{"dataset":{"id":"426","dataset_id":"nm000150","name":"The Brain, Body, and Behaviour Dataset (1.0.0) - Experiment 1","description":"The Brain, Body, and Behaviour Dataset (Experiment 1) is a multimodal neuroimaging dataset comprising eye-tracking recordings from 27 subjects across two sessions during educational video viewing. Subjects watched five informative videos under two conditions: an attentive condition with post-video comprehension testing, and a distracted condition with concurrent cognitive load (backward counting). The dataset includes gaze coordinates, pupil size, blinks, saccades, and fixations, along with behavioral questionnaires assessing domain knowledge and memory retention, providing a resource for studying attention, learning, and cognitive engagement during multimedia presentation.","owner_user_id":19,"status":"active","github_repo":"nemarDatasets/nm000150","concept_doi":"10.82901/nemar.nm000150","latest_version_doi":"10.82901/nemar.nm000150.v1.0.0","created_at":"2026-04-13 21:37:59","updated_at":"2026-07-10 21:48:35","zenodo_concept_id":"20737984","is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"enriched\",\n  \"title\": \"The Brain, Body, and Behaviour Dataset (1.0.0) - Experiment 1\",\n  \"description\": \"The Brain, Body, and Behaviour Dataset (Experiment 1) is a multimodal neuroimaging dataset comprising eye-tracking recordings from 27 subjects across two sessions during educational video viewing. Subjects watched five informative videos under two conditions: an attentive condition with post-video comprehension testing, and a distracted condition with concurrent cognitive load (backward counting). The dataset includes gaze coordinates, pupil size, blinks, saccades, and fixations, along with behavioral questionnaires assessing domain knowledge and memory retention, providing a resource for studying attention, learning, and cognitive engagement during multimedia presentation.\",\n  \"methods_description\": \"Eye-tracking data were collected while subjects viewed five educational videos under two experimental conditions: attentive (with post-video multiple-choice questions) and distracted (with concurrent backward counting task). Raw data were converted from MATLAB .mat files to standardized formats (.tsv.gz for eye-tracking recordings) using MATLAB. Recorded modalities include gaze position (X, Y coordinates), pupil size, blinks, saccades, and fixations. Preprocessing derivatives include saccade detection, fixation identification, blink detection, and filtered pupil and gaze data.\",\n  \"license\": \"CC BY 4.0\",\n  \"dataset_type\": \"derivative\",\n  \"authors\": {\n    \"Jens Madsen\": {\n      \"orcid\": \"0000-0001-8163-001X\"\n    },\n    \"Nikhil Kuppa\": {},\n    \"Lucas Parra\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"eye tracking\"\n    },\n    {\n      \"term\": \"attention\"\n    },\n    {\n      \"term\": \"learning\"\n    },\n    {\n      \"term\": \"pupil size\"\n    },\n    {\n      \"term\": \"gaze\"\n    },\n    {\n      \"term\": \"educational videos\"\n    },\n    {\n      \"term\": \"cognitive load\"\n    },\n    {\n      \"term\": \"multimedia learning\"\n    },\n    {\n      \"term\": \"video comprehension\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"10.1101/2025.04.29.651259\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"References\"\n    },\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/nm000150\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataexplorer/detail?dataset_id=nm000150\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.1038/s41597-026-07215-1\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"funding_references\": [\n    {\n      \"funder_name\": \"National Science Foundation\",\n      \"award_number\": \"DRL-1660548\"\n    },\n    {\n      \"funder_name\": \"National Science Foundation\",\n      \"award_number\": \"DRL-2201835\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"Neuroimaging Dataset\",\n  \"modalities\": [\n    \"beh\"\n  ],\n  \"sizes\": [\n    \"923.3 MB (2913 files)\"\n  ],\n  \"formats\": [\n    \".gz\",\n    \".json\",\n    \".md\",\n    \".sh\",\n    \".tsv\",\n    \".yml\"\n  ],\n  \"source_hash\": \"117406204cc03dd9805a13a9841268527985a43e3996754bd0416845ea05fcca\"\n}","last_activity_at":"2026-06-03 17:55:25","source":null,"source_id":null,"subject_count":null,"modalities":"beh","age_min":null,"age_max":null,"file_size":923266093,"total_files":2913,"tasks":"stim01,stim02,stim03,stim04,stim05","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Jens Madsen, Nikhil Kuppa, Lucas Parra","license":"CC BY 4.0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.nm000150-blue)](https://doi.org/10.82901/nemar.nm000150)\n\n# The Brain, Body, and Behaviour Dataset - Experiment 1 \n## Summary:\n\n**Description:**  Subjects watched five videos, knowing they'd be tested afterward. After each video, they answered 11 to 12 factual multiple-choice questions. Videos and questions were presented in random order.