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  Neuronal coupling across spatiotemporal scales and dimensions of cortical population activity


   School of Psychology and Vision Sciences

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  Dr Michael Okun  No more applications being accepted  Competition Funded PhD Project (Students Worldwide)

About the Project

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 rely on recordings using next-generation high-density silicon probes for data collection (Jun et al., 2017; Lebedeva et al., 2020) and advanced computational methods for their analysis. We are particularly interested in dynamics of cortical neuronal populations on infraslow timescales (tens of seconds and minutes) and under the influence of specific classes of psychoactive drugs (hallucinogens and anaesthetics).

There are several experimental and computational projects available in this research area. Purely computational projects will rely on data we are collecting in the laboratory as part of ongoing projects, as well as on publicly available datasets. Such computational projects are particularly suitable for students with a background in exact sciences or computer science and programming.

Entry requirements:

• Those who have a 1st or a 2.1 undergraduate degree in a relevant field are eligible.

• Evidence of quantitative training is required. For example, AS or A level Maths, IB Standard or Higher Maths, or university level maths/statistics course.

• Those who have a 2.2 and an additional Masters degree in a relevant field may be eligible.

• Those who have a 2.2 and at least three years post-graduate experience in a relevant field may be eligible.

• Those with degrees abroad (perhaps as well as postgraduate experience) may be eligible if their qualifications are deemed equivalent to any of the above

• University English language requirements apply. https://le.ac.uk/study/research-degrees/entry-reqs/eng-lang-reqs/ielts-65

For further information please contact [Email Address Removed]

Application advice:

To apply please refer the application instructions at https://le.ac.uk/study/research-degrees/funded-opportunities/bbsrc-mibtp

You will need to apply for the PhD place and also submit your online application notification to MIBTP. Links for both are on the above web page.

Project / Funding Enquiries: For further information please contact [Email Address Removed]

Application enquiries to [Email Address Removed]

Biological Sciences (4)

Funding Notes

All MIBTP students will be provided with a 4 years studentship.
Tuition Fees at UK fee rates
- a tax free stipend of at least £15,295 p.a (to rise in line with UKRI recommendation)
- a travel allowance in year 1
- a travel / conference budget
- a generous consumables budget
- use of a laptop for the duration of the programme

References

Jun JJ et al. (2017) Fully integrated silicon probes for high-density recording of neural activity. Nature 551:232–236.

Lebedeva A, Steinmetz N, Pachitariu M, Bhagat J, Harris K, Carandini M, Okun M (2020) Recording from the same cortical neurons over months with Neuropixels probes. https://figshare.com/articles/poster/Recording_from_the_same_cortical_neurons_over_months_with_Neuropixels_probes/12591686.
Lewis S (2015) Computational neuroscience: Population coupling. Nat Rev Neurosci 16:313–313.

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