[Comp-neuro] U. Ottawa Computational Neuroscience Summer School

Andre Longtin alongtin at uottawa.ca
Sun Nov 30 01:44:56 CET 2008





JUNE 7-20, 2009




We are pleased to announce the 3rd summer School in Computational Neuroscience, which will be held from Sunday June 7, 2009 until Saturday June 20, 2009 inclusively. It is organized by the Center for Neural Dynamics at the University of Ottawa. The highly pedagogical 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. 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 on the presentation of a research project by the end of the course, with write-up to follow within a week. The first day of the school (Sunday June 7th) 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. 


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. 




Prof. Ramesh Balasubramaniam, School of Human Kinetics, McMaster University

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 



see the application form at:   http://www.neurodynamic.uottawa.ca/summer.html





Accommodation will be available at the Stanton 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 or double room (with respectively one or two single beds, desks and internet access), with communal kitchen and living area and shared bathroom. The cost is approximately $40 CAN per night per person, taxes included. 




Partial financial support is available for those demonstrating the need.  




February 1st , 2009: Application, including a letter of recommendation sent to compneuro09 at uottawa.ca

February 15, 2009: Notification of acceptance and level of financial support.

March 1st, 2009: Notification of acceptance by the participant.

Accommodation: as soon as possible after notification of acceptance, participants can reserve their accommodation online at reserve at uottawa.ca <mailto:reserve at uottawa.ca>  or by phoning 1-888-564-4545.


REGISTER AT: www.neurodynamic.uottawa.ca/summer.html   


CONTACT US: compneuro09 at uottawa.ca <mailto:compneuro09 at uottawa.ca>    




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 models

     -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) 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


6) Synaptic Plasticity

     -short term depression and facilitation

     -long term plasticity    

     -implications for information processing


7) Coupled Neurons

     -gap junction

     -excitatory and inhibitory synaptic coupling

     -effect of coupling on neural population behavior


8) Waves of Activity in Neural Networks

     -neural field models

     -traveling waves

     -spiral waves

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