Auricular vagal nerve stimulation (AVNS) is an evolving neuromodulation technology that has a wide range of therapeutic applications across multiple disciplines of medical science. To date, AVNS ...results had been interpreted in the context of a monolog concept of the auricular branch of the vagus nerve (ABVN): that this is the sole network of the mechanism of action and/or structure in the auricular area of the stimulation in the context of activations in the brainstem nuclei, including the nucleus tractus solitarius (NTS), locus coeruleus (LC), trigeminal brainstem nuclei, and the nucleus cuneatus. This review considers the overlooked aspects of neural networks, connections, hijacking axons from cranial nerves and cervical sympathetic ganglions, the inhomogeneous distribution of perivascular sympathetic nerves, and intrinsic/extrinsic auricular muscles in the auricular zone that can explain the vagal and non-vagal nucleus activations in AVNS. In addition, the unique cortical representation of the human ear and interspecies differences in the auricula are discussed. The detailed auricular anatomy of the AVNS zone explored in the present study references structural and functional neural network information to overcome default designs and misinterpretations of existing research on AVNS to provide a better foundation for future investigations that use this modality.
Pupillary alterations in virtual humans induce neurophysiological responses within an observer. Technological advances have enabled rapid developments in artificial intelligence (AI), from verbal ...systems, to visual AI interfaces with the ability to express, and respond to emotional states of a user. Visual AI interfaces are able to change their physical parameters, such as pupil diameter. Pupillary changes can alter heart rate, however, effects on heart rate variability (HRV) are unknown. HRV, is an autonomic, non-conscious parameter which monitors sympathetic and parasympathetic nervous system (PNS) activity. N = 34 male participants aged between 19-33 were subjected to a number of conditions such as pupil dilation, constriction and blushing. The present research is the first to investigate the effects of virtual human interactions on human HRV. Outcomes of this study were obtained using eye tracking and HRV measurements. Pupil dilation relative to constriction presented in the female virtual partner induced a significant right pupillary diameter increase (
= 0.041) in human observers. Additionally, female virtual partner pupil constriction relative to dilation induced a significant increase in participants' PNS HRV response (
= 0.036). These findings indicate the ability of a female virtual interaction partner to modulate parasympathetic autonomic functioning in young healthy male humans. This allows first insights into the effects of interacting with virtual AI interaction partners, on human autonomic functioning, and may aid development of future virtual humans, and their implementation into relevant clinical settings.
The Unified Parkinson's Disease Rating Scale (UPDRS) is a subjective Parkinson's Disease (PD) physician scoring/monitoring system. To date, there is no single upper limb wearable/non-contact system ...that can be used objectively to assess all UPDRS-III motor system subgroups (i.e., tremor (T), rigidity (R), bradykinesia (B), gait and posture (GP), and bulbar anomalies (BA)). We evaluated the use of a non-contact hand motion tracking system for potential extraction of GP information using forearm pronation-supination (P/S) motion parameters (speed, acceleration, and frequency). Twenty-four patients with idiopathic PD participated, and their UPDRS data were recorded bilaterally by physicians. Pearson's correlation, regression analyses, and Monte Carlo validation was conducted for all combinations of UPDRS subgroups versus motion parameters. In the 262,125 regression models that were trained and tested, the models within 1% of the lowest error showed that the frequency of P/S contributes to approximately one third of all models; while speed and acceleration also contribute significantly to the prediction of GP from the left-hand motion of right handed patients. In short, the P/S better indicated GP when performed with the non-dominant hand. There was also a significant negative correlation (with medium to large effect size, range: 0.3-0.58) between the P/S speed and the single BA score for both forearms and combined UPDRS score for the dominant hand. This study highlights the potential use of wearable or non-contact systems for forearm P/S to remotely monitor and predict the GP information in PD.
