A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results

From Lung to Brain: Respiration Modulates Neural and Mental Activity

Respiration protocols have been developed to manipulate mental states, including their use for therapeutic purposes. In this systematic review, we discuss evidence that respiration may play a fundamental role in coordinating neural activity, behavior, and emotion. The main findings are: (1) respiration affects the neural activity of a wide variety of regions in the brain; (2) respiration modulates different frequency ranges in the brain's dynamics; (3) different respiration protocols (spontaneous, hyperventilation, slow or resonance respiration) yield different neural and mental effects; and (4) the effects of respiration on the brain are related to concurrent modulation of biochemical (oxygen delivery, pH) and physiological (cerebral blood flow, heart rate variability) variables. We conclude that respiration may be an integral rhythm of the brain's neural activity. This provides an intimate connection of respiration with neuro-mental features like emotion. A respiratory-neuro-mental connection holds the promise for a brain-based therapeutic usage of respiration in mental disorders.

Development of a 3D Relative Motion Method for Human-Robot Interaction Assessment

Exoskeletons have been assessed by qualitative and quantitative features known as performance indicators. Within these, the ergonomic indicators have been isolated, creating a lack of methodologies to analyze and assess physical interfaces. In this sense, this work presents a three-dimensional relative motion assessment method. This method quantifies the difference of orientation between the user’s limb and the exoskeleton link, providing a deeper understanding of the Human–Robot interaction. To this end, the AGoRA exoskeleton was configured in a resistive mode and assessed using an optoelectronic system. The interaction quantified a difference of orientation considerably at a maximum value of 41.1 degrees along the sagittal plane. It extended the understanding of the Human–Robot Interaction throughout the three principal human planes. Furthermore, the proposed method establishes a performance indicator of the physical interfaces of an exoskeleton.

Breath-hold task induces temporal heterogeneity in electroencephalographic regional field power in healthy subjects

We demonstrated that changes in CO₂ values cause oscillations in the cortical activity in δ-and α-bands. The analysis of the regional field power (RFP) showed evidence that different cortical areas respond with different time delays to CO₂ challenges. An opposite behavior was found for the end-tidal O₂. We suppose that the different cortical time delays likely expresse specific ascending pathways to the cortex, generated by chemoreceptor nuclei in the brain stem. Although the brain stem is in charge of the automatic control of ventilation, the cortex is involved in the voluntary control of breathing but also receives inputs from the brain stem, which influences the perception of breathing, the arousal state and sleep architecture in conditions of hypoxia/hypercapnia. We evaluated in 11 healthy subjects the effects of breath hold (BH; 30 s of apneas and 30 s of normal breathing) and BH-related CO₂/O₂ changes on electroencephalogram (EEG) global field power (GFP) and RFP in nine different areas (3 rostrocaudal sections: anterior, central, and posterior; and 3 sagittal sections: left, middle, and right) in the δ- and α-bands by cross correlation analysis. No significant differences were observed in GFP or RFP when comparing free breathing (FB) with the BH task. Within the BH task, the shift from apnea to normal ventilation was accompanied by an increase in the δ-power and a decrease in the α-power. The end-tidal pressure of CO₂ ([Formula: see text]) was positively correlated with the δ-band and negatively with the α- band with a positive time shift, whereas an opposite behavior was found for the end-tidal pressure of O₂ ([Formula: see text]). Notably, the time shift between [Formula: see text] / [Formula: see text] signals and cortical activity at RFP was heterogenous and seemed to follow a hierarchical activation, with the δ-band responding earlier than the α-band. Overall, these findings suggest that the effect of BH on the cortex may follow specific ascending pathways from the brain stem and be related to chemoreflex stimulation.NEW & NOTEWORTHY We demonstrated that the end tidal CO₂ oscillation causes oscillations of delta and alpha bands. The analysis of the regional field power showed that different cortical areas respond with different time delays to CO₂ challenges. An opposite behavior was found for the end-tidal O₂. We can suppose that the different cortical time delay response likely expresses specific ascending pathways to the cortex generated by chemoreceptor nuclei in the brainstem.

