{"success":true,"database":"eegdash","data":{"_id":"6953f4249276ef1ee07a33dd","dataset_id":"ds005397","associated_paper_doi":null,"authors":["Christopher Hilton","Lilian Befort","Ronja Brinkmann","Matthias Ballestrem","Joerg Fingerhut","Klaus Gramann"],"bids_version":"1.6.0","contact_info":["Christopher Hilton"],"contributing_labs":null,"data_processed":false,"dataset_doi":"doi:10.18112/openneuro.ds005397.v1.0.4","datatypes":["eeg"],"demographics":{"subjects_count":26,"ages":[24,22,24,23,25,34,33,27,23,55,30,24,30,30,24,25,30,25,23,23,27,27,27,24,33,32],"age_min":22,"age_max":55,"age_mean":27.846153846153847,"species":null,"sex_distribution":{"m":10,"f":16},"handedness_distribution":{"r":26}},"experimental_modalities":null,"external_links":{"source_url":"https://openneuro.org/datasets/ds005397","osf_url":null,"github_url":null,"paper_url":null},"funding":[],"ingestion_fingerprint":"5f6de5574e937c84bb4ff48ac6dab9ec4dee3680800486bc977a51b7f299a1c8","license":"CC0","n_contributing_labs":null,"name":"Affordances of stairs","readme":"An EEG dataset and behavioural response data for a task that required participants to view images of scenes and rate their aesthetic properties (beauty, complexity, interestingness), or rate their appropriateness for either a reading activity, or a social activity.\nYou can also find the behavioural data already extracted from the EEG events for convenience, and the full stimuli set with identifiable file names.\nFor detailed information about the methods and an analysis of the data please see the published article: https://doi.org/10.1016/j.jenvp.2025.102528\nContact: c.hilton@tu-berlin.de in case of questions.","recording_modality":["eeg"],"senior_author":"Klaus Gramann","sessions":[],"size_bytes":12872404161,"source":"openneuro","study_design":null,"study_domain":null,"tasks":["tectonic"],"timestamps":{"digested_at":"2026-04-22T12:27:43.878442+00:00","dataset_created_at":"2024-08-01T12:27:38.523Z","dataset_modified_at":"2025-11-10T12:51:56.000Z"},"total_files":26,"storage":{"backend":"s3","base":"s3://openneuro.org/ds005397","raw_key":"dataset_description.json","dep_keys":["CHANGES","README","participants.json","participants.tsv","task-tectonic_events.json"]},"tagger_meta":{"config_hash":"4a051be509a0e3d0","metadata_hash":"c551a399f7f9cb0b","model":"openai/gpt-5.2","tagged_at":"2026-01-20T17:51:00.669753+00:00"},"tags":{"pathology":["Healthy"],"modality":["Visual"],"type":["Affect"],"confidence":{"pathology":0.6,"modality":0.8,"type":0.7},"reasoning":{"few_shot_analysis":"Closest few-shot convention match on stimulus/task format is the healthy visual rating/valuation style in the example “EEG: Three armed bandit gambling task” (Healthy, Visual, Affect): although the content differs (gambling vs aesthetics), both involve evaluating visually presented stimuli and producing subjective ratings/valuation-related responses, which is typically mapped to Type=Affect rather than Perception. As a contrasting visual example, “Meta-rdk: Preprocessed EEG data” (Schizophrenia/Psychosis, Visual, Perception) is a visual discrimination task (left/right motion), illustrating that when the goal is sensory discrimination it maps to Perception—unlike the present dataset’s aesthetic judgments.","metadata_analysis":"Key task facts come directly from the README:\n1) Stimulus/input channel is visual: “participants to view images of scenes”.\n2) The purpose is subjective evaluation/valuation of aesthetics and context suitability: “rate their aesthetic properties (beauty, complexity, interestingness), or rate their appropriateness for either a reading activity, or a social activity.”\nNo explicit recruitment/diagnosis information is given (no mention of patient groups, disorders, or special populations).","paper_abstract_analysis":"No useful paper information (only a DOI link is provided in metadata; no abstract text included here).","evidence_alignment_check":"Pathology: Metadata SAYS nothing about a clinical population (no diagnosis/recruitment descriptors; only task description). Few-shot pattern SUGGESTS many such cognitive/affective EEG tasks are run in Healthy cohorts, but this is an inference. ALIGNMENT: weak (metadata is silent; no conflict).\nModality: Metadata SAYS visual stimuli: “view images of scenes”. Few-shot pattern SUGGESTS Visual for image-based tasks. ALIGNMENT: yes.\nType: Metadata SAYS aesthetic/appropriateness ratings: “rate their aesthetic properties (beauty, complexity, interestingness)” and “rate their appropriateness…”. Few-shot pattern SUGGESTS mapping subjective valuation/affective appraisal to Affect (as in the bandit/gambling valuation example), whereas Perception is used for sensory discrimination (as in visual motion discrimination). ALIGNMENT: yes (affective appraisal better matches than sensory perception).","decision_summary":"Pathology top-2: (1) Healthy — evidence: metadata provides no clinical recruitment and describes a standard behavioral rating task with stimuli; (2) Unknown — evidence: no explicit participant health statement. Winner: Healthy (common convention for non-clinical aesthetic rating datasets, but inferred). Alignment status: inference due to metadata silence.\nModality top-2: (1) Visual — evidence: “view images of scenes”; (2) Other/Multisensory — only if non-visual stimuli existed (not indicated). Winner: Visual. Alignment status: aligned.\nType top-2: (1) Affect — evidence: “rate their aesthetic properties (beauty, complexity, interestingness)” implies affective/aesthetic appraisal; (2) Decision-making — ratings/choices could be framed as decisions, but the construct is aesthetic evaluation rather than choice policy/value-learning. Winner: Affect. Alignment status: aligned."}},"nemar_citation_count":0,"computed_title":"Affordances of stairs","nchans_counts":[{"val":64,"count":26}],"sfreq_counts":[{"val":500.0,"count":26}],"stats_computed_at":"2026-04-21T23:17:03.731573+00:00","total_duration_s":100523.306,"author_year":"Hilton2024","canonical_name":null}}