Closed-Loop Neuromodulation in Physiological and Translational Research

Non-Invasive Brain Sensing Technologies for Modulation of Neurological Disorders

The non-invasive brain sensing modulation technology field is experiencing rapid development, with new techniques constantly emerging. This study delves into the field of non-invasive brain neuromodulation, a safer and potentially effective approach for treating a spectrum of neurological and psychiatric disorders. Unlike traditional deep brain stimulation (DBS) surgery, non-invasive techniques employ ultrasound, electrical currents, and electromagnetic field stimulation to stimulate the brain from outside the skull, thereby eliminating surgery risks and enhancing patient comfort. This study explores the mechanisms of various modalities, including transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), highlighting their potential to address chronic pain, anxiety, Parkinson's disease, and depression. We also probe into the concept of closed-loop neuromodulation, which personalizes stimulation based on real-time brain activity. While we acknowledge the limitations of current technologies, our study concludes by proposing future research avenues to advance this rapidly evolving field with its immense potential to revolutionize neurological and psychiatric care and lay the foundation for the continuing advancement of innovative non-invasive brain sensing technologies.

Vagus nerve stimulation for cardiovascular diseases: Is there light at the end of the tunnel?

Autonomic dysfunction and chronic inflammation contribute to the pathogenesis and progression of several cardiovascular diseases (CVD), such as heart failure with preserved ejection fraction, atherosclerotic CVD, pulmonary arterial hypertension, and atrial fibrillation. The vagus nerve provides parasympathetic innervation to the heart, vessels, and lungs, and is also implicated in the neural control of inflammation through a neuroimmune pathway involving the spleen. Stimulation of the vagus nerve (VNS) can in principle restore autonomic balance and suppress inflammation, with potential therapeutic benefits in these diseases. Although VNS ameliorated CVD in several animal models, early human studies have demonstrated variable efficacy. The purpose of this review is to discuss the rationale behind the use of VNS in the treatment of CVD, to critically review animal and human studies of VNS in CVD, and to propose possible means to overcome the challenges in the clinical translation of VNS in CVD.

Neuromodulation by nanozymes and ultrasound during Alzheimer's disease management

Alzheimer's disease (AD) is a neurodegenerative disorder with complex pathogenesis and effective clinical treatment strategies for this disease remain elusive. Interestingly, nanomedicines are under extensive investigation for AD management. Currently, existing redox molecules show highly bioactive property but suffer from instability and high production costs, limiting clinical application for neurological diseases. Compared with natural enzymes, artificial enzymes show high stability, long-lasting catalytic activity, and versatile enzyme-like properties. Further, the selectivity and performance of artificial enzymes can be modulated for neuroinflammation treatments through external stimuli. In this review, we focus on the latest developments of metal, metal oxide, carbon-based and polymer based nanozymes and their catalytic mechanisms. Recent developments in nanozymes for diagnosing and treating AD are emphasized, especially focusing on their potential to regulate pathogenic factors and target sites. Various applications of nanozymes with different stimuli-responsive features were discussed, particularly focusing on nanozymes for treating oxidative stress-related neurological diseases. Noninvasiveness and focused application to deep body regions makes ultrasound (US) an attractive trigger mechanism for nanomedicine. Since a complete cure for AD remains distant, this review outlines the potential of US responsive nanozymes to develop future therapeutic approaches for this chronic neurodegenerative disease and its emergence in AD management.

Repetitive Transcranial Magnetic Stimulation for Working Memory Deficits in Schizophrenia: A Systematic Review of Randomized Controlled Trials

Working memory (WM) deficits are a significant component of neurocognitive impairment in individuals with schizophrenia (SCZ). Two previous meta-analyses, conducted on randomized controlled trials (RCTs), examined the effectiveness of repetitive transcranial magnetic stimulation (rTMS) in addressing WM deficits in individuals diagnosed with SCZ. However, the conclusions drawn from these analyses were inconsistent. Additionally, the commonly used random effects (RE) models might underestimate statistical errors, attributing a significant portion of perceived heterogeneity between studies to variations in study quality. Therefore, this review utilized both RE and quality effects (QE) models to assess relevant RCTs comparing TMS with sham intervention in terms of clinical outcomes. A comprehensive literature search was conducted using PubMed and Scopus databases, resulting in the inclusion of 13 studies for data synthesis. Overall, regardless of whether the RE or QE model was used, eligible RCTs suggested that the TMS and sham groups exhibited comparable therapeutic effects after treatment. The current state of research regarding the use of rTMS as a treatment for WM deficits in patients with SCZ remains in its preliminary phase. Furthermore, concerning the mechanism of action, the activation of brain regions focused on the dorsolateral prefrontal cortex and alterations in gamma oscillations may hold significant relevance in the therapeutic application of rTMS for addressing WM impairments. Finally, we believe that the application of closed-loop neuromodulation may contribute to the optimization of rTMS for WM impairment in patients with SCZ.

