Brain-Responsive Neurostimulation for Loss of Control Eating: Early Feasibility Study

Weight Trends After Spinal Cord Stimulation Therapy for Chronic Pain

OBJECTIVES

Spinal cord stimulation (SCS) therapy is an effective treatment for chronic pain, particularly in conditions such as postlaminectomy syndrome and complex regional pain syndrome (CRPS). Rare case reports described significant weight loss in patients who underwent dorsal column SCS therapy for chronic pain. Recently, neuromodulation for obesity has become a novel field for research. We aimed to investigate weight trends among patients treated with SCS for chronic pain.

MATERIALS AND METHODS

We conducted a retrospective chart review in 342 patients treated with SCS or dorsal root ganglion stimulators at our institution between 2010 and 2023. Patients had their weight recorded before SCS implantation and at least once within 12 months after surgery. We also conducted interviews with 28 patients who experienced significant weight loss or had revision procedures owing to weight loss.

RESULTS

We found that 105 of 342 patients (30.7%) experienced weight loss of ≥5% within a year of implantation, and 32 of 105 (30.5%, 9.4% of all patients) experienced weight loss of ≥ 10%. A multivariate regression analysis revealed a modest increase in the likelihood of weight loss among patients with CRPS (odds ratio [OR] = 1.17, 95% CI [1.04, 1.30], p = 0.007) and in those who achieved pain relief after implantation (OR = 1.22, 95% CI [1.05,1.40], p = 0.008). Of the 28 patients with significant weight loss who were interviewed, 12 (43%) could not explain the reasons for their weight loss, whereas eight (29%) reported decreased appetite. Leads placed at higher thoracic levels were associated with increased rates of weight loss (37.2% at T6-T8 and 22.3% at T8-T10; p = 0.038).

CONCLUSIONS

Our findings suggest that SCS therapy may affect weight in patients with chronic pain. Further studies are needed to investigate the potential role of SCS in weight modulation.

Neuromorphic neuromodulation: Towards the next generation of closed-loop neurostimulation

Neuromodulation techniques have emerged as promising approaches for treating a wide range of neurological disorders, precisely delivering electrical stimulation to modulate abnormal neuronal activity. While leveraging the unique capabilities of AI holds immense potential for responsive neurostimulation, it appears as an extremely challenging proposition where real-time (low-latency) processing, low-power consumption, and heat constraints are limiting factors. The use of sophisticated AI-driven models for personalized neurostimulation depends on the back-telemetry of data to external systems (e.g. cloud-based medical mesosystems and ecosystems). While this can be a solution, integrating continuous learning within implantable neuromodulation devices for several applications, such as seizure prediction in epilepsy, is an open question. We believe neuromorphic architectures hold an outstanding potential to open new avenues for sophisticated on-chip analysis of neural signals and AI-driven personalized treatments. With more than three orders of magnitude reduction in the total data required for data processing and feature extraction, the high power- and memory-efficiency of neuromorphic computing to hardware-firmware co-design can be considered as the solution-in-the-making to resource-constraint implantable neuromodulation systems. This perspective introduces the concept of Neuromorphic Neuromodulation, a new breed of closed-loop responsive feedback system. It highlights its potential to revolutionize implantable brain-machine microsystems for patient-specific treatment.

Acoustic deep brain modulation: Enhancing neuronal activation and neurogenesis

BACKGROUND

Non-invasive deep brain modulation (DBM) stands as a promising therapeutic avenue to treat brain diseases. Acoustic DBM represents an innovative and targeted approach to modulate the deep brain, employing techniques such as focused ultrasound and shock waves. Despite its potential, the optimal mechanistic parameters, the effect in the brain and behavioral outcomes of acoustic DBM remains poorly understood.

OBJECTIVE

To establish a robust protocol for the shock wave DBM by optimizing its mechanistic profile of external stimulation, and to assess its efficacy in preclinical settings.

METHODS

We used shockwaves due to their capacity to leverage a broader spectrum of peak intensity (10-127 W/mm2) in contrast to ultrasound (0.1-5.0 W/mm2), thereby enabling a more extensive range of neuromodulation effects. We established various types of shockwave pressure profiles of DBM and compared neural and behavioral responses. To ascertain the anticipated cause of the heightened neural activity response, numerical analysis was employed to examine the mechanical dynamics within the brain.

RESULTS

An optimized profile led to an enhancement in neuronal activity within the hypothalamus of mouse models. The optimized profile in the hippocampus elicited a marked increase in neurogenesis without neuronal damage. Behavioral analyses uncovered a noteworthy reduction in locomotion without significant effects on spatial memory function.

