Clip 29 / Politieke vertegenwoordiging
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Stimuli
48 clips
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Transcript
Clip 30 / Politieke vertegenwoordiging
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Clip 31 / Politieke vertegenwoordiging
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Clip 32 / Politieke vertegenwoordiging
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Clip 33 / Klimaat en milieu
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Clip 34 / Klimaat en milieu
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Clip 35 / Klimaat en milieu
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Clip 36 / Klimaat en milieu
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Clip 37 / Gezondheidszorg
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Clip 38 / Gezondheidszorg
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Clip 39 / Gezondheidszorg
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Clip 40 / Gezondheidszorg
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Clip 41 / Migratie
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Clip 42 / Migratie
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Clip 43 / Migratie
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Clip 44 / Migratie
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Clip 45 / Armoede
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Clip 46 / Armoede
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Clip 47 / Armoede
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Clip 48 / Armoede
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Clip 49 / Onderwijs
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Clip 50 / Onderwijs
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Clip 51 / Onderwijs
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Clip 52 / Onderwijs
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Clip 53 / Economie en werkgelegenheid
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Clip 54 / Economie en werkgelegenheid
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Clip 55 / Economie en werkgelegenheid
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Clip 56 / Economie en werkgelegenheid
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Clip 57 / Internationale veiligheid en defensie
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Clip 58 / Internationale veiligheid en defensie
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Clip 59 / Internationale veiligheid en defensie
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Clip 60 / Internationale veiligheid en defensie
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Clip 61 / Criminaliteit en justitie
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Clip 62 / Criminaliteit en justitie
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Clip 63 / Criminaliteit en justitie
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Clip 64 / Criminaliteit en justitie
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Clip 65 / Begroting
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Clip 66 / Begroting
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Clip 67 / Begroting
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Clip 68 / Begroting
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Clip 69 / Wonen
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Clip 70 / Wonen
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Clip 71 / Wonen
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Clip 72 / Wonen
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Clip 73 / Staatsstructuur
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Clip 74 / Staatsstructuur
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Clip 75 / Staatsstructuur
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Clip 76 / Staatsstructuur
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How the study was run
Methodology
Overview
The hypotheses were tested by means of an experiment in which participants were exposed to political speeches on a range of themes. The gender of the speaker (man or woman) and the rhetorical style (agentic or communal) were varied. Evaluation of the politician was operationalised as perceived persuasiveness after exposure to a political speech.
Participants
This research was carried out with a sample of 30 Flemish men between 18 and 32 years old. Inclusion criteria were, voting age (18 or over) and the ability to understand material in Dutch. The mean age of the participants was M = 23.10 (SD = 4.04). Recruitment was by convenience sampling through social media and the networks of friends and family. In exchange for taking part in the experiment and completing a preceding survey, participants received compensation of EUR 60. Only male participants were recruited deliberately, since earlier research shows that male voters react more strongly to female leaders, and judge female politicians more harshly on persuasiveness and leadership (Huddy & Terkildsen, 1993; Madsen, 2019; Sigelman et al., 1986).
Design
The experiment was carried out in the Antwerp Social Lab at the University of Antwerp. At the start, participants signed an informed consent form and were informed about the course and the expected duration of the research, which was about one hour. During the experiment participants were exposed to 12 different audio fragments while their skin conductance was recorded.
Variation in speaking style together with the gender of the politician results in four possible conditions of the speech, per political theme: a female politician with an agentic speech, a female politician with a communal speech, a male politician with an agentic speech, and a male politician with a communal speech. In this experiment the conditions were distributed over the participants by within-subject randomisation. Each participant was exposed to three different fragments of each condition. The fragments were shown in random order.
Stimuli and pre-testing
Each audio fragment is a fictional political speech on a specific political theme. The 12 chosen themes are based on which themes Flemish voters consider most important according to De Stemming 2025 (Lefevere, 2025), such as climate change, migration or healthcare. The agentic versus communal framework (Bakan, 1966) and a dictionary of agentic and communal language, compiled by Pietraszkiewicz et al. (2019), were used to draw up a stereotypically masculine (agentic) and a stereotypically feminine (communal) variant for each political theme.
To guarantee the internal validity of the stimuli, a pre-test was carried out with five independent raters. They evaluated the speeches on three dimensions: agency-communion (1-9), valence (1-5) and arousal (1-5). Inter-rater reliability was evaluated and the results indicate a high degree of agreement for all dimensions: agency-communion (alpha = 0.987), valence (alpha = 0.882) and arousal (alpha = 0.940). These values indicate a strong consistency in the ratings, which suggests that the stimuli were interpreted in an unambiguous way. The speeches were then recorded by 12 different men and 12 different women. These audio recordings were strengthened in terms of intonation and expression with an AI tool.
