CARE-rCortex: A Matlab toolbox for the analysis of CArdio-REspiratory-related activity in the Cortex

Medical hypnosis mitigates laboratory dyspnoea in healthy humans: a randomised, controlled experimental trial

QUESTION

Dyspnoea persisting despite treatments of underlying causes requires symptomatic approaches. Medical hypnosis could provide relief without the untoward effects of pharmacological approaches. We addressed this question through experimentally induced dyspnoea in healthy humans (inspiratory threshold loading (excessive inspiratory effort) and carbon dioxide stimulation (air hunger)).

MATERIAL AND METHODS

20 volunteers (10 women, aged 21-40 years) were studied on four separate days. The order of the visits was randomised in two steps: firstly, the "inspiratory threshold loading first" versus "carbon dioxide first" group (n=10 in each group); secondly, the "medical hypnosis first" versus "visual distraction first" subgroup (n=5 in each subgroup). Each visit comprised three 5-min periods (reference, intervention, washout) during which participants used visual analogue scales (VAS) to rate the sensory and affective dimensions of dyspnoea, and after which they completed the Multidimensional Dyspnea Profile.

RESULTS

Medical hypnosis reduced both dimensions of dyspnoea significantly more than visual distraction (inspiratory threshold loading: sensory reduction after 5 min 34% of full VAS versus 8% (p=0.0042), affective reduction 17.6% versus 2.4% (p=0.044); carbon dioxide: sensory reduction after 5 min 36.9% versus 3% (p=0.0015), affective reduction 29.1% versus 8.7% (p=0.0023)). The Multidimensional Dyspnea Profile showed more marked sensory effects during inspiratory threshold loading and more marked affective effects during carbon dioxide stimulation.

ANSWER TO THE QUESTION

Medical hypnosis was more effective than visual distraction at attenuating the sensory and affective dimensions of experimentally induced dyspnoea. This provides a strong rationale for clinical studies of hypnosis in persistent dyspnoea patients.

Neurophysiological basis of respiratory discomfort improvement by mandibular advancement in awake OSA patients

Patients with obstructive sleep apneas (OSA) do not complain from dyspnea during resting breathing. Placement of a mandibular advancement device (MAD) can lead to a sense of improved respiratory comfort ("pseudo-relief") ascribed to a habituation phenomenon. To substantiate this conjecture, we hypothesized that, in non-dyspneic awake OSA patients, respiratory-related electroencephalographic figures, abnormally present during awake resting breathing, would disappear or change in parallel with MAD-associated pseudo-relief. In 20 patients, we compared natural breathing and breathing with MAD on: breathing discomfort (transitional visual analog scale, VAS-2); upper airway mechanics, assessed in terms of pressure peak/time to peak (TTP) ratio respiratory-related electroencephalography (EEG) signatures, including slow event-related preinspiratory potentials; and a between-state discrimination based on continuous connectivity evaluation. MAD improved breathing and upper airway mechanics. The 8 patients in whom the EEG between-state discrimination was considered effective exhibited higher Peak/TTP improvement and transitional VAS ratings while wearing MAD than the 12 patients where it was not. These results support the notion of habituation to abnormal respiratory-related afferents in OSA patients and fuel the causative nature of the relationship between dyspnea, respiratory-related motor cortical activity and impaired upper airway mechanics in this setting.

Short-term cognitive loading deteriorates breathing pattern and gas exchange in adult patients with congenital central hypoventilation syndrome

Question

Human PHOX2B mutations result in life-threatening sleep-related hypoventilation (congenital central hypoventilation syndrome, CCHS). Most patients retain ventilatory activity when awake through a respiratory-related cortical network. We hypothesised that this need to mobilise cortical resources to breathe would lead to breathing-cognition interferences during cognitive loading.

Patients and methods

Seven adult CCHS patients (five women; median age 21) performed standard neuropsychological tests (paced auditory serial addition test - calculation capacity, working memory, sustained and divided attention; trail making test - visuospatial exploration capacity, cognitive processing speed, attentional flexibility; Corsi block-tapping test - visuospatial memory, short-term memory, working memory) during unassisted breathing and under ventilatory support. Ventilatory variables and transcutaneous haemoglobin oxygen saturation were recorded. Cortical connectivity changes between unassisted breathing and ventilatory support were assessed using electroencephalographic recordings (EEG).

