{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a3338","dataset_id":"ds004330","associated_paper_doi":null,"authors":["Johannes J.D. Singer","Radoslaw M. Cichy","Martin N. Hebart"],"bids_version":"1.7.0","contact_info":["Johannes Janek Daniel Singer"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds004330.v1.0.0","datatypes":["meg"],"demographics":{"subjects_count":30,"ages":[],"age_min":null,"age_max":null,"age_mean":null,"species":null,"sex_distribution":null,"handedness_distribution":null},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds004330","osf_url":null,"github_url":null,"paper_url":null},"funding":["ERC-StG-2021-101039712","CI241/1-1","CI241/3-1","CI241/7-1","ERC-StG-2018-803370"],"ingestion_fingerprint":"1cf701d0b0f9aac35d07e251ffbc7c8699c881a64945355bc522df119641c3bc","license":"CC0","n_contributing_labs":null,"name":"The spatiotemporal neural dynamics of object recognition for natural images and line drawings (MEG)\n","readme":"This dataset contains the raw MEG data accompanying the paper \"The spatiotemporal neural dynamics of object recognition for natural images and line drawings\" (Link to preprint: https://biorxiv.org/cgi/content/short/2022.08.12.503484v1). Please cite the above paper if you use this data.\nThe dataset includes:\nMEG data for 9 runs for each subjects. Events files that contain the onsets, durations and trial types for each trial in the experiment (excluding catch trials).\nFor a full description of the paradigm and the employed procedures please see the manuscript.\nResults for the first-level analyses for this data can be found on OSF (https://osf.io/vsc6y/). Code for the analysis of the data can be found on Github (https://github.com/Singerjohannes/object_drawing_dynamics/).","recording_modality":["meg"],"senior_author":"Martin N. Hebart","sessions":["01"],"size_bytes":165027293648,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["main"],"timestamps":{"digested_at":"2026-04-22T12:26:27.591417+00:00","dataset_created_at":"2022-11-07T14:41:49.699Z","dataset_modified_at":"2022-11-08T10:16:44.000Z"},"total_files":270,"storage":{"backend":"s3","base":"s3://openneuro.org/ds004330","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"542ecdd4c04e7f76","model":"openai/gpt-5.2","tagged_at":"2026-01-20T10:36:38.553823+00:00"},"tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Perception"],"confidence":{"pathology":0.6,"modality":0.8,"type":0.8},"reasoning":{"few_shot_analysis":"Closest few-shot conventions: (1) The schizophrenia visual discrimination dataset is labeled Visual + Perception because it uses visual stimuli and the goal is perceptual judgment/recognition; this supports mapping an object-recognition paradigm with visual stimuli to Modality=Visual and Type=Perception. (2) The music-vs-speech ABR dataset is labeled Auditory + Perception because the primary focus is sensory processing of stimuli; by analogy, a dataset focused on object recognition dynamics for images/drawings aligns with Perception rather than Learning/Memory.","metadata_analysis":"Key phrases indicating a visual object recognition paradigm: (1) \"The spatiotemporal neural dynamics of object recognition for natural images and line drawings\". (2) \"Events files that contain the onsets, durations and trial types for each trial in the experiment\" (implies an active stimulus-driven task rather than resting/sleep). No metadata indicates a clinical recruitment or diagnosis; the README only describes the experimental paradigm and data contents (\"raw MEG data\").","paper_abstract_analysis":"No useful paper information.","evidence_alignment_check":"Pathology: Metadata SAYS no diagnosis/clinical group is mentioned (only \"raw MEG data\" and task description). Few-shot pattern SUGGESTS that when no disorder is described and the dataset is a standard cognitive task, label as Healthy. ALIGN (no conflict).\nModality: Metadata SAYS \"object recognition for natural images and line drawings\" (visual stimuli). Few-shot pattern SUGGESTS natural images/drawings are Visual modality. ALIGN.\nType: Metadata SAYS \"object recognition\" with stimulus categories (images vs line drawings), which is primarily sensory/perceptual recognition. Few-shot pattern SUGGESTS discrimination/recognition of sensory stimuli maps to Perception rather than Decision-making/Motor/Resting-state. ALIGN.","decision_summary":"Top-2 candidates per category:\nPathology: (A) Healthy — supported by absence of any clinical recruitment/diagnosis in README and typical basic MEG perception study framing (\"object recognition\"). (B) Unknown — plausible because participants are not explicitly described. Winner: Healthy (metadata implies a normative cognitive experiment; no clinical terms).\nModality: (A) Visual — supported by \"natural images and line drawings\" and \"object recognition\". (B) Multisensory — unlikely; no auditory/tactile cues mentioned. Winner: Visual.\nType: (A) Perception — supported by \"object recognition\" of visual stimuli and trial-based events. (B) Memory — possible if it were a recognition-memory test, but no memory/encoding/recall language is present. Winner: Perception.\nConfidence justifications: Pathology lower because there is no explicit participant description/health status quote; Modality and Type higher because the task/stimulus goal is explicitly stated (\"object recognition for natural images and line drawings\")."}},"nemar_citation_count":1,"computed_title":"The spatiotemporal neural dynamics of object recognition for natural images and line drawings (MEG)","nchans_counts":[{"val":310,"count":270}],"sfreq_counts":[{"val":1000.0,"count":270}],"stats_computed_at":"2026-04-22T23:16:00.307398+00:00","total_duration_s":132057.73,"author_year":"Singer2022","canonical_name":null}}