Each audio fragment lasts between 68 and 105 seconds and is accompanied during the experiment by AI-generated photographs of fictional politicians. Every picture was generated in two versions: male and female, with all surrounding elements held constant. The generated photographs were evaluated by six independent raters (three men and three women) on perceived realism. The photographs were then assessed on attractiveness, b because attractive persons are systematically judged as more competent, more social and more positive (Eagly et al., 1991). This resulted in a selection of 48 photographs that were considered realistic and scored the same on attractiveness. From these, 12 pairs of photographs were selected at random: 12 men and 12 women.
Source
Lifted from the master's thesis of Emma Verbeeck, "Te mannelijk, te vrouwelijk - nooit goed: Is er een retorische strijd die vrouwelijke politici altijd verliezen?" (University of Antwerp, 2025-2026), section 4 Methode.
Notes
Master's thesis of Emma Verbeeck, supervised by Dr. Konrad Rudnicki and Dr. Willem Buyens, Antwerp Social Lab. Sample is 30 Flemish men aged 18-32.
Metadata
Variables
Every column of the three data tables, with its definition. The data themselves are not published; see the home page for access.
Participant level
participants.csv · one row per participant · 90 variables
| Variable | Description |
|---|---|
| Participant | Pseudonymous participant identifier |
| Age | Participant age in years |
| Gender | Participant gender, 1 = man, 0 = otherwise. This study recruited only men. |
| Extroversion | Participant extraversion score from the Big Five personality battery (BFI-2-S; Soto & John, 2017); sum of six items rated 1-5, range 6-30 |
| Agreeableness | Participant agreeableness score from the Big Five personality battery (BFI-2-S; Soto & John, 2017); sum of six items rated 1-5, range 6-30 |
| Conscientiousness | Participant conscientiousness score from the Big Five personality battery (BFI-2-S; Soto & John, 2017); sum of six items rated 1-5, range 6-30 |
| Neuroticism | Participant neuroticism score from the Big Five personality battery (BFI-2-S; Soto & John, 2017); sum of six items rated 1-5, range 6-30 |
| Openness | Participant openness score from the Big Five personality battery (BFI-2-S; Soto & John, 2017); sum of six items rated 1-5, range 6-30 |
| SVO_angle | Participant Social Value Orientation angle from the Social Value Orientation measure (SVO; Van Lange, 1999), in degrees; higher = more prosocial |
| LeftRightDSLV | Self-placed left-right ideological orientation, 0 = left to 10 = right. The thesis reports this item as RightWingID on a 1-10 scale; those values are this variable plus one. |
| LeftRight_EconDSLV | Participant economic left-right ideological self-placement score, 0 = left to 10 = right |
| LeftRight_CultDSLV | Participant cultural left-right ideological self-placement score, 0 = left to 10 = right |
| Authoritarianism | Right-wing authoritarianism, summed Very Short Authoritarianism scale (Bizumic & Duckitt): six items on a 1-9 agreement scale, with the three counter-worded items reversed. Range 6-54. This reproduces the VSA total reported in the thesis for every participant. |
| EmpathicConcern | Participant empathic-concern score from the Interpersonal Reactivity Index (IRI, Dutch version; De Corte et al., 2007); sum of seven items rated 1-5, range 7-35 |
| PerspectiveTaking | Participant perspective-taking score from the Interpersonal Reactivity Index (IRI, Dutch version; De Corte et al., 2007); sum of seven items rated 1-5, range 7-35 |
| Fantasy | Participant fantasy score from the Interpersonal Reactivity Index (IRI, Dutch version; De Corte et al., 2007); sum of seven items rated 1-5, range 7-35 |
| PersonalDistress | Participant personal-distress score from the Interpersonal Reactivity Index (IRI, Dutch version; De Corte et al., 2007); sum of seven items rated 1-5, range 7-35 |
| NeedForAffect | Participant need-for-affect score from the Need for Affect Questionnaire (NAQ-10; Appel & Richter, 2010); sum of ten items rated 1-7, range 10-70 |
| Handedness | Self-reported handedness: 'Are you left- or right-handed?' (Dutch response labels: Rechtshandig / Linkshandig / Andere) |
| EducationLevel | Highest completed level of education (Dutch response labels as administered) |
| Employment | Main occupation or activity (Dutch response labels as administered) |
| EmploymentOther | Free-text specification given by respondents who selected 'Andere' for Employment |
| MaritalStatus | Current marital status (Dutch response labels as administered) |
| HasChildren | 'Do you have children?' (Ja / Nee) |
| HouseholdAdults | Number of adults (18 and over) in the household, respondent included |
| HouseholdChildren | Number of children (under 18) in the household |
| Province | Province of residence (Dutch response labels as administered) |
| Postcode | Four-digit postal code of the respondent's main residence |
