{"dataset":{"id":"61264","dataset_id":"on008083","name":"Hierarchical Priors in Perceptual Uncertainty and Psychosis Proneness - A Random-Dot Kinematogram task with low- and high-level priors","description":"This dataset contains cue-locked EEG recordings and behavioral event annotations from 43 healthy adults performing a random-dot kinematogram (RDK) task designed to dissociate low-level and high-level hierarchical priors during perceptual decision-making. The study examines how such priors bias behavior via signal detection theory and generalized drift-diffusion modeling, and how they modulate occipital oscillatory and aperiodic EEG activity. Participants also completed questionnaires assessing psychosis proneness and psychological flexibility traits.","owner_user_id":15,"status":"active","github_repo":"nemarDatasets/on008083","concept_doi":"10.82901/nemar.on008083","latest_version_doi":"10.82901/nemar.on008083.v1.0.0","created_at":"2026-07-02 08:01:37","updated_at":"2026-08-18 23:25:01","zenodo_concept_id":null,"is_sandbox":0,"visibility":"public","ezid_status":"public","enrichment_json":"{\n  \"version\": \"2.0\",\n  \"pipeline_stage\": \"validated\",\n  \"title\": \"Hierarchical Priors in Perceptual Uncertainty and Psychosis Proneness - A Random-Dot Kinematogram task with low- and high-level priors\",\n  \"description\": \"This dataset contains cue-locked EEG recordings and behavioral event annotations from 43 healthy adults performing a random-dot kinematogram (RDK) task designed to dissociate low-level and high-level hierarchical priors during perceptual decision-making. The study examines how such priors bias behavior via signal detection theory and generalized drift-diffusion modeling, and how they modulate occipital oscillatory and aperiodic EEG activity. Participants also completed questionnaires assessing psychosis proneness and psychological flexibility traits.\",\n  \"methods_description\": \"Continuous EEG was recorded from 31 active Ag/AgCl electrodes (10/20 system) using an actiChamp Plus amplifier at 1000 Hz, referenced online to FCz with ground at FPz. Participants performed a random-dot kinematogram task with auditory cues predicting motion direction under baseline, low-level prior, and high-level prior conditions, with individualized motion coherence set via QUEST staircases targeting 75% discrimination accuracy.\",\n  \"license\": \"CC0\",\n  \"dataset_type\": \"raw\",\n  \"authors\": {\n    \"Jonathan Buchholz\": {},\n    \"Guido Hesselmann\": {}\n  },\n  \"keywords\": [\n    {\n      \"term\": \"EEG\"\n    },\n    {\n      \"term\": \"perceptual decision-making\"\n    },\n    {\n      \"term\": \"random-dot kinematogram\"\n    },\n    {\n      \"term\": \"drift-diffusion model\"\n    },\n    {\n      \"term\": \"psychosis proneness\"\n    },\n    {\n      \"term\": \"signal detection theory\"\n    },\n    {\n      \"term\": \"aperiodic activity\"\n    }\n  ],\n  \"related_identifiers\": [\n    {\n      \"identifier\": \"https://github.com/nemarDatasets/on008083\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"https://nemar.org/dataset/on008083\",\n      \"identifier_type\": \"URL\",\n      \"relation_type\": \"IsDescribedBy\"\n    },\n    {\n      \"identifier\": \"10.18112/openneuro.ds008083.v1.0.0\",\n      \"identifier_type\": \"DOI\",\n      \"relation_type\": \"IsDerivedFrom\"\n    }\n  ],\n  \"resource_type_general\": \"Dataset\",\n  \"resource_type_specific\": \"EEG Dataset\",\n  \"modalities\": [\n    \"eeg\"\n  ],\n  \"sizes\": [\n    \"9.4 GB (45 files)\"\n  ],\n  \"formats\": [\n    \".csv\",\n    \".edf\",\n    \".json\",\n    \".md\",\n    \".tsv\",\n    \".yml\"\n  ],\n  \"source_hash\": \"40368573095b3307c8ad30381f6a1e21a9a6e6664fb2efb18666da1aa957b549\"\n}","last_activity_at":"2026-07-02 08:01:37","source":"openneuro","source_id":"ds008083","subject_count":43,"modalities":"eeg","age_min":18,"age_max":40,"file_size":9409738867,"total_files":355,"tasks":"HierPrior","metadata_columns_error":null,"staleness_warn_stage":null,"staleness_admin_notified_at":null,"authors":"Jonathan Buchholz, Guido Hesselmann","license":"CC0","readme":"[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on008083-blue)](https://doi.org/10.82901/nemar.on008083)\n\n# README: Experiment Guide — Hierarchical Priors RDK EEG Task\n\nThis file provides a experimental guide linking the analysis of *Buchholz & Hesselmann (in review) - Hierarchical Priors Shape Dynamic Evidence Accumulation and Aperiodic EEG Activity* with the here provided data and code. This can be used as an assisting tool for first running a semi-automated BIDS-EEG pipeline.