Personalized strategies of neurostimulation: from static biomarkers to dynamic closed-loop assessment of neural function

Despite considerable advancement of first choice treatment (pharmacological, physical therapy, etc.) over many decades, neurological disorders still represent a major portion of the worldwide disease burden. Particularly concerning, the trend is that this scenario will worsen given an ever expanding and aging population. The many different methods of brain stimulation (electrical, magnetic, etc.) are, on the other hand, one of the most promising alternatives to mitigate the suffering of patients and families when conventional treatment fall short of delivering efficacious treatment. With applications in virtually all neurological conditions, neurostimulation has seen considerable success in providing relief of symptoms. On the other hand, a large variability of therapeutic outcomes has also been observed, particularly in the usage of non-invasive brain stimulation (NIBS) modalities. Borrowing inspiration and concepts from its pharmacological counterpart and empowered by unprecedented neurotechnological advancement, the neurostimulation field has seen in recent years a widespread of methods aimed at the personalization of its parameters, based on biomarkers of the individuals being treated. The rationale is that, by taking into account important factors influencing the outcome, personalized stimulation can yield a much-improved therapy. Here, we review the literature to delineate the state-of-the-art of personalized stimulation, while also considering the important aspects of the type of informing parameter (anatomy, function, hybrid), invasiveness, and level of development (pre-clinical experimentation versus clinical trials). Moreover, by reviewing relevant literature on closed loop neuroengineering solutions in general and on activity dependent stimulation method in particular, we put forward the idea that improved personalization may be achieved when the method is able to track in real time brain dynamics and adjust its stimulation parameters accordingly. We conclude that such approaches have great potential of promoting the recovery of lost functions and enhance the quality of life for patients.

Wireless closed-loop deep brain stimulation using microelectrode array probes

Deep brain stimulation (DBS), including optical stimulation and electrical stimulation, has been demonstrated considerable value in exploring pathological brain activity and developing treatments for neural disorders. Advances in DBS microsystems based on implantable microelectrode array (MEA) probes have opened up new opportunities for closed-loop DBS (CL-DBS) in situ. This technology can be used to detect damaged brain circuits and test the therapeutic potential for modulating the output of these circuits in a variety of diseases simultaneously. Despite the success and rapid utilization of MEA probe-based CL-DBS microsystems, key challenges, including excessive wired communication, need to be urgently resolved. In this review, we considered recent advances in MEA probe-based wireless CL-DBS microsystems and outlined the major issues and promising prospects in this field. This technology has the potential to offer novel therapeutic options for psychiatric disorders in the future.

Closing the loop and raising the bar: Automated control systems in neuromodulation

INTRODUCTION

Neuromodulation has emerged as a promising therapy for the management of chronic pain, movement disorders, and other neurological conditions. Spinal cord stimulation (SCS) is a widely used form of neuromodulation that involves the delivery of electrical impulses to the spinal cord to modulate the transmission of pain signals to the brain. In recent years, there has been increasing interest in the use of automation systems to improve the efficacy and safety of SCS. This narrative review summarizes the status of Food and Drug Administration-approved autonomous neuromodulation devices including closed loop, feedforward, and feedback systems. The review discusses the advantages and disadvantages of each system and focuses specifically on the use of these systems for SCS. It is important for clinicians to understand the expanding role of automation in neuromodulation in order to select appropriate therapies founded on automation systems to the specific needs of the patient and the underlying condition.

CONCLUSION

The review also provides insights into the current state of the art in neuromodulation automation systems and discusses potential future directions for research in this field.

