Open data: Neural electrophysiological correlates of detection and identification awareness - Wiens, Stefan (Stockholm University, 2023)
New version: The python scripts to run the lab experiment were added.

Open data: Neural electrophysiological correlates of detection and identification awareness

Supplementary material for the associated publication.

OVERVIEW

Humans have conscious experiences of the events in their environment. Previous research from electroencephalography (EEG) has shown visual awareness negativity (VAN) at about 200 ms to be a neural correlate of consciousness (NCC). In the present study, the stimulus was a ring with a Gabor patch tilting either left or right. On each trial, subjects rated their awareness on a three-level perceptual awareness scale that captured both detection (something vs. nothing) and identiﬁcation (identiﬁcation vs. something). Separate staircases were used to adjust stimulus opacity to the detection threshold and the identiﬁcation threshold. Event-related potentials were extracted for VAN and late positivity.

DATE & LOCATION OF DATA COLLECTION:

Subjects (N = 43, student volunteers) were tested between 2022-maj-23 and 2022-june-30 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.

For convenience, the report files of the main analyses in the manuscript are saved separately.

Visual awareness negativity (VAN) results: analysis_VANo_clean_data_blocklength_16_pawarelimit0.8_maxopadetect_maxopaidentify_badEEGyes_ntrials25.html

Late positivity (LP) results: analysis_LPo_clean_data_blocklength_16_pawarelimit0.8_maxopadetect_maxopaidenify_badEEGyes_ntrials25.html

bdf_up_to_20.zip: contains EEG data files for the first 20 subjects in .bdf format (generated by the Biosemi amplifier)

bdf_after_20.zip: contains EEG data files for the remaining subjects in .bdf format (generated by the Biosemi amplifier)

Log.zip: contains log files of the EEG session (generated by Python)

readme_notes_on_id.txt: Information about issues during data collection

psychopy.zip: contains scripts in python and psychopy to run the experiment. Scripts were written by Rasmus Eklund.

MNE-python.zip: contains scripts in MNE-python to preprocess the EEG data. Scripts were written by Rasmus Eklund.

R_graded.zip

The main reports are in R_graded > results > reports. They are .html files generated with Quarto.

photodiode_supplement.pdf: Supplementary analysis of the relationship between python opacity settings and actual changes on the computer screen

METHODOLOGICAL INFORMATION

The visual stimuli were gabor-grated rings. Subjects rated their awareness of the rings. Event-related potentials were computed from the EEG data.

The experiment was programmed in Python: https://www.python.org/

The EEG data were recorded as .bdf files with an Active Two BioSemi system (BioSemi, Amsterdam, Netherlands; www.biosemi.com)

Instrument- or software-specific information needed to interpret the data:

- MNE-Python (Gramfort A., et al., 2013): https://mne.tools/stable/index.html#
- R and relevant packages: https://www.r-project.org/
Keywords: Cognitive neuroscience; Sensory processes, perception and performance; Psychophysiology; Psychology; Psykologi; Neurosciences; Neurovetenskaper