# Partitioning source estimated data based on broadmann atlas

**URL:** <https://mne.discourse.group/t/partitioning-source-estimated-data-based-on-broadmann-atlas/3163>\
**Category:** Support & Discussions\
**Tags:** source-localization, preprocessing, meg, sensor-space\
**Created:** [May 21, 2021, 1:37pm UTC](https://mne.discourse.group/t/partitioning-source-estimated-data-based-on-broadmann-atlas/3163 "2021-05-21T13:37:15Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![shirinV](https://avatars.discourse-cdn.com/v4/letter/s/779978/32.png) [@shirinV](https://mne.discourse.group/u/shirinV)\
**Post date:** [May 21, 2021, 1:37pm UTC](https://mne.discourse.group/t/partitioning-source-estimated-data-based-on-broadmann-atlas/3163/1 "2021-05-21T13:37:15Z")

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**If you have a question or issue with MNE-Python, please include the following info:**

- MNE-Python version: 0.23.0
- operating system: Mac oS

I want to partition my source estimated data and get the values for each region from famous atlas such as broadmann. How can I do that? Is there any function/tutorial about it?

Thanks in advance

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**Author:** ![drammock](https://yyz2.discourse-cdn.com/free1/user_avatar/mne.discourse.group/drammock/32/4_2.png) [@drammock](https://mne.discourse.group/u/drammock)\
**Post date:** [May 21, 2021, 2:36pm UTC](https://mne.discourse.group/t/partitioning-source-estimated-data-based-on-broadmann-atlas/3163/2 "2021-05-21T14:36:23Z")

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you can use [stc.in\_label()](https://mne.tools/stable/generated/mne.SourceEstimate.html?highlight=stc%20in_label#mne.SourceEstimate.in_label) inside a for-loop over atlas labels. You can get the labels from [read\_labels\_from\_annot()](https://mne.tools/stable/generated/mne.read_labels_from_annot.html#mne.read_labels_from_annot).