Hellgren Kotaleski Laboratory
The main focus of Professor Jeanette Hellgren Kotaleski’s research is to use mathematical modeling to understand the neural mechanisms underlying information processing, rhythm generation and learning in motor systems. Of specific interest are the basal ganglia, a structure in the brain that is important for the selection and initiation of motor (and cognitive) actions. The levels of investigation using computational models range from simulations of large-scale neural networks, using both biophysically detailed as well as abstract systems level models, down to kinetic models of subcellular processes (e.g. dopamine-induced cascades). The latter approach is important for understanding mechanisms involved in e.g. synaptic plasticity and learning.
Besides leading a research group at KTH, J. Hellgren Kotaleski is affiliated with Department of Neuroscience at Karolinska Institute (KI). A longstanding collaborative effort between the computational biology group at KTH and the Department of Neuroscience at KI has been ongoing for many years, and the goal is to understand the mechanisms for generation and coordination of activity in the spinal cord of vertebrates. Here the lamprey, which is an evolutionary old vertebrate, is used as a model system.
Hellgren Kotaleski is furthermore linked with the International Neuroinformatics Coordinating Facility (INCF), and is presently the leader of the Swedish National INCF node. As a result of activities ongoing among the INCF member countries, she is now also coordinator of an international Erasmus Mundus PhD program in Neuroinformatics (www.kth.se/eurospin).
Illustration of multi-scale modelling approaches used to understand information processing and learning in the basal ganglia.
Gating of steering signals through phasic modulation of reticulospinal neurons during locomotion.
Proc. Natl. Acad. Sci. U.S.A. 2014 Mar;111(9):3591-6
Bo Bekkouche -Research assistant
Jeanette Hellgren Kotaleski - Senior researcher
Kai Du - PhD student
Robert Lindroos - PhD student, R&D trainee