A comparison of two sleep spindle detection methods based on all night averages: individually adjusted vs. fixed frequencies
Publication year
2015Source
Frontiers in Human Neuroscience, 9, (2015), article 52ISSN
Publication type
Article / Letter to editor
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Organization
Neurobiology
Cognitive Neuroscience
PI Group Memory & Emotion
Journal title
Frontiers in Human Neuroscience
Volume
vol. 9
Languages used
English (eng)
Subject
130 000 Cognitive Neurology & Memory; Neuroinformatics; Radboudumc 13: Stress-related disorders DCMN: Donders Center for Medical NeuroscienceAbstract
Sleep spindles are frequently studied for their relationship with state and trait cognitive variables, and they are thought to play an important role in sleep-related memory consolidation. Due to their frequent occurrence in NREM sleep, the detection of sleep spindles is only feasible using automatic algorithms, of which a large number is available. We compared subject averages of the spindle parameters computed by a fixed frequency (FixF) (11-13 Hz for slow spindles, 13-15 Hz for fast spindles) automatic detection algorithm and the individual adjustment method (IAM), which uses individual frequency bands for sleep spindle detection. Fast spindle duration and amplitude are strongly correlated in the two algorithms, but there is little overlap in fast spindle density and slow spindle parameters in general. The agreement between fixed and manually determined sleep spindle frequencies is limited, especially in case of slow spindles. This is the most likely reason for the poor agreement between the two detection methods in case of slow spindle parameters. Our results suggest that while various algorithms may reliably detect fast spindles, a more sophisticated algorithm primed to individual spindle frequencies is necessary for the detection of slow spindles as well as individual variations in the number of spindles in general.
This item appears in the following Collection(s)
- Academic publications [245050]
- Donders Centre for Cognitive Neuroimaging [4019]
- Electronic publications [132309]
- Faculty of Medical Sciences [93209]
- Faculty of Science [37364]
- Open Access publications [105922]
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