Sleep spindle alterations in patients with Parkinson's disease

Abstract

The aim of this study was to identify changes of sleep spindles (SS) in the EEG of patients with Parkinson's disease (PD). Five sleep experts manually identified SS at a central scalp location (C3-A2) in 15 PD and 15 age- and sex-matched control subjects. Each SS was given a confidence score, and by using a group consensus rule, 901 SS were identified and characterized by their (1) duration, (2) oscillation frequency, (3) maximum peak-to-peak amplitude, (4) percent-to-peak amplitude, and (5) density. Between-group comparisons were made for all SS characteristics computed, and significant changes for PD patients vs. control subjects were found for duration, oscillation frequency, maximum peak-to-peak amplitude and density. Specifically, SS density was lower, duration was longer, oscillation frequency slower and maximum peak-to-peak amplitude higher in patients vs. controls. We also computed inter-expert reliability in SS scoring and found a significantly lower reliability in scoring definite SS in patients when compared to controls. How neurodegeneration in PD could influence SS characteristics is discussed. We also note that the SS morphological changes observed here may affect automatic detection of SS in patients with PD or other neurodegenerative disorders (NDDs).

Investigation of sleep spindle activity and morphology as predictors of neurocognitive functioning in medicated patients with schizophrenia

“…Each detected spindle was characterized by its: (1) duration; (2) oscillation frequency; (3) maximum peak‐to‐peak amplitude; and (4) symmetry (percent‐to‐peak amplitude); all of which are well evaluated and have been used elsewhere (Christensen et al., ; Warby et al., ). Before any of the measures were computed, the central EEG signal was filtered with the same filters (notch and band‐pass of 0.3–35 Hz) as in the pre‐processing step before the spindle detection.…”

“…Basically, this way of estimating the oscillation frequency is based on the mean of each full cycle of the spindle (captured in the vectors and ), and is therefore less biased by the low resolution of the duration of each spindle. The extrema points were detected in the same way as previously validated (Christensen et al., ) using Matlab's findpeaks ‐function applied on a five‐point moving average smoothed version of the spindle signal and with a minimum peak‐to‐peak distance of 11 samples. Similar to previously, the maximum points were found applying the function directly, while the minima points were found by applying the function on the flipped signal.…”

Assessment of Sleep Spindle Density among Genetically Positive Spinocerebellar Ataxias Types 1, 2, and 3 Patients

“…Patients with Parkinson’s disease (PD) have decreased sleep spindle densities and altered spindle characteristics when compared to controls [29]. It was found that patients with PD have a lower sleep spindle density compared to age- and gender-matched controls.…”

“…It is therefore likely that the neurodegenerative involvement of prethalamic fibers from the brain stem may affect spindle activity to a certain degree [31]. Christensen et al [29] has proposed sleep spindles as one of the biomarkers of ongoing neurodegeneration in PD. Substantial decrease in sleep spindles is seen in patients of progressive supranuclear palsy as compared to controls [32].…”

Sleep Spindle Deficit in Schizophrenia: Contextualization of Recent Findings

“…Atypical spindles with abnormal duration/frequency or those surrounded by EEG that is not typical of N2 sleep are seldom detected. The description of such events using specific parameters that describe their morphology could yield precious information on disease-specific morphological changes on which the duration and severity of the disorder impacts [58]. Moreover, sleep architecture and other sleepspecific features need to be always carefully considered when evaluating sleep spindles to avoid confounding biases.…”