THE AUTONOMIC NERVOUS SYSTEM

Molecular Imaging in CANVAS: A Contribution for Differential Diagnosis?

BACKGROUND

Phenotypes of CANVAS are increasingly diversified, including bradykinesia and dysautonomia, so that its primary differential diagnoses are multiple system atrophy-cerebellar type (MSA-c), and spinocerebellar ataxia type 3 (SCA3). This case series aims to highlight key molecular imaging findings in CANVAS.

CASES

We report a case series of six patients with CANVAS who underwent nuclear medicine examinations in our center and 13 patients from the literature. These include 18F-FDG brain positron emission tomography (PET), single photon emission computed tomography (SPECT) of dopamine transporter (DaT) activity, and 123I-MIBG cardiac scintigraphy of noradrenergic transmission.

CONCLUSIONS

In CANVAS, 18F-FDG brain PET mainly shows cerebellar hypometabolism, with preserved brainstem and striatum metabolism, contrasting with SCA3 and MSA-c. Dopaminergic denervation on scintigraphy seems to be associated with clinical parkinsonism, ranging from normal to severely impaired DaT SPECT. Additionally, 123I-MIBG cardiac scintigraphy might show denervation in CANVAS, similar to SCA3, but not in most MSA-c patients.

Central autonomic network and early prognosis in patients with disorders of consciousness

The central autonomic network (CAN) plays a crucial role in modulating the autonomic nervous system. Heart rate variability (HRV) is a valuable marker for assessing CAN function in disorders of consciousness (DOC) patients. We used HRV analysis for early prognosis in 58 DOC patients enrolled within ten days of hospitalization. They underwent a five-minute electrocardiogram during baseline and acoustic/visual stimulation. The coma recovery scale-revised (CRS-R) was used to define the patient's consciousness level and categorize the good/bad outcome at three months. The high-frequency Power Spectrum Density and the standard deviation of normal-to-normal peaks in baseline, the sample entropy during the stimulation, and the time from injury features were used in the support vector machine analysis (SVM) for outcome prediction. The SVM predicted the patients' outcome with an accuracy of 96% in the training test and 100% in the validation test, underscoring its potential to provide crucial clinical information about prognosis.

Vasovagal Syncope Is Associated with Variants in Genes Involved in Neurohumoral Signaling Pathways

Vasovagal syncope (VVS) is the most common cause of sudden loss of consciousness. VVS results from cerebral hypoperfusion, due to abnormal autonomic control of blood circulation, leading to arterial hypotension. It is a complex disease, and its development is largely associated with genetic susceptibility. Since abnormal neurohumoral regulation plays an important role in VVS development, we analyzed the association of VVS with polymorphic variants of ADRA1A, ADRB1, HTR1A, ADORA2A, COMT, and NOS3 genes, the products of which are involved in neurohumoral signaling, in patients with a confirmed VVS diagnosis (157 subjects) and individuals without a history of syncope (161 subjects). We were able to identify the associations between VVS and alleles/genotypes ADRA1A rs1048101, ADRB1 rs1801253, ADORA2A rs5751876, and COMT rs4680, as well as NOS3 rs2070744 in biallelic combination with COMT rs4680. Thus, we are the first to observe, within a single study, the role of the genes that encode α- and β-adrenergic receptors, catechol-O-methyltransferase, adenosine receptors and nitric oxide synthase in VVS development. These findings demonstrate that the genes involved in neurohumoral signaling pathways contribute to the formation of a genetic susceptibility to VVS.

Inhibitory Control and Brain–Heart Interaction: An HRV-EEG Study

Background: Motor inhibition is a complex cognitive function regulated by specific brain regions and influenced by the activity of the Central Autonomic Network. We investigate the two-way Brain–Heart interaction during a Go/NoGo task. Spectral EEG ϑ, α powerbands, and HRV parameters (Complexity Index (CI), Low Frequency (LF) and High Frequency (HF) powers) were recorded. Methods: Fourteen healthy volunteers were enrolled. We used a modified version of the classical Go/NoGo task, based on Rule Shift Cards, characterized by a baseline and two different tasks of different complexity. The participants were divided into subjects with Good (GP) and Poor (PP) performances. Results: In the baseline, CI was negatively correlated with α/ϑ. In task 1, the CI was negatively correlated with the errors and α/ϑ, while the errors were positively correlated with α/ϑ. In task 2, CI was negatively correlated with the Reaction Time and positively with α, and the errors were negatively correlated with the Reaction Time and positively correlated with α/ϑ. The GP group showed, at baseline, a negative correlation between CI and α/ϑ. Conclusions: We provide a new combined Brain–Heart model underlying inhibitory control abilities. The results are consistent with the complementary role of α and ϑ oscillations in cognitive control.

