[Mne_analysis] Topoplot

[Alexandre Gramfort]

yes by taking the RMS of the gradiometers you loose the sign.

I don't know what could be a better way here.

You could display just the planar1 or planar2 setting eg ch_type='planar1'
in plot_topomap

HTH
Alex

On Wed, Feb 21, 2018 at 10:06 PM, JR KING <jeanremi.king at gmail.com> wrote:

> Hi Jeff,
>
> Could it be that your topos are combined gradiometers (and are thus
> squared and positive), whereas the time freqs are all sensors?
>
> (By the way, cmap='jet' is not recommended: https://jakevdp.github.io/
> blog/2014/10/16/how-bad-is-your-colormap/)
>
> JR
>
> On 21 February 2018 at 11:32, Stout, Jeffrey <jstout at mcw.edu> wrote:
>
>> MNE group,
>>
>>
>>
>> When I plot the time frequency display, I predominantly get beta
>> desynchrony with a strong negative z-score (using power.plot_topo).  When I
>> plot that same data using the topomap (power.plot_topomap) and selecting
>> the appropriate frequencies and time latencies the data appears as a
>> positive Z-score.  Is there a sign flip during the topomap plotting and is
>> there a flag to set to prevent the flip?
>>
>>
>>
>> Attached are the outputs of the code below.  The data frequencies are
>> 20-25Hz to highlight the difference in plots.  Data is from a Neuromag
>> system  - using the gradiometers only.
>>
>>
>>
>> Some code:
>>
>> freqs = np.logspace(*np.log10([20, 25]), num=20)
>>
>> n_cycles = freqs / 2.  # different number of cycle per frequency
>>
>> power_3, itc = tfr_morlet(epochs['3'], freqs=freqs, n_cycles=n_cycles,
>> use_fft=True,
>>
>>                         return_itc=True, decim=3, n_jobs=-1)
>>
>> power_2, itc = tfr_morlet(epochs['2'], freqs=freqs, n_cycles=n_cycles,
>> use_fft=True,
>>
>>                         return_itc=True, decim=3, n_jobs=-1)
>>
>>
>>
>> power_minus=copy.copy(power_3)
>>
>> power_minus._data=power_3._data - power_2._data
>>
>> ##### TOPOPLOT#######
>>
>> tf_plot=power_minus.plot_topo(baseline=(-0.5, 0), mode='zscore',
>> title='Average power', vmin=-10, vmax=10, tmin=-.1, tmax=.9, cmap='jet')
>>
>>
>>
>> timepoints=[-.1,.1,.3,.5,.7,]
>>
>> fig, axis = plt.subplots(1, len(timepoints), figsize=(20,3))
>>
>> for i,laten in enumerate(timepoints):
>>
>> ####TOPOPLOT MAP######
>>
>>     power_minus.plot_topomap(ch_type='grad', tmin=laten, tmax=laten+.1,
>> fmin=20, fmax=25,
>>
>>                        baseline=(-0.5, 0), mode='zscore', axes=axis[i],
>>
>>                        vmin=-10, vmax=10, show=False, cmap='jet',
>> title=str(laten))
>>
>> mne.viz.tight_layout()
>>
>> plt.show()
>>
>>
>>
>>
>>
>> Thanks,
>>
>> Jeff Stout
>>
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