Introduction
Sleep is essential for healthy cognitive development. The last decade has seen a dramatic increase in chronic sleep deprivation among children that amounts to what is now a public health epidemic. Despite the substantial societal impact of sleep deprivation on cognitive neurodevelopmental disorders, we still know very little about the neural mechanisms that promote cognitive development during sleep.
The Boccara lab mission is to address this crucial gap in our knowledge with innovative research projects at the junction of developmental neurobiology, system neuroscience and sleep research. In addition, we use advanced computational methods to analyse how representations are encoded and updated both in the adult and the developing brain
Goal
The masters’ students will have the opportunity to work in a state-of-the-art neuroscience lab in close collaboration with experimental and computational neuroscientists. With the help of the supervisors, you will acquire some theoretical foundations on brain recordings, sleep, animal behaviour and neural data analysis. In particular, you will explore various analytical techniques based on machine learning, dimensionality reduction (PCA, UMAP etc.), hidden Markov models and equation-free modelling. You will then apply these methods to characterize how brain activity changes during developmental sleep.
Projects
We have the following master’s thesis project focused on developing computational tools to study various aspects of developmental sleep
Project 1: Development of Sleep: Maturation of Sleep Stage Transitions
Project 2: Topology of developmental sleep
Project 3: Developmental ripples and cortical cascades
Project 4: Population recruitment during development sleep
Qualifications
Ideal candidates should have basic experience with Python/MATLAB/C++ programming. Prior experience in neuroscience and math is appreciated, but not required.
Interested students should contact Dr. Brijesh Modi (brijesh.modi@ncmm.uio.no) and Dr. Charlotte Boccara (charlotte.boccara@ncmm.uio.no) with their CV.
Internal supervisor from IBV is Marianne Fyhn (marianne.fyhn@ibv.uio.no).