Early and accurate dysphagia diagnosis is essential for reducing the risk of associated co-morbidities and mortalities. Barriers to current evaluation methods may alter the effectiveness of ...identifying at-risk patients. This preliminary study evaluates the feasibility of using iPhone X-captured videos of swallowing as a non-contact dysphagia screening tool. Video recordings of the anterior and lateral necks were captured simultaneously with videofluoroscopy in dysphagic patients. Videos were analyzed using an image registration algorithm (phase-based Savitzky-Golay gradient correlation (P-SG-GC)) to determine skin displacements over hyolaryngeal regions. Biomechanical swallowing parameters of hyolaryngeal displacement and velocity were also measured. Swallowing safety and efficiency were assessed by the Penetration Aspiration Scale (PAS), Residue Severity Ratings (RSR), and the Normalized Residue Ratio Scale (NRRS). Anterior hyoid excursion and horizontal skin displacements were strongly correlated with swallows of a 20 mL bolus (r
= 0.67). Skin displacements of the neck were moderately to very strongly correlated with scores on the PAS (r
= 0.80), NRRS (r
= 0.41-0.62), and RSR (r
= 0.33). This is the first study to utilize smartphone technology and image registration methods to produce skin displacements indicating post-swallow residual and penetration-aspiration. Enhancing screening methods provides a greater chance of detecting dysphagia, reducing the risk of negative health impacts.
In recent decades, it has been uncovered that the autonomic nervous system (ANS) can be influenced using non-contact neuromodulation
odor stimulation. Increasing parasympathetic-vagal activation of ...the ANS is integral to improving the sympathovagal balance between the sympathetic- and parasympathetic nervous systems, which is often imbalanced in several chronic inflammatory disorders, such as rheumatoid arthritis and inflammatory bowel diseases. Although research into olfactory stimulation has been observed on the ANS, it is still lacking in the exploration of odor concentration and odor-specific effects. This is particularly the case as research has not utilized specified tools, such as the olfactometer to provide precise odor delivery. Furthermore, no research has compared the results in separate sex cohorts to investigate the role of sex or the menstrual stage on the subsequent interactions. In this study, we investigated the olfactory stimulation effects of four natural odors (mushroom, lavender, jasmine, and rose) in three concentrations (low, moderate, and high) on the ANS. To observe activity from the ANS, we used an electrocardiogram (ECG) based heart rate variability (HRV) and eye-tracker technology (pupil diameter). We found for the first time in literature that there were acute dose- and duration-specific odor effects of odors on the ANS. We also found sex and menstrual cycle effects in this interaction. Furthermore, there were stark distinctions in sympathovagal activity dependent ANS activation (HRV) in comparison to the oculomotor nerve-parasympathetic/cervical sympathetic nerves dependent ANS responses (pupil diameter). Sympathovagal activity dependent HRV showed odor, sex, and menstrual-stage interactions in both divisions of the ANS while the pupil responses only indicated increased sympathetic activation. These results shed light on the use of odor-specific stimulation to modulate the ANS activity in the context of sex and the menstrual stage. Future studies should be performed using a chronic odor delivery design to investigate the long-term effects of odors on the ANS.
Australian New Zealand Clinical Trials Registry, identifier ACTRN12622000415707.
The olfactory system is known to be dysfunctional in the early stages of Parkinson's disease (PD) and Alzheimer's disease (AD). It is also shown that intact olfactory function can be a key role ...player for regaining consciousness after brain injuries. Modulation of the olfactory regions has been attempted successfully with electrical stimulation over the years, either directly (transethmoidally, intraoperatively, internasally, etc.) or indirectly through the vagus nerve. We sought to develop a means of delivering optimized electrical stimulation to the olfactory region in a non-invasive fashion and in a way that is simpler, easier, and less cumbersome. The ultimate goal was to develop a system that would allow easier testing in future clinical trials presenting an opportunity to fully develop this potential treatment option. We devised six potential electrode placements leveraging commonly accepted facts of electrical stimulation, easier access through relatively higher conductive pathways into the brain, and practicality. Using an ultra-high-resolution finite element model, we screened each one of these montages for their ability to target the olfactory regions primarily and thereafter for select sub-cortical regions implicated in the pathogenesis of PD and AD. Modeling results indicate that some placements do result in inducing meaningful electric field magnitudes in the regions of interest. A practical headgear concept is proposed to realize the most ideal configuration. Our results pave the way for developing the first non-invasive electrical stimulation wearable system for targeting the olfactory regions which can help to alleviate the symptoms or suppress the progression of these neurological disorders.
