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Original Research 


A Fundamental Question about the Application of High-Density Electroencephalography and Time-Series Analysis in Examining Synchronous Networks During Sleep – Does the Use of Different Referencing and Data Preprocessing Methods Really Matter?

Calvin Kai-ching Yu, Wang-on Li.


Abstract
This study tested whether different referencing and data preprocessing strategies would influence the results of electroencephalographic network analyses. Data were collected from two volunteers during the last 60 seconds of the second and fourth rapid-eye-movement epochs using a 256-channel electroencephalographic system and prior to correlation analyses, were preprocessed by varying combinations of techniques, including referencing/re-referencing (vertex, average mastoid, and common average), bandpass filtering, differencing, and autoregressive integrative moving average (ARIMA) modeling. The findings suggest that using different methods to eliminate temporal structures, noise, and extraneous signals embedded in a time series does not substantially influence the results of subsequent network analyses. However, ARIMA parameters should be carefully chosen to ensure that all or almost all 256 EEG time series can be preserved after the ARIMA prewhitening procedure. In contrast to the analogous correlation networks between different data preprocessing protocols, different referencing can lead to significantly dissimilar correlation patterns. Specifically, the use of a common average reference moderates the overall strength of a connectivity network, while vertex referencing and mastoid referencing may respectively underestimate the strength of connections over the central and mastoid regions. All in all, it appears that the combination of average referencing, filtering, and differencing provides a relatively reliable protocol for dense EEG network analysis.

Key words: ARIMA, functional connectivity, dense array EEG, synchronous cortical activity, rapid eye movement


 
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Pubmed Style

Yu CK, Li W. A Fundamental Question about the Application of High-Density Electroencephalography and Time-Series Analysis in Examining Synchronous Networks During Sleep – Does the Use of Different Referencing and Data Preprocessing Methods Really Matter?. Sleep Hypn. 2018; 20(1): 67-84.

Web Style

Yu CK, Li W. A Fundamental Question about the Application of High-Density Electroencephalography and Time-Series Analysis in Examining Synchronous Networks During Sleep – Does the Use of Different Referencing and Data Preprocessing Methods Really Matter?. https://www.sleepandhypnosis.com/?mno=256345 [Access: June 23, 2026].

AMA (American Medical Association) Style

Yu CK, Li W. A Fundamental Question about the Application of High-Density Electroencephalography and Time-Series Analysis in Examining Synchronous Networks During Sleep – Does the Use of Different Referencing and Data Preprocessing Methods Really Matter?. Sleep Hypn. 2018; 20(1): 67-84.


Vancouver/ICMJE Style

Yu CK, Li W. A Fundamental Question about the Application of High-Density Electroencephalography and Time-Series Analysis in Examining Synchronous Networks During Sleep – Does the Use of Different Referencing and Data Preprocessing Methods Really Matter?. Sleep Hypn. (2018), [cited June 23, 2026]; 20(1): 67-84.


Harvard Style

Yu, C. K. & Li, . W. (2018) A Fundamental Question about the Application of High-Density Electroencephalography and Time-Series Analysis in Examining Synchronous Networks During Sleep – Does the Use of Different Referencing and Data Preprocessing Methods Really Matter?. Sleep Hypn, 20 (1), 67-84.


Turabian Style

Yu, Calvin Kai-ching, and Wang-on Li. 2018. A Fundamental Question about the Application of High-Density Electroencephalography and Time-Series Analysis in Examining Synchronous Networks During Sleep – Does the Use of Different Referencing and Data Preprocessing Methods Really Matter?. Sleep and Hypnosis, 20 (1), 67-84.


Chicago Style

Yu, Calvin Kai-ching, and Wang-on Li. "A Fundamental Question about the Application of High-Density Electroencephalography and Time-Series Analysis in Examining Synchronous Networks During Sleep – Does the Use of Different Referencing and Data Preprocessing Methods Really Matter?." Sleep and Hypnosis 20 (2018), 67-84.


MLA (The Modern Language Association) Style

Yu, Calvin Kai-ching, and Wang-on Li. "A Fundamental Question about the Application of High-Density Electroencephalography and Time-Series Analysis in Examining Synchronous Networks During Sleep – Does the Use of Different Referencing and Data Preprocessing Methods Really Matter?." Sleep and Hypnosis 20.1 (2018), 67-84. Print.


APA (American Psychological Association) Style

Yu, C. K. & Li, . W. (2018) A Fundamental Question about the Application of High-Density Electroencephalography and Time-Series Analysis in Examining Synchronous Networks During Sleep – Does the Use of Different Referencing and Data Preprocessing Methods Really Matter?. Sleep and Hypnosis, 20 (1), 67-84.


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