The brain is never at rest: the activity state of the brain constantly changes over multiple timescales. Over the last decades, the role of ongoing brain activity in various brain functions has been intensively explored with a variety of experimental and theoretical/computational approaches. However, we still lack an integrative understanding of how global brain states change over multiple timescales, from milliseconds to months or years, and how such state changes affect brain functions, in particular sensory processing. Our research group concerns this fundamental issue in systems neuroscience.
In this PhD project, we will investigate age-related and cell-type-specific changes in neural ensembles in the mouse auditory system. By applying advanced data analytical approaches including deep learning, we will analyse a large amount of neurophysiological data, which has been collected from the mouse central auditory system across age by combining in vivo electrophysiological and optogenetic approaches with pupillometry recording. We will specifically ask (1) how spontaneous population activity changes over multiple timescales in a cell-type-specific fashion, and (2) how stimulus encoding strategies of neural populations change depending on brain states, cell-types, age, and peripheral inputs. This project will provide further insight into state-dependent and cell-type-specific information processing in the brain over multiple timescales.
In this project, data analysis with computer programs (e.g., Python, MATLAB) is an essential component. A successful candidate should have or expect to have an Honours Degree at 2.1 or above (or equivalent) in Computational Neuroscience, Data Science, Computer Science, Statistics or related fields. During their PhD, they will also have an excellent opportunity to learn about state-of-the-art in vivo experimental approaches including Neuropixels-based in vivo electrophysiological, optogenetic and behavioural approaches as well as neurotechnology including the development of microLED-based neural probes.
In the first instance, candidates may send their application to Dr Shuzo Sakata (shuzo.sakata@strath.ac.uk), including a CV and cover letter, detailing their motivation for this particular PhD project and their career goal.
This project is fully funded (Home / EU tuition fees and stipend at RCUK rates) for three years by the University’s SRS Scheme.
Lyngholm D, and Sakata S. (2018).
Cre-dependent optogenetic transgenic mice without early age-related hearing loss. bioRxiv 416164; doi: https://doi.org/10.1101/416164.
Yague JG, Tsunematsu T, and Sakata S. (2017)
Distinct temporal coordination of spontaneous population activity between basal forebrain and auditory cortex. Frontiers in Neural Circuits, 11:64.
Sakata S. (2016)
State-dependent and cell type-specific temporal processing in auditory thalamocortical circuit. Scientific Reports 6:18873.
Kayser C, Wilson C, Saffai H, Sakata S*, Panzeri S*. (2015).
Rhythmic auditory cortex activity at multiple time scales shapes stimulus-response gain and background firing. Journal of Neuroscience 35 (20), 7750-7762.
Sakata S, and Harris KD. (2012).
Laminar-dependent effects of cortical states on auditory cortical spontaneous activity. Frontiers in Neural Circuits 6: 109.
Sakata S, and Harris KD. (2009).
Laminar structure of spontaneous and sensory-evoked population activity in auditory cortex. Neuron 64 (3), 404-418.
For more information and to apply, click here
Dr Shuzo Sakata: shuzo.sakata@strath.ac.uk