| ForeignBornSelfOrParent | 'Were you, or was at least one of your parents, born abroad?' (Ja / Nee); gates the three country-of-birth items |
| CountryBirthSelf | Country of birth of the respondent; asked only when ForeignBornSelfOrParent = Ja |
| CountryBirthFather | Country of birth of the respondent's father; asked only when ForeignBornSelfOrParent = Ja |
| CountryBirthMother | Country of birth of the respondent's mother; asked only when ForeignBornSelfOrParent = Ja |
| EthnicMinority | 'Do you belong to an ethnic minority group in Belgium?' (Ja / Nee / Weet ik niet / prefer not to say) |
| EthnicityDescription | Open-ended self-description of ethnicity |
| HouseholdIncomeNet | Banded average net monthly household income from all sources, after tax and social contributions |
| Religion | Religious or philosophical self-identification (Dutch response labels as administered) |
| Disability | 'Do you currently have a (long-term) disability or condition that affects your daily activities, work or study?' (Ja / Nee / prefer not to say) |
| DisabilityType | Category or categories selected by respondents who answered Ja to Disability; comma-separated for multiple selections |
| SexualOrientation | Self-reported sexual orientation (Dutch response labels as administered) |
| MFQ_Care | Care/Harm score from the Moral Foundations Questionnaire (MFQ-30; Graham et al., 2011); sum of six items recoded 0-5, range 0-30 |
| MFQ_Fairness | Fairness/Reciprocity score from the Moral Foundations Questionnaire (MFQ-30; Graham et al., 2011); sum of six items recoded 0-5, range 0-30 |
| MFQ_Loyalty | Ingroup/Loyalty score from the Moral Foundations Questionnaire (MFQ-30; Graham et al., 2011); sum of six items recoded 0-5, range 0-30 |
| MFQ_Authority | Authority/Respect score from the Moral Foundations Questionnaire (MFQ-30; Graham et al., 2011); sum of six items recoded 0-5, range 0-30 |
| MFQ_Purity | Purity/Sanctity score from the Moral Foundations Questionnaire (MFQ-30; Graham et al., 2011); sum of six items recoded 0-5, range 0-30 |
| MFQ_CatchRelevance | MFQ-30 attention-check item 'Whether or not someone was good at math', 0 = not at all relevant to 5 = extremely relevant; low values indicate attentive responding |
| MFQ_CatchJudgment | MFQ-30 attention-check item 'It is better to do good than to do bad', 0 = strongly disagree to 5 = strongly agree; high values indicate attentive responding |
| MostImportantProblemOpen | Open-ended answer to 'In your own words, what do you think is the biggest problem our country currently faces?' |
| VoteIssue1 | First of at most two issues named as most important for the respondent's vote choice if elections were held now |
| VoteIssue2 | Second of at most two issues named as most important for the respondent's vote choice if elections were held now |
| SatisfactionDemocracy | 'How satisfied are you overall with the way democracy works in Belgium?' 0 = extremely dissatisfied to 10 = extremely satisfied (ESS item); 'don't know' coded missing |
| EUIntegration | European unification: 0 = has already gone too far to 10 = should go further (ESS item); 'don't know' coded missing |
| MigrationEconomy | 'Is it generally bad or good for the Belgian economy that people come to live here from other countries?' 0 = bad to 10 = good (ESS item); 'don't know' coded missing |
| MigrationCulture | 'Is cultural life in Belgium generally undermined or enriched by people coming to live here from other countries?' 0 = undermined to 10 = enriched (ESS item); 'don't know' coded missing |
| MigrationCountry | 'Has Belgium become a worse or a better place to live because of people coming here from other countries?' 0 = worse to 10 = better (ESS item); 'don't know' coded missing |
| MarketVsStateSupervision | Organisation of the economy: 0 = companies should be completely free to do what they want, 10 = the community should supervise companies (ISPO item); 'don't know' coded missing |
| StateReform | State reform: 0 = Flanders and Wallonia should decide everything themselves, 10 = Belgium, Flemings and Walloons together, should decide everything (ISPO item) |
| ClimateResponsibility | 'To what extent do you feel personally responsible for trying to reduce climate change?' 0 = not at all responsible to 10 = very responsible (ESS item) |
| ClimateFossilFuelTax | Support for raising taxes on fossil fuels such as oil, gas and coal, 1 = strongly in favour to 5 = strongly against (ESS item); 'don't know' coded missing |
| ClimateRenewableSubsidy | Support for using public money to subsidise renewable energy, 1 = strongly in favour to 5 = strongly against (ESS item); 'don't know' coded missing |
| ClimateApplianceBan | Support for a law banning the sale of the least energy-efficient household appliances, 1 = strongly in favour to 5 = strongly against (ESS item); 'don't know' coded missing |
| EqualityIncomeRedistribution | 'The government should take measures to reduce differences in income levels', 1 = agree strongly to 5 = disagree strongly (ESS item); 'don't know' coded missing |