\n\nThis EEG-BIDS dataset contains cue-locked EEG recordings and event annotations from a random-dot kinematogram (RDK) task designed to dissociate low-level and high-level priors during perceptual decision-making. The accompanying analysis tests whether hierarchical priors bias behavior through signal detection theory (SDT) and generalized drift-diffusion modeling (gDDM), and whether they modulate occipital oscillatory or aperiodic EEG activity.\n\nThe trial-level variables needed for analysis are stored in `epochs.metadata` and are illustrated by the accompanying `metadata.csv` file. Each row corresponds to one cue-locked epoch/trial retained in the MNE `Epochs` object. Participant-level questionnaire and trait variables are stored in `trait_variables.csv`, with one row per participant. Additionally, [trigger codes](#trigger-codes) stored as annotations enable (less flexible) trial-wise analyses.\n\n## Data collection\n\nData were collected from neurotypical adults with normal or corrected-to-normal vision and no neurological or psychiatric diagnoses. Fifty-three participants were tested; twelve were excluded for failing the preregistered discrimination-performance criterion, leaving 43 participants in the final sample (27 female, 1 trans; mean age 24.47 +/- 5.46 years). Participants gave written informed consent, were tested in the EEG laboratory of Psychologische Hochschule Berlin, and received course credit or monetary compensation.\n\nStimuli were random-dot kinematograms (RDKs) with 1200 white dots (0.078 deg; 2.53 deg/s) presented inside a circular aperture (radius 9.09 deg). A subset of dots moved coherently leftward or rightward while the remaining dots moved randomly; dot lifetime was limited to 24 frames (~100 ms). Stimuli were presented with PsychoPy on a 24.5-inch LCD monitor (240 Hz refresh rate) at a fixed viewing distance of 65 cm. Auditory cues were delivered for 500 ms at 84.8 dB(A); each trial then included an approximately 1000 ms fixation-only interval, RDK presentation for up to approximately 3000 ms or until response, and a jittered 1000-1500 ms intertrial interval.\n\nThe experiment used a within-subject design with three conditions: baseline/no prior, low-level prior, and high-level prior. Baseline blocks used a neutral 750 Hz tone and comprised 8 blocks of 20 trials. Low-level priors were induced implicitly by 600/900 Hz tones that predicted leftward or rightward motion with 75% contingency; tone-motion mappings were counterbalanced, learned across 3 blocks of 20 trials, and tested across 8 blocks of 20 trials. High-level priors were induced by a standardized cover story about tinted glasses that allegedly enhanced leftward or rightward motion; beliefs were reinforced across 4 learning blocks of 20 trials and tested across 8 blocks of 20 trials. Condition order was fully counterbalanced, and 160 trials per condition entered the main analyses.\n\nBefore the experiment, individual motion sensitivity was estimated with two 40-trial QUEST staircases targeting 75% discrimination accuracy. The final threshold defined medium coherence; low and high coherence were 50% and 200% of this threshold, respectively. Learning blocks overrepresented medium- and high-coherence trials to support prior acquisition, whereas baseline and test blocks overrepresented low-coherence trials and contained no high-coherence trials to increase reliance on prior information.