University of Hong Kong Featured PhD Programmes
University of Southampton Featured PhD Programmes
University of Exeter Featured PhD Programmes

The origins of pain perception: Studying the role of somatosensory area p3c connectivity.


Faculty of Health and Life Science

Dr Andrew Marshall , Prof Marcus Kaiser , Dr Simon Keller , Dr J Riddell Friday, January 22, 2021 Competition Funded PhD Project (Students Worldwide)
Liverpool United Kingdom Bioinformatics Biomedical Engineering

About the Project

The symptom of pain results from a complex interaction of segregated brain regions involved in sensory input, mood and behaviour - also called the dynamic pain connectome (DPC). No brain region in isolation signals all dimensions of pain but may be possible to treat pain by identifying and modulating critical nodes within the DPC.

This exciting PhD studentship will focus on the application of in-vivo neuroimaging methods in combination with behavioural assessments and novel non-invasive neuromodulation techniques to determine the significance of a newly identified region of the human brain, area 3c, which is believed to form a critical node in signalling pain. Area 3c, which responds specifically to long duration noxious stimulation, is situated in a localised region of the primary somatosensory cortex. How 3c links in to the wider DPC is not known. However, 3c is thought to have an important antagonistic relationship with brain areas that respond to touch which, a relationship that is disturbed under conditions of chronic pain.

To address these important questions structural and functional connectomes (network matrices) of area 3c will be acquired and computed using diffusion tensor imaging and resting-state functional MRI, including state-of-the-art ultrahigh field 7T imaging. In-vivo models will be used to test whether functional connectivity can be altered dynamically in line with measures of pain perception. Finally, brain stimulation experiments will be used to test hypotheses about the involved circuits.

This highly interdisciplinary project would suit students with a neuroscience, experimental psychology or engineering background. You will have at least a 2.1 in a relevant undergraduate degree programme (e.g. Biological Sciences, Anatomy, Psychology, Computer Science, Engineering). Experience of neuroimaging research in context of a postgraduate degree course is desirable. Full training will be provided in relevant image analysis, network science and modelling. This studentship will be based primarily at the University of Liverpool and will include training visits to both the University of Newcastle and University of Glasgow. For questions about the project, please contact the Primary Supervisor in the first instance.

Informal enquiries may be made to

HOW TO APPLY

Applications should be made by emailing with a CV and a covering letter, including whatever additional information you feel is pertinent to your application; you may wish to indicate, for example, why you are particularly interested in the selected project/s and at the selected University. Applications not meeting these criteria will be rejected. We will also require electronic copies of your degree certificates and transcripts.

In addition to the CV and covering letter, please email a completed copy of the NLD BBSRC DTP Studentship Application Details Form (Word document) to , noting the additional details that are required for your application which are listed in this form. A blank copy of this form can be found at: https://www.nld-dtp.org.uk/how-apply.


Funding Notes

Studentships are funded by the Biotechnology and Biological Sciences Research Council (BBSRC) for 4 years. Funding will cover tuition fees at the UK rate only, a Research Training and Support Grant (RTSG) and stipend. We aim to support the most outstanding applicants from outside the UK and are able to offer a limited number of bursaries that will enable full studentships to be awarded to international applicants. These full studentships will only be awarded to exceptional quality candidates, due to the competitive nature of this scheme.

References

(1) Changing Connectomes: Evolution, Development and Dynamics in Network Neuroscience. MIT Press, 2020.
(2) Predicting the Impact of Electric Field Stimulation in a Detailed Computational Model of Cortical Tissue. Journal of Neural Engineering, in press (arXiv preprint arXiv:2001.10414).
(3) A nociresponsive specific area of human somatosensory cortex within BA3a: BA3c? Neuroimage. 2020 Jul 22;221:117187. doi: 10.1016/j.neuroimage.2020.117187.
(4) Temporal Lobe Epilepsy Surgical Outcomes Can Be Inferred Based on Structural Connectome Hubs: A Machine Learning Study. Ann Neurol. 2020 Aug 22. doi:10.1002/ana.25888.
(5) Computational modelling of the long-term effects of brain stimulation on the local and global structural connectivity of epileptic patients. PLOS ONE 15 (2), e0221380, 2020.
(6) An ultrafast system for signaling mechanical pain in human skin. Sci Adv. 2019 Jul 3;5(7):eaaw1297. doi: 10.1126/sciadv.aaw1297.
(7) Resting-state functional brain networks in adults with a new diagnosis of focal epilepsy. Brain Behav. 2019 Jan;9(1):e01168. doi: 10.1002/brb3.1168.
(8) Within brain area tractography suggests local modularity using high resolution connectomics. Scientific Reports, 7:39859, 2017.
(9) Predicting Surgery Targets in Temporal Lobe Epilepsy through Structural Connectome Based Simulations. PLoS Comput Biol. 2015 Dec 10;11(12):e1004642. doi:10.1371/journal.pcbi.1004642.
(10) Discriminative and affective touch in human experimental tactile allodynia. Neurosci Lett. 2014 Mar 20;563:75-9. doi: 10.1016/j.neulet.2014.01.041.
Search Suggestions

Search Suggestions

Based on your current searches we recommend the following search filters.



FindAPhD. Copyright 2005-2021
All rights reserved.