[Eeglablist] std_envtopo (plotchans and pvaf)

[Makoto Miyakoshi]

Dear Ana,

>First, I was wondering wether I could use something like the 'plotchans'
(available in envtopo) to compute the contributions in just one or a few
channels of interest. The default function computes the contributions for
the grand ERPs which gives me a lot of variability that I'm not interested
in.

Currently this is not supported. I see how to do it though.
I would suggest that you exclude clusters of non-interest, or specify the
clusters to use, so that your outermost envelope is consist of only
necessary ones.

>Also, I'm still confuse about the pvaf for the individual clusters.
For example, I'm looking for the clusters that explain the P300 variability
and there is a cluster (out of 7 clusters) that seems to me (based on the
cluster's ERP) that explains most of the variability of the P300.
When I run std_envtopo, I get a pvaf of -550.46 for that cluster. First, I
understand that this is not talking about the P300 activity alone, but the
grand average, and this implicates a lot of variance from many areas that
I'm not interested in (and this is the reason why I'm trying to use just a
few channels of interest). Therefore, because what I think is the 'P300
cluster' may have a different signal than all the other activities (that
I'm not interested in), then I get a negative value for this cluster pvaf
(-550.46). Am I getting something wrong so far?

-550.46 should be a number of latency. Where does the line (extending from
the scalp topos) pointing? Isn't it -550.46 ms? If so, you should limit the
latency window to evaluate contribution.

>Also, I imagine that, because this is the percent variance accounted for,
for positive numbers, 100 should be the maximum possible value?

No, actually pvaf never sums to 100% if you add up each clusters. That
means, pvaf(Cls1+Cls2) ~= pvaf(Cls1)+pvaf(Cls2). By the way the default
100% is pvaf(Cls1+Cls2+...ClsN) if you have N number of clusters.

The measure pvaf is always superadditive i.e. exceeds 100% if summed
separately.

Makoto

2013/4/10 Ana Navarro Cebrian <anavarrocebrian at gmail.com>

> Hi,
>  I have two questions about the function std_envtopo.m
>
> First, I was wondering wether I could use something like the 'plotchans'
> (available in envtopo) to compute the contributions in just one or a few
> channels of interest. The default function computes the contributions for
> the grand ERPs which gives me a lot of variability that I'm not interested
> in.
>
> Also, I'm still confuse about the pvaf for the individual clusters.
> For example, I'm looking for the clusters that explain the P300
> variability and there is a cluster (out of 7 clusters) that seems to me
> (based on the cluster's ERP) that explains most of the variability of the
> P300.
> When I run std_envtopo, I get a pvaf of -550.46 for that cluster. First, I
> understand that this is not talking about the P300 activity alone, but the
> grand average, and this implicates a lot of variance from many areas that
> I'm not interested in (and this is the reason why I'm trying to use just a
> few channels of interest). Therefore, because what I think is the 'P300
> cluster' may have a different signal than all the other activities (that
> I'm not interested in), then I get a negative value for this cluster pvaf
> (-550.46). Am I getting something wrong so far?
>
> Also, I imagine that, because this is the percent variance accounted for,
> for positive numbers, 100 should be the maximum possible value?
>
> I hope that makes sense. Thanks in advance for your help.
>  Ana
>
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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