Download Modeling Synaptic Plasticity

Department of Statistics
STATISTICS COLLOQUIUM
NICOLAS BRUNEL
Departments of Statistics and Neurobiology
The University of Chicago
Modeling Synaptic Plasticity
MONDAY, November 25, 2013, at 4:00 PM
133 Eckhart Hall, 5734 S. University Avenue
Refreshments following the seminar in Eckhart 110
ABSTRACT
Synapses are the structures through which neurons communicate, and the loci of information
storage in neural circuits. Synapses store information (‘learn’) thanks to synaptic plasticity:
the efficacy of the communication between the two neurons connected by the synapse can
change, as a function of the history of the activity of these two neurons. Many experiments
have documented the phenomenology of synaptic plasticity in the last four decades, but the
precise ‘learning rule’ used by synapses and the mechanisms of plasticity still elude us.
In this talk, I will first review the relevant experimental data. I will then present a model
of synaptic plasticity which describes the temporal evolution of two variables: the calcium
concentration in the post-synaptic spine, which is driven by the activity of pre and postsynaptic neurons, and the synaptic efficacy, which is driven by the calcium concentration
variable. This model is simple enough so that it can be studied analytically, for deterministic
as well as stochastic activity patterns of the two neurons. I will show that it reproduces
naturally a large amount of experimental data in various preparations, and provides a mechanistic understanding of how various activity patterns provoke specific synaptic changes.
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