plebrun at fysp1.vub.ac.be
Wed Aug 28 05:56:44 EST 1996
In article <32239C12.4F0A at itol.com>,
Gary Frank <garyfrank at itol.com> writes:
>I am designing a computational neural network to do object recognition.
> I am basing it as closely as possible on the brain. I have been
>reading brain researcher David Hubel's book "Eye, Brain, and Vision" as
>a guide. There is some information, important to the design of the ANN
>that I don't understand. As I understand it, neurons fire at
>increasingly high rates as the conditions they were designed for are
>met. I wonder if the post synaptic neurons that receive these impulses
>are "charged up" as a result. In other words, if a neuron doesn't
>receive enough inputs at a single instant in time to cause it to fire
>right away, is it more likely to fire in the near future, upon receiving
>more inputs, because of the inputs it received a short time ago? If so,
>how long does this "charge" last?
I'm a bit lazy, so I don't want to go into long explanations. Why don't
you try looking up "temporal summation" in a basic neuroscience textbook,
like Kandel and Schwartz - Principles of neuroscience. This should get
The visual cortex also shows long term potentiation as well as other
forms of synaptic plasticity worth looking up if you are trying to model
a process involving memory.
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