IHR in Nottingham, PhD in Neuroscience

Neural adaptation – from single neurons to evoked potentials

with Dr Chris Sumner and Dr Katrin Krumbholz
chris@ihr.mrc.ac.uk, katrin@ihr.mrc.ac.uk

IHR commands state-of-the-art techniques in both neurophysiological and non-invasive electrophysiological measurements of brain activity. This project will use these techniques, as well as advanced computational methods for data analysis, to investigate the mechanisms by which neurons in the auditory system adapt to past stimulus input. You will work in close collaboration with one of the neuroimaging groups at IHR.

The brain’s response to a sensory stimulus decreases when the stimulus is repeated, and recovers when the stimulus is changed. This “stimulus-specific” adaptation is thought to underlie our ability to react quickly to change in the sensory environment (change detection; Jääskeläinen et al., 2004) and to process familiar stimuli more efficiently than novel ones (priming). Adaptation to sensory stimulation can be readily measured with non-invasive electrophysiological methods, such as electroencephalography (EEG). However, it has been difficult to relate adaptational effects in these non-invasive measures to the behaviour of single neurons (Ulanovsky et al., 2003). The aim of this project is to gain a better understanding of the mechanism of adaptation at the single-neuron level and to relate the findings to the results from EEG. The project will also give insights into the relationship between the EEG signal and activity at the single-neuron level.

This project is aimed at mathematically adept graduates with a first- or upper second-class degree in the life sciences (such as biology or neuroscience) or in mathematical subjects (including physics and computer science). You will be taught state-of-the-art laboratory methods for recording from neurons in the brain and use advanced computational techniques for data analysis.

Jääskeläinen IP et al. (2004). Human posterior auditory cortex gates novel sounds to consciousness. PNAS USA 101, 6809-6814.

Ulanovsky N et al. (2003). Processing of low-probability sounds by cortical neurons. Nat Neurosci 6, 391-398.