| EqualitySmallDifferences | 'For a society to be fair, differences in people's standard of living should be small', 1 = agree strongly to 5 = disagree strongly (ESS item); 'don't know' coded missing |
| GayFreedomToLive | 'Gay men and lesbians should be free to live their own life as they wish', 1 = agree strongly to 5 = disagree strongly (ESS item); 'don't know' coded missing |
| GayFamilyMemberShame | 'If a close family member was gay or lesbian, I would feel ashamed', 1 = agree strongly to 5 = disagree strongly (ESS item); 'don't know' coded missing |
| SameSexAdoptionRights | 'Gay and lesbian couples should have the same rights to adopt children as straight couples', 1 = agree strongly to 5 = disagree strongly (ESS item); 'don't know' coded missing |
| PublicServicesVsTaxes | Improving public services versus cutting taxes: 0 = strongly favours improving public services, 10 = strongly favours cutting taxes (Chapel Hill-style item; Bakker et al., 2015); 'don't know' coded missing |
| WelfareBurdenEconomy | 'Social benefits and services in Belgium place too great a strain on the economy', 1 = agree strongly to 5 = disagree strongly (ESS item); 'don't know' coded missing |
| WelfareCostBusiness | 'Social benefits and services in Belgium cost businesses too much in taxes and charges', 1 = agree strongly to 5 = disagree strongly (ESS item); 'don't know' coded missing |
| WelfareMakesLazy | 'Social benefits and services in Belgium make people lazy', 1 = agree strongly to 5 = disagree strongly (ESS item); 'don't know' coded missing |
| WelfareReducesCare | 'Social benefits and services in Belgium make people less willing to care for one another', 1 = agree strongly to 5 = disagree strongly (ESS item); 'don't know' coded missing |
| StateInterventionEconomy | Government intervention in the economy: 0 = fully in favour of state intervention, 10 = fully opposed to state intervention (Chapel Hill-style item; Bakker et al., 2015); 'don't know' coded missing |
| LibertiesVsCrimeControl | Civil liberties versus tough measures against crime: 0 = strong preference for civil liberties, 10 = strong preference for tough measures to fight crime (Chapel Hill-style item; Bakker et al., 2015); 'don't know' coded missing |
| WelfareChauvinism | When newly arrived migrants should gain the same rights to social benefits as Belgians; response options as administered, including 'Weet niet'. |
| DirectVsRepresentativeDemocracy | Who should take the most important decisions: 0 = the people, for instance through referendums, 10 = elected representatives (Chapel Hill-style item; Bakker et al., 2015); 'don't know' coded missing |
| VoteChoice2024 | Party voted for at the federal election of June 2024 |
| PartisanIdentity | 'I feel that the political party I prefer is an important part of who I am', 1 = strongly disagree to 7 = strongly agree |
| PTV_NVA | Propensity to vote: 'How likely is it that you would ever vote for this party?' for N-VA, 0 = not at all likely to 10 = very likely |
| PTV_VlaamsBelang | Propensity to vote for Vlaams Belang, 0 = not at all likely to 10 = very likely |
| PTV_CDV | Propensity to vote for CD&V, 0 = not at all likely to 10 = very likely |
| PTV_OpenVLD | Propensity to vote for Open VLD, 0 = not at all likely to 10 = very likely |
| PTV_Vooruit | Propensity to vote for Vooruit, 0 = not at all likely to 10 = very likely |
| PTV_Groen | Propensity to vote for Groen, 0 = not at all likely to 10 = very likely |
| PTV_PVDA | Propensity to vote for PVDA, 0 = not at all likely to 10 = very likely |
| Thermometer_NVA | Feeling thermometer towards N-VA voters, 0 = very cold (negative) to 10 = very warm (positive) |
| Thermometer_VlaamsBelang | Feeling thermometer towards Vlaams Belang voters, 0 = very cold (negative) to 10 = very warm (positive) |
| Thermometer_CDV | Feeling thermometer towards CD&V voters, 0 = very cold (negative) to 10 = very warm (positive) |
| Thermometer_OpenVLD | Feeling thermometer towards Open VLD voters, 0 = very cold (negative) to 10 = very warm (positive) |
| Thermometer_Vooruit | Feeling thermometer towards Vooruit voters, 0 = very cold (negative) to 10 = very warm (positive) |
| Thermometer_Groen | Feeling thermometer towards Groen voters, 0 = very cold (negative) to 10 = very warm (positive) |
| Thermometer_PVDA | Feeling thermometer towards PVDA voters, 0 = very cold (negative) to 10 = very warm (positive) |
Clip level
clips.csv · one row per stimulus · 8 variables
| Variable | Description |
|---|---|
| ClipID | Stimulus identifier, equal to the marker number used during recording (29-76) |
| ClipLength | Duration of the audio fragment in seconds |
| PoliticianFemale | Gender of the fictional politician voicing the speech: 1 = female, 0 = male |
| AgenticLanguage | Rhetorical style of the speech: 1 = agentic (stereotypically masculine), 0 = communal (stereotypically feminine) |