CONCLUSIONS

The present study provides an optimized shock wave stimulation protocol for non-invasive DBM. Our optimized stimulation profile selectively triggers neural functions in the deep brain. Our protocol paves the way for new non-invasive DBM devices to treat brain diseases.

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.

Accumbens connectivity during deep-brain stimulation differentiates loss of control from physiologic behavioral states

BACKGROUND

Loss of control (LOC) eating, the subjective sense that one cannot control what or how much one eats, characterizes binge-eating behaviors pervasive in obesity and related eating disorders. Closed-loop deep-brain stimulation (DBS) for binge eating should predict LOC and trigger an appropriately timed intervention.

OBJECTIVE/HYPOTHESIS

This study aimed to identify a sensitive and specific biomarker to detect LOC onset for DBS. We hypothesized that changes in phase-locking value (PLV) predict the onset of LOC-associated cravings and distinguish them from potential confounding states.

METHODS

Using DBS data recorded from the nucleus accumbens (NAc) of two patients with binge eating disorder (BED) and severe obesity, we compared PLV between inter- and intra-hemispheric NAc subregions for three behavioral conditions: craving (associated with LOC eating), hunger (not associated with LOC), and sleep.

RESULTS

In both patients, PLV in the high gamma frequency band was significantly higher for craving compared to sleep and significantly higher for hunger compared to craving. Maximum likelihood classifiers achieved accuracies above 88% when differentiating between the three conditions.

CONCLUSIONS

High-frequency inter- and intra-hemispheric PLV in the NAc is a promising biomarker for closed-loop DBS that differentiates LOC-associated cravings from physiologic states such as hunger and sleep. Future trials should assess PLV as a LOC biomarker across a larger cohort and a wider patient population transdiagnostically.

Closed-loop enhancement and neural decoding of cognitive control in humans

Deficits in cognitive control-that is, in the ability to withhold a default pre-potent response in favour of a more adaptive choice-are common in depression, anxiety, addiction and other mental disorders. Here we report proof-of-concept evidence that, in participants undergoing intracranial epilepsy monitoring, closed-loop direct stimulation of the internal capsule or striatum, especially the dorsal sites, enhances the participants' cognitive control during a conflict task. We also show that closed-loop stimulation upon the detection of lapses in cognitive control produced larger behavioural changes than open-loop stimulation, and that task performance for single trials can be directly decoded from the activity of a small number of electrodes via neural features that are compatible with existing closed-loop brain implants. Closed-loop enhancement of cognitive control might remediate underlying cognitive deficits and aid the treatment of severe mental disorders.

Pilot study of responsive nucleus accumbens deep brain stimulation for loss-of-control eating

Cravings that precede loss of control (LOC) over food consumption present an opportunity for intervention in patients with the binge eating disorder (BED). In this pilot study, we used responsive deep brain stimulation (DBS) to record nucleus accumbens (NAc) electrophysiology during food cravings preceding LOC eating in two patients with BED and severe obesity (trial registration no. NCT03868670). Increased NAc low-frequency oscillations, prominent during food cravings, were used to guide DBS delivery. Over 6 months, we observed improved self-control of food intake and weight loss. These findings provide early support for restoring inhibitory control with electrophysiologically-guided NAc DBS. Further work with increased sample sizes is required to determine the scalability of this approach.

Nucleus accumbens, low-frequency, responsive deep brain stimulation improved self-control of food intake and weight loss in two patients with binge eating disorder and severe obesity

Aberrant impulse control circuitry in obesity

The ventromedial prefrontal cortex (vmPFC) to nucleus accumbens (NAc) circuit has been implicated in impulsive reward-seeking. This disinhibition has been implicated in obesity and often manifests as binge eating, which is associated with worse treatment outcomes and comorbidities. It remains unclear whether the vmPFC-NAc circuit is perturbed in impulsive eaters with obesity. Initially, we analyzed publicly available, high-resolution, normative imaging data to localize where vmPFC structural connections converged within the NAc. These structural connections were found to converge ventromedially in the presumed NAc shell subregion. We then analyzed multimodal clinical and imaging data to test the a priori hypothesis that the vmPFC-NAc shell circuit is linked to obesity in a sample of female participants that regularly engaged in impulsive eating (i.e., binge eating). Functionally, vmPFC-NAc shell resting-state connectivity was inversely related to body mass index (BMI) and decreased in the obese state. Structurally, vmPFC-NAc shell structural connectivity and vmPFC thickness were inversely correlated with BMI; obese binge-prone participants exhibited decreased vmPFC-NAc structural connectivity and vmPFC thickness. Finally, to examine a causal link to binge eating, we directly probed this circuit in one binge-prone obese female using NAc deep brain stimulation in a first-in-human trial. Direct stimulation of the NAc shell subregion guided by local behaviorally relevant electrophysiology was associated with a decrease in number of weekly episodes of uncontrolled eating and decreased BMI. This study unraveled vmPFC-NAc shell circuit aberrations in obesity that can be modulated to restore control over eating behavior in obesity.

