[Eeglablist] std_envtopo (plotchans and pvaf)

[Makoto Miyakoshi]

Dear Ana,

Sorry for slow response.

Thanks Makoto. This is very helpful. I'd still love to be able to choose
> some channels though; My P300 comes along with an effect of an opposite
> (negative) signal in the frontal electrodes (I think this happens because I
> use the average as a reference), and I believe that choosing just some
> centro-parietal electrodes would give me a better estimate. I'll see if I
> can try something myself.
>

Maybe you want to try my toolbox to backproject cluster ERPs to channels.
I'll send it to you in the separate mail.

It seems to me that the line is pointing at 559 and what I'm talking about
> says "pvaf: 550.46. I had limited the latency anyway (from 200 to 600ms).
> Another example is the cluster close to it, which shows "pvaf: -111.61".
> This one is also pointing at latency ~559ms. I've attached an example of
> the output I get from std_envtopo.
>

I saw it. It is quite strange indeed. I want to diagnose the situation.
At least I can tell that your 'outermost envelope' (shown in thick black)
is surpassed by other envelopes, which is not normal. That is like saying
some of your clusters have larger values than the sum of all (it's not
exactly like this but pretty much about it). Can you think of any reason
why you see this?

If you can't find anything wrong by yourself, I need to ask you to either
1. transfer all of your data to our server or 2. video conference by
sharing your desktop. You can choose whichever you want. Sorry for
inconvenience.

Makoto


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

> >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.
>
> Thanks Makoto. This is very helpful. I'd still love to be able to choose
> some channels though; My P300 comes along with an effect of an opposite
> (negative) signal in the frontal electrodes (I think this happens because I
> use the average as a reference), and I believe that choosing just some
> centro-parietal electrodes would give me a better estimate. I'll see if I
> can try something myself.
>
> >-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.
>
> It seems to me that the line is pointing at 559 and what I'm talking about
> says "pvaf: 550.46. I had limited the latency anyway (from 200 to 600ms).
> Another example is the cluster close to it, which shows "pvaf: -111.61".
> This one is also pointing at latency ~559ms. I've attached an example of
> the output I get from std_envtopo.
>
> >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.
>
> Here I was talking about the individual pvaf (for each individual cluster)
> shown under the cluster topoplot, and not the total pvaf. I'm not sure if
> the response is still the same.
> For example, for those two clusters that I'm talking about above, with
> pvaf -550.46% and -111.61%. Would it be possible to get positive values
> like those for individual clusters? i.e. pvaf: 550.46?
>
> Thank you again for your help, Makoto.
>
>
>
>
> 2013/4/10 Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
>
>> 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
>>
>
>
>
> --
> Ana Navarro-Cebrian
> Postdoctoral Fellow. UCSF
>



-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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