Information flow, integration and complexity in neural dynamics

Perception, cognition and ultimately consciousness arise from the complex interaction of multiple brain regions processing and integrating distinct information. Therefore, understanding the neural basis of mind and consciousness requires the development of measures of information flow, integration and complexity that can be applied to brain imaging datasets. In this project, novel measures and analysis pipelines will be developed and applied to electroencephalographic (EEG), magnetoencephalographic (MEG), and/or functional magnetic resonance imaging (fMRI) data. These data will encapsulate manipulations of both conscious level and conscious content. For conscious level, recordings will come from sleep and anaesthesia as well as pharmacological manipulations (including psychedelic states). For conscious content, participants will encounter a range of visual stimuli, including white noise, stroboscopic lighting, naturalistic movies, and masking paradigms with subliminal content. The overall objective is to link theory to application in the quantitative characterization of the neural dynamics underlying conscious states. The project will suit highly motivated students with a strong technical background, preferably also with experience in cognitive neuroscience.

This project is offered as part of the 2017 Sackler Centre for Consciousness Science Ph.D. programme, for which two funded scholarships are available across a range of projects. Founded in 2010, the Sackler Centre is an internationally leading research group in the area of consciousness science. Researchers across three schools (Psychology, Informatics and Engineering, Brighton and Sussex Medical School) work together to unravel the biological basis of conscious experience, and to develop new approaches to clinical diagnosis and intervention in a wide range of psychiatric and neurological disorders. For more information about the Centre see www.sussex.ac.uk/sackler, and follow the links for information about the 2017 Ph.D. programme.

Application web page

University’s application page: http://www.sussex.ac.uk/study/apply/

Department of Informatics: http://www.sussex.ac.uk/informatics/pgstudy/doctoral/applying

Sackler Centre: http://www.sussex.ac.uk/sackler/research/postgraduatestudy/sackler2017phds

Eligibility requirements for potential candidates:
This award will only pay fees at the Home/EU rate. Candidates may not be eligible for the full award if they do not meet UK residency requirements.
For full details of eligibility, please check the ESRC guidelines:

http://www.esrc.ac.uk/skills-and-careers/studentships/prospective-students/am-i-eligible-for-an-esrc-studentship/

Candidates must have, or expect to obtain, a First or a high Upper Second Class Honours undergraduate degree, or equivalent qualification, and/or a Master’s degree in a related discipline.

Guidance for applicants

To apply, candidates should make an application via the university’s online application system: http://www.sussex.ac.uk/study/apply/. Please see http://www.sussex.ac.uk/sackler/research/postgraduatestudy/sackler2017phds for more information about the application process.

Shortlisted candidates will be invited to interview, likely in February 2017.