# Manifest not found message in minnie65 meshes

**URL:** <https://community.brain-map.org/t/manifest-not-found-message-in-minnie65-meshes/3881>\
**Category:** Technical\
**Created:** [November 22, 2024, 10:55pm UTC](https://community.brain-map.org/t/manifest-not-found-message-in-minnie65-meshes/3881 "2024-11-22T22:55:40Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![shandran](https://yyz1.discourse-cdn.com/flex027/user_avatar/community.brain-map.org/shandran/32/675_2.png) [@shandran](https://community.brain-map.org/u/shandran)\
**Post date:** [November 22, 2024, 10:55pm UTC](https://community.brain-map.org/t/manifest-not-found-message-in-minnie65-meshes/3881/1 "2024-11-22T22:55:40Z")

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When using meshparty to download meshes in the minnie65 dataset, I get, for example: ‘MeshDecodeError: Manifest not found for segment 864691136118988312.’

This is a PTC inhibitory neuron (from the AIBS data table) and also shows up in the synapse query tables. When attempting to visualize this root\_id in neuroglancer, there is no visible segmentation and when attempting to download, the manifest error message is returned.

Is there a workaround? Any advice is much appreciated.  
Shawn

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**Author:** ![fcollman](https://yyz1.discourse-cdn.com/flex027/user_avatar/community.brain-map.org/fcollman/32/1290_2.png) [@fcollman](https://community.brain-map.org/u/fcollman)\
**Post date:** [November 22, 2024, 11:15pm UTC](https://community.brain-map.org/t/manifest-not-found-message-in-minnie65-meshes/3881/2 "2024-11-22T23:15:49Z")

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I think this is because you are using the wrong cloudvolume source to download the most recent version of the meshes. Unfortunately, the pipeline that generates the static segmentation and static meshes is expensive and we cannot afford to run it on every data release, but we can for the dynamic meshes which are available for all root\_ids, even historical versions.

This is explained here [Cubic Millimeter — MICrONS Explorer](https://www.microns-explorer.org/cortical-mm3#segmentation-meshes)

having a code snippet of what you are trying to do will also help here.

cv=client.info.segmentation\_cloudvolume()

will get you the right cloudvolume to utilize for meshes. We made the documentation for that static meshes as those are also useful in that they have multiple resolutions and correspond directly to the neuroglancer view we have available with the static segmentation and meshes.