The purpose of our PhD program is to provide people the skills needed to become an independent researcher, whether in academia or in industry. We aim to develop methodological and technical expertise while also exposing students to different ways of thinking about brain science. This foundation then allows them to plan and undertake robust original research on their chosen topic.

The PhD takes an average of four years and starts with a period of classes designed to develop methodological and conceptual rigour. Students then focus on their research projects to build up a set of results that advance knowledge in their chosen area. The results of these experiments are written up as a thesis for appraisal. It is normal for students to also publish several peer-reviewed papers in this period.

We believe that students learn best in a friendly and supportive environment where students can be responsible for their own work. We have the opportunity to welcome people from all over the world and with a wide range of academic backgrounds, helping us build a diverse social and intellectual environment.


Total credits for Graduation: 31 including 22 required and 9 elective credits. Students can take up to 6 elective credits from other PhD programs where approved by their advisor.


Statistics is the science whereby inferences are made about specific random phenomena on the basis of relatively limited sample material. This advanced statistics course will investigate the theory behind statistical inference and then work through techniques such as mixed linear models and neural networks. The aim of this course is to provide a strong theoretical background so that students can apply statistical techniques in a robust and critical manner. The course will be taught through discussion of a series of papers followed by practical exercises where different techniques will be applied.
This course aims at understanding basic mechanisms of biological circadian clocks and their applications. Both neural circuits and molecular mechanisms will be covered, so students can also use these concepts in their respective studies in medicine and other related fields in basic science. We discuss historical background of the circadian rhythmicity in the brain and move on to explore mechanisms of timekeeping in the brain. The neural circuit and molecular mechanism underlying the timekeeping mechanisms can be quite distinct, while both mechanisms can drive timekeeping of circadian clocks. In the two thirds of the course, we will discuss history and detailed theory, covering both experimental evidence and theoretical background. Specific research topics for the final term paper are presented during these classes, and students will then present their research topic. In the latter one third of the course, we will study more deeply about the theories of circadian clocks. The consequence of the network clock mechanisms in the suprachiasmatic nucleus will be discussed through aftereffects and chronotypes. Students submit the term paper on the last day of the class.
The topic “evolution and cognition” triggers questions and answers from various fields of biology and psychology alike. In the most modern form, evolutionary biology, and experimental psychology and neuroscience, together, can best address questions regarding the evolutionary need for cognitive mechanisms and functions of cognition. In this lecture, we cover several higher cognitive functions in a comparable fashion, i.e. across animal species. Organisms are driven by an instinct of survival. Finding, extracting and protecting food are the most fundamental abilities. Mating and forming relationships guarantee the progression of future generations. Social life, technology, traditions and culture build the highest form of cognition in evolution. Still, these capabilities and cognitive functions vary greatly across species. We here explore, why this is, and indirectly, why we humans became human.
The primary goal is to introduce what quantitative techniques are out there that can be used to describe neural systems. We will discuss electrophysiology, intracellular calcium dynamics, signal transduction, and gene expression while showcasing essential mathematical techniques. A neuron is considered the basic computational unit of the brain. This course focuses on the cellular biology of neurons and computational approaches used to study dynamics of them. We go through biological components that make up a neuron and quantitative configurations that enable their functioning. Although we go through necessary computational and physical concepts, the course will be more about neuroscience than computation, and more biological than physical.
In this course, we will review and discuss recent studies showing how the interaction between the brain and visceral organs affects cognition and emotion. First, we will discuss why brain-body interaction could be an important topic in neuroscience, mainly reading conceptual papers. Then, we will investigate brain-heart / brain-lung / brain-stomach interactions, in turn. For each internal organs, we will investigate 1) how to measure physiological signals, 2) how to link such bodily signals to the brain, 3) how such interactions have effect on cognition and emotion. This course will end by students’ talk presenting their reseach idea developed throughout the course.
Our conscious experience presents one of the great remaining mysteries. Why do we have experience and how can it emerge from non-experiencing matter? These questions for a large part of centuries of philosophical debate. More recently, this conceptual analysis has been complimented by experimental work seeking to understand the physical properties of consciousness. The course aims to give a broad foundation in philosophy mind topics that relate to the problem of consciousness. This conceptual background will then be used to critically approach recent scientific research into levels and contents of consciousness.