\n\n**Subjects:**  27, **Sessions:**  2 \n1. *Attentive* - Watch videos with focus and answer questions after\n2. *Distracted* - Watch videos while counting backwards in your head, no test after watching\n\n# Tasks (Stimuli)\n\n## Experiment 1\n------------------------------------------------------------------------------------------------------------------------\n| **Stimulus ID** | **Name**                                 | **URL**                                                 |\n|-----------------|------------------------------------------|---------------------------------------------------------|\n| Stim-01         | Why are Stars Star-Shaped                | [Watch Here](https://www.youtube.com/embed/VVAKFJ8VVp4) |\n| Stim-02         | How Modern Light Bulbs Work              | [Watch Here](https://www.youtube.com/embed/oCEKMEeZXug) |\n| Stim-03         | The Immune System Explained – Bacteria   | [Watch Here](https://www.youtube.com/embed/zQGOcOUBi6s) |\n| Stim-04         | Who Invented the Internet - And Why      | [Watch Here](https://www.youtube.com/embed/21eFwbb48sE) |\n| Stim-05         | Why Do We Have More Boys Than Girls      | [Watch Here](https://www.youtube.com/embed/3IaYhG11ckA) |\n|----------------------------------------------------------------------------------------------------------------------|\n\n**Modalities Recorded:**\n-   Gaze (X, Y)\n-   Pupil Size\n-   Blinks\n-   Saccades\n-   Fixations\n\n# Experiment Setup:\nIn experiment 1 we only performed eye tracking, where our subjects watched 5 different informative videos and we tracked their gaze and pupil size. The position of gaze is an indicator of attention and this information is useful in knowing what points of the video they’re focused on and at what points their mind starts wandering away. This experiment was **intentional** learning because the subjects knew they would be questioned about the contents of the video.\n\nSessions:\n\n-   Ses-01 contains these signals recorded on subjects watching these videos in an attentive condition. They answered questions pertaining to each video after watching the videos one at a time.\n-   Ses-02 contains the data recorded on subjects watching all of the videos again in a distracted condition in the same order as Ses-01 described above. The distraction from the stimuli was to silently count backwards from a random prime number in steps of 7. No questions were asked after this session.\n\n# Questionnaires:  \nQuestionnaires and answers to them can be found in the phenotype/ directory.\n\n1.  **stimuli_questionnaire:**\n\nThe stimuli_questionnaire tsv and json files have the questions, answers and correct answers.\n\n- “Domain” question type is a general domain knowledge question that was asked before the subject watched a video.\n- “Memory” question type is a memory testing question that is asked after the subject finishes watching the video, and has questions that are directly pertaining to the video content.\n\n# General BIDS dataset structure overview for all MEVD experiments\n\nEach BIDS dataset (one per experiment) has files that describe the dataset, its participants, and related metadata at the root directory - dataset_description.json, participants.tsv and participants.json, providing essential information about the study and participants to anyone working with the dataset.\n\nIn the root directory, the raw data of each participant is organized by subject (sub-XX) and then further divided into sessions (ses-XX) to accommodate multi-session data collection (some experiments have 2 sessions: attentive and distracted). Inside each session folder, you'll find modality-specific subfolders, such as:\n\n-   **eeg**: Contains electroencephalogram data files (.bdf), event logs (events.tsv), and additional metadata (.json) that describe the experiment and recording conditions.  \n    \n-   **beh**: Contains physiological recordings like ECG (electrocardiogram) and EOG (electrooculogram) stored in compressed .tsv.gz files, with accompanying metadata in .json files.  \n    \n-   **eyetrack**: Contains physiological recordings like eye-tracking (gaze coordinates and pupil size), and head movement data, stored in compressed .tsv.gz files, with accompanying metadata in .json files.\n-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n| Modality  | Filename Format                                                     | Data File Extension | Metadata                                     | Notes                                                                                      |\n|-----------|---------------------------------------------------------------------|---------------------|----------------------------------------------|--------------------------------------------------------------------------------------------|\n| EEG       | `sub_xx-ses_xx-task-stimxx_{file_of_interest.extension}`            | `.bdf`              | Exists for each file as a `.json` file       |  There are event files with a `.tsv` extension that include start and end times in seconds.