| ThemeID | Political theme of the speech, 1-12. Each theme was recorded in all four gender x style conditions, so the four clips sharing a ThemeID differ only in condition. |
| MediaFilename | Filename of the audio fragment for this clip, as referenced by the PsychoPy experiment. The audio files themselves are not yet in the vault. |
| ThemeName | Political theme of the speech, in Dutch, as listed in the thesis appendix. |
| PoliticalBeliefItem | The statement participants rated on a visual analogue scale from 0 to 100 immediately before the study (PoliticalbeliefPrior) and again straight after this clip (PoliticalBeliefResponse); the difference is PoliticalbeliefChange. The four clips sharing a ThemeID share this statement. |
Trial level
trials.csv · one row per participant per stimulus · 61 variables
| Variable | Description |
|---|---|
| Participant | Pseudonymous participant identifier |
| ClipOrder | Position of this clip in the participant's randomised sequence, 1-12 |
| ClipID | Stimulus identifier, equal to the marker number used during recording (29-76) |
| PoliticianFemale | Gender of the fictional politician voicing the speech: 1 = female, 0 = male |
| AgenticLanguage | Rhetorical style of the speech: 1 = agentic (stereotypically masculine), 0 = communal (stereotypically feminine) |
| ArousalResponse | Self-reported arousal after the clip, visual analogue scale 0-100 |
| ValenceResponse | Self-reported valence after the clip, visual analogue scale 0-100 |
| SalienceResponse | Self-reported salience of the topic after the clip, visual analogue scale 0-100 |
| AuthenticityResponse | Perceived authenticity of the speaker, visual analogue scale 0-100 |
| AgreementResponse | Agreement with the content of the speech, visual analogue scale 0-100 |
| FamiliarityResponse | Reported familiarity with the speaker, 1 = not familiar to 5 = very familiar. The politicians are fictional, so this is expected to be uniformly low. |
| PersuasivenessResponse | Primary self-report outcome. Answer to 'Regardless of the content, how convincing did you find the speaker?', visual analogue scale 0-100 |
| PoliticalbeliefPrior | Agreement with this clip's policy statement measured in the pre-experiment survey, visual analogue scale 0-100, before any exposure |
| PoliticalBeliefResponse | Agreement with the same policy statement measured immediately after the clip, visual analogue scale 0-100 |
| PoliticalbeliefChange | PoliticalBeliefResponse minus PoliticalbeliefPrior, in VAS points, -100 to 100. Positive values mean the speech moved the participant towards the statement. |
| PhasicEDA | Phasic skin conductance over the clip, in µS. The 500 Hz skin-conductance recording of the trial (BIOPAC BioNomadix, wet electrodes on the palm of the non-dominant hand) was downsampled to 32 Hz in Ledalab and decomposed by continuous decomposition analysis (Benedek & Kaernbach, 2010) into a tonic component and a phasic driver, with the tau parameters of the impulse response optimised automatically by Ledalab and a minimum response amplitude of 0.1 µS. The value is the mean of the phasic driver over the clip (Ledalab's CDA.SCR); it indexes discrete sympathetic responses during the clip, disregards the slowly changing level of skin conductance, and, being an average, does not grow with clip length. |
| TonicEDA | Tonic skin conductance level over the clip, in µS. The 500 Hz skin-conductance recording of the trial (BIOPAC BioNomadix, wet electrodes on the palm of the non-dominant hand) was downsampled to 32 Hz in Ledalab and decomposed by continuous decomposition analysis (Benedek & Kaernbach, 2010) into a tonic component and a phasic driver, with the tau parameters of the impulse response optimised automatically by Ledalab and a minimum response amplitude of 0.1 µS. The value is the mean of the tonic component over the clip (Ledalab's CDA.Tonic); it indexes the participant's general level of sympathetic activity, which changes too slowly to differ between clips of one to two minutes. |
| AlphaAsymmetry | Frontal alpha asymmetry: log10 of Alpha_F4 minus log10 of Alpha_F3, the absolute alpha-band (8-12 Hz) powers at the right and left frontal sites computed for this trial (Reznik & Allen, 2018). Dimensionless, a difference of log10 µV² values. Positive values mean more alpha on the right than on the left, that is relatively greater left-hemispheric activation, read as a balance tilted towards approach rather than avoidance motivation. |
| Alpha_Cz | Absolute EEG power in the alpha band (8-12 Hz) at Cz (central midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 8-12 Hz. No trials were rejected. |
| Alpha_F3 | Absolute EEG power in the alpha band (8-12 Hz) at F3 (left frontal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 8-12 Hz. No trials were rejected. |
| Alpha_F4 | Absolute EEG power in the alpha band (8-12 Hz) at F4 (right frontal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 8-12 Hz. No trials were rejected. |
| Alpha_Fz | Absolute EEG power in the alpha band (8-12 Hz) at Fz (frontal midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 8-12 Hz. No trials were rejected. |
