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Neuronal coupling across spatiotemporal scales and dimensions of cortical population activity

  • Full or part time
  • Application Deadline
    Sunday, January 12, 2020
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

About This PhD Project

Project Description

The human cortex is the most complex known system. It is responsible for a vast range of sensorimotor, decision making, and other cognitive abilities of humans and other mammals. The activity of cortical neuronal networks is organised across multiple spatiotemporal scales, and remains poorly understood. Our laboratory is particularly interested in the relationship between the activity of an individual neuron and of the larger networks within which the neuron is embedded (Lewis, 2015). For example, we have recently compared the coupling between neurons and their local network across an extensive range of timescales, finding major timescale-dependent distinctions, suggestive of different mechanisms regulating cortical activity on different timescales (Okun et al., 2019).

We use recordings using next-generation high-density silicon probes for data collection (Jun et al., 2017) and advanced computational methods for their analysis. There are several computational projects available in the above research area, relying on data we are collecting in the laboratory as part of ongoing projects, as well as on publicly available datasets. The projects are suitable for students with a background in exact sciences or computer science and programming.

UK/EU applicants only.

Entry requirements:
Applicants are required to hold/or expect to obtain a UK Bachelor Degree 2:1 or better in a relevant subject.
The University of Leicester English language requirements apply where applicable:

How to apply:
Please refer carefully to the application guidance and apply using the online application link at

Project / Funding Enquiries:
Application enquiries to
Closing date for applications: Sunday 12th January 2020


Jun, J.J., Steinmetz, N.A., Siegle, J.H., Denman, D.J., Bauza, M., Barbarits, B., Lee, A.K., Anastassiou, C.A., Andrei, A., Aydın, Ç., et al. (2017). Fully integrated silicon probes for high-density recording of neural activity. Nature 551, 232–236.

Lewis, S. (2015). Computational neuroscience: Population coupling. Nat Rev Neurosci 16, 313–313.

Okun, M., Steinmetz, N.A., Lak, A., Dervinis, M., and Harris, K.D. (2019). Distinct Structure of Cortical Population Activity on Fast and Infraslow Timescales. Cereb Cortex 29, 2196–2210.

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