A multivariate physiological model of vagus nerve signalling during metabolic challenges in anaesthetised rats for diabetes treatment

Objective.This study aims to develop a comprehensive decoding framework to create a multivariate physiological model of vagus nerve transmission that reveals the complex interactions between the nervous and metabolic systems.Approach.Vagus nerve activity was recorded in female Sprague-Dawley rats using gold hook microwires implanted around the left cervical vagus nerve. The rats were divided into three experimental cohorts (intact nerve, ligation nerve for recording afferent activation, and ligation for recording efferent activation) and metabolic challenges were administered to change glucose levels while recording the nerve activity. The decoding methodology involved various techniques, including continuous wavelet transformation, extraction of breathing rate (BR), and correlation of neural metrics with physiological signals.Main results.Decrease in glucose level was consistently negatively correlated with an increase in the firing activity of the intact vagus nerve that was found to be conveyed by both afferent and efferent pathways, with the afferent response being more similar to the one on the intact nerve. A larger variability was observed in the sensory and motor responses to hyperglycaemia. A novel strategy to extract the BR over time based on inter-burst-interval is also presented. The vagus afferent was found to encode breathing information through amplitude and firing rate modulation. Modulations of the signal amplitude were also observed due to changes in heart rate in the intact and efferent recordings, highlighting the parasympathetic control of the heart.Significance.The analytical framework presented in this study provides an integrative understanding that considers the relationship between metabolic, cardiac, and breathing signals and contributes to the development of a multivariable physiological model for the transmission of vagus nerve signals. This work progresses toward the development of closed-loop neuro-metabolic therapeutic systems for diabetes.

A Comprehensive Review of Emerging Trends and Innovative Therapies in Epilepsy Management

Epilepsy is a complex neurological disorder affecting millions worldwide, with a substantial number of patients facing drug-resistant epilepsy. This comprehensive review explores innovative therapies for epilepsy management, focusing on their principles, clinical evidence, and potential applications. Traditional antiseizure medications (ASMs) form the cornerstone of epilepsy treatment, but their limitations necessitate alternative approaches. The review delves into cutting-edge therapies such as responsive neurostimulation (RNS), vagus nerve stimulation (VNS), and deep brain stimulation (DBS), highlighting their mechanisms of action and promising clinical outcomes. Additionally, the potential of gene therapies and optogenetics in epilepsy research is discussed, revealing groundbreaking findings that shed light on seizure mechanisms. Insights into cannabidiol (CBD) and the ketogenic diet as adjunctive therapies further broaden the spectrum of epilepsy management. Challenges in achieving seizure control with traditional therapies, including treatment resistance and individual variability, are addressed. The importance of staying updated with emerging trends in epilepsy management is emphasized, along with the hope for improved therapeutic options. Future research directions, such as combining therapies, AI applications, and non-invasive optogenetics, hold promise for personalized and effective epilepsy treatment. As the field advances, collaboration among researchers of natural and synthetic biochemistry, clinicians from different streams and various forms of medicine, and patients will drive progress toward better seizure control and a higher quality of life for individuals living with epilepsy.

Bridging the Gap between Basic Research and Clinical Practice: The Growing Role of Translational Neurorehabilitation

Translational neuroscience is intended as a holistic approach in the field of brain disorders, starting from the basic research of cerebral morphology and with the function of implementing it into clinical practice. This concept can be applied to the rehabilitation field to promote promising results that positively influence the patient's quality of life. The last decades have seen great scientific and technological improvements in the field of neurorehabilitation. In this paper, we discuss the main issues related to translational neurorehabilitation, from basic research to current clinical practice, and we also suggest possible future scenarios.

Delay Analysis in Closed-Loop EEG Phase-Triggered Transcranial Magnetic Stimulation

The recent development of closed-loop EEG phase-triggered transcranial magnetic stimulation (TMS) has advanced potential applications of adaptive neuromodulation based on the current brain state. Closed-loop TMS involves instantaneous acquisition of the EEG rhythm, timing prediction of the target phase, and triggering of TMS. However, the accuracy of EEG phase prediction algorithms is largely influenced by the system's transport delay, and their relationship is rarely considered in related work. This paper proposes a delay analysis that considers the delay of the closed-loop EEG phase-triggered TMS system as a primary factor in the validation of phase prediction algorithms. An in-silico validation using real EEG data was performed to compare the performance of commonly used algorithms. The experimental results indicate a significant influence of the total delay on the algorithm performance, and the performance ranking among algorithms varies at different levels of delay. We conclude that the delay analysis framework should be widely adopted in the design and validation of phase prediction algorithms for closed-loop EEG phase-triggered TMS systems.