| Alpha_P3 | Absolute EEG power in the alpha band (8-12 Hz) at P3 (left parietal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 8-12 Hz. No trials were rejected. |
| Alpha_P4 | Absolute EEG power in the alpha band (8-12 Hz) at P4 (right parietal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 8-12 Hz. No trials were rejected. |
| Alpha_Pz | Absolute EEG power in the alpha band (8-12 Hz) at Pz (parietal midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 8-12 Hz. No trials were rejected. |
| Beta_Cz | Absolute EEG power in the beta band (13-30 Hz) at Cz (central midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 13-30 Hz. No trials were rejected. |
| Beta_F3 | Absolute EEG power in the beta band (13-30 Hz) at F3 (left frontal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 13-30 Hz. No trials were rejected. |
| Beta_F4 | Absolute EEG power in the beta band (13-30 Hz) at F4 (right frontal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 13-30 Hz. No trials were rejected. |
| Beta_Fz | Absolute EEG power in the beta band (13-30 Hz) at Fz (frontal midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 13-30 Hz. No trials were rejected. |
| Beta_P3 | Absolute EEG power in the beta band (13-30 Hz) at P3 (left parietal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 13-30 Hz. No trials were rejected. |
| Beta_P4 | Absolute EEG power in the beta band (13-30 Hz) at P4 (right parietal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 13-30 Hz. No trials were rejected. |
| Beta_Pz | Absolute EEG power in the beta band (13-30 Hz) at Pz (parietal midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 13-30 Hz. No trials were rejected. |
| Delta_Cz | Absolute EEG power in the delta band (1-3 Hz) at Cz (central midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 1-3 Hz. No trials were rejected. |
| Delta_F3 | Absolute EEG power in the delta band (1-3 Hz) at F3 (left frontal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 1-3 Hz. No trials were rejected. |
| Delta_F4 | Absolute EEG power in the delta band (1-3 Hz) at F4 (right frontal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 1-3 Hz. No trials were rejected. |
| Delta_Fz | Absolute EEG power in the delta band (1-3 Hz) at Fz (frontal midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 1-3 Hz. No trials were rejected. |
| Delta_P3 | Absolute EEG power in the delta band (1-3 Hz) at P3 (left parietal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 1-3 Hz. No trials were rejected. |
| Delta_P4 | Absolute EEG power in the delta band (1-3 Hz) at P4 (right parietal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 1-3 Hz. No trials were rejected. |
| Delta_Pz | Absolute EEG power in the delta band (1-3 Hz) at Pz (parietal midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 1-3 Hz. No trials were rejected. |
| LowGamma_Cz | Absolute EEG power in the low-gamma band (30-40 Hz) at Cz (central midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 30-40 Hz. No trials were rejected. |
| LowGamma_F3 | Absolute EEG power in the low-gamma band (30-40 Hz) at F3 (left frontal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 30-40 Hz. No trials were rejected. |
| LowGamma_F4 | Absolute EEG power in the low-gamma band (30-40 Hz) at F4 (right frontal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 30-40 Hz. No trials were rejected. |
| LowGamma_Fz | Absolute EEG power in the low-gamma band (30-40 Hz) at Fz (frontal midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 30-40 Hz. No trials were rejected. |
| LowGamma_P3 | Absolute EEG power in the low-gamma band (30-40 Hz) at P3 (left parietal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 30-40 Hz. No trials were rejected. |
| LowGamma_P4 | Absolute EEG power in the low-gamma band (30-40 Hz) at P4 (right parietal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 30-40 Hz. No trials were rejected. |
| LowGamma_Pz | Absolute EEG power in the low-gamma band (30-40 Hz) at Pz (parietal midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 30-40 Hz. No trials were rejected. |
| Theta_Cz | Absolute EEG power in the theta band (4-7 Hz) at Cz (central midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 4-7 Hz. No trials were rejected. |
| Theta_F3 | Absolute EEG power in the theta band (4-7 Hz) at F3 (left frontal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 4-7 Hz. No trials were rejected. |
| Theta_F4 | Absolute EEG power in the theta band (4-7 Hz) at F4 (right frontal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 4-7 Hz. No trials were rejected. |
| Theta_Fz | Absolute EEG power in the theta band (4-7 Hz) at Fz (frontal midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 4-7 Hz. No trials were rejected. |
| Theta_P3 | Absolute EEG power in the theta band (4-7 Hz) at P3 (left parietal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 4-7 Hz. No trials were rejected. |
