Proceedings of the Ninth Annual Deep Brain Stimulation Think Tank: Advances in Cutting Edge Technologies, Artificial Intelligence, Neuromodulation, Neuroethics, Pain, Interventional Psychiatry, Epilepsy, and Traumatic Brain Injury

Irregular optogenetic stimulation waveforms can induce naturalistic patterns of hippocampal spectral activity

Objective. Therapeutic brain stimulation is conventionally delivered using constant-frequency stimulation pulses. Several recent clinical studies have explored how unconventional and irregular temporal stimulation patterns could enable better therapy. However, it is challenging to understand which irregular patterns are most effective for different therapeutic applications given the massively high-dimensional parameter space.Approach. Here we applied many irregular stimulation patterns in a single neural circuit to demonstrate how they can enable new dimensions of neural control compared to conventional stimulation, to guide future exploration of novel stimulation patterns in translational settings. We optogenetically excited the septohippocampal circuit with constant-frequency, nested pulse, sinusoidal, and randomized stimulation waveforms, systematically varying their amplitude and frequency parameters.Main results.We first found equal entrainment of hippocampal oscillations: all waveforms provided similar gamma-power increase, whereas no parameters increased theta-band power above baseline (despite the mechanistic role of the medial septum in driving hippocampal theta oscillations). We then compared each of the effects of each waveform on high-dimensional multi-band activity states using dimensionality reduction methods. Strikingly, we found that conventional stimulation drove predominantly 'artificial' (different from behavioral activity) effects, whereas all irregular waveforms induced activity patterns that more closely resembled behavioral activity.Significance. Our findings suggest that irregular stimulation patterns are not useful when the desired mechanism is to suppress or enhance a single frequency band. However, novel stimulation patterns may provide the greatest benefit for neural control applications where entraining a particular mixture of bands (e.g. if they are associated with different symptoms) or behaviorally-relevant activity is desired.

Deep Brain Stimulation of the Medial Forebrain Bundle for Treatment-Resistant Depression: A Systematic Review Focused on the Long-Term Antidepressive Effect

OBJECTIVE

Major depression affects millions of people worldwide and has important social and economic consequences. Since up to 30% of patients do not respond to several lines of antidepressive drugs, deep brain stimulation (DBS) has been evaluated for the management of treatment-resistant depression (TRD). The superolateral branch of the medial forebrain bundle (slMFB) appears as a "hypothesis-driven target" because of its role in the reward-seeking system, which is dysfunctional in depression. Although initial results of slMFB-DBS from open-label studies were promising and characterized by a rapid clinical response, long-term outcomes of neurostimulation for TRD deserve particular attention. Therefore, we performed a systematic review focused on the long-term outcome of slMFB-DBS.

MATERIALS AND METHODS

A literature search using Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria was conducted to identify all studies reporting changes in depression scores after one-year follow-up and beyond. Patient, disease, surgical, and outcome data were extracted for statistical analysis. The Montgomery-Åsberg Depression Rating Scale (ΔMADRS) was used as the clinical outcome, defined as percentage reduction from baseline to follow-up evaluation. Responders' and remitters' rates were also calculated.

RESULTS

From 56 studies screened for review, six studies comprising 34 patients met the inclusion criteria and were analyzed. After one year of active stimulation, ΔMADRS was 60.7% ± 4%; responders' and remitters' rates were 83.8% and 61.5%, respectively. At the last follow-up, four to five years after the implantation, ΔMADRS reached 74.7% ± 4.6%. The most common side effects were stimulation related and reversible with parameter adjustments.

CONCLUSIONS

slMFB-DBS appears to have a strong antidepressive effect that increases over the years. Nevertheless, to date, the overall number of patients receiving implantations is limited, and the slMFB-DBS surgical technique seems to have an important impact on the clinical outcome. Further multicentric studies in a larger population are needed to confirm slMFB-DBS clinical outcomes.