Results

Baseline performances were lower than expected in individuals of this age. During unassisted breathing, cognitive loading coincided with increased breathing variability, and decreases in oxygen saturation inversely correlated with an increasing number of apnoeic cycles per minute (rho -0.46, 95% CI -0.76 to -0.06, p=0.01). During ventilatory support, cognitive tasks did not disrupt breathing pattern and were not associated with decreased oxygen saturation. Ventilatory support was associated with changes in EEG cortical connectivity but not with improved test performances.

Conclusions

Acute cognitive loads induce oxygen desaturation in adult CCHS patients during unassisted breathing, but not under ventilatory support. This justifies considering the use of ventilatory support during mental tasks in CCHS patients to avoid repeated episodes of hypoxia.

Neural Networks to Recognize Patterns in Topographic Images of Cortical Electrical Activity of Patients with Neurological Diseases

Software such as EEGLab has enabled the treatment and visualization of the tracing and cortical topography of the electroencephalography (EEG) signals. In particular, the topography of the cortical electrical activity is represented by colors, which make it possible to identify functional differences between cortical areas and to associate them with various diseases. The use of cortical topography with EEG origin in the investigation of diseases is often not used due to the representation of colors making it difficult to classify the disease. Thus, the analyses have been carried out, mainly, based on the EEG tracings. Therefore, a computer system that recognizes disease patterns through cortical topography can be a solution to the diagnostic aid. In view of this, this study compared five models of Convolutional Neural Networks (CNNs), namely: Inception v3, SqueezeNet, LeNet, VGG-16 and VGG-19, in order to know the patterns in cortical topography images obtained with EEG, in Parkinson's disease, Depression and Bipolar Disorder. SqueezeNet performed better in the 3 diseases analyzed, with Parkinson's disease being better evaluated for Accuracy (88.89%), Precison (86.36%), Recall (91.94%) and F1 Score (89.06%), the other CNNs had less performance. In the analysis of the values of the Area under ROC Curve (AUC), SqueezeNet reached (93.90%) for Parkinson's disease, (75.70%) for Depression and (72.10%) for Bipolar Disorder. We understand that there is the possibility of classifying neurological diseases from cortical topographies with the use of CNNs and, thus, creating a computational basis for the implementation of software for screening and possible diagnostic assistance.

Impact of inspiratory threshold loading on brain activity and cognitive performances in healthy humans

In healthy humans, inspiratory threshold loading deteriorates cognitive performances. This can result from motor-cognitive interference (activation of motor respiratory-related cortical networks vs. executive resources allocation), sensory-cognitive interference (dyspnea vs. shift in attentional focus), or both. We hypothesized that inspiratory loading would concomitantly induce dyspnea, activate motor respiratory-related cortical networks, and deteriorate cognitive performance. We reasoned that a concomitant activation of cortical networks and cognitive deterioration would be compatible with motor-cognitive interference, particularly in case of a predominant alteration of executive cognitive performances. Symmetrically, we reasoned that a predominant alteration of attention-depending performances would suggest sensory-cognitive interference. Twenty-five volunteers (12 men; 19.5-51.5 years) performed the Paced Auditory Serial Addition test (PASAT-A and B; calculation capacity, working memory, attention), the Trail Making Test (TMT-A, visuospatial exploration capacity; TMT-B, visuospatial exploration capacity and attention), and the Corsi block-tapping test (visuospatial memory, short-term and working memory) during unloaded breathing and inspiratory threshold loading in random order. Loading consistently induced dyspnea and respiratory-related brain activation. It was associated with deteriorations inPASAT A (52 [45.5;55.5] (median [interquartile range]) to 48 [41;54.5], p=0.01), PASAT B (55 [47.5;58] to 51 [44.5;57.5], p=0.01), and TMT B (44s [36;54.5] to 53s [42;64], p=0.01), but did not affect TMT-A and Corsi. The concomitance of cortical activation and cognitive performance deterioration is compatible with competition for cortical resources (motor-cognitive interference), while the profile of cognitive impairment (PASAT and TMT-B but not TMT-A and Corsi) is compatible with a contribution of attentional distraction (sensory-cognitive interference). Both mechanisms are therefore likely at play.