| Theta_P4 | Absolute EEG power in the theta band (4-7 Hz) at P4 (right parietal, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 4-7 Hz. No trials were rejected. |
| Theta_Pz | Absolute EEG power in the theta band (4-7 Hz) at Pz (parietal midline, 10-20 system) over the clip, in µV². Computed from the raw EEG recording of the trial (Enobio 8, 500 Hz): a 50 Hz notch filter (Q = 30) and a fourth-order Butterworth band-pass filter of 0.5-40 Hz were applied, both zero-phase; ocular artefacts were removed by regressing the channel on the demeaned EOG channel and subtracting the fit; the power spectral density was estimated by Welch's method with 2-second Hann windows and 50% overlap; and the band power is the trapezoidal integral of the density over 4-7 Hz. No trials were rejected. |
| ThetaBetaRatio_Cz | Theta/beta ratio at Cz (central midline, 10-20 system): Theta_Cz divided by Beta_Cz, the absolute theta-band (4-7 Hz) and beta-band (13-30 Hz) powers at Cz computed for this trial. Dimensionless. Higher values mean relatively more slow-wave than fast-wave activity, read as a balance tilted from effortful, deliberative processing towards affective engagement and emotional regulation (Putman et al., 2014; Angelidis et al., 2018). |
| ThetaBetaRatio_F3 | Theta/beta ratio at F3 (left frontal, 10-20 system): Theta_F3 divided by Beta_F3, the absolute theta-band (4-7 Hz) and beta-band (13-30 Hz) powers at F3 computed for this trial. Dimensionless. Higher values mean relatively more slow-wave than fast-wave activity, read as a balance tilted from effortful, deliberative processing towards affective engagement and emotional regulation (Putman et al., 2014; Angelidis et al., 2018). |
| ThetaBetaRatio_F4 | Theta/beta ratio at F4 (right frontal, 10-20 system): Theta_F4 divided by Beta_F4, the absolute theta-band (4-7 Hz) and beta-band (13-30 Hz) powers at F4 computed for this trial. Dimensionless. Higher values mean relatively more slow-wave than fast-wave activity, read as a balance tilted from effortful, deliberative processing towards affective engagement and emotional regulation (Putman et al., 2014; Angelidis et al., 2018). |
| ThetaBetaRatio_Fz | Theta/beta ratio at Fz (frontal midline, 10-20 system): Theta_Fz divided by Beta_Fz, the absolute theta-band (4-7 Hz) and beta-band (13-30 Hz) powers at Fz computed for this trial. Dimensionless. Higher values mean relatively more slow-wave than fast-wave activity, read as a balance tilted from effortful, deliberative processing towards affective engagement and emotional regulation (Putman et al., 2014; Angelidis et al., 2018). |
| ThetaBetaRatio_P3 | Theta/beta ratio at P3 (left parietal, 10-20 system): Theta_P3 divided by Beta_P3, the absolute theta-band (4-7 Hz) and beta-band (13-30 Hz) powers at P3 computed for this trial. Dimensionless. Higher values mean relatively more slow-wave than fast-wave activity, read as a balance tilted from effortful, deliberative processing towards affective engagement and emotional regulation (Putman et al., 2014; Angelidis et al., 2018). |
| ThetaBetaRatio_P4 | Theta/beta ratio at P4 (right parietal, 10-20 system): Theta_P4 divided by Beta_P4, the absolute theta-band (4-7 Hz) and beta-band (13-30 Hz) powers at P4 computed for this trial. Dimensionless. Higher values mean relatively more slow-wave than fast-wave activity, read as a balance tilted from effortful, deliberative processing towards affective engagement and emotional regulation (Putman et al., 2014; Angelidis et al., 2018). |
| ThetaBetaRatio_Pz | Theta/beta ratio at Pz (parietal midline, 10-20 system): Theta_Pz divided by Beta_Pz, the absolute theta-band (4-7 Hz) and beta-band (13-30 Hz) powers at Pz computed for this trial. Dimensionless. Higher values mean relatively more slow-wave than fast-wave activity, read as a balance tilted from effortful, deliberative processing towards affective engagement and emotional regulation (Putman et al., 2014; Angelidis et al., 2018). |
| MeanPupilDiameter | Mean pupil diameter over the clip in millimetres, averaged across both eyes. The 60 Hz Tobii Pro Spark recording of the trial was processed per eye following Kret and Sjak-Shie (2019): samples outside 1.5-9 mm were removed; dilation-speed outliers (median + 16 median absolute deviations), which mark the edges of blinks, were removed; the two eyes were combined by averaging whichever samples remained valid; gaps up to 250 ms were linearly interpolated; and a trial with fewer than 50% valid samples after these steps was left empty. The value is the mean of the reconstructed trace. Not baseline-corrected: the recordings run from clip onset to clip offset and contain no pre-clip period. |
Raw signals
Recordings
What was recorded during each trial and how it is stored. One plain-text file per participant per clip, tab-separated, with a time column in seconds on the session clock followed by one column per channel. The figures below are counts over the whole study; no recording is published.
