2 Year Postdoctoral Position in multimodal neuroimaging
at Trinity Institute of Neuroscience and the Trinity Centre for Biomedical Engineering
The Neural Engineering Group within the Trinity Centre for Biomedical Engineering and the Trinity College Institute of Neuroscience invites applications for a Post-Doctoral Researcher with specific neuroimaging and machine learning skills and research interest in movement disorders.
Dystonia is a complex and particularly heterogenous movement disorder. It is also a multi-network system disorder involving multiple regions in the brain including the basal ganglia, midbrain, sensory-motor network and cerebellum. Yet despite improvements in individual neuroimaging modalities, such as structural, resting state and functional MRI, it is becoming increasingly clear that in order to improve our understanding of mechanisms in dystonia, a group analytical approach must be utilized which fuses information across modalities. Joint modelling of neuroimaging data may achieve synergistic effects by exploiting the complementary information from individual data sources. The approach of joint modelling involves integrating, formulating and reorganizing data as a hybrid model that is superior to using any one of the three neuroimaging modalities (structural, resting state and functional) alone.
This approach is innovative in dystonia research as it will provide a means of computing between comparisons (patients and relatives) across rich representations of neuroimage data, which will be used to further our understanding of the network dysfunction concept of dystonia – assisting with the development of future diagnostic and treatment tools.
In this study we will employ multimodal analysis (multivoxel pattern analysis) and machine learning to a recently acquired neuroimaging dataset of structural, resting state and functional MRI data from a cohort of 16 cervical dystonia patients and from 32 sex- and age-matched first degree relatives and 16 controls. Temporal Discrimination Threshold (TDT) data is also available for all subjects and provides a means to correlate multimodal imaging with mediational endophenotype for cervical dystonia.
The fellow will also be involved in developing new neuroimaging projects to probe Social Cognition in patients and relatives with cervical dystonia. Neuroimaging facilities at Trinity College Institute of Neuroscience include a state-of-the-art Siemens 3T PRISMA for the fast, precise imaging of the human brain.
The postdoctoral fellow will work in an internationally oriented multidisciplinary research environment at the Clinical Neural Engineering Research Group, consisting of several research clusters and clinical departments at Trinity College Dublin and St Vincent’s University Hospital, Dublin. In this particular project, the fellow is also expected to work closely with our international collaborators with expertise in neuroimaging and dystonia at the Massachusetts Eye and Ear Hospital in Boston. There will be a strong emphasis on writing manuscripts for publication as well as disseminating findings at leading conferences such as the Movement Disorders Society conference and The International Dystonia Symposia.
SPECIFIC AIMS
In this multicentre study, involving centres in Dublin and Boston, the specific aims are:
Probe the network dysfunctionality concept of cervical dystonia by implementing a multivoxel pattern analysis approach on existing structural, resting state and functional neuroimaging data to examine the dysfunctional nodes with greater sensitivity
Evaluate pattern recognition approaches such as early vs. late integration for feature combination from multiple modalities
Investigate ensemble learning for consolidating complementary information from multiple modalities.
Examine the relationship between the resultant multivoxel pattern analysis output with psychophysical TDT values across subjects.
Compare the developed multivoxel pattern analysis approach based on data from a cervical dystonia cohort with data from a spasmodic dystonia cohort.
QUALIFICATIONS
A PhD in neuroimaging or equivalent is required. The candidate must have demonstrated strong skills in one or more areas of neuroimaging and/or other forms of advanced data analysis. In the assessment of the candidates, the following qualifications will be emphasised:
Previous experience with advanced analytic methods as applied to neuroimaging data (e.g. multivariate approaches, dynamic causal modelling, machine learning, graph theory etc.).
Documented skills in programming (e.g. Matlab, Python, shell scripting etc.)
Strong theoretical and conceptual knowledge within clinical and/or cognitive neuroscience
Documented skills in writing manuscripts, and a strong publication track record within the relevant field.
Excellent collaboration skills, showing flexibility and motivation to contribute to a good work environment.
The candidate must have journal publications in the field of neuroimaging and data analysis.
APPLICATION PROCESS
Applications should include a publication list, a motivation letter (max. two pages), names and contact details of two referees and a CV with information on education and previous research experience in the analysis of neuroimaging data. This information should be submitted by email to Professor Richard Reilly at reillyri@tcd.ie
Information about the group and the research project can be found at:
Details and extra information can be obtained from
Professor Richard Reilly email: reillyri@tcd.ie
Professor of Neural Engineering
School of Medicine
and School of Engineering
Trinity College Dublin
The University of Dublin
Dublin 2, Republic of Ireland
https://reillylab.net/richard-reilly
Further Information
Clinical Neural Engineering Lab http://reillylab.net/
The focus of the lab is on clinical neural engineering based on signal processing of neuroimaging and physiological data for specific clinical problems.
Objectives:
-Harvest information from signals acquired from excitable tissue.
-Development of quantitative methods to understand neurological function.
-Development of new analytical, neurophysiological and neuroimaging methods which allow outcomes of interventions to be more accurately predicted.
Our research is in collaboration with clinical colleagues in neurology, neurophysiology, psychiatry, otolaryngology, gerontology and respiratory medicine. The Reilly Lab is a constituent laboratory of the Trinity Centre of Biomedical Engineering and the Trinity Institute of Neuroscience at Trinity College, The University of Dublin.
Irish Dystonia Research Group
The Irish Dystonia Research Group is leading dystonia research in Ireland. As the national representative organisation for dystonia, Dystonia Ireland, has a strong collaborative relationship with the Irish Dystonia Research Group, and a keen interest in their research findings. Extensive research into dystonia is also ongoing worldwide.
The Irish Dystonia Research Group is focused on uncovering the cause, or causes, of adult-onset dystonia and increasing our understanding of this disorder. This multidisciplinary team comprises neurologists from the Department of Neurology, St Vincent’s University Hospital, and engineers and scientists from the Neural Engineering Laboratory, Trinity College Dublin (with additional national and international collaborators).
For information about the ongoing dystonia research projects please visit the Irish Dystonia Research Group website: http://www.dystoniaresearch.ie/