Neural oscillations are a key feature of brain activity and have been studied extensively in the context of cognitive functions and sensorimotor processing. However, recent studies have highlighted that oscillations in the brain are often transient in nature, consisting only of a few oscillation cycles (Fig. 1), rather than being sustained throughout performing a cognitive task [1-3]. Such transient oscillations have been observed in a variety of oscillation frequencies, including the theta, beta, and gamma bands, as well as in different cortical and subcortical brain regions for a range of cognitive tasks and species. In this project you will analyse oscillations recorded in the local field potential of mice performing a decision-making task (using open neural data from the International Brain Laboratory ). This big data set offers a unique opportunity to study oscillations in all brain regions. You will characterize the transient nature of these oscillations using e.g. lagged coherence analysis [2,5] or Hidden Markov models. Furthermore, you will examine how these oscillations relate to cognitive and motor processes in the decision-making task. The results of this project are important to better understand how transient oscillations contribute to information processing in the brain and affect behaviour.
Prerequisites: Python programming, completed courses related to neuroscience
 Fransen, A. M., van Ede, F., & Maris, E. (2015). Identifying neuronal oscillations using rhythmicity. Neuroimage, 118, 256-267.
Fig. 1: Example illustration of transient oscillations in the brain (image courtesy by V. Muralidharan)