Main content
Nap EEG
Date created: | Last Updated:
: DOI | ARK
Creating DOI. Please wait...
Category: Project
Description: 64 channel continuously-sampled scalp EEG data from humans napping after completing a scene working memory task. These data are being used to develop objective and automated methods for sleep stage identification and for classifying spindles and k-complexes in stage 2 NREM sleep. **Code is not maintained here since 08-2018, please visit https://github.com/nmningmei/Get_Sleep_data for updated version of the data and model**
Sleep Spindle
Based on the dominant frequency of a segment around a spindle, each is classified as a slow spindle (9-10 Hz; 10 – 12 Hz) or a fast spindle (13 – 15 Hz; 12 – 14 Hz), which are believed to occur during different phases of slow oscillations (< 1 Hz). Measuring sleep spindles and analyzing their relationship to behavior and cognition may provide insight into how these neural events infl…Files
Files can now be accessed and managed under the Files tab.
Citation
Components
Load data and inspection, Spindle detection
1) load data, 2) ICA correcting data, 3) visualize data and power spectral density of data, 4) detection spindles.
Spindle detection results
Results of slow spindles (10-12 Hz) and fast spindles (12-14 Hz)
Behavioral Results
Behavioral Results and Memory Tasks Description
Recent Activity
Unable to retrieve logs at this time. Please refresh the page or contact support@osf.io if the problem persists.
Start managing your projects on the OSF today.
Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.