Toward an interventional science of recovery after coma

Recovery of consciousness after coma remains one of the most challenging areas for accurate diagnosis and effective therapeutic engagement in the clinical neurosciences. Recovery depends on preservation of neuronal integrity and evolving changes in network function that re-establish environmental responsiveness. It typically occurs in defined steps: it begins with eye opening and unresponsiveness in a vegetative state, then limited recovery of responsiveness characterizes the minimally conscious state, and this is followed by recovery of reliable communication. This review considers several points for novel interventions, for example, in persons with cognitive motor dissociation in whom a hidden cognitive reserve is revealed. Circuit mechanisms underlying restoration of behavioral responsiveness and communication are discussed. An emerging theme is the possibility to rescue latent capacities in partially damaged human networks across time. These opportunities should be exploited for therapeutic engagement to achieve individualized solutions for restoration of communication and environmental interaction across varying levels of recovery.

Deep brain stimulation for refractory major depressive disorder: a comprehensive review

Deep brain stimulation (DBS) has emerged as a promising treatment for select patients with refractory major depressive disorder (MDD). The clinical effectiveness of DBS for MDD has been demonstrated in meta-analyses, open-label studies, and a few controlled studies. However, randomized controlled trials have yielded mixed outcomes, highlighting challenges that must be addressed prior to widespread adoption of DBS for MDD. These challenges include tracking MDD symptoms objectively to evaluate the clinical effectiveness of DBS with sensitivity and specificity, identifying the patient population that is most likely to benefit from DBS, selecting the optimal patient-specific surgical target and stimulation parameters, and understanding the mechanisms underpinning the therapeutic benefits of DBS in the context of MDD pathophysiology. In this review, we provide an overview of the latest clinical evidence of MDD DBS effectiveness and the recent technological advancements that could transform our understanding of MDD pathophysiology, improve the clinical outcomes for MDD DBS, and establish a path forward to develop more effective neuromodulation therapies to alleviate depressive symptoms.

Automatic sleep-wake classification and Parkinson's disease recognition using multifeature fusion with support vector machine

AIMS

Sleep disturbance is a prevalent nonmotor symptom of Parkinson's disease (PD), however, assessing sleep conditions is always time-consuming and labor-intensive. In this study, we performed an automatic sleep-wake state classification and early diagnosis of PD by analyzing the electrocorticography (ECoG) and electromyogram (EMG) signals of both normal and PD rats.

METHODS

The study utilized ECoG power, EMG amplitude, and corticomuscular coherence values extracted from normal and PD rats to construct sleep-wake scoring models based on the support vector machine algorithm. Subsequently, we incorporated feature values that could act as diagnostic markers for PD and then retrained the models, which could encompass the identification of vigilance states and the diagnosis of PD.

RESULTS

Features extracted from occipital ECoG signals were more suitable for constructing sleep-wake scoring models than those from frontal ECoG (average Cohen's kappa: 0.73 vs. 0.71). Additionally, after retraining, the new models demonstrated increased sensitivity to PD and accurately determined the sleep-wake states of rats (average Cohen's kappa: 0.79).

CONCLUSION

This study accomplished the precise detection of substantia nigra lesions and the monitoring of sleep-wake states. The integration of circadian rhythm monitoring and disease state assessment has the potential to improve the efficacy of therapeutic strategies considerably.

At home adaptive dual target deep brain stimulation in Parkinson's disease with proportional control

Continuous deep brain stimulation (cDBS) of the subthalamic nucleus (STN) or globus pallidus is an effective treatment for the motor symptoms of Parkinson's disease. The relative benefit of one region over the other is of great interest but cannot usually be compared in the same patient. Simultaneous DBS of both regions may synergistically increase the therapeutic benefit. Continuous DBS is limited by a lack of responsiveness to dynamic, fluctuating symptoms intrinsic to the disease. Adaptive DBS (aDBS) adjusts stimulation in response to biomarkers to improve efficacy, side effects, and efficiency. We combined bilateral DBS of both STN and globus pallidus (dual target DBS) in a prospective within-participant, clinical trial in six patients with Parkinson's disease (n = 6, 55-65 years, n = 2 females). Dual target cDBS was tested for Parkinson's disease symptom control annually over 2 years, measured by motor rating scales, on time without dyskinesia, and medication reduction. Random amplitude experiments probed system dynamics to estimate parameters for aDBS. We then implemented proportional-plus-integral aDBS using a novel distributed (off-implant) architecture. In the home setting, we collected tremor and dyskinesia scores as well as individualized β and DBS amplitudes. Dual target cDBS reduced motor symptoms as measured by Unified Parkinson's Disease Rating Scale (UPDRS) to a greater degree than either region alone (P < 0.05, linear mixed model) in the cohort. The amplitude of β-oscillations in the STN correlated to the speed of hand grasp movements for five of six participants (P < 0.05, Pearson correlation). Random amplitude experiments provided insight into temporal windowing to avoid stimulation artefacts and demonstrated a correlation between STN β amplitude and DBS amplitude. Proportional plus integral control of aDBS reduced average power, while preserving UPDRS III scores in the clinic (P = 0.28, Wilcoxon signed rank), and tremor and dyskinesia scores during blinded testing at home (n = 3, P > 0.05, Wilcoxon ranked sum). In the home setting, DBS power reductions were slight but significant. Dual target cDBS may offer an improvement in treatment of motor symptoms of Parkinson's disease over DBS of either the STN or globus pallidus alone. When combined with proportional plus integral aDBS, stimulation power may be reduced, while preserving the increased benefit of dual target DBS.

