Computational Neuroscience Summer School, University of Ottawa

The first Canadian Summer School in Computational Neuroscience, which will be held from Sunday June 17, 2007 until Friday June 29, 2007 inclusively.
It is organized by the Center for Neural Dynamics and Computation at the University of Ottawa. The course is directed at graduate students and postdoctoral fellows from the physical sciences (e.g. physics, applied mathematics, engineering, computer science) and the life sciences (e.g. neuroscience, biology, physiology, human kinetics) who wish to develop their skills in neural data analysis and in mathematical modeling of neural activity. The topics will range from cellular to systems neuroscience, with a focus on sensory and motor systems.

The course will consist of 3 hours of lectures in the mornings, followed by 3-hour MATLAB-based computer laboratories in the afternoons. Participants will pair up for these laboratories, and an effort will be made to pair someone from the life sciences with someone from the physical sciences. All classes and laboratories will be held on the main downtown campus of the University of Ottawa (Biosciences Complex). The School will be held in English, although many of the lecturers also speak French. The course can be taken for credit, since it is a University of Ottawa three-credit graduate course (NSC8104). The mark will be based on work done in the computer laboratories and a short project. The first day of the school (Sunday June 17th) will be a mathematics refresher open to all participants, which will include some introduction to differential equations.
Enrollment in the course will be limited to 40 participants.
The summer school ends just before Canada Day (July 1st), and a week before the beginning of the Computational Neuroscience Meeting (www.cnsorg.org) which will be held next year in Toronto from July 8-12, 2007. Please contact the local organizer, F.Skinner (fskinner@uhnres.utoronto.ca) for further information and/or if you are interested in organizing a workshop associated with this conference.
MATH PRE-REQUISITES: Calculus I and II, first-year university level Linear Algebra and Probability and Statistics.
LIFE SCIENCES PRE-REQUISITES: first-year university level life science courses for students in the physical sciences.
FACULTY
Prof. Ramesh Balasubramaniam, School of Human Kinetics, University of Ottawa
Prof. Maurice Chacron, Center for Nonlinear Dynamics, Dept. Physiology, McGill
Prof. Victor LeBlanc, Mathematics and Statistics, University of Ottawa
Prof. John Lewis, Biology, University of Ottawa
Prof. Tim Lewis, Mathematics, University of California at Davis
Prof. André Longtin, Physics, Cellular and Molecular Medicine, University of Ottawa
Prof. Len Maler, Cellular and Molecular Medicine, University of Ottawa
TUITION: $1400 CAN with credit, $800 CAN without credit.
ACCOMMODATION
Accommodation will be available at the New Residence of the University of Ottawa, a few minutes walk away from the Biosciences Complex, cafeterias and downtown Ottawa with its restaurants, museums etc… Accommodation consists of a single room with a double bed, with two such rooms per apartment. Each apartment has a living room, kitchen and bathroom. The cost is approximately $48 CAN per night per person, taxes included.
FINANCIAL SUPPORT
Partial financial support is available for those demonstrating the need.
IMPORTANT DATES
February 15th , 2007: Application (website ready in the second week of January).
March 15th 2007: Notification of acceptance and level of financial support.
April 1st, 2007: Notification of acceptance by the participant.
Accommodation: as soon as possible after notification of acceptance, participants can reserve their accommodation online at reserve@uottawa.ca or by phoning 1-888-564-4545.
REGISTER AT: www.neurodynamic.uottawa.ca
CONTACT US: compneuro07@uottawa.ca
SYLLABUS
1) Introduction to Linear and Nonlinear Dynamical Systems
-solutions of linear differential equations
-qualitative analysis of nonlinear differential equations
2) Single Neuron Models
-ionic models
-simplified deterministic and stochastic models
3) Neural Spike Train Analysis and Modeling
-basic statistics
-autocorrelation, spectrum
-information theory toolbox
4) Sensory Coding
-artificial and naturalistic stimuli
-modeling activity along the afferent pathways
-modeling feedback
-population coding and information theory
5) Synaptic Plasticity
-short term depression and facilitation
-long term plasticity
-implications for information processing
6) Coupled Neurons
-gap junction
-excitatory and inhibitory synaptic coupling
-effect of coupling on neural population behavior
7) Computational and Dynamical Approaches to Motor Control
-posture control and equilibrium point approaches
-movement adaptation to force fields
-timing and rhythmic movements
-computational approaches to movement pathologies Waves of Activity in Neural Networks
-neural field models
-traveling waves
-spiral waves