Ld-EEG Effective Brain Connectivity in Patients With Cheyne-Stokes Respiration

The characterization of brain cortical activity in heart-failure patients affected by Cheyne-Stokes Respiration might provide relevant information about the mechanism underlying this pathology. Central autonomic network is gaining increasing attention for its role in the regulation of breathing and cardiac functions. In this scenario, evaluating changes in cortical connectivity associated with Cheyne-Stokes Respiration may be of interest in the study of specific brain-activity related to such disease. Nonetheless, the inter subject variability, the temporal dynamics of Central-Apnea/Hyperpnea cycles and the limitations of clinical setups lead to different methodological challenges. To this aim, we present a framework for the assessment of cortico-cortical interactions from Electroencephalographic signals acquired using low-density caps and block-design paradigms, arising from endogenous triggers. The framework combines ICA-decomposition, unsupervised clustering, MVAR modelling and a permutation-bootstrap strategy for evaluating significant connectivity differences between conditions. A common network, lateralized towards the left hemisphere, was depicted across 8 patients exhibiting Cheyne-Stokes Respiration patterns during acquisitions. Significant differences in connectivity at the group level were observed based on patients' ventilatory condition. Interactions were significantly higher during hyperpnea periods with respect to central apneas and occurred mainly in the delta band. Opposite-sign differences were observed for higher frequencies (i.e. beta, low-gamma).

Characterization of Industry 4.0 Lean Management Problem-Solving Behavioral Patterns Using EEG Sensors and Deep Learning

Industry 4.0 leaders solve problems all of the time. Successful problem-solving behavioral pattern choice determines organizational and personal success, therefore a proper understanding of the problem-solving-related neurological dynamics is sure to help increase business performance. The purpose of this paper is two-fold: first, to discover relevant neurological characteristics of problem-solving behavioral patterns, and second, to conduct a characterization of two problem-solving behavioral patterns with the aid of deep-learning architectures. This is done by combining electroencephalographic non-invasive sensors that capture process owners' brain activity signals and a deep-learning soft sensor that performs an accurate characterization of such signals with an accuracy rate of over 99% in the presented case-study dataset. As a result, the deep-learning characterization of lean management (LM) problem-solving behavioral patterns is expected to help Industry 4.0 leaders in their choice of adequate manufacturing systems and their related problem-solving methods in their future pursuit of strategic organizational goals.

Analysis of generic coupling between EEG activity and PETCO2 in free breathing and breath-hold tasks using Maximal Information Coefficient (MIC)

Brain activations related to the control of breathing are not completely known. The respiratory system is a non-linear system. However, the relationship between neural and respiratory dynamics is usually estimated through linear correlation measures, completely neglecting possible underlying nonlinear interactions. This study evaluate the linear and nonlinear coupling between electroencephalographic (EEG) signal and variations in carbon dioxide (CO₂) signal related to different breathing task. During a free breathing and a voluntary breath hold tasks, the coupling between EEG power in nine different brain regions in delta (1–3 Hz) and alpha (8–13 Hz) bands and end-tidal CO₂ (P_ET CO₂) was evaluated. Specifically, the generic associations (i.e. linear and nonlinear correlations) and a “pure” nonlinear correlations were evaluated using the maximum information coefficient (MIC) and MIC-ρ² between the two signals, respectively (where ρ² represents the Pearson’s correlation coefficient). Our results show that in delta band, MIC indexes discriminate the two tasks in several regions, while in alpha band the same behaviour is observed for MIC-ρ², suggesting a generic coupling between delta EEG power and P_ETCO₂ and a pure nonlinear interaction between alpha EEG power and P_ETCO₂. Moreover, higher indexes values were found for breath hold task respect to free breathing.