SCIENTIFIC PROGRAMS AND ACTIVITIES

December 14, 2024

July 7, 2007
Workshop on Perspectives for Future Directions in Computational and Mathematical Neuroscience
to be held at the Fields Institute

Organizers:
Frances K. Skinner, Ph.D.
Senior Scientist, Toronto Western Research Institute, University Health Network
Associate Professor, Depts. Medicine (Neurology), Physiology, IBBME, University of Toronto
Sue Ann Campbell, Ph.D.
Professor, Department of Applied Mathematics, University of Waterloo

Mary Pugh, Ph.D.
Associate Professor, Department of Mathematics, University of Toronto
Richard Zemel, Ph.D
Associate Professor, Department of Computer Science, University of Toronto


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Overview

Computational Neuroscience is now identified as an established field. In this field we seek to understand how the brain and nervous system compute. This challenging endeavour requires both theory and experiment, and thus it is a highly interdisciplinary field involving mathematics, physics, physiology, computer science, biology, engineering, psychology, and so on. As such, it can be a difficult field to navigate and to understand where and how one might be able to fit in.

The goal of this event is to obtain perspectives for future directions in the field. This will be derived from the sharing of past experiences by invited speakers in the field, and from interactions between participants and invited speakers in the form of smaller group and panel discussions. Invited speakers are asked to provide their opinions and insights on any or all of the following:

(i) Definition of the field,
(ii) Research highlights in the field,
(iii) Critical considerations for someone wanting to enter the field today,
(iv) Ideal type(s) of training, and
(v) Suggested changes and directions for the field.

This event occurs as a pre-meeting Satellite to the Annual Computational Neuroscience meeting being held in Toronto from July 8th-12th 2007 (see www.cnsorg.org for further details).

Invited Speakers

Speakers will include senior people in the Computational Neuroscience field from mathematical, experimental and theoretical perspectives.

Sue Becker,
McMaster University
Ron Calabrese
, Emory University
Doug Crawford
, Centre for Vision Research, York University
André Longtin, University of Ottawa
Jonathan Rubin,
University of Pittsburg
Hugh Wilson
, Centre for Vision Research, York University

Schedule


Saturday, July 7, 2007
8:30 – 9:00 Registration and Coffee
9:00 – 9:30 Doug Crawford, Centre for Vision Research,
York University
Levels of theory in Sensorimotor Neuroscience
9:30 - 10:00 Andrι Longtin, University of Ottawa
Active sensory dynamics
10:00 – 10:30 Hugh Wilson, Centre for Vision Research, York University
Binocular rivalry: Waves, Feedback, Hysteresis & Perceptual Memory
10:30 – 11:00 Coffee Break
11:00 – 11:30 Ron Calabrese, Emory University
A future for experimental models?
11:30 – 12:00 Sue Becker, McMaster University
Understanding hippocampal-cortical interactions in memory, sleep and dreaming: linking computational theory to large-scale brain dynamics
12:00 – 12:30 Jonathan Rubin, University of Pittsburg
From the Evans function to deep brain stimulation and back
12:30 – 1:00 Lunch acquisition and go to breakout rooms
1:00 – 1:30 Breakout Group
1:30 – 2:00 Breakout Group
2:00 – 2:30 Breakout Group
2:30 – 3:00 Coffee Break
3:00 – 4:00 Panel Discussion

Doug Crawford, York University
Levels of theory in Sensorimotor Neuroscience

This talk will focus on 1) how theoretical models apply to different levels of sensorimotor processing - from behavioral input-output
relations, to algorithms, to neuronal populations, to individual units, and
2) how these models may be tested experimentally. Examples will be provided of problems in the field that were tackled using a combination of theoretical and empirical approaches, for example non-commutativity in the vestibulo-ocular reflex, reference frame transformations in saccades and eye-hand coordination, and computational mechanisms for spatial updating. The emphasis for the future will be in formalizing our understanding of how one level of theory is expressed at another level (for example how control system algorithms are implemented within artificial and real networks), building more systematically integrated theoretical-empirical approaches in neuroscience, and applying these approaches to practical problems in clinical research.


Other Information

Registration is required. . Registration is free, however there are a limited number of spaces available due to space restrictions so advance registration is recommended.

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