Kavli Institute for Systems Neuroscience

Kavli Institute for Systems Neuroscience (KISN)

Kavli Institute for Systems Neuroscience (KISN) is a leading research centre investigating the emergence of space, time and memory in the brain.

News (karusell)

Our mission

Our mission: To understand the emergence of higher brain functions

KISN

The research centre is since 1996 led by Scientific Directors, Professors and Nobel Laureates May-Britt Moser and Edvard Moser, and since 2018 Managing Director Doctor Kay Gastinger.

The institute is a Kavli Foundation Institute since 2007, a Centre of Excellence (CoE) since 2002, and a department at the Faculty of Medicine and Health Sciences, at Norwegian University of Science and Technology (NTNU) since 2017.

Kavli Institute for Systems Neuroscience (KISN) consists of the centres Centre for Neural Computation (CNC) and Egil and Pauline Braathen and Fred Kavli Centre for Cortical Microcircuits (BKC).

The staff is organized into eight work units: seven research labs with associated team of scientists, students and technicians under the leadership of eight principal investigators, as well as one support group of administration and technical staff.

The department is responsible for an international Master of Science in Neuroscience programme and is connected to the Ph.D. programme in Medicine.

The normal human brain is made up of about 100 billion nerve cells (neurons). Each nerve cell can have an average of approximately 10-20,000 points of contact with other nerve cells. These contact points are called synapses, which is where the storage of memories takes place.

Researchers at the Kavli Institute for Systems Neuroscience explore the brain's functioning by detecting and analysing the electrical signals in the brain, primarily in the regions of the brain called the entorhinal cortex and hippocampus. The hippocamus is an older part of the cerebral cortex and has a central role in the functioning of human and animal memory, while the entorhinal cortex contains grid cells, border cells, direction cells, and speed cells that together give the brain the ability to make highly advanced maps.

Since the centre’s inception, Kavli researchers have used laboratory rats as study animals. In the experiments, rats run around in boxes and corridors chasing treats. Simultaneously, very thin electrodes inserted into their brains enable researchers to detect their brain activity. The electrodes, placed in the space between the brain cells, are so sensitive that they distinguish signals from individual neurons in the network. Today KISN research groups study higher brain functions in rats, mice, zebrafish and humans using experimental and theoretical approaches.

Centre for Neural Computation

Boards

(To be announced)

Kari Melby

Chair
NTNU

Björn Gustafsson

Dean at Faculty of Medicine and Health Sciences, NTNU
Professor

Jan Morten Dyrstad

Associate Professor, Department of Economics, NTNU

Stig Slørdahl

Managing Director, Hospital Trusts in Central Norway

Edvard Moser
Secretary, Professor KI/CNC, NTNU

May-Britt Moser
Secretary, Professor KI/CNC, NTNU

K. G. Jebsen Centre for Alzheimer’s Disease

K. G. Jebsen Centre for
Alzheimer’s Disease

Kavli Communications Hub

The Dimensionality Reduction and Population Dynamics in Neural Data conference were held at Nordita in Stockholm 11-14 February 2020. Most parts of the conference were recorded (see links below).

About the conference

The brain represents and processes information through the activity of many neurons whose firing patterns are correlated with each other in non-trivial ways. These correlations, in general, imply that the activity of a population of neurons involved in a task has a lower dimensional representation. Naturally, then, discovering and understanding such representations are important steps in understanding the operations of the nervous system, and theoretical and experimental neuroscientists have been making interesting progress on this subject. The aim of this conference is to gather together a number of key players in the effort for developing methods for dimensionality reduction in neural data and studying the population dynamics of networks of neurons from this angle. We aim to review the current approaches to the problem, identify the major questions that need to be addressed in the future, and discuss how we should move forward with those questions.