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Dynamical Neuroscience: A Viewpoint |
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Neuroscience, the study of the brain and
nervous system, is one of the most rapidly developing and exciting fields in
all of modern science today (see reviews by Albright et al., Neuron,
25:S1-S55, 2000 and Kandel and Squire, Science,
290:1113-1120, 2000). This likely
stems from its highly interdisciplinary nature together with its effect on
each and every one of us in terms of understanding how we think, feel, grow,
remember and interact with our environment. Moreover, an understanding of our
most complex organ, the brain, is required if we are to be able to prevent
and relieve pathological conditions such as epilepsy, Parkinson's disease,
Alzheimer’s disease, schizophrenia, depression and other mental
disorders. The long-term goal of the lab is to forge
links between the dynamics that exist at the different levels of the brain
and nervous system (molecular/cellular/multi-cellular/network). In particular, to obtain
biophysically-based mechanisms underlying network dynamics. A fundamental aim in the computational
neuroscience field is to understand how the rich interplay of highly
nonlinear, intrinsic properties of individual neurons together with their
coupling properties give rise to the several
dynamical activities of neuronal networks. Mathematical modelling
is uniquely poised to make such a linkage and provide functional insights.
However, it is far from clear what level of model detail is needed to
generate new insights. We should neither ignore the details of particular
systems nor be overwhelmed by them. The balance is the challenge in advancing
our understanding. We work
towards our goal by: (i) establishing intimate
links with experimental studies to allow mathematical models to be developed
and to determine where modeling studies are warranted, and (ii) simulating
and analyzing developed mathematical models to enable insights and
predictions to emerge. The present focus is
on modelling inhibitory, GABAergic
hippocampal interneurons
and networks, in the context of coherent rhythmic output, and with
consideration of their diverse, heterogeneous natures. The effects of
anesthetics, the effect of gap-junctional and
inhibitory coupling characteristics, and the contribution of synaptic
plasticity in the form of depression are of interest. Present and past collaborators and
labs include: Dr. Liang Zhang, Dr. Sue Ann Campbell, Dr. Chris McBain, Dr. Jean-Claude Lacaille,
Dr. Beverley Orser, Dr. Peter Pennefather
and Dr. Peter Carlen.
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