{"schema_version":"0.3.0","doc_type":"dataset","dataset_id":"on005810","name":"NOD-MEG","description":"NOD-MEG provides magnetoencephalography (MEG) recordings from human participants viewing large-scale naturalistic ImageNet stimuli, extending the previously collected Natural Object Dataset (NOD-fMRI) with temporally resolved neural data. Combined with corresponding fMRI and EEG datasets from the same subjects, NOD-MEG enables multimodal investigation of object recognition across both spatial and temporal domains. The dataset is intended as a resource for studying neural mechanisms of visual object recognition under naturalistic viewing conditions.","source":"nemar","recording_modality":["ANAT","MEG"],"bids_version":null,"license":"CC0","authors":[{"name":"Guohao Zhang","name_type":"Personal"},{"name":"Ming Zhou","name_type":"Personal"},{"name":"Shuyi Zhen","name_type":"Personal"},{"name":"Shaohua Tang","name_type":"Personal"},{"name":"Zheng Li","name_type":"Personal"},{"name":"Zonglei Zhen","name_type":"Personal"}],"keywords":[{"term":"Magnetoencephalography","subject_scheme":"MeSH","value_uri":"http://id.nlm.nih.gov/mesh/D015225"},{"term":"object recognition"},{"term":"naturalistic stimuli"},{"term":"visual cognition"},{"term":"ImageNet"},{"term":"multimodal neuroimaging"}],"related_identifiers":[{"identifier":"10.18112/openneuro.ds004496.v1.2.2","identifier_type":"DOI","relation_type":"IsDerivedFrom"},{"identifier":"https://github.com/nemarDatasets/on005810","identifier_type":"URL","relation_type":"IsDescribedBy"},{"identifier":"https://nemar.org/dataset/on005810","identifier_type":"URL","relation_type":"IsDescribedBy"},{"identifier":"10.18112/openneuro.ds004496.v2.1.2","identifier_type":"DOI","relation_type":"IsSupplementedBy"},{"identifier":"10.1038/sdata.2018.110","identifier_type":"DOI","relation_type":"References"},{"identifier":"10.18112/openneuro.ds005810.v2.0.0","identifier_type":"DOI","relation_type":"IsDerivedFrom"},{"identifier":"10.18112/openneuro.ds005811.v1.0.0","identifier_type":"DOI","relation_type":"IsPartOf"}],"contributors":[],"dates":[],"rights":[{"rights":"CC0","rights_uri":null,"rights_identifier":"CC0","rights_identifier_scheme":"SPDX"}],"language":null,"funding":[{"funder_name":"Beijing Natural Science Foundation","award_number":"L247010","award_title":null,"funder_identifier":null,"funder_identifier_type":null,"award_uri":null},{"funder_name":"National Natural Science Foundation of China","award_number":"62433015","award_title":null,"funder_identifier":null,"funder_identifier_type":null,"award_uri":null},{"funder_name":"National Natural Science Foundation of China","award_number":"31771251","award_title":null,"funder_identifier":null,"funder_identifier_type":null,"award_uri":null},{"funder_name":"STI 2030-Major Projects of the Ministry of Science and Technology of China","award_number":"2021ZD0200407","award_title":null,"funder_identifier":null,"funder_identifier_type":null,"award_uri":null}],"tasks":["ImageNet","noise"],"datatypes":["anat","meg"],"sessions":["20210413","20210428","20210512","20210513","20210519","20210520","20210526","20210531","20210602","20210603","20210607","20210610","20210616","20210617","20210619","20210621","20210626","20211108","20211111","20211114","ImageNet01","ImageNet02","ImageNet03","ImageNet04","MRI"],"sessions_count":25,"demographics":{"subjects_count":31,"age_min":18,"age_max":26},"data_summary":{"total_files":82320,"size_bytes":230970282183,"size_human":"215 GB"},"provenance":{"latest_snapshot":"v1.0.0","publish_date":"2026-06-27 22:06:45"},"external_links":{"dataset_doi":"10.82901/nemar.on005810","github_url":"https://github.com/nemarDatasets/on005810"},"extensions":{"nemar":{"versions":[{"version":"v1.0.0","doi":"10.82901/nemar.on005810.v1.0.0","created_at":"2026-06-27 22:06:45","manifest_url":"/on005810/v1.0.0/manifest.json"}],"bids_index":{"version":"v1.0.0","subjects":{"sub-01":{"sessions":["ImageNet01","ImageNet02","ImageNet03","ImageNet04","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05","06","07","08"]}}}}},"sub-02":{"sessions":["ImageNet01","ImageNet02","ImageNet03","ImageNet04","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05","06","07","08"]}}}}},"sub-03":{"sessions":["ImageNet01","ImageNet02","ImageNet03","ImageNet04","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05","06","07","08"]}}}}},"sub-04":{"sessions":["ImageNet01","ImageNet02","ImageNet03","ImageNet04","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05","06","07","08"]}}}}},"sub-05":{"sessions":["ImageNet01","ImageNet02","ImageNet03","ImageNet04","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05","06","07","08"]}}}}},"sub-06":{"sessions":["ImageNet01","ImageNet02","ImageNet03","ImageNet04","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05","06","07","08"]}}}}},"sub-07":{"sessions":["ImageNet01","ImageNet02","ImageNet03","ImageNet04","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05","06","07","08"]}}}}},"sub-08":{"sessions":["ImageNet01","ImageNet02","ImageNet03","ImageNet04","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05","06","07","08"]}}}}},"sub-09":{"sessions":["ImageNet01","ImageNet02","ImageNet03","ImageNet04","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05","06","07","08"]}}}}},"sub-10":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-11":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-12":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-13":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-14":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-15":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-16":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-17":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-18":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-19":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-20":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-21":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-22":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-23":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-24":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-25":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-26":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-27":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-28":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-29":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-30":{"sessions":["ImageNet01","MRI"],"modalities":{"anat":{"tasks":{}},"meg":{"tasks":{"ImageNet":{"runs":["01","02","03","04","05"]}}}}},"sub-emptyroom":{"sessions":["20210413","20210428","20210512","20210513","20210519","20210520","20210526","20210531","20210602","20210603","20210607","20210610","20210616","20210617","20210619","20210621","20210626","20211108","20211111","20211114"],"modalities":{"meg":{"tasks":{"noise":{"runs":[]}}}}}}},"pipeline_stage":"validated","data_complete":1,"bytes_present":230950697567}}}