Workshop on Mathematical Neuroscience – Montreal, Sept 16-19, 2007

Workshop: Workshop on Mathematical Neuroscience. September 16-19, 2007. Centre de Recherches Mathématiques, Montréal, Canada.

Includes focus sessions on (1) audition and (2) parkinsonian tremor and deep brain stimulation.

FIRST ANNOUNCEMENT AND CALL FOR PARTICIPANTS

WORKSHOP ON MATHEMATICAL NEUROSCIENCE

Including two focus sessions: 1) AUDITION, 2) PARKINSONIAN TREMOR AND DEEP BRAIN STIMULATION

Centre de Recherches Mathématiques, Université de Montréal, Montréal, Canada

September 16-19, 2007

SPONSORED BY NSERC (CRM), MITACS AND MATHEON

CONFERENCE URL: http://www.crm.umontreal.ca/Neuro07/index_e.shtml

Organizers: S. Coombes (Nottingham), A. Longtin (Ottawa), J. Rubin (Pittsburgh)

The goal of this workshop is to provide an overview of the current state of research in mathematical approaches to neuroscience. This vibrant area, seeded by successes in understanding nerve action potentials, dendritic processing, and the neural basis of EEG, has moved on to encompass increasingly sophisticated tools of modern applied mathematics. Included among these are Evans functions techniques for studying wave stability and bifurcation in tissue level models of synaptic and EEG activity, heteroclinic cycling in theories of olfactory coding, the use of geometric singular perturbation theory in understanding rhythmogenesis, stochastic differential equations describing inherent sources of neuronal noise, spike-density approaches to modelling network evolution, weakly nonlinear analysis of pattern formation, and the role of canards in organising neural dynamics.

IMPORTANTLY, the workshop will also address the novel application of such techniques in two half-day sessions, one on AUDITION and the other on PARKINSONIAN TREMOR AND DEEP BRAIN STIMULATION. Hence, participants will be drawn from both the mathematical and experimental sciences.

A further aim of this workshop will be to encourage other applied mathematicians into this thriving area of research where their work can have an impact on both experimental and computational neuroscience. Indeed a major challenge for the mathematical neuroscience community is to complement new biological understanding of network function with a mathematical understanding of dynamics for computation. In particular this will require studies that go beyond the mathematically tractable cases of highly symmetric and homogeneous networks and for us to understand the role that noise, inhomogeneities, delays, and feedback have to play in shaping the dynamic states of biological neural networks.

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