[Eeglablist] std_envtopo (plotchans and pvaf)

Thu May 9 11:01:48 PDT 2013

Yes, good, Makoto - Scott

On Thu, May 9, 2013 at 10:56 AM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>wrote:

> Dear Scott,
>
> Yes I've seen it, and also seen negative variance too. These things
> themselves do not mean evidence of a bug. However, I thought one cluster
> showing pvaf of -505% is pathological and needs to be investigated.
>
> Makoto
>
>
> 2013/5/9 Scott Makeig <smakeig at gmail.com>
>
>> Makoto -   Cluster envelopes can indeed exceed the scalp ERP bounds -- IF
>> the clusters contribute activity with different polarities at maximal
>> projection channels.... whose sum is therefore smaller than the strongest
>> cluster contribution, not larger...
>>
>> Scott
>>
>>
>> On Wed, Apr 17, 2013 at 6:09 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>wrote:
>>
>>> 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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>>
>>
>>
>> --
>> Scott Makeig, Research Scientist and Director, Swartz Center for
>> Computational Neuroscience, Institute for Neural Computation, University of
>> California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott
>>
>
>
>
> --
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>

-- 
Scott Makeig, Research Scientist and Director, Swartz Center for
Computational Neuroscience, Institute for Neural Computation, University of
California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott
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