Wireless and battery-free technologies for neuroengineering

Tethered and battery-powered devices that interface with neural tissues can restrict natural motions and prevent social interactions in animal models, thereby limiting the utility of these devices in behavioural neuroscience research. In this Review Article, we discuss recent progress in the development of miniaturized and ultralightweight devices as neuroengineering platforms that are wireless, battery-free and fully implantable, with capabilities that match or exceed those of wired or battery-powered alternatives. Such classes of advanced neural interfaces with optical, electrical or fluidic functionality can also combine recording and stimulation modalities for closed-loop applications in basic studies or in the practical treatment of abnormal physiological processes.

Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering

Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that 'case-study', we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as 'brain-prostheses', capable of rewiring and/or substituting the injured nervous system.

Correction of Stress-Induced States Using Sensory Stimulation Automatically Modulated by Endogenous Human Rhythms

This article considers the dynamics of the development of a potential approach to correcting stress-induced states in humans, i.e., adaptive neurostimulation. The approach consists of presenting sensory stimulation automatically modulated by intrinsic rhythmic human processes such as the respiratory rhythm, the heartbeat rhythm, and electroencephalograph (EEG) rhythms. Many examples have shown that real-time self-adjustment of the stimulation parameters by these rhythms leads to a high level personalization of therapeutic stimulation and increases in its efficacy in suppressing stress-induced states. The publications reviewed here point to the advantages of this approach for developing innovatory technologies using complex feedback from endogenous human rhythms to correct a wide spectrum of functional disorders.

Corticospinal circuit neuroplasticity may involve silent synapses: Implications for functional recovery facilitated by neuromodulation after spinal cord injury

Spinal cord injury (SCI) leads to devastating physical consequences, such as severe sensorimotor dysfunction even lifetime disability, by damaging the corticospinal system. The conventional opinion that SCI is intractable due to the poor regeneration of neurons in the adult central nervous system (CNS) needs to be revisited as the CNS is capable of considerable plasticity, which underlie recovery from neural injury. Substantial spontaneous neuroplasticity has been demonstrated in the corticospinal motor circuitry following SCI. Some of these plastic changes appear to be beneficial while others are detrimental toward locomotor function recovery after SCI. The beneficial corticospinal plasticity in the spared corticospinal circuits can be harnessed therapeutically by multiple contemporary neuromodulatory approaches, especially the electrical stimulation-based modalities, in an activity-dependent manner to improve functional outcomes in post-SCI rehabilitation. Silent synapse generation and unsilencing contribute to profound neuroplasticity that is implicated in a variety of neurological disorders, thus they may be involved in the corticospinal motor circuit neuroplasticity following SCI. Exploring the underlying mechanisms of silent synapse-mediated neuroplasticity in the corticospinal motor circuitry that may be exploited by neuromodulation will inform a novel direction for optimizing therapeutic repair strategies and rehabilitative interventions in SCI patients.

A lightweight learning-based decoding algorithm for intraneural vagus nerve activity classification in pigs

OBJECTIVE

Bioelectronic medicine is an emerging field that aims at developing closed-loop neuromodulation protocols for the autonomic nervous system (ANS) to treat a wide range of disorders. When designing a closed-loop protocol for real time modulation of the ANS, the computational execution time and the memory and power demands of the decoding step are important factors to consider. In the context of cardiovascular and respiratory diseases, these requirements may partially explain why closed-loop clinical neuromodulation protocols that adapt stimulation parameters on patient's clinical characteristics are currently missing.

APPROACH

Here, we developed a lightweight learning-based decoder for the classification of cardiovascular and respiratory functional challenges from neural signals acquired through intraneural electrodes implanted in the cervical vagus nerve (VN) of 5 anaesthetized pigs. Our algorithm is based on signal temporal windowing, 9 handcrafted features, and Random Forest (RF) model for classification. Temporal windowing ranging from 50 ms to 1 sec, compatible in duration with cardio-respiratory dynamics, was applied to the data in order to mimic a pseudo real-time scenario.

MAIN RESULTS

We were able to achieve high balanced accuracy (BA) values over the whole range of temporal windowing duration. We identified 500 ms as the optimal temporal windowing duration for both BA values and computational execution time processing, achieving more than 86% for BA and a computational execution time of only ∼6.8 ms. Our algorithm outperformed in terms of balanced accuracy and computational execution time a state of the art decoding algorithm tested on the same dataset [1]. We found that RF outperformed other machine learning models such as Support Vector Machines, K-Nearest Neighbors, and Multi-Layer Perceptrons.

SIGNIFICANCE

Our approach could represent an important step towards the implementation of a closed-loop neuromodulation protocol relying on a single intraneural interface able to perform real-time decoding tasks and selective modulation of the VN.

