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دسته بندی:
تشخیص الگو - Pattern recognition
سال انتشار:
2019
عنوان انگلیسی مقاله:
Slow wave detection in sleeping mice: Comparison of traditional and machine learning methods
ترجمه فارسی عنوان مقاله:
تشخیص موج آهسته در موش های خواب: مقایسه روش های یادگیری سنتی و ماشین
منبع:
Sciencedirect - Elsevier - Journal of Neuroscience Methods, 316 (2019) 35-45: doi:10:1016/j:jneumeth:2018:08:016
نویسنده:
Olga Bukhtiyarovaa,b, Sara Soltania,b, Sylvain Chauvetteb, Igor Timofeeva,b,⁎
چکیده انگلیسی:
Background: During slow-wave sleep the electroencephalographic (EEG) and local field potential (LFP) recordings
reveal the presence of large amplitude slow waves. Systematic extraction of individual slow waves is not trivial.
New method: In this study, we used the neural network pattern recognition to detect individual slow waves in
LFP recorded from mice as well as other commonly used methods that are based on fast frequencies modulation,
amplitude, or duration.
Results: The number and quality of events detected as slow waves depended on the chosen method of detection,
level of thresholds, or on combination of methods. Each individual method yields some false-positive and falsenegative
detections. Typically, the fast frequency-method has a higher false discovery rate, but almost no missing
waves; amplitude-based method has relatively high false-positive and false-negative rates; duration-based
method has low false-negative rates; neural network pattern recognition approach has the lowest false-positive
rate among individual methods, often rejecting waves that were falsely detected by other approaches.
Combining all 4 detection methods practically eliminated false-positive errors, but a large number of slow waves
remained undetected.
Conclusions: The use of a particular method of slow wave detection needs to be adjusted to the objectives of a
given study: to detect all slow waves, but also numerous false positives can be achieved using the fast frequency
approach. Neural network pattern recognition method alone can detect slow waves with the lowest false-positive
rate, that can be further minimized with the use of combination of other methods.
Keywords: Slow-wave sleep | Slow waves | Automatic methods | Artificial neural network
قیمت: رایگان
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