The brain is among one of the most complex systems known to man. An understanding of its dynamics and function requires quantitative analysis, and a fusion from multiple disciplines. In Neural Metrics 2.0 we will build on the success from the previous year, focussing on methods for understanding brain networks such as Connectomics, Bayesian modeling and Neural Maps, with world class speakers and a focus on hands-on tutorials and student projects.To mechanistically understand the neuronal substrate of cognition, we need to study the brain as a network where pattern of neural activity is (at least in part) determined by the connectivity within. With many neurological and mental disorders increasingly viewed as the result of a malfunction at the network level, there has been a growing interest in brain networks, which resulted in rapid theoretical and technical developments. We will embrace these developments throughout the course to help us understand the network organisation in the brain. This will be done by examining the theoretical background and by learning the necessary measurement and data analysis techniques used to study brain connectivity.The brain connectivity will be defined at three complementary scale of organization: Micro-scale connectivity involves neuron communication at the cellular and synaptic level; mesa-scale connectivity addresses communication between brain regions; and macro-scale connectivity explores the structure and dynamics of large brain networks. We will strive to include components of electrophysiology, structural connectivity, functional blood flow measures, computational modeling and advanced data analysis at each level. While doing so, we will focus on both the animal and human brain. The course consists of lectures (40%) and computer exercises (40%), supplemented with in-depth problem solving and discussion sessions (20%). You will be encouraged to bring your own experimental data and apply the methods described throughout the course.This course follows our inaugural Neural Metrics course, organised under the auspices of RSS, in 2014, which was attended by 32 students from 3 continents and 14 countries.
Course leaderAss. Prof. B. (Bernard) EnglitzProf. T. (Tansu) Celikel, Professor NeurophysiologyDonders Institute for Brain, Cognition and BehaviourRadboud University
Target groupPhD candidates and postdoctoral researchers in the field of Neuroscience with an MSc in Biology,Computer Science, Psychology, Physics, Al or similar subject.Entry levelPhD Post doc Professional
Course aimAfter this course you are able to;Understand new techniques and approaches in the field of neuroscience networks Understand the basics of new connectivity analysis tools Understand new theories and computational modeling approaches Identify the appropriate research methodology for answering specific research questions on brain connectivity Improve your communication skills and develop research questions in a group setting
Credits info2 ECTS European Credits
Fee infoEUR 600: The course fee includes the registration fee, course materials, access to library and IT facilities, coffee/tea, lunch, and a number of social activities.Possible discounts10% discount for early bird applicants. The early bird deadline is 1 April 2015. 15% discount for students and PhD candidates from Radboud University and partner universities
: P.O Box 9102 Nijmegen
Postal code: 6500 HC
City: Nijmegen
Country: Netherlands
Website: http://www.ru.nl/radboudsummerschool/
E-mail: radboudsummerschool@ru.nl
Phone: +31 (0)24 8187706
