A 3.5-year PhD studentship funded by the MRC is available at the University of Glasgow. The project will examine sensory predictions in MEG-Data in schizophrenia and will be supervised by Dr. Peter Uhlhaas and Joachim Gross.
The financial package will include a 3.5-year stipend, approved University of Glasgow fees, Research Training Support Grant (RTSG) and a conference allowance. An abstract of the project can be found below. Deadline for applicants is the 2nd of May. More information can be found here: http://www.gla.ac.uk/colleges/mvls/graduateschool/researchopportunities/researchopportunities/medicalresearchcouncil/
Applicants will normally be expected to reside (or have residency) within the UK. EU nationals will have to demonstrate that they have spent the three years prior to application resident in the UK (this can include residence whilst undertaking undergraduate study).
For further information please contact: Dr. Peter Uhlhaas peter.uhlhaas@glasgow.ac.uk
Neurophysiology of Dysfunctional Sensory Predictions in Schizophrenia
One core property of brain networks is the ability to predict sensory events and to anticipate the consequences of one’s own actions. Recent evidence suggests that failures in predictive mechanisms may also be fundamentally involved in neuropsychiatric disorders, such as schizophrenia. Specifically, patients with schizophrenia are characterized by a reduced ability to distinguish between self-generated actions and externally generated stimuli that could underlie the development of core symptoms of the disorder, such delusions of control and auditory hallucinations.
The proposed project will examine sensory predictions and its relationship to neural oscillations in schizophrenia through Magnetoencephalography (MEG). MEG is ideally suited to explore this link because of its excellent temporal resolution and previous evidence suggesting that rhythmic activity is related to cognitive dysfunctions in schizophrenia. Specifically, we will investigate the neural signatures underlying the ability to differentiate between self-generated sensory events and externally generated stimuli in the auditory domain. To this end, we will develop a MEG-compatible paradigm to examine sensory predictions in patients with schizophrenia as well as in a group of individuals who are at an elevated risk for developing psychosis to investigate the potential role of predictions failures as a biomarker for early detection and diagnosis.