The Timecourse of Electrophysiological Brain-Heart Interaction in DoC Patients

Disorders of Consciousness (DOC) are a spectrum of pathologies affecting one's ability to interact with the external world. Two possible conditions of patients with DOC are Unresponsive Wakefulness Syndrome/Vegetative State (UWS/VS) and Minimally Conscious State (MCS). Analysis of spontaneous EEG activity and the Heart Rate Variability (HRV) are effective techniques in exploring and evaluating patients with DOC. This study aims to observe fluctuations in EEG and HRV parameters in the morning/afternoon resting-state recording. The study enrolled 13 voluntary Healthy Control (HC) subjects and 12 DOC patients (7 MCS, 5 UWS/VS). EEG and EKG were recorded. PSDalpha, PSDtheta powerband, alpha-blocking, alpha/theta of the EEG, Complexity Index (CI) and SDNN of EKG were analyzed. Higher values of PSDalpha, alpha-blocking, alpha/theta and CI values and lower values of PSD theta characterized HC individuals in the morning with respect to DOC patients. In the afternoon, we detected a significant difference between groups in the CI, PSDalpha, PSDtheta, alpha/theta and SDNN, with lower PSDtheta value for HC. CRS-R scores showed a strong correlation with recorded parameters mainly during evaluations in the morning. Our finding put in evidence the importance of the assessment, as the stimulation of DOC patients in research for behavioural response, in the morning.

Addressing Pain for a Proper Rehabilitation Process in Patients With Severe Disorders of Consciousness

Consciousness constitutes a fundamental prerequisite in the individual appraisal and experience of pain. In the same way, a person needs to be able to report on pain perception. Patients who suffered a severe brain injury with disorders of consciousness (DOC) represent a spectrum of pathologies affecting patients' capacity to interact with the external world. In these patients, the most relevant aspects in response to pain are physiologic and behavioral. The treatments and management of pain are challenging issues in these patients, arising serious ethical concerns and bringing emotional load among medical staff, caregivers, and relatives. In this review, we report the importance of having a correct pain management in DOC patients, to individuate the best pharmacological treatment that can make the difference in detecting a behavioral response, indicative of a change in the level of consciousness, and in planning a more effective rehabilitative approach.

Measures of CNS-Autonomic Interaction and Responsiveness in Disorder of Consciousness

Neuroimaging studies have demonstrated functional interactions between autonomic (ANS) and brain (CNS) structures involved in higher brain functions, including attention and conscious processes. These interactions have been described by the Central Autonomic Network (CAN), a concept model based on the brain-heart two-way integrated interaction. Heart rate variability (HRV) measures proved reliable as non-invasive descriptors of the ANS-CNS function setup and are thought to reflect higher brain functions. Autonomic function, ANS-mediated responsiveness and the ANS-CNS interaction qualify as possible independent indicators for clinical functional assessment and prognosis in Disorders of Consciousness (DoC). HRV has proved helpful to investigate residual responsiveness in DoC and predict clinical recovery. Variability due to internal (e.g., homeostatic and circadian processes) and environmental factors remains a key independent variable and systematic research with this regard is warranted. The interest in bidirectional ANS-CNS interactions in a variety of physiopathological conditions is growing, however, these interactions have not been extensively investigated in DoC. In this brief review we illustrate the potentiality of brain-heart investigation by means of HRV analysis in assessing patients with DoC. The authors' opinion is that this easy, inexpensive and non-invasive approach may provide useful information in the clinical assessment of this challenging patient population.

Heart Rate Variability as an Indicator of Nociceptive Pain in Disorders of Consciousness?

CONTEXT

Heart rate variability is thought to reflect the affective and physiological aspects of pain and is emerging as a possible descriptor of the functional brain organization contributing to homeostasis.

OBJECTIVES

To investigate whether the short-term Complexity Index (CIs), a measure of heart rate variability complexity is useful to discriminate responses to potentially noxious and nonnoxious stimulation in patients with different levels of consciousness.