\n\nContinuous EEG was recorded from 31 active Ag/AgCl electrodes arranged according to the international 10/20 system using an actiChamp Plus amplifier at 1000 Hz. The ground electrode was placed at FPz and data were online referenced to FCz. Electrode impedances were kept below 20 kOhm, and participants were instructed to minimize blinks, saccades, muscle activity, and body movement during recording. Post-experimental questionnaires assessed demographics, manipulation checks, belief strength, psychosis proneness, and psychological flexibility/inflexibility traits. These participant-level variables are documented in `[trait_variables.csv](#traits_cleancsv-questionnaire-and-trait-column-dictionary)`.\n\n## Task summary\n\nEach trial followed this sequence:\n\n1. auditory cue/tone onset;\n2. fixation-only interstimulus interval (ISI; approximately 1000 ms);\n3. RDK onset with leftward or rightward net motion at individualized coherence;\n4. left/right response, followed by a jittered intertrial interval (ITI; approximately 1000–1500 ms).\n\nMotion coherence was individualized with two QUEST staircases targeting 75% discrimination accuracy. The resulting threshold defined the medium coherence level. Low coherence was 50% of this threshold; high coherence was 200% of this threshold.\n\nThe experiment contained three within-subject conditions:\n\n- **Baseline / no prior** (`exp = base`): a neutral, nonpredictive 750 Hz tone preceded the RDK.\n- **Low-level prior** (`exp = lowlevel`): two tones (600/900 Hz) predicted leftward or rightward motion with 75% contingency. Participants were not informed about the tone-motion association.\n- **High-level prior** (`exp = highlevel`): the tone was neutral/nonpredictive, but participants wore transparent tinted glasses and were led to believe that the glasses enhanced perception of either leftward or rightward motion. This belief was reinforced during learning blocks before the analyzed test blocks.\n\nThe main analyses use baseline trials and prior-condition test trials. Learning blocks served to establish the tone-motion associations or glass beliefs and should not be included unless explicitly intended.\n\n## Raw BIDS events\n\nEach `*_events.tsv` file contains raw trigger-level events, and the `*_events.json` sidecar defines the BIDS event columns. Events are stored under `sub-0XX/ses-01/eeg/`.\n\n**BIDS naming note:** the provided example sidecar is named `task-RDK_events.json`, whereas the provided example events file is named `task-HierPrior_events.tsv`. For strict BIDS compatibility, task labels should be identical across the EEG data file, events file, and JSON sidecar.\n\n### Event columns\n\n\n| Column       | Meaning                                                           |\n| ------------ | ----------------------------------------------------------------- |\n| `onset`      | Event onset in seconds from the first stored data point.          |\n| `duration`   | Event duration in seconds. Non-informative in this dataset        |\n| `sample`     | Event onset in sampling points; first sample is 0.                |\n| `value`      | Numeric trigger/event code.                                       |\n| `trial_type` | Human-readable trigger label, for example `S_1`, `S_8`, or `R_1`. |\n\n\n### Trigger codes\n\n\n| `value` | `trial_type` | Meaning                                                                                               |\n| ------- | ------------ | ----------------------------------------------------------------------------------------------------- |\n| 1       | `S_1`        | left prior; tone (600/900 Hz) for low-level / left-enhancing glasses for high-level prior condition   |\n| 2       | `S_2`        | right prior; tone (600/900 Hz) for low-level / right-enhancing glasses for high-level prior condition |\n| 4       | `S_4`        | no prior; 750 Hz tone cue onset in baseline.                                                          |\n| 8       | `S_8`        | RDK onset with leftward net motion.                                                                   |\n| 16      | `S_16`       | RDK onset with rightward net motion.                                                                  |\n| 101     | `R_1`        | Correct response.                                              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