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Developing Multi-Modal Neuroimaging Biomarkers for the Detection of Early-Stage Psychosis


Project Description

The project will develop new predictive algorithms for mental health outcomes in young people at high-risk for Schizophrenia (ScZ) that will synthesize expertise from cognitive neuroimaging, clinical psychology and data-analytics. This framework will utilize a unique multi-modal neuroimaging data-set that has been collected as part of the MRC-funded Youth Mental Health Risk and Resilience (YouR) study. The YouR-study is the only study worldwide to employ Magnetoencephalography (MEG) in combination with Magnetic Resonance Imaging (MRI) and Magnetic Resonance Spectroscopy (MRS)-data to develop predictors for ScZ in at-risk individuals. Currently, n=150 participants meeting clinical high-risk (CHR) criteria have been comprehensively assessed with a multi-modal imaging battery in combination with follow-up data for up to three years. In addition, n=40 participants with affective disorders and substance abuse (CHR-negative) as well as n=50 controls have been recruited.

The project will employ cutting-edge machine learning techniques to identify multi-modal biomarkers for the prediction of psychosis in CHR-participants and related mental health outcomes. We expect that the resulting predictors for mental health outcomes in at-risk individuals are significantly more powerful than biomarkers from single modalities. Moreover, we expect to identify subgroups of CHR-participants based on multi-modal neuroimaging data that will reveal insights into pathophysiology processes underlying emerging psychosis that will likely be important for the development of novel psychological and pharmacological therapies.

Funding Notes

The scholarship includes:

• Up to 4 years enhanced stipend above Research Council rates, £17,334 for 2019/20.
• Annual consumables allowance of £,3000 to contribute towards the running of the project, student travel and conference attendance.
• Full tuition fee waiver at Home/EU or International rate.

References

Grent-'t-Jong, T. et al., .... Uhlhaas, P.J. Resting-state gamma-band power alterations in schizophrenia reveal E/I-balance abnormalities across illness stages. Elife. pii: e37799. doi: 10.7554/eLife.37799.

Grent-'t-Jong, T., ... Uhlhaas, P.J. Acute Ketamine dysregulates task-related gamma-band oscillations in thalamo-cortical circuits. Brain DOI: 10.1093/brain/awy17.

Uhlhaas, P.J., Singer, W. (2010). Abnormal neural oscillations and synchrony in schizophrenia. Nature Rev Neurosci, 11: 100-114

How good is research at University of Glasgow in Psychology, Psychiatry and Neuroscience?

FTE Category A staff submitted: 34.20

Research output data provided by the Research Excellence Framework (REF)

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