A fast and accurate learning-based decoding algorithm for the classification of cardiovascular and respiratory challenges using intraneural electrodes in the pig vagus nerve

Bioelectronic medicine is a new approach for developing closed-loop neuromodulation protocols on the peripheral nervous system (PNS) to treat a wide range of disorders currently treated with pharmacological approaches. Algorithms need to have low computational cost in order to acquire, process and model data for the modulation of the PNS in real time. Here, we present a fast learning-based decoding algorithm for the classification of cardiovascular and respiratory functional alterations (i.e., challenges) by using neural signals recorded from intraneural electrodes implanted in the vagus nerve of 5 pigs. Our algorithm relies on 9 handcrafted features, extracted following signal temporal windowing, and a multi-layer perceptron (MLP) for feature classification. We achieved fast and accurate classification of the challenges, with a computational time for feature extraction and prediction lower than 1.5 ms. The MLP achieved a balanced accuracy higher than 80 % for all recordings. Our algorithm could represent a step towards the development of a closed-loop system based on a single intraneural interface with both the potential of real time classification and selective modulation of the PNS.

Dopaminergic dysfunction and excitatory/inhibitory imbalance in treatment-resistant schizophrenia and novel neuromodulatory treatment

Antipsychotic drugs are the mainstay in the treatment of schizophrenia. However, one-third of patients do not show adequate improvement in positive symptoms with non-clozapine antipsychotics. Additionally, approximately half of them show poor response to clozapine, electroconvulsive therapy, or other augmentation strategies. However, the development of novel treatment for these conditions is difficult due to the complex and heterogenous pathophysiology of treatment-resistant schizophrenia (TRS). Therefore, this review provides key findings, potential treatments, and a roadmap for future research in this area. First, we review the neurobiological pathophysiology of TRS, particularly the dopaminergic, glutamatergic, and GABAergic pathways. Next, the limitations of existing and promising treatments are presented. Specifically, this article focuses on the therapeutic potential of neuromodulation, including electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation. Finally, we propose multivariate analyses that integrate various perspectives of the pathogenesis, such as dopaminergic dysfunction and excitatory/inhibitory imbalance, thereby elucidating the heterogeneity of TRS that could not be obtained by conventional statistics. These analyses can in turn lead to a precision medicine approach with closed-loop neuromodulation targeting the detected pathophysiology of TRS.

Transcutaneous auricular vagus nerve stimulators: a review of past, present and future devices

INTRODUCTION

As an emerging neuromodulation therapy, transcutaneous auricular vagus nerve stimulation (taVNS) has been proven to be safe and effective for epilepsy, major depressive disorders, insomnia, glucose metabolic disorders, pain, stroke, post stroke rehabilitation, anxiety, fear, cognitive impairment, cardiovascular disorders, tinnitus, Prader-Willi Syndrome and COVID-19.

AREAS COVERED

Although the history of taVNS is only two decades, the devices carrying taVNS technique have been constantly updated. Especially in recent years, the development of taVNS devices has presented a new trend. To conclude, the development of taVNS devices has entered a new era, thus the update speed and quality of taVNS devices will be considerably improved in the future. This article reviewed the history and classification of taVNS devices.

EXPERT OPINION

The correlation between the effectiveness and stimulation parameters from taVNS devices still remains unclear. There is a lack of standard or harmonization among different taVNS devices. Strategies, including further comparative research and establishment of standard, have been recommended in this article to promote the future development of taVNS devices.

Computational modelling of nerve stimulation and recording with peripheral visceral neural interfaces

Objective.Neuromodulation of visceral nerves is being intensively studied for treating a wide range of conditions, but effective translation requires increasing the efficacy and predictability of neural interface performance. Here we use computational models of rat visceral nerve to predict how neuroanatomical variability could affect both electrical stimulation and recording with an experimental planar neural interface.Approach.We developed a hybrid computational pipeline,VisceralNerveEnsembleRecording andStimulation (ViNERS), to couple finite-element modelling of extracellular electrical fields with biophysical simulations of individual axons. Anatomical properties of fascicles and axons in rat pelvic and vagus nerves were measured or obtained from public datasets. To validate ViNERS, we simulated pelvic nerve stimulation and recording with an experimental four-electrode planar array.Main results.Axon diameters measured from pelvic nerve were used to model a population of myelinated and unmyelinated axons and simulate recordings of electrically evoked single-unit field potentials (SUFPs). Across visceral nerve fascicles of increasing size, our simulations predicted an increase in stimulation threshold and a decrease in SUFP amplitude. Simulated threshold changes were dominated by changes in perineurium thickness, which correlates with fascicle diameter. We also demonstrated that ViNERS could simulate recordings of electrically-evoked compound action potentials (ECAPs) that were qualitatively similar to pelvic nerve recording made with the array used for simulation.Significance.We introduce ViNERS as a new open-source computational tool for modelling large-scale stimulation and recording from visceral nerves. ViNERS predicts how neuroanatomical variation in rat pelvic nerve affects stimulation and recording with an experimental planar electrode array. We show ViNERS can simulate ECAPS that capture features of our recordings, but our results suggest the underlying NEURON models need to be further refined and specifically adapted to accurately simulate visceral nerve axons.

