Why do people do it this way? Let me provide an example that I am
most familiar with. Take the development of inhibitory synapses in
the lateral superior olive: they start out predominantly comprised of
GABA type A receptors and gradually glycine receptors are introduced
so that there is a mixture of the two at the synapse and then
eventually become predominantly comprised of glycine receptors. The
IPSCs from GABAaRs is slow, while GlyRs are fast. In this case it is
useful to have a weighted mean time constant to describe the
exponential decay of the IPSCs over the different developmental
stages - since at some stages there will be two exponential
components, and other stages just one component. Thus, the change
from the slow IPSCs to the fast IPSCs can be described with a single
parameter and can be easily plotted against time. Of course, you
wouldn't rely solely on this analysis to describe what is happening.
Certainly, if you were wanting to compare the relative contributions
of the fast and slow components then a more robust statistical
comparison would be useful (like a 2-way ANOVA).
At 04:04 AM 20/01/2009, you wrote:
>Date: Sat, 17 Jan 2009 20:02:19 -0800 (PST)
>From: Bill <connelly.bill from gmail.com>
>Subject: [Neuroscience] Re: Decay constants. What does "weighted"
>To: neur-sci from net.bio.net>Message-ID:
> <9247173e-1e8a-42e5-b05e-cd8d89ccd12a from r10g2000prf.googlegroups.com>
>Content-Type: text/plain; charset=ISO-8859-1
>>Thanks Trevor, that explains it nicely (I geussed it was something
>>Why do people do it in that way? Wouldn't it make more sense if you
>were comparing an intervention to do a 2-way ANOVA with Intervention
>vs Slow Decay Constant vs Fast Decay Constant?