG-parameters as well as the complimentary information from neuropsychology, psychopathology and MRS-data.

Schizophrenia remains one of the most challenging and urgent problems in science and medical research because of the severe disability associated with the disorder and the lack of progress in identifying core pathophysiological mechanisms. One critical factor in potentially improving the outcome of the disorder would be the identification of individuals at high-risk for the development of ScZ, to allow the possibility to intervene prior to the full manifestation of the syndrome.

Recent work in neuroimaging has attempted to develop biomarkers for diagnosis and early detection based on functional and anatomical magnetic resonance imaging (MRI/fMRI). These techniques have an excellent spatial but limited temporal resolution for neural events. This issue may be crucial because normal brain functioning and the associated cognitive processes are fundamentally depended upon fast (millisecond) and transient synchronization of neural oscillations (neural synchrony) which are ideally captured with Electro/Magnetoencephalography (EEG/MEG) approaches.

In the proposed project, we will employ a state-of-the-art MEG approach to investigate neural synchrony in participants at ultra high-risk (UHR) for the development of ScZ with the aim of developing a diagnostic index. In addition, we will employ magnetic resonance spectroscophy (MRS) to establish links between aberrant GABAergic and Glutamategic neurotransmission and neural synchrony parameters in prodromal schizophrenia.

In essence, the impact of this research will be threefold. Firstly, we will gain an unprecedented amount of insight into the contribution of neural synchrony in prodromal schizophrenia through the reconstruction of large-scale oscillatory networks during resting-state and cognitive processes. This will give rise to new explanatory theories and specific models of pathophysiological processes. Secondly, we will develop a diagnostic index based on MEG-data that will allow the early detection of participants with an elevated risk for the development of schizophrenia. Thirdly, we will establish links with core dysfunctions in GABAergic and Glutamatergic neurotransmission through correlations with MRS-data which will be crucial for links with translational research.

The academic community will be reached via its standard ways of dissemination at conferences and in high impact journals aiming not only at researchers of ScZ, but at the wider academic audience interested clinically or generally in neural synchrony and the application of MEG. The wider public will be informed in an appropriate manner via internet, radio, television, and specific publications in outlets aimed at such an audience. Sufferers of ScZ and their relatives will be reached via appropriate organisations and charities by providing information for use on their websites and the offer to give oral presentations to their members. Finally, we will specifically target potential users of our research maximising the chances of immediate impact. Via established networks within the Institute of Neuroscience and Psychology (INP) we will widely disseminate our findings to users in clinics and the pharmaceutical industry using their feedback to identify potential attendees for a dedicated workshop to disseminate our findings in concentrated form and to identify potential synergies for the future.