Cortical Responses to Vagus Nerve Stimulation Are Modulated by Brain State in Nonhuman Primates

Vagus nerve stimulation (VNS) has been tested as therapy for several brain disorders and as a means to modulate cortical excitability and brain plasticity. Cortical effects of VNS, manifesting as vagal-evoked potentials (VEPs), are thought to arise from activation of ascending cholinergic and noradrenergic systems. However, it is unknown whether those effects are modulated by brain state at the time of stimulation. In 2 freely behaving macaque monkeys, we delivered short trains of 5 pulses to the left cervical vagus nerve at different frequencies (5-300 Hz) while recording local field potentials (LFPs) from sites in contralateral prefrontal, sensorimotor and parietal cortical areas. Brain states were inferred from spectral components of LFPs and the presence of overt movement: active awake, resting awake, REM sleep and NREM sleep. VNS elicited VEPs in all sampled cortical areas. VEPs comprised early (<70 ms), intermediate (70-250 ms) and late (>250 ms) components. The magnitude of the intermediate and late components was largest during NREM sleep and smallest during wakefulness, whereas that of the early component was not modulated by brain state. VEPs during NREM were larger for stimuli delivered at the depolarized phase of ongoing delta oscillations. Higher pulsing frequencies generated larger VEPs. These short VNS trains did not affect brain state transitions during wakefulness or sleep. Our findings suggest that ongoing brain state modulates the evoked effects of VNS on cortical activity. This has implications for the role of ongoing cortical activity and brain state in shaping cortical responses to peripheral stimuli, for the modulation of vagal interoceptive signaling by cortical activity, and for the dose calibration of VNS therapies.

Simultaneous decoding of cardiovascular and respiratory functional changes from pig intraneural vagus nerve signals

Objective. Bioelectronic medicine is opening new perspectives for the treatment of some major chronic diseases through the physical modulation of autonomic nervous system activity. Being the main peripheral route for electrical signals between central nervous system and visceral organs, the vagus nerve (VN) is one of the most promising targets. Closed-loop VN stimulation (VNS) would be crucial to increase effectiveness of this approach. Therefore, the extrapolation of useful physiological information from VN electrical activity would represent an invaluable source for single-target applications. Here, we present an advanced decoding algorithm novel to VN studies and properly detecting different functional changes from VN signals.Approach. VN signals were recorded using intraneural electrodes in anaesthetized pigs during cardiovascular and respiratory challenges mimicking increases in arterial blood pressure, tidal volume and respiratory rate. We developed a decoding algorithm that combines discrete wavelet transformation, principal component analysis, and ensemble learning made of classification trees.Main results. The new decoding algorithm robustly achieved high accuracy levels in identifying different functional changes and discriminating among them. Interestingly our findings suggest that electrodes positioning plays an important role on decoding performances. We also introduced a new index for the characterization of recording and decoding performance of neural interfaces. Finally, by combining an anatomically validated hybrid neural model and discrimination analysis, we provided new evidence suggesting a functional topographical organization of VN fascicles.Significance. This study represents an important step towards the comprehension of VN signaling, paving the way for the development of effective closed-loop VNS systems.

The Fourth Bioelectronic Medicine Summit "Technology Targeting Molecular Mechanisms": current progress, challenges, and charting the future

There is a broad and growing interest in Bioelectronic Medicine, a dynamic field that continues to generate new approaches in disease treatment. The fourth bioelectronic medicine summit "Technology targeting molecular mechanisms" took place on September 23 and 24, 2020. This virtual meeting was hosted by the Feinstein Institutes for Medical Research, Northwell Health. The summit called international attention to Bioelectronic Medicine as a platform for new developments in science, technology, and healthcare. The meeting was an arena for exchanging new ideas and seeding potential collaborations involving teams in academia and industry. The summit provided a forum for leaders in the field to discuss current progress, challenges, and future developments in Bioelectronic Medicine. The main topics discussed at the summit are outlined here.

