NYU Dataset

Simultaneous recordings of brain activity and pupil size in resting state and during a visual perceptual decision-making task

UID: 10457
* Corresponding Author
Description

To investigate the relationship between two behavioral markers of arousal (pupil size and brain activity) and perceptual decision-making, recordings were simultaneously obtained on pupil size and brain activity using magnetoencephalography (MEG). Data was collected from a total of 24 adult participants during eyes-open rest sessions and a visual perceptual decision-making task.

Two 5-minute rest session recordings were obtained from 21 participants; 3 participants completed one rest session each. Every task trial included a prestimulus interval followed by a liminal object stimulus, then two forced-choice decisions to categorize the stimulus (i.e., face, house, object, or animal) and to indicate whether the stimulus was recognizable (i.e., yes or no). During the prestimulus interval, participants were presented with a fixation cross on a gray background for 3 to 6 seconds. A total of 360 trials were completed; 300 with meaningful stimulus and 60 with scrambled images.

The investigators have shared subject-level source data for the following analyses:

  • Prestimulus baseline data for power-pupil relationship per RSN and frequency band
  • Resting state power-pupil relationship per RSN and frequency band
  • Perceptual behavior (hit rate, false alarms rate, reaction time, sensitivity, criterion, and accuracy) as a function of pupil size
  • Post-stimulus categorization accuracy according to time point and prestimulus pupil size
  • “Yes”/“No” discrimination
  • Residual power’s relationship to perceptual behavior for each RSN and frequency band
  • Perceptual behavior sorted by prestimulus fast pupil dynamics

Subject of Study
Subject Domain
Population Age
Adult (19 years - 64 years)
Keywords

Access

Restrictions
Free to All
Instructions
Subject-level source data underlying the figures in the associated publication can be accessed through PubMed Central (PMC) as comma-separated values (CSV) files. Analysis code that was used in the project may be downloaded through GitHub or Software Heritage archive (listed under Other Resources).
Access via PMC

CSV files with subject-level data

Associated Publications
Data Type
Equipment Used
EyeLink 1000 Plus
General Electric 3T Scanner
Siemens 7T MRI System
Siemens MAGNETOM Skyra
VSM MedTech CTF MEG
Software Used
FreeSurfer
MNE-Python v0.19.1
PiecewiseSEM
statsmodels v0.12.2
Study Type
Observational
Dataset Format(s)
CSV
Grant Support
1753218/BCS NSF
Other Resources
GitHub

Analysis code

Software Heritage

Analysis code