Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Prospective Cohort Study

Healthy biological systems exhibit complex patterns of variability that can be described by mathematical chaos. Heart rate variability (HRV) consists of changes in the time intervals between consecutive heartbeats called interbeat intervals (IBIs). A healthy heart is not a metronome. The oscillations of a healthy heart are complex and constantly changing, which allow the cardiovascular system to rapidly adjust to sudden physical and psychological challenges to homeostasis. This article briefly reviews current perspectives on the mechanisms that generate 24 h, short-term (~5 min), and ultra-short-term (<5 min) HRV, the importance of HRV, and its implications for health and performance. The authors provide an overview of widely-used HRV time-domain, frequency-domain, and non-linear metrics. Time-domain indices quantify the amount of HRV observed during monitoring periods that may range from ~2 min to 24 h. Frequency-domain values calculate the absolute or relative amount of signal energy within component bands. Non-linear measurements quantify the unpredictability and complexity of a series of IBIs. The authors survey published normative values for clinical, healthy, and optimal performance populations. They stress the importance of measurement context, including recording period length, subject age, and sex, on baseline HRV values. They caution that 24 h, short-term, and ultra-short-term normative values are not interchangeable. They encourage professionals to supplement published norms with findings from their own specialized populations. Finally, the authors provide an overview of HRV assessment strategies for clinical and optimal performance interventions.

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An Overview of Heart Rate Variability Metrics and Norms.

The International League Against Epilepsy (ILAE) Classification of the Epilepsies has been updated to reflect our gain in understanding of the epilepsies and their underlying mechanisms following the major scientific advances that have taken place since the last ratified classification in 1989. As a critical tool for the practicing clinician, epilepsy classification must be relevant and dynamic to changes in thinking, yet robust and translatable to all areas of the globe. Its primary purpose is for diagnosis of patients, but it is also critical for epilepsy research, development of antiepileptic therapies, and communication around the world. The new classification originates from a draft document submitted for public comments in 2013, which was revised to incorporate extensive feedback from the international epilepsy community over several rounds of consultation. It presents three levels, starting with seizure type, where it assumes that the patient is having epileptic seizures as defined by the new 2017 ILAE Seizure Classification. After diagnosis of the seizure type, the next step is diagnosis of epilepsy type, including focal epilepsy, generalized epilepsy, combined generalized, and focal epilepsy, and also an unknown epilepsy group. The third level is that of epilepsy syndrome, where a specific syndromic diagnosis can be made. The new classification incorporates etiology along each stage, emphasizing the need to consider etiology at each step of diagnosis, as it often carries significant treatment implications. Etiology is broken into six subgroups, selected because of their potential therapeutic consequences. New terminology is introduced such as developmental and epileptic encephalopathy. The term benign is replaced by the terms self-limited and pharmacoresponsive, to be used where appropriate. It is hoped that this new framework will assist in improving epilepsy care and research in the 21st century.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/epi.13709

ILAE classification of the epilepsies: Position paper of the ILAE Commission for Classification and Terminology.

background Previous studies have suggested that the obstructive sleep apnea syndrome may be an important risk factor for stroke. It has not been determined, however, whether the syndrome is independently related to the risk of stroke or death from any cause after adjustment for other risk factors, including hypertension. methods In this observational cohort study, consecutive patients underwent polysomnography, and subsequent events (strokes and deaths) were verified. The diagnosis of the obstructive sleep apnea syndrome was based on an apnea–hypopnea index of 5 or higher (five or more events per hour); patients with an apnea–hypopnea index of less than 5 served as the comparison group. Proportional-hazards analysis was used to determine the independent effect of the obstructive sleep apnea syndrome on the composite outcome of stroke or death from any cause. results Among 1022 enrolled patients, 697 (68 percent) had the obstructive sleep apnea syndrome. At baseline, the mean apnea–hypopnea index in the patients with the syndrome was 35, as compared with a mean apnea–hypopnea index of 2 in the comparison group. In an unadjusted analysis, the obstructive sleep apnea syndrome was associated with stroke or death from any cause (hazard ratio, 2.24; 95 percent confidence interval, 1.30 to 3.86; P=0.004). After adjustment for age, sex, race, smoking status, alcohol-consumption status, body-mass index, and the presence or absence of diabetes mellitus, hyperlipidemia, atrial fibrillation, and hypertension, the obstructive sleep apnea syndrome retained a statistically significant association with stroke or death (hazard ratio, 1.97; 95 percent confidence interval, 1.12 to 3.48; P=0.01). In a trend analysis, increased severity of sleep apnea at baseline was associated with an increased risk of the development of the composite end point (P=0.005). conclusions The obstructive sleep apnea syndrome significantly increases the risk of stroke or death from any cause, and the increase is independent of other risk factors, including hypertension.

https://www.nejm.org/doi/pdf/10.1056/NEJMoa043104

Obstructive sleep apnea as a risk factor for stroke and death.

Phase and amplitude correlations in resting-state activity in human stereotactical EEG recordings.

Cholinergic modulation, visual function and Alzheimer's dementia.

Nocturnal frontal lobe epilepsy (NFLE) is a syndrome of heterogeneous etiology, characterized by the occurrence of sleep-related seizures with different complexity and duration. Genetic, lesional, and cryptogenetic NFLE forms have been described. NFLE is generally considered a benign clinical entity, although severe, drug-resistant forms do exist. A significant proportion of sleep-related complex motor seizures, hardly distinguishable from NFLE, originate outside the frontal lobe. Moreover, the distinction of NFLE from the non-rapid eye movement arousal parasomnias may be challenging. A correct diagnosis of NFLE should be based on a diagnostic approach that includes the anamnestic, video-polysomnographic, morphological, and genetic aspects. Studies on the relationships between genes, arousal regulatory mechanisms, and epileptogenesis, using both clinical and experimental models of NFLE might provide key insights in the interrelationship between sleep and epilepsy.

https://link.springer.com/content/pdf/10.1007%2Fs11910-013-0424-6.pdf

Nocturnal frontal lobe epilepsy.

The microstructure of REM sleep: Why phasic and tonic?

A method for the automatic detection of arousals in digital polysomnographic recordings is described. The computer program analyzed two EEG and one EMG derivations marking variable length segments as arousals. The processing of EEG data started from the wavelet transform, which characterizes the signal in the time-frequency domain, and resulted in a set of indices used to discriminate possible arousal segments. Transient increases in muscle activity were also identified, while a multichannel and context sensitive analysis allowed arousal detection. Out of 11 overnight recordings, 3 were used as the training set and 8 as the program testing set. In the first stage of the study two EEG experts inspected the tracings independently to score arousals. They then reviewed all recordings and jointly examined each event for validation, both those scored by themselves and those scored by the computer. A reference set of definite arousals (1125 in the testing set) and a number of uncertain events (266) were thus obtained. The sensitivity of the automatic system (88.1%) was higher than that of the human experts (72.4 and 78.4%) while the selectivity was lower (74.5% for the automatic system, 83.0 and 82.0% for the experts). This suggested that automatic detection, followed by an expert's validation, may render the analysis of arousals more widely feasible as well as support the study of arousal features.

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Lino Nobili

Papers

Phase and amplitude correlations in resting-state activity in human stereotactical EEG recordings.

Cholinergic modulation, visual function and Alzheimer's dementia.

Nocturnal frontal lobe epilepsy.

The microstructure of REM sleep: Why phasic and tonic?

A method for the automatic detection of arousals during sleep.