Human Body Rhythms in the Development of Non-Invasive Methods of Closed-Loop Adaptive Neurostimulation

The creation and improvement of non-invasive closed-loop brain stimulation technologies represent an exciting and rapidly expanding field of neuroscience. To identify the appropriate way to close the feedback loop in adaptive neurostimulation procedures, it was previously proposed to use on-line automatic sensory stimulation with the parameters modulated by the patient's own rhythmical processes, such as respiratory rate, heart rate, and electroencephalogram (EEG) rhythms. The current paper aims to analyze several recent studies demonstrating further development in this line of research. The advantages of using automatic closed-loop feedback from human endogenous rhythms in non-invasive adaptive neurostimulation procedures have been demonstrated for relaxation assistance, for the correction of stress-induced functional disturbances, for anxiety management, and for the cognitive rehabilitation of an individual. Several distinctive features of the approach are noted to delineate its further development.

Prelimbic Cortical Stimulation Improves Spatial Memory Through Distinct Patterns of Hippocampal Gene Expression in Aged Rats

Dementia poses major health challenges worldwide, yet current treatments are faced with issues of efficacy and toxicity. Deep brain stimulation (DBS) is a promising non-pharmacological treatment for dementia, but most DBS studies use young healthy animals, which may not be aetiologically relevant. In this study, we used an aged rat model in which cognitive decline occurs through a natural ageing process. We used a Morris water maze (MWM) to determine the effects of prelimbic cortex (PrL) DBS on memory in aged rats. To investigate the underlying mechanisms of the effects of DBS, we carried out microarray, quantitative PCR analysis, and mass spectrometry to detect gene expression and neurotransmitter changes in the hippocampus. We showed PrL DBS improved the performance in MWM, with related distinct patterns of gene expression involving G protein-coupled receptor pathways. We further found neurotransmitter changes in the dorsal hippocampus, which corroborated and extended the microarray findings. Our results suggest that non-neurogenesis pathways play roles in the effects of DBS. Further studies are needed to investigate the effects of DBS on memory beyond neurogenesis and to consider the highlighted pathways suggested by our data.

Quantitative estimation of nerve fiber engagement by vagus nerve stimulation using physiological markers

BACKGROUND

Cervical vagus nerve stimulation (VNS) is an emerging bioelectronic treatment for brain, metabolic, cardiovascular and immune disorders. Its desired and off-target effects are mediated by different nerve fiber populations and knowledge of their engagement could guide calibration and monitoring of VNS therapies.

OBJECTIVE

Stimulus-evoked compound action potentials (eCAPs) directly provide fiber engagement information but are currently not feasible in humans. A method to estimate fiber engagement through common, noninvasive physiological readouts could be used in place of eCAP measurements.

METHODS

In anesthetized rats, we recorded eCAPs while registering acute physiological response markers to VNS: cervical electromyography (EMG), changes in heart rate (ΔHR) and breathing interval (ΔBI). Quantitative models were established to capture the relationship between A-, B- and C-fiber type activation and those markers, and to quantitatively estimate fiber activation from physiological markers and stimulation parameters.

RESULTS

In bivariate analyses, we found that EMG correlates with A-fiber, ΔHR with B-fiber and ΔBI with C-fiber activation, in agreement with known physiological functions of the vagus. We compiled multivariate models for quantitative estimation of fiber engagement from these markers and stimulation parameters. Finally, we compiled frequency gain models that allow estimation of fiber engagement at a wide range of VNS frequencies. Our models, after calibration in humans, could provide noninvasive estimation of fiber engagement in current and future therapeutic applications of VNS.

Biomarker Optimization of Spinal Cord Stimulation Therapies

OBJECTIVES

We are in the process of designing and testing an intradural stimulation device that will shorten the distance between the location of the electrode array and the targeted neural tissue, thus improving the efficacy of electrical current delivery. Identifying a biomarker that accurately reflects the response to this intervention is highly valued because of the potential to optimize interventional parameters or predict a response before it is clinically measurable. In this report, we summarize the findings pertaining to the study of biomarkers so that we and others will have an up-to-date reference that critically evaluates the current approaches and select one or several for testing during the development of our device.