Can responsive deep brain stimulation be a cost-effective treatment for severe obesity?

OBJECTIVE

A first-in-human responsive deep brain stimulation (rDBS) trial (NCT03868670) for obesity is under way, which is based on promising preclinical evidence. Given the upfront costs of rDBS, it is prudent to examine the success threshold for cost-effectiveness compared with laparoscopic Roux-en-Y gastric bypass (LRYGB).

METHODS

Efficacy and safety data on LRYGB and safety data on rDBS were collected for established indications through a literature search. The success threshold was defined as minimum BMI reduction. Treatment costs were calculated via Medicare national reimbursement data.

RESULTS

LRYGB had a mean BMI reduction of 13.75 kg/m² . Based on adverse events, LRYGB was a less-preferred health state (overall adverse event utility of 0.96 [0.02]) than rDBS (0.98 [0.01]), but LRYGB ($14,366 [$6,410]) had a significantly lower treatment cost than rDBS ($29,951 [$4,490]; p < 0.0001). Therefore, for rDBS to be cost-effective compared with LRYGB, the multiple models yielded a success threshold range of 13.7 to 15.2 kg/m² .

CONCLUSIONS

This study established a preliminary efficacy success threshold for rDBS to be cost-effective for severe obesity, and results from randomized controlled trials are needed. This analysis allows for interpretation of the economic impact of advancing rDBS for obesity in light of ongoing trial results and suggests an attainable threshold is needed for cost-effectiveness.

Chronic electroencephalography in epilepsy with a responsive neurostimulation device: current status and future prospects

INTRODUCTION

Implanted neurostimulation devices are gaining traction as therapeutic options for people with certain forms of drug-resistant focal epilepsy. Some of these devices enable chronic electroencephalography (cEEG), which offers views of the dynamics of brain activity in epilepsy over unprecedented time horizons.

AREAS COVERED

This review focuses on clinical insights and basic neuroscience discoveries enabled by analyses of cEEG from an exemplar device, the NeuroPace RNS® System. Applications of RNS cEEG covered here include counting and lateralizing seizures, quantifying medication response, characterizing spells, forecasting seizures, and exploring mechanisms of cognition. Limitations of the RNS System are discussed in the context of next-generation devices in development.

EXPERT OPINION

The wide temporal lens of cEEG helps capture the dynamism of epilepsy, revealing phenomena that cannot be appreciated with short duration recordings. The RNS System is a vanguard device whose diagnostic utility rivals its therapeutic benefits, but emerging minimally invasive devices, including those with subscalp recording electrodes, promise to be more applicable within a broad population of people with epilepsy. Epileptology is on the precipice of a paradigm shift in which cEEG is a standard part of diagnostic evaluations and clinical management is predicated on quantitative observations integrated over long timescales.

Proceedings of the Eighth Annual Deep Brain Stimulation Think Tank: Advances in Optogenetics, Ethical Issues Affecting DBS Research, Neuromodulatory Approaches for Depression, Adaptive Neurostimulation, and Emerging DBS Technologies

We estimate that 208,000 deep brain stimulation (DBS) devices have been implanted to address neurological and neuropsychiatric disorders worldwide. DBS Think Tank presenters pooled data and determined that DBS expanded in its scope and has been applied to multiple brain disorders in an effort to modulate neural circuitry. The DBS Think Tank was founded in 2012 providing a space where clinicians, engineers, researchers from industry and academia discuss current and emerging DBS technologies and logistical and ethical issues facing the field. The emphasis is on cutting edge research and collaboration aimed to advance the DBS field. The Eighth Annual DBS Think Tank was held virtually on September 1 and 2, 2020 (Zoom Video Communications) due to restrictions related to the COVID-19 pandemic. The meeting focused on advances in: (1) optogenetics as a tool for comprehending neurobiology of diseases and on optogenetically-inspired DBS, (2) cutting edge of emerging DBS technologies, (3) ethical issues affecting DBS research and access to care, (4) neuromodulatory approaches for depression, (5) advancing novel hardware, software and imaging methodologies, (6) use of neurophysiological signals in adaptive neurostimulation, and (7) use of more advanced technologies to improve DBS clinical outcomes. There were 178 attendees who participated in a DBS Think Tank survey, which revealed the expansion of DBS into several indications such as obesity, post-traumatic stress disorder, addiction and Alzheimer’s disease. This proceedings summarizes the advances discussed at the Eighth Annual DBS Think Tank.