METHODS

Twenty-two patients (11 minimally conscious state [MCS], 11 vegetative state/unresponsive wakefulness syndrome [VS/UWS]) and 14 healthy controls (HC) were enrolled. We recorded the electrocardiographic response and calculated the CIs before (baseline), during, and after nonnoxious and noxious stimulation. Mann-Whitney and Wilcoxon's tests were used to investigate differences in CIs according to the level of consciousness (i.e., HC vs. patients and VS/UWS vs. MCS) and the three conditions (i.e., baseline, nonnoxious, noxious). The correlation between the three conditions and the Coma Recovery Scale-Revised was investigated by Spearman's correlations.

RESULTS

We observed higher CIs values in HC as compared with patients during the baseline (P < 0.034) and after the noxious stimulation (P < 0.0001). We also found higher values in MCS versus VS/UWS patients after the noxious condition (P < 0.001) and lower values in the noxious versus nonnoxious condition solely for the VS/UWS group (P < 0.007). A correlation was found between CIs in noxious condition and Coma Recovery Scale-Revised scores.

CONCLUSION

Our results suggest a less complex autonomic response to noxious stimuli in VS/UWS patients. Such method may help to better understand sympathovagal response to potentially painful stimulation in brain-injured patients.

A Heartbeat Away From Consciousness: Heart Rate Variability Entropy Can Discriminate Disorders of Consciousness and Is Correlated With Resting-State fMRI Brain Connectivity of the Central Autonomic Network

Background: Disorders of consciousness are challenging to diagnose, with inconsistent behavioral responses, motor and cognitive disabilities, leading to approximately 40% misdiagnoses. Heart rate variability (HRV) reflects the complexity of the heart-brain two-way dynamic interactions. HRV entropy analysis quantifies the unpredictability and complexity of the heart rate beats intervals. We here investigate the complexity index (CI), a score of HRV complexity by aggregating the non-linear multi-scale entropies over a range of time scales, and its discriminative power in chronic patients with unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS), and its relation to brain functional connectivity. Methods: We investigated the CI in short (CIs) and long (CIl) time scales in 14 UWS and 16 MCS sedated. CI for MCS and UWS groups were compared using a Mann-Whitney exact test. Spearman's correlation tests were conducted between the Coma Recovery Scale-revised (CRS-R) and both CI. Discriminative power of both CI was assessed with One-R machine learning model. Correlation between CI and brain connectivity (detected with functional magnetic resonance imagery using seed-based and hypothesis-free intrinsic connectivity) was investigated using a linear regression in a subgroup of 10 UWS and 11 MCS patients with sufficient image quality. Results: Higher CIs and CIl values were observed in MCS compared to UWS. Positive correlations were found between CRS-R and both CI. The One-R classifier selected CIl as the best discriminator between UWS and MCS with 90% accuracy, 7% false positive and 13% false negative rates after a 10-fold cross-validation test. Positive correlations were observed between both CI and the recovery of functional connectivity of brain areas belonging to the central autonomic networks (CAN). Conclusion: CI of MCS compared to UWS patients has high discriminative power and low false negative rate at one third of the estimated human assessors' misdiagnosis, providing an easy, inexpensive and non-invasive diagnostic tool. CI reflects functional connectivity changes in the CAN, suggesting that CI can provide an indirect way to screen and monitor connectivity changes in this neural system. Future studies should assess the extent of CI's predictive power in a larger cohort of patients and prognostic power in acute patients.

Heart Rate Variability, Homeostasis, and Brain Function

Measures of heart rate variability (HRV) are major indices of the sympathovagal balance in cardiovascular research. These measures are thought to reflect complex patterns of brain activation as well and HRV is now emerging as a descriptor thought to provide information on the nervous system organization of homeostatic responses in accordance with the situational requirements. Current models of integration equate HRV to the affective states as parallel outputs of the central autonomic network, with HRV reflecting its organization of affective, physiological, “cognitive,” and behavioral elements into a homeostatic response. Clinical application is in the study of patients with psychiatric disorders, traumatic brain injury, impaired emotion-specific processing, personality, and communication disorders. HRV responses to highly emotional sensory inputs have been identified in subjects in vegetative state and in healthy or brain injured subjects processing complex sensory stimuli. In this respect, HRV measurements can provide additional information on the brain functional setup in the severely brain damaged and would provide researchers with a suitable approach in the absence of conscious behavior or whenever complex experimental conditions and data collection are impracticable, as it is the case, for example, in intensive care units.