A substantial body of research on this Research Topic has focused on the developments and progress made in the embodiment of tools that extend the functionality of the body to support rehabilitation ...and to improve the capability for acting in the environment of patients with nervous system damage. ...it seems crucial to consider the different contributions of proprioception, sensory input from multiple modalities, body appearance, identity, position, tool function, proper grip, tool expertise, goals, and agency (Sun and Tang; Bruno et al.), as these factors cause different gradients of change in body representations. Additionally, a few studies have further examined the neural underpinning of the action observation network (Pazzaglia and Galli, 2019) in relation to object use and effector independence through the application of voxel-based lesion-symptom mapping (Pizzamiglio et al.) and transcranial magnetic stimulation (Betti et al.). ...this Research Topic collects an impressive body of literature on “Embodying Tool Use.”
The mammalian external ear houses extrinsic and intrinsic auricular muscles. There are three extrinsic auricular muscles-the posterior, superior, and anterior auricular muscles-and six intrinsic ...muscles-the helicis major and minor, tragicus, anti-tragicus, transverse and oblique muscles. These muscles have been considered vestigial in humans. However, numerous therapeutic and diagnostic wearable devices are designed to monitor and alleviate the symptoms of neurological disorders, brainstem injuries, emotional states, and auditory functions, by making use of the neural networks of the auricular muscles and their locations, which are easily accessible for ergonomic wearable biomedical devices. They can also serve as a bio-controller of human neuroprosthetics. The functionality of these auricular muscles remains elusive and requires further experimentation for a more in-depth understanding of their anatomy. The aims of this review are (1) to provide a detailed account of the neural networks of the extrinsic and intrinsic auricular muscles, (2) to describe diagnostic and therapeutic functions of these muscles as demonstrated in the current literature, and (3) to outline existing and potential neuroprosthetic applications making use of the auricular muscles and their neural networks.
This systematic review offers a world-first critical analysis of machine learning methods and systems, along with future directions for the study of cybersickness induced by virtual reality (VR). VR ...is becoming increasingly popular and is an important part of current advances in human training, therapies, entertainment, and access to the metaverse. Usage of this technology is limited by cybersickness, a common debilitating condition experienced upon VR immersion. Cybersickness is accompanied by a mix of symptoms including nausea, dizziness, fatigue and oculomotor disturbances. Machine learning can be used to identify cybersickness and is a step towards overcoming these physiological limitations. Practical implementation of this is possible with optimised data collection from wearable devices and appropriate algorithms that incorporate advanced machine learning approaches. The present systematic review focuses on 26 selected studies. These concern machine learning of biometric and neuro-physiological signals obtained from wearable devices for the automatic identification of cybersickness. The methods, data processing and machine learning architecture, as well as suggestions for future exploration on detection and prediction of cybersickness are explored. A wide range of immersion environments, participant activity, features and machine learning architectures were identified. Although models for cybersickness detection have been developed, literature still lacks a model for the prediction of first-instance events. Future research is pointed towards goal-oriented data selection and labelling, as well as the use of brain-inspired spiking neural network models to achieve better accuracy and understanding of complex spatio-temporal brain processes related to cybersickness.
Virtual Reality (VR) allows users to interact with 3D immersive environments and has the potential to be a key technology across many domain applications, including access to a future metaverse. Yet, ...consumer adoption of VR technology is limited by cybersickness (CS)—a debilitating sensation accompanied by a cluster of symptoms, including nausea, oculomotor issues and dizziness. A leading problem is the lack of automated objective tools to predict or detect CS in individuals, which can then be used for resistance training, timely warning systems or clinical intervention. This paper explores the spatiotemporal brain dynamics and heart rate variability involved in cybersickness and uses this information to both predict and detect CS episodes. The present study applies deep learning of EEG in a spiking neural network (SNN) architecture to predict CS prior to using VR (85.9%, F7) and detect it (76.6%, FP1, Cz). ECG-derived sympathetic heart rate variability (HRV) parameters can be used for both prediction (74.2%) and detection (72.6%) but at a lower accuracy than EEG. Multimodal data fusion of EEG and sympathetic HRV does not change this accuracy compared to ECG alone. The study found that Cz (premotor and supplementary motor cortex) and O2 (primary visual cortex) are key hubs in functionally connected networks associated with both CS events and susceptibility to CS. F7 is also suggested as a key area involved in integrating information and implementing responses to incongruent environments that induce cybersickness. Consequently, Cz, O2 and F7 are presented here as promising targets for intervention.
PDF
