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MesoNet: automated scaling and segmentation of mouse mesoscale cortical maps using machine learning

Description: Raw wide-field calcium imaging data was recorded from male awake head-fixed GCaMP6 mice. This dataset is used to discovery cortical activity motifs and generate motif based functional maps.
The main demo code to run:
The codes are available on the OSF repository:
“OSF Storage/4_Data_code” at
The demo code was tested on:
Operating systems: Windows10
Versions the software has been tested on: Matlab 2020a
Expected run time for demo on a "normal" desktop computer: the code may need several hours or days to run.
Authors: Murphy, Timothy; University of British Columbia; ORCID iD 0000-0002-0093-4490
Xiao, Dongsheng; University of British Columbia; ORCID iD 0000-0002-1669-0021
Keywords: mesoscale
Field of Research: 
Basic medicine and life sciences
Neurosciences, medical and physiological and health aspects
Neurosciences, medical and health and physiological aspects, not elsewhere classified
Publication Date: 2024-04-01
Publisher: Federated Research Data Repository / dépôt fédéré de données de recherche
Funder: Canadian Institutes of Health Research (CIHR)
Canadian Open Neuroscience Platform (CONP)
Related Identifiers: 
This dataset is a supplement to
Geographic Coverage: 
Province /
Province / Territory
British Columbia
Appears in Collections:UBC Brain Circuits

Files in Dataset 
The list of files is not currently shown

Access to this dataset is subject to the following terms:
Creative Commons Attribution 4.0 International (CC BY 4.0)
Murphy, T., Xiao, D. (2024). MesoNet: automated scaling and segmentation of mouse mesoscale cortical maps using machine learning. Federated Research Data Repository.