MATERIALS AND METHODS

We have conducted a broad survey of the existing literature to catalogue the biomarkers that could be coupled to intradural spinal cord stimulation. We describe in detail some of the most promising biomarkers, existing limitations, and suitability to managing chronic pain.

RESULTS

Chronic, intractable pain is an all-encompassing condition that is incurable. Many treatments for managing chronic pain are nonspecific in action and intermittently administered; therefore, patients are particularly susceptible to large fluctuations in pain control over the course of a day. The absence of a reliable biomarker challenges assessment of therapeutic efficacy and contributes to either incomplete and inconsistent pain relief or, alternatively, intolerable side effects. Fluctuations in metabolites or inflammatory markers, signals captured during dynamic imaging, and genomics will likely have a role in governing how a device is modulated.

CONCLUSIONS

Efforts to identify one or more biomarkers are well underway with some preliminary evidence supporting their efficacy. This has far-reaching implications, including improved outcomes, fewer adverse events, harmonization of treatment and individuals, performance gains, and cost savings. We anticipate that novel biomarkers will be used widely to manage chronic pain.

Cortical stimulation in aphasia following ischemic stroke: toward model-guided electrical neuromodulation

The aim of this paper is to integrate different bodies of research including brain traveling waves, brain neuromodulation, neural field modeling and post-stroke language disorders in order to explore the opportunity of implementing model-guided, cortical neuromodulation for the treatment of post-stroke aphasia. Worldwide according to WHO, strokes are the second leading cause of death and the third leading cause of disability. In ischemic stroke, there is not enough blood supply to provide enough oxygen and nutrients to parts of the brain, while in hemorrhagic stroke, there is bleeding within the enclosed cranial cavity. The present paper focuses on ischemic stroke. We first review accumulating observations of traveling waves occurring spontaneously or triggered by external stimuli in healthy subjects as well as in patients with brain disorders. We examine the putative functions of these waves and focus on post-stroke aphasia observed when brain language networks become fragmented and/or partly silent, thus perturbing the progression of traveling waves across perilesional areas. Secondly, we focus on a simplified model based on the current literature in the field and describe cortical traveling wave dynamics and their modulation. This model uses a biophysically realistic integro-differential equation describing spatially distributed and synaptically coupled neural networks producing traveling wave solutions. The model is used to calculate wave parameters (speed, amplitude and/or frequency) and to guide the reconstruction of the perturbed wave. A stimulation term is included in the model to restore wave propagation to a reasonably good level. Thirdly, we examine various issues related to the implementation model-guided neuromodulation in the treatment of post-stroke aphasia given that closed-loop invasive brain stimulation studies have recently produced encouraging results. Finally, we suggest that modulating traveling waves by acting selectively and dynamically across space and time to facilitate wave propagation is a promising therapeutic strategy especially at a time when a new generation of closed-loop cortical stimulation systems is about to arrive on the market.

Pulmonary arterial hypertension: the case for a bioelectronic treatment

Pulmonary arterial hypertension (PAH) is a rare disease of unknown etiology that progresses to right ventricular failure. It has a complex pathophysiology, which involves an imbalance between vasoconstrictive and vasodilative processes in the pulmonary circulation, pulmonary vasoconstriction, vascular and right ventricular remodeling, systemic inflammation, and autonomic imbalance, with a reduced parasympathetic and increased sympathetic tone. Current pharmacological treatments for PAH include several classes of drugs that target signaling pathways in vascular biology and cardiovascular physiology, but they can have severe unwanted effects and they do not typically stop the progression of the disease. Pulmonary artery denervation has been tested clinically as a method to suppress sympathetic overactivation, however it is a nonspecific and irreversible intervention. Bioelectronic medicine, in particular vagus nerve stimulation (VNS), has been used in cardiovascular disorders like arrhythmias, heart failure and arterial hypertension and could, in principle, be tested as a treatment in PAH. VNS can produce pulmonary vasodilation and renormalize right ventricular function, via activation of pulmonary and cardiac vagal fibers. It can suppress systemic inflammation, via activation of fibers that innervate the spleen. Finally, VNS can gradually restore the balance between parasympathetic and sympathetic tone by regulating autonomic reflexes. Preclinical studies support the feasibility of using VNS in PAH. However, there are challenges with such an approach, arising from the need to affect a relatively small number of relevant vagal fibers, and the potential for unwanted cardiac and noncardiac effects of VNS in this sensitive patient population.