{"id":183,"date":"2015-11-18T00:00:00","date_gmt":"2015-11-17T23:00:00","guid":{"rendered":"http:\/\/semmelweis.hu\/psychophysiology\/bodizs-r-kormendi-j-rigo-p-lazar-as-the-individual-adjustment-method-of-sleep-spindle-analysis-methodological-improvements-and-roots-in-the-fingerprint-paradigm-j-neurosci-methods-178-1-205-213-20-2\/"},"modified":"2018-12-28T17:30:12","modified_gmt":"2018-12-28T16:30:12","slug":"bodizs-r-kormendi-j-rigo-p-lazar-as-the-individual-adjustment-method-of-sleep-spindle-analysis-methodological-improvements-and-roots-in-the-fingerprint-paradigm-j-neurosci-methods-178-1-205-213-20-2","status":"publish","type":"post","link":"https:\/\/semmelweis.hu\/psychophysiology\/2015\/11\/18\/bodizs-r-kormendi-j-rigo-p-lazar-as-the-individual-adjustment-method-of-sleep-spindle-analysis-methodological-improvements-and-roots-in-the-fingerprint-paradigm-j-neurosci-methods-178-1-205-213-20-2\/","title":{"rendered":"B\u00f3dizs R*, K\u00f6rmendi J, Rig\u00f3 P, L\u00e1z\u00e1r AS : The individual adjustment method of sleep spindle analysis: Methodological improvements and roots in the fingerprint paradigm. J. Neurosci. Methods 178(1) 205-213. 2009 – 1. Introduction"},"content":{"rendered":"\n\n\n
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1. Introduction<\/h3>\n

Sleep spindles are usually de\ufb01ned as groups of 12\u201315 Hz sinusoidal electroencephalogram (EEG) waves occurring mainly during stage 2 non-rapid eye movement (NREM) sleep but occasionally appearing in stages 3 and 4 sleep as well (De Gennaro and Ferrara, 2003). There is growing neurophysiological knowledge regarding the nature of neural mechanisms generating sleep spindles, suggesting the role of hyperpolarization-rebound sequences in thalamocortical relay cells triggered, grouped and synchronized by cortico-cortical networks (Steriade, 2003). Moreover, there is a high-degree of interindividual difference in sleep spindle features accompanied by a remarkable intraindividual (night-to-night) stability (Silverstein and Levy, 1976; Gaillard and Blois, 1981; Werth et al., 1997; Tan et al., 2000; De Gennaro et al., 2005). The NREM sleep EEG power spectra at the 8 to 16 Hz frequency covering alpha and spindle activities is characterized by an individual pro\ufb01le, which is stable over time, resistant to experimental perturbations and strongly in\ufb02uenced by genetic factors (De Gennaro et al., 2008). A distinction of slower and faster sleep spindles based on frequency and topography was given by Gibbs and Gibbs (1950) and con\ufb01rmed by studies using modern techniques like low-resolution electromagnetic tomography (Anderer et al., 2001), magnetoencephalography (Urakami, 2008), electrocorticography (Nakamura et al., 2003) and functional magnetic resonance imaging (Schabus et al., 2007). The frequency of slow spindles mostly corresponds to the alpha frequency range and detailed EEG studies suggest the possibility that slow spindles are anterior peaks of alpha activity during NREM sleep (De Gennaro and Ferrara, 2003). Given these evidences it is quite surprising that most of the methods of sleep spindle analysis are ultimately still based on, validated by, and tied to visual detection of spindles performed by experienced human scorers. By accepting visual scoring as the \ufb01nal test of automatic sleep spindle analysis one is implicitly assuming that human pattern recognition capacities are still superior to computer-based methods of spindle detection or that modern neurophysiological knowledge did not in\ufb02uence the de\ufb01nition of sleep spindles. Since we do not agree with these assumptions, we developed an improved method of sleep spindle analysis, which is a modi\ufb01ed version of our previously published one (B\u00f3dizs et al., 2005). Our main starting points in the development of our method were the followings:<\/p>\n