Noise-driven adaptation: in
vitro and mathematical analysis
Published as
Neurocomputing
52: 877-883
Presented at
Computational Neuroscience 2002, Alicante, Spain
Variance adaptation processes have recently been examined in cells of
the fly visual system and various vertebrate preparations. To better
understand the contributions of somatic mechanisms to this kind of
adaptation, we recorded intracellularly in vitro from neurons of rat
sensorimotor cortex. The cells were stimulated with a noise current
whose standard deviation was varied parametrically. We observed
systematic variance-dependent adaptation (defined as a scaling of a
nonlinear transfer function) similar in many respects to the effects
observed in vivo. The fact that similar adaptive phenomena are seen in
such different preparations led us to investigate a simple model of
stochastic stimulus-driven neural activity. The simplest such model,
the leaky integrate-and-fire (LIF) cell driven by noise current,
permits us to analytically compute many quantities relevant to our
observations on adaptation. We show that the LIF model displays
"adaptive" behavior which is quite similar to the effects observed in
vivo and in vitro.
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