Independent Component Analysis for Source Localization of EEG Sleep Spindle Components

Sleep spindles are bursts of sleep electroencephalogram (EEG) quasirhythmic activity within the frequency band of 11–16 Hz, characterized by progressively increasing, then gradually decreasing amplitude. The purpose of the present study was to process sleep spindles with Independent Component Analysis (ICA) in order to investigate the possibility of extracting, through visual analysis of the spindle EEG and visual selection of Independent Components (ICs), spindle “components” (SCs) corresponding to separate EEG activity patterns during a spindle, and to investigate the intracranial current sources underlying these SCs. Current source analysis using Low-Resolution Brain Electromagnetic Tomography (LORETA) was applied to the original and the ICA-reconstructed EEGs. Results indicated that SCs can be extracted by reconstructing the EEG through back-projection of separate groups of ICs, based on a temporal and spectral analysis of ICs. The intracranial current sources related to the SCs were found to be spatially stable during the time evolution of the sleep spindles

Automated Sleep Spindle Detection System using Period-Amplitude Analysis

Sleep spindles are rhythmic transient waveforms present in the electroencephalogram (EEG) of non-rapid eye movement (NREM) sleep. In the present study a period-amplitude analysis method was applied for the automated detection of sleep spindles in all-night sleep EEG recordings of young healthy subjects. The method relies on the characterization of individual half-waves of the EEG data, by estimating electrographic parameters such as amplitude and duration and by assigning a grade to each half-wave depending on where it lies in the amplitude-frequency plane. The grading is followed by the detection system, checking consecutive half-wave characteristics and implementing a set of rules for determining the start and the end of spindle bursts and for retaining or rejecting sleep spindle indications provided during the various stages of the detection system. The sensitivity and false positive rate across subjects was 78.9% and 10.9%, respectively, providing indication that the method could be successfully applied to larger sets of healthy subjects of various age groups, as well as to patient populations

Melatonin secretion after head injury: A pilot study

Primary objective: To investigate the circadian rhythm of serum melatonin in patients with traumatic brain injury (TBI) during Intensive Care Unit (ICU) stay and its relationship with core body temperature fluctuations and measures of severity of their condition. Methods and procedures: The pilot study was conducted in the ICU of a general hospital in Athens, Greece. Blood melatonin was determined in eight patients consecutively admitted at the ICU following severe head injury, eight times per day during the first and second day following admission. Core body temperature was recorded at hourly intervals. Patients were also assessed with the Glasgow Coma Score (GCS) and the APACHE II score. Results: Melatonin concentrations were lower than the normally reported values. Mean night-time melatonin levels were higher than mean daytime levels both on the first and second days, although not statistically significant. Diurnal variation of melatonin was associated with the GCS. Thus, patients with low GCS (n=4) did not exhibit a consistent diurnal variation of melatonin, whereas those with high GCS (n = 4) retained the normally expected fluctuations. Conclusions: ICU-treated TBI patients exhibit reduced melatonin levels and a circadian secretion profile which is related to the severity of the injury. Patients with more severe head trauma exhibit a clearly disrupted pattern of melatonin secretion, whereas those with less severe trauma preserve a relatively intact diurnal rhythm. Furthermore, the diurnal secretion pattern of melatonin appeared to be dissociated from the circadian rhythm of core body temperature. These preliminary findings may have implications for the management of TBI patients

Sleep EEG and Spindle Characteristics After Combination Treatment With Clozapine in Drug-Resistant Schizophrenia: A Pilot Study

Purpose: Clozapine is an atypical neuroleptic agent, effective in treating drug-resistant schizophrenia. The aim of this work was to investigate overall sleep architecture and sleep spindle morphology characteristics, before and after combination treatment with clozapine, in patients with drug-resistant schizophrenia who underwent polysomnography. Methods: Standard polysomnographic techniques were used. To quantify the sleep spindle morphology, a modeling technique was used that quantifies time-varying patterns in both the spindle envelope and the intraspindle frequency. Results: After combination treatment with clozapine, the patients showed clinical improvement. In addition, their overall sleep architecture and, more importantly, parameters that quantify the time-varying sleep spindle morphology were affected. Specifically, the results showed increased stage 2 sleep, reduced slow-wave sleep, increased rapid eye movement sleep, increased total sleep time, decreased wake time after sleep onset, as well as effects on spindle amplitude and intraspindle frequency parameters. However, the above changes in overall sleep architecture were statistically non-significant trends. Conclusions: The findings concerning statistically significant effects on spindle amplitude and intraspindle frequency parameters may imply changes in cortical sleep EEG generation mechanisms, as well as changes in thalamic pacing mechanisms or in thalamo-cortical network dynamics involved in sleep EEG generation, as a result of combination treatment with clozapine. Significance: Sleep spindle parameters may serve as metrics for the eventual development of effective EEG biomarkers to investigate treatment effects and pathophysiological mechanisms in schizophrenia

Dynamics of regional brain activity in epilepsy: a cross-disciplinary study on both intracranial and scalp-recorded epileptic seizures

Objective. Recent cross-disciplinary literature suggests a dynamical analogy between earthquakes and epileptic seizures. This study extends the focus of inquiry for the applicability of models for earthquake dynamics to examine both scalp-recorded and intracranial electroencephalogram recordings related to epileptic seizures. Approach. First, we provide an updated definition of the electric event in terms of magnitude and we focus on the applicability of (i) a model for earthquake dynamics, rooted in a nonextensive Tsallis framework, (ii) the traditional Gutenberg and Richter law and (iii) an alternative method for the magnitude-frequency relation for earthquakes. Second, we apply spatiotemporal analysis in terms of nonextensive statistical physics and we further examine the behavior of the parameters included in the nonextensive formula for both types of electroencephalogram recordings under study. Main results. We confirm the previously observed power-law distribution, showing that the nonextensive formula can adequately describe the sequences of electric events included in both types of electroencephalogram recordings. We also show the intermittent behavior of the epileptic seizure cycle which is analogous to the earthquake cycles and we provide evidence of self-affinity of the regional electroencephalogram epileptic seizure activity. Significance. This study may provide a framework for the analysis and interpretation of epileptic brain activity and other biological phenomena with similar underlying dynamical mechanisms

Differences in EEG Delta Frequency Characteristics and Patterns in Slow-Wave Sleep Between Dementia Patients and Controls: A Pilot Study

Purpose: To evaluate the modifications of EEG activity during slow-wave sleep in patients with dementia compared with healthy elderly subjects, using spectral analysis and period-amplitude analysis. Methods: Five patients with dementia and 5 elderly control subjects underwent night polysomnographic recordings. For each of the first three nonrapid eye movement-rapid eye movement sleep cycles, a well-defined slow-wave sleep portion was chosen. The delta frequency band (0.4-3.6 Hz) in these portions was analyzed with both spectral analysis and period-amplitude analysis. Results: Spectral analysis showed an increase in the delta band power in the dementia group, with a decrease across the night observed only in the control group. For the dementia group, period-amplitude analysis showed a decrease in well-defined delta waves of frequency lower than 1.6 Hz and an increase in such waves of frequency higher than 2 Hz, in incidence and amplitude. Conclusions: Our study showed (1) a loss of the dynamics of delta band power across the night sleep, in dementia, and (2) a different distribution of delta waves during slow-wave sleep in dementia compared with control subjects. This kind of computer-based analysis can highlight the presence of a pathologic delta activity during slow-wave sleep in dementia and may support the hypothesis of a dynamic interaction between sleep alteration and cognitive decline