[Mne_analysis] spatio-temporal cluster on sensor level?

[Alexandre Gramfort]

hi,

it would be great to have an example for this feature. Any volunteer?

Cheers,
Alex


On Fri, Aug 15, 2014 at 3:09 PM, Denis-Alexander Engemann
<denis.engemann at gmail.com> wrote:
> Dear Elisabeth,
>
> with regard to data organization, you can proceed exactly as with the source
> space examples, just replace vertices with channels.
> The critical difference amounts to how to define the neighboring spatiall
> features, a.k.a. connectivity.
> To compute this information you should use the FieldTrip neigbour
> definitions. You can read those using this function:
> http://martinos.org/mne/stable/generated/mne.read_ch_connectivity.html#mne.read_ch_connectivity
>
> for exmple like this for a 4D/BTi 248 channels magnetometer system:
>
> neighbor_file = 'fieldtrip/template/neighbours/bti248_neighb.mat'
>
> connectivity = mne.channels.read_ch_connectivity(neighbor_file)
>
> In case you have missing channels, you can define those to return the
> connectivity matrix of the subset of remaining channels:
>
> connectivity = mne.channels.read_ch_connectivity(neighbor_file, picks=picks)
>
> The rest is the same, make sure your data matrices match the contrast type
> (F vs T test) and make sure that the last dimension carries the spatial
> information.
>
> I hope that helps (we'll soon add a corresponding example).
>
> Best,
> Denis
>
>
>
>
>
> On Fri, Aug 15, 2014 at 2:52 PM, Elisabeth Fonteneau <ef309 at cam.ac.uk>
> wrote:
>>
>> Hello MNE (python) user,
>>
>>
>>
>> I have another question related to mne_python v.08
>>
>> I was wondering if there is a script for running Permutation t-test with
>> spatio-temporal clustering on sensor data?
>>
>> I found one for source level (which looks brilliant), however for sensor
>> level, I found “only” temporal clustering on 1 specific sensor.
>>
>> Thanks for your help
>>
>> Elisabeth
>>
>>
>>
>>
>>
>>
>>
>> __________________________________________________________
>>
>>
>>
>> Dr Elisabeth Fonteneau
>>
>> Neurolex Group
>>
>> Department of Psychology
>>
>> University of Cambridge
>>
>> Downing Street, Cambridge CB2 3EB, UK
>>
>> Phone: +44 1223 333 548
>>
>> Email: ef309 at cam.ac.uk
>>
>> Web: www.neurolex.psychol.cam.ac.uk/directory/ef309 at cam.ac.uk
>>
>>
>>
>>
>>
>>
>>
>>
>>
>>
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