PhD training

NRSN will work to make the best neuroscience PhD courses at all partner universities available to all PhD candidates in Norway. We offer travel- and accommodation grants to participants at PhD courses outside of their home institution. Normally, these travel grants are limited to NOK 2000 for the roundtrip. In the award letter, you will be informed if the hotel accommodation will be provided my NRSN, or if you have to make this arrangements yourself.  More on NRSN reimbursements here

Starting in summer 2015, NRSN aims to host an ambitious summer school programme, in close collaboration with international research groups and invited speakers.


You have to apply to the institution that is offering the course to be accepted as an external participant. Likewise, it is the candidate's own institution which is responsible for the formal approval of the course into the educational component of the PhD degree.

Currently available PhD courses:

Essentials of Neurophysiology: from neurons to circuits to behaviours (5 ECTS)
This course is offered by the University in Oslo and takes place 29 September - 6  October 2014.  The course covers the basic principles of neuron signalling and interactions that underlie brain function. Teaching includes lectures by top researchers in neuroscience, group discussions and demonstrations/lab work. A take-home examination will be given at the end of the course. Application deadline: 1 September 2014.

Integrated Neuroscience (6 ECTS)
This course is organized by the International Graduate School in Integrated Neuroscience (IGSIN) at the University in Bergen, and takes place in Bergen 13 - 23 October 2014. The course is intended to give the students a basic and integrated understanding of the interplay between neurobiological systems and cognition, affect and behaviour. Thirty hours of lectures, demonstrations and/or laboratory work, concentrated over a two week period. Application deadline: 20 September 2014

Computational Neuroscience (10 ECTS)
This course is offered by the Norwegian University of Life Sciences (NMBU) in spring 2015 and will teach how the properties of neurobiological systems can be modelled mathematically, and how to
navigate in the academic literature on computational neuroscience. Teaching will include lectures and assisted exercsies,  organized in 2-3 sessions throughout the semester to facilitate participation by external participants. The timetable and details on how to register for the course will be published later.

Past courses and events:

White Matter Meeeting in Trondheim, 6-7 February 2014
The National Center of Competence for fMRI organized the 1st White Matter Meeting in Trondheim 6-7 February 2014.  19 NRSN members participated and completed an MCQ examination at the end of the meeting (accreditation: 2 ECTS).

PhD course: PSY8005 - Human psychophysiology at NTNU (week 11-12, 2014)
Course content: Event related potentials (ERP's) and time-frequency analyses combined with clustering techniques such as principal and independent component analyses (PCA/ICA) will be taught and practised in the course. High-density EEG recordings are often challenging to analyse. Conventional ERP analysis typically focuses on a small number of channels and identifies differences between trial types in certain time windows. Although this method can be used with high-density data, it does not take full advantage of the spatiotemporal information present in the data. One way of analysing electrical recordings made at the scalp is based on the assumption that EEG signals may be interpreted as a mixture of the activity of a number of underlying sources in the brain. Source separation consists of identifying different sources in the brain, where each source is described in terms of a varying course of activity and a consistent distribution across the scalp. In other words, a statistically independent source can be represented as both a time-invariant scalp-surface map and a time course of the strength of expression of that spatial map in accounting for the overall EEG at that point in time. Further, a blind (unbiased) separation of sources in terms of PCA and ICA will be used allowing us to extract more general stuctures of brain activity.