Sleep-Dependent Directional Interactions of the Central Nervous System-Cardiorespiratory Network

Neural coding of autonomic functions in different states of consciousness

Detecting signs of residual neural activity in patients with altered states of consciousness is a crucial issue for the customization of neurorehabilitation treatments and clinical decision-making. With this large observational prospective study, we propose an innovative approach to detect residual signs of consciousness via the assessment of the amount of autonomic information coded within the brain. The latter was estimated by computing the mutual information (MI) between preprocessed EEG and ECG signals, to be then compared across consciousness groups, together with the absolute power and an international qualitative labeling. One-hundred seventy-four patients (73 females, 42%) were included in the study (median age of 65 years [IQR = 20], MCS +: 29, MCS -: 23, UWS: 29). Electroencephalography (EEG) information content was found to be mostly related to the coding of electrocardiography (ECG) activity, i.e., with higher MI (p < 0.05), in Unresponsive Wakefulness Syndrome and Minimally Consciousness State minus (MCS -). EEG-ECG MI, besides clearly discriminating patients in an MCS - and +, significantly differed between lesioned areas (sides) in a subgroup of unilateral hemorrhagic patients. Crucially, such an accessible and non-invasive measure of residual consciousness signs was robust across electrodes and patient groups. Consequently, exiting from a strictly neuro-centric consciousness detection approach may be the key to provide complementary insights for the objective assessment of patients' consciousness levels and for the patient-specific planning of rehabilitative interventions.

Can Respiration Complexity Help the Diagnosis of Disorders of Consciousness in Rehabilitation?

BACKGROUND

Autonomic Nervous System (ANS) activity, as cardiac, respiratory and electrodermal activity, has been shown to provide specific information on different consciousness states. Respiration rates (RRs) are considered indicators of ANS activity and breathing patterns are currently already included in the evaluation of patients in critical care.

OBJECTIVE

The aim of this work was to derive a proxy of autonomic functions via the RR variability and compare its diagnostic capability with known neurophysiological biomarkers of consciousness.

METHODS

In a cohort of sub-acute patients with brain injury during post-acute rehabilitation, polygraphy (ECG, EEG) recordings were collected. The EEG was labeled via descriptors based on American Clinical Neurophysiology Society terminology and the respiration variability was extracted by computing the Approximate Entropy (ApEN) of the ECG-derived respiration signal. Competing logistic regressions were applied to evaluate the improvement in model performances introduced by the RR ApEN.

RESULTS

Higher RR complexity was significantly associated with higher consciousness levels and improved diagnostic models' performances in contrast to the ones built with only electroencephalographic descriptors.

CONCLUSIONS

Adding a quantitative, instrumentally based complexity measure of RR variability to multimodal consciousness assessment protocols may improve diagnostic accuracy based only on electroencephalographic descriptors. Overall, this study promotes the integration of biomarkers derived from the central and the autonomous nervous system for the most comprehensive diagnosis of consciousness in a rehabilitation setting.

Investigating the influence of an adjustable zoned air mattress on sleep: a multinight polysomnography study

Introduction

A comfortable mattress should improve sleep quality. In this study, we sought to investigate the specific sleep parameters that could be affected by a mattress and explore any potential differences between the effects felt by each sex.

Methods

A total of 20 healthy young adults (10 females and 20 males; 22.10 ± 1.25 years) participated in the experiments. A smart adjustable zoned air mattress was designed to maintain comfortable support, and an ordinary mattress was used for comparison. The participants individually spent four nights on these two mattresses in four orders for polysomnography (PSG) scoring. Sleep architecture, electroencephalogram (EEG) spectrum, and heart rate variability (HRV), which reflect the central and autonomic nervous activities, were used to compare the difference between the two mattresses.

Results

An individual difference exited in sleep performance. The modes of influence of the mattresses were different between the sexes. The adjustable air mattress and the increase in experimental nights improved female participants' sleep efficiency, while male participants exhibited a smaller response to different mattresses. With an increasing number of experiment nights, both sexes showed increased REM and decreased N2 proportions; the N3 sleep proportion decreased in the male participants, and the heart rate decreased in both sexes. The performance of the EEG spectrum supports the above results. In addition, the adjustable air mattress weakened automatic nerve activity during N3 sleep in most participants. The female participants appeared to be more sensitive to mattresses. Experiment night was associated with psychological factors. There were differences in the results for this influence between the sexes.

Conclusion

This study may shed some light on the differences between the ideal sleep environment of each sex.

Interactions of central and autonomic nervous systems in patients with sleep apnea-hypopnea syndrome during sleep

PURPOSE

Sleep apnea-hypopnea syndrome (SAHS) is an independent risk factor for various cardiovascular and cerebrovascular diseases, but the underlying relationship of its physiological subsystems remains unclear. Thus, we aimed to investigate the effect of SAHS on central and autonomic nervous system (CNS-ANS) interactions during sleep.

METHODS

Thirty-five patients with SAHS and 19 healthy age-matched controls underwent overnight polysomnography. The absolute spectral powers of five frequency bands from six EEG channels and ECG morphological features (HR, PR interval, QT interval) were calculated. Multivariable transfer entropy was applied to analyze the differences of the CNS-ANS network interactions between patients with SAHS of different severities and healthy controls during deep, light, and rapid eye movement sleep.

RESULTS

The CNS-ANS network interacted bidirectionally in all researched groups, with the cardiac information modulating the brain activity. The information strength from QT to most EEG components and PR to some EEG components was significantly affected by SAHS severity during light sleep, which indicates the coupling features of QT-brain nodes are important indicators. The driver effects from the β-band significantly increased in patients with SAHS.

CONCLUSIONS

Respiratory events may be the main reason for the CNS-ANS interaction changes in SAHS. These findings help explain the physiological regulation process of SAHS and provide valuable information for analysis of the development of SAHS-related cardiovascular and chronic diseases.