Open data: EEG correlates of detection and identification awareness for digits and letters

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Dataset information

Country of origin
Updated
2026.02.12 00:00
Created
2026.02.12
Available languages
English
Keywords
Cognitive neuroscience, Psychophysiology, Sensory processes, perception and performance
Quality scoring

Dataset description

ABSTRACT A central feature of consciousness is the association between external events and subjective experiences of content. These experiences range from low level (detection) to high level (identification). For example, a visual experience may range from seeing something on a computer screen (detection) to seeing the digit 3 (identification). In research, neural processes that correlate with these experiences are called neural correlates of consciousness (NCCs). In vision, a candidate NCC is the visual awareness negativity (VAN) that is derived from event-related potentials, occurring about 200 ms after stimulus onset over posterior electrode sites. Because previous research does not resolve whether VAN is more sensitive to low-level experiences (detection awareness) than high-level experiences (identification awareness), we conducted two preregistered experiments. In both experiments, two staircases continuously adjusted stimulus opacity to separately target detection awareness and identification awareness. In Experiment 1, subjects viewed either individual digits (N = 15) or individual letters or digits (N = 15). For both types of stimuli, VAN was similarly sensitive to detection awareness and identification awareness. As a follow up, Experiment 2 (N = 28) examined whether stimulus size affects VAN to identification awareness using digit stimuli. Results showed identification VAN for both digit sizes, and VAN was unaffected by stimulus size. These results confirm the sensitivity of VAN to both low-level experiences (detection) and high-level experiences (identification). However, results emphasize the limited specificity of VAN in separating between low-level and high-level experiences, suggested by the similarity of VAN in both conditions. ETHICS STATEMENT In accordance with the Declaration of Helsinki, subjects provided their written informed consent (this included their consent that their data would be shared in anonymized form). The study was approved by the Swedish Ethical Review Authority (2022-06409-01). The uploaded data are considered anonymized because there is no key that links test subjects to their data. DATE & LOCATION OF DATA COLLECTION The study comprised two experiments. Subjects for experiment 1 (N = 31; Final sample: N = 30) were tested between May 2023 and June 2023 at the Department of Psychology, Campus Albano, Stockholm, Sweden. Subjects for experiment 2 (N =29; Final sample: N = 28) were tested between October 2023 and November 2023 at the Department of Psychology, Campus Albano, Stockholm, Sweden. DATA & FILE OVERVIEW The files contain the raw data, scripts, and results of main and supplementary analyses of the electroencephalography (EEG) study reported in the main publication. Note: In the figures and analysis scripts, experiment 1 is called K17, and experiment 2 is called VAN3. File Structure There are three main folders: - CompleteResults: Contains all results files generated in R-quarto (in html format), taken from each experiment folder. - Experiment_1: Contains all material, including figures, regarding experiment 1. - Experiment_2: Contains all material, including figures, regarding experiment 2. This folder also contains R folder with scripts to analyze data across experiments. Raw Data and Scripts for Experiment and Analysis For raw data and scripts, see folders Experiment_1 and Experiment_2 for supplementary files regarding experiment 1 and experiment 2, respectively. The structure of these folders is identical. Within these folders, see: - Data folder for raw .bdf-files and corresponding logfiles. - MNE folder for scripts of MNE-python for processing EEG-data. - Psychopy folder for scripts to run the experiments. - R folders for scripts to analyze the data.
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