The role of electroencephalography electrical reference in the assessment of functional brain-heart interplay: From methodology to user guidelines

BACKGROUND

The choice of EEG reference has been widely studied. However, the choice of the most appropriate re-referencing for EEG data is still debated. Moreover, the role of EEG reference in the estimation of functional Brain-Heart Interplay (BHI), together with different multivariate modelling strategies, has not been investigated yet.

METHODS

This study identifies the best methodology combining a proper EEG electrical reference and signal processing methods for an effective functional BHI assessment. The effects of the EEG reference among common average, mastoids average, Laplacian reference, Cz reference, and the reference electrode standardization technique (REST) were explored throughout different BHI methods including synthetic data generation (SDG) model, heartbeat-evoked potentials, heartbeat-evoked oscillations, and maximal information coefficient.

RESULTS

The SDG model exhibited high robustness between EEG references, whereas the maximal information coefficient method exhibited a high sensitivity. The common average and REST references for EEG showed a good consistency in the between-method comparisons. Laplacian, and Cz references significantly bias a BHI measurement.

COMPARISON WITH EXISTING METHODS

The use of EEG reference based on a common average outperforms on the use of other references for consistency in estimating directed functional BHI. We do not recommend the use of EEG references based on analytical derivations as the experimental conditions may not meet the requirements of their optimal estimation, particularly in clinical settings.

CONCLUSION

The use of a common average for EEG electrical reference is concluded to be the most appropriate choice for a quantitative, functional BHI assessment.

Methodological Considerations on EEG Electrical Reference: A Functional Brain-Heart Interplay Study

The growing interest in the study of functional brain-heart interplay (BHI) has motivated the development of novel methodological frameworks for its quantification. While a combination of electroencephalography (EEG) and heartbeat-derived series has been widely used, the role of EEG preprocessing on a BHI quantification is yet unknown. To this extent, here we investigate on four different EEG electrical referencing techniques associated with BHI quantifications over 4-minute resting-state in 15 healthy subjects. BHI methods include the synthetic data generation model, heartbeat-evoked potentials, heartbeat-evoked oscillations, and maximal information coefficient (MIC). EEG signals were offline referenced under the Cz channel, common average, mastoids average, and Laplacian method, and statistical comparisons were performed to assess similarities between references and between BHI techniques. Results show a topographical agreement between BHI estimation methods depending on the specific EEG reference. Major differences between BHI methods occur with the Laplacian reference, while major differences between EEG references are with the MIC analysis. We conclude that the choice of EEG electrical reference may significantly affect a functional BHI quantification.

Adjusting ventilator settings to relieve dyspnoea modifies brain activity in critically ill patients: an electroencephalogram pilot study

Dyspnoea is frequent and distressing in patients receiving mechanical ventilation, but it is often not properly evaluated by caregivers. Electroencephalographic signatures of dyspnoea have been identified experimentally in healthy subjects. We hypothesized that adjusting ventilator settings to relieve dyspnoea in MV patients would induce EEG changes. This was a first-of-its-kind observational study in a convenience population of 12 dyspnoeic, mechanically ventilated patients for whom a decision to adjust the ventilator settings was taken by the physician in charge (adjustments of pressure support, slope, or trigger). Pre- and post-ventilator adjustment electroencephalogram recordings were processed using covariance matrix statistical classifiers and pre-inspiratory potentials. The pre-ventilator adjustment median dyspnoea visual analogue scale was 3.0 (interquartile range: 2.5–4.0; minimum-maximum: 1–5) and decreased by (median) 3.0 post-ventilator adjustment. Statistical classifiers adequately detected electroencephalographic changes in 8 cases (area under the curve ≥0.7). Previously present pre-inspiratory potentials disappeared in 7 cases post-ventilator adjustment. Dyspnoea improvement was consistent with electroencephalographic changes in 9 cases. Adjusting ventilator settings to relieve dyspnoea produced detectable changes in brain activity. This paves the way for studies aimed at determining whether monitoring respiratory-related electroencephalographic activity can improve outcomes in critically ill patients under mechanical ventilation.