|\n| Beh       | `sub_xx-ses_xx-task-stimxx_recording-{modality}_physio.{extension}` | `.tsv.gz`           | Exists for each file as a `.json` file       |                                                                                            |\n| EyeTrack  | `sub_xx-ses_xx-task-stimxx_{modality}_eyetrack.{extension}`         | `.tsv.gz`           | Exists for each file as a `.json` file       |                                                                                            |\n-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n\nThere is also a **derivatives** directory which contains preprocessed data derived from the raw recordings, such as filtered heart rate data or preprocessed physiological signals, making it easy to work with and apply advanced analyses. Files in this directory are also stored in the BIDS structure (subject-wise → session-wise → modality-wise). A brief overview on what you can expect in the derivatives directory:\n\n-   **eeg**: Contains filtered electroencephalogram (EEG) data files (.bdf).  \n-   **beh**: Contains heart beats (r-peak timestamps synchronized with the stimulus), heart-rates, filtered ECG, breath-rates, and they are stored in compressed .tsv.gz files.  \n-   **eyetrack**: Contains saccades (timestamps), saccade-rates, fixations (timestamps), fixation-rates, blinks (timestamps), blink-rates, and filtered pupil and gaze files all stored in compressed .tsv.gz files.\n    \n\n## How to Navigate the Dataset\n\n-   **Top-Level Files**: Files like dataset_description.json and participants.tsv give you an overview of the study and participants, serving as your starting point when exploring a dataset.\n    \n-   **Derivatives Folder**: In this folder, processed data is organized like how raw data is organized in the BIDS directory.\n    \n-   **Subject Folders (sub-XX):** Inside these folders, data is organized by individual participants, providing separate directories for each person involved in the study.\n    \n-   **Session Folders (ses-XX)**: For longitudinal or multi-session studies, session folders contain the raw and derived data for each session, making it easy to track and analyze data collected over time.\n    \n-   **Modality-Specific Subfolders:** Each session is further split into subfolders according to data modalities (e.g., EEG, behavior/physio), helping you to quickly locate the data of interest, whether it’s br","bids_version":"1.10.0","sessions_count":2,"publish_date":"2026-04-13 21:37:59","embedding_dirty":0,"license_tier":"attribution","zarr_status":"ready","zarr_converted_at":"2026-09-06 02:11:04","zarr_store_count":0,"zarr_index_etag":"e06f42d9afedcdbd5f8d58c7f80c12af","zarr_source_commit":"2df02a0f33b8d5b89ec66cb1c57dc3e7e53d7609","archive_status":"ready","archive_size":924379627,"archive_retry_count":0,"records_status":"ready","archive_skip_reason":null,"zarr_errors":0,"zarr_failure_count":0,"zarr_deterministic":0,"zarr_failed_at":null,"num_dataset_citations":0,"num_datapaper_citations":0,"n_channels":null,"electrode_system":null,"has_hed":0,"hed_version":null,"is_exemplar":0,"bytes_present":null,"data_complete":null,"withdrawn_at":null,"withdrawn_reason":null,"archive_complete":null,"archive_absent_files":null,"archive_declared_files":null,"zarr_pool_breaks":0,"total_recording_duration":null,"recording_duration_min":null,"recording_duration_max":null,"recording_count":0,"recordings_unavailable":0,"recordings_measured":0,"channel_count_min":null,"channel_count_max":null,"sampling_frequency":null,"power_line_frequency":null,"eeg_reference":null,"placement_scheme":null,"sweep_stamps":"{\"enrichment_updated_at\":\"2026-06-17 20:29:22\",\"metadata_updated_at\":\"2026-06-18 06:27:26\",\"archive_checked_at\":\"2026-06-17 20:34:34\",\"zarr_checked_at\":null,\"records_checked_at\":\"2026-06-17 20:31:26\",\"citations_updated_at\":null,\"channel_montage_checked_at\":null,\"hed_checked_at\":\"2026-06-30 04:12:29\",\"data_checked_at\":null,\"availability_report_at\":\"2026-07-23 01:05:54\",\"signal_defaults_at\":\"2026-09-02 11:39:18\",\"recording_stats_at\":\"2026-09-06 03:00:36\"}","participants":0,"num_citations":0,"latest_version":"v1.0.0","zarr_verify_status":null,"zarr_verified_at":null,"owner_username":"bruaristimunha","owner_github":"bruAristimunha","file_size_formatted":"880 MB","zarr_data_failures":null,"zarr_index_url":"https://zarr.nemar.org/nm000150/zarr/index.json","attestation_deposit_type":null,"attestation_key_status":null,"attestation_deidentified":null,"attestation_no_duplicate":null,"attestation_upstream_source":null,"attestation_accepted_at":null}}