<p dir="ltr">The data here was generated during the study "Exploring flicker light mechanisms". This study measured personal characteristics before three magnetoencephalography (MEG) scans, investigating brain activity during rest and different flicker light conditions. After each flicker condition, participants rated aspects of their experience.</p><p dir="ltr">Personal characteristics include trait mental imagery, Phenomenological Control and previous experience with altered states of consciousness.</p><p dir="ltr">Barring exclusions, three 10-minute recordings are present for each participant: resting state, 15Hz flicker and "300Hz" sham flicker (where steady light was falsely described to the participant as light flashing too fast to perceive). This MEG data is preprocessed as outlined in the paper. Python scripts used to analyse the data for the paper are provided.</p><p dir="ltr">Survey data includes ratings of expectancy, experienced visual and auditory imagery and altered states of consciousness.</p><p dir="ltr">Additionally, the PsychoPy materials used to present the flicker conditions to participants is provided.</p>
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FAIR Self Assessment Summary
This text has been generated from a tool that has been adapted from the ARDC FAIR Assessment Tool
Findable
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Does the dataset have any identifiers assigned?
Global
Is the dataset identifier included in all metadata records/files describing the data?
Yes
How is the data described with metadata?
Comprehensively (see suggestion) using a recognised formal machine-readable metadata schema
What type of repository or registry is the metadata record in?
Data is in one place but discoverable through several registries
Accessible
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How accessible is the data?
Publicly accessible
Is the data available online without requiring specialised protocols or tools once access has been approved?
Standard web service API (e.g. OGC)
Will the metadata record be available even if the data is no longer available?
Yes
Interoperable
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What (file) format(s) is the data available in?
In a structured, open standard, machine-readable format
What best describes the types of vocabularies/ontologies/tagging schemas used to define the data elements?
Standardised vocabularies/ontologies/schema without global identifiers
How is the metadata linked to other data and metadata (to enhance context and clearly indicate relationships)?
Metadata is represented in a machine readable format, e.g. in a linked data format such as Resource Description Framework (RDF).
Reusable
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Which of the following best describes the license/usage rights attached to the data?
Standard machine-readable license (e.g. Creative Commons)
How much provenance information has been captured to facilitate data reuse?
Fully recorded in a machine-readable format