Electrodermal activity EDA
360 recordings covering 30 participants and 48 clips · 100% of trials · 500 Hz · typical recording 85 s
Skin conductance recorded during clip playback at 500 Hz with a BIOPAC BioNomadix wireless transmitter and an MP160 acquisition unit under AcqKnowledge 5.0.10, through wet electrodes on the palm of the non-dominant hand, in microsiemens; the phasic and tonic components in trials.csv were derived from these files
| Channel | Description |
|---|---|
| EDA | Skin conductance level, in µS |
File layout · eda/raw/Participant<n>_Clip<n>_EDA.txt
time EDA 0.0000 … 0.0020 …
Electroencephalogram EEG
336 recordings covering 28 participants and 48 clips · 93% of trials · 500 Hz · typical recording 84.2 s
Electroencephalogram recorded during clip playback with an Enobio 8 wireless system (Neuroelectrics) at 500 Hz: seven electrodes at scalp sites of the 10-20 system (F3, Fz, F4, Cz, P3, Pz, P4), one electrode above the right eye recording the electro-oculogram, and the reference on the earlobe, with conductive gel at every site and impedances below 10 kΩ. Stored as the raw amplifier output in microvolts, without filtering or re-referencing; the band powers in trials.csv were derived from these files.
| Channel | Description |
|---|---|
| F3 | Left frontal electrode (F3, 10-20 system), in µV |
| Fz | Frontal midline electrode (Fz, 10-20 system), in µV |
| F4 | Right frontal electrode (F4, 10-20 system), in µV |
| Cz | Central midline electrode (Cz, 10-20 system), in µV |
| P3 | Left parietal electrode (P3, 10-20 system), in µV |
| Pz | Parietal midline electrode (Pz, 10-20 system), in µV |
| P4 | Right parietal electrode (P4, 10-20 system), in µV |
| EOG | Electro-oculogram from an electrode above the right eye, in µV; records eye movements and blinks and was used to remove ocular artefacts from the EEG channels |
File layout · eeg/Participant<n>_Clip<n>_EEG.txt
time F3 Fz F4 Cz P3 Pz P4 EOG 0.0000 … … … … … … … … 0.0020 … … … … … … … …
Pupil diameter PUPIL
330 recordings covering 29 participants and 48 clips · 92% of trials · 59.9 Hz · typical recording 83.4 s
Pupil diameter recorded during clip playback with a Tobii Pro Spark eye tracker at 60 Hz, in millimetres per eye, after a nine-point calibration that was repeated when its accuracy was insufficient, under constant room illumination of about 12 lux with the participant's head on a chin rest; MeanPupilDiameter in trials.csv was derived from these files
| Channel | Description |
|---|---|
| PupilLeft | Left pupil diameter as reported by the eye tracker, in mm; empty where the eye was not tracked |
| PupilRight | Right pupil diameter as reported by the eye tracker, in mm; empty where the eye was not tracked |
| PupilFiltered | Diameter combined over both eyes after removing samples outside 1.5-9 mm and dilation-speed outliers (median + 16 MAD), averaging whichever eyes remained valid, and linearly interpolating gaps up to 250 ms, in mm |
File layout · pupil/Participant<n>_Clip<n>_PUPIL.txt
time PupilLeft PupilRight PupilFiltered 0.0000 … … … 0.0167 … … …
Not recorded in this study: Photoplethysmogram.