Sensing with deep brain stimulation device in epilepsy: Aperiodic changes in thalamic local field potential during seizures

OBJECTIVE

Thalamic deep brain stimulation (DBS) is an effective therapeutic option in patients with drug-resistant epilepsy. Recent DBS devices with sensing capabilities enable chronic, outpatient local field potential (LFP) recordings. Whereas beta oscillations have been demonstrated to be a useful biomarker in movement disorders, the clinical utility of DBS sensing in epilepsy remains unclear. Our aim was to determine LFP features that distinguish ictal from inter-ictal states, which may aid in tracking seizure outcomes with DBS.

METHODS

Electrophysiology data were obtained from DBS devices implanted in the anterior nucleus (N = 12) or centromedian nucleus (N = 2) of the thalamus. Power spectra recorded during patient/caregiver-marked seizure events were analyzed with a method that quantitatively separates the oscillatory and non-oscillatory/aperiodic components of the LFP using non-parametric statistics, without the need for pre-specification of the frequency bands of interest. Features of the LFP parameterized using this algorithm were compared with those from inter-ictal power spectra recorded in clinic.

RESULTS

Oscillatory activity in multiple canonical frequency bands was identified from the power spectra in 86.48% of patient-marked seizure events. Delta oscillations were present in all patients, followed by theta (N = 10) and beta (N = 9). Although there were no differences in oscillatory LFP features between the ictal and inter-ictal states, there was a steeper decline in the 1/f slope of the aperiodic component of the LFP during seizures.

SIGNIFICANCE

Our work highlights the potential and shortcomings of chronic LFP recordings in thalamic DBS for epilepsy. Findings suggest that no single frequency band in isolation clearly differentiates seizures, and that features of aperiodic LFP activity may be clinically-relevant biomarkers of seizures.

Publication Rates and Characteristics of Clinical Trials in Deep Brain and Responsive Neurostimulation

INTRODUCTION

Prompt dissemination of clinical trial results is essential for ensuring the safety and efficacy of intracranial neurostimulation treatments, including deep brain stimulation (DBS) and responsive neurostimulation (RNS). However, the frequency and completeness of results publication, and reasons for reporting delays, are unknown. Moreover, the patient populations, targeted anatomical locations, and stimulation parameters should be clearly reported for both reproducibility and to identify lacunae in trial design. Here, we examine DBS and RNS trials from 1997 to 2022, chart their characteristics, and examine rates and predictors of results reporting.

METHODS

Trials were identified using ClinicalTrials.gov. Associated publications were identified using ClinicalTrials.gov and PubMed.gov. Pearson's χ2 tests were used to assess differences in trial characteristics between published and unpublished trials.

RESULTS

Across 449 trials, representing a cumulative cohort of 42,769 patient interventions, there were 37 therapeutic indications and 44 stimulation targets. The most common indication and target were Parkinson's disease (40.55%) and the subthalamic nucleus (35.88%), respectively. Only 0.89% of trials were in pediatric patients (11.58% were mixed pediatric and adult). Explored targets represented 75% of potential basal ganglia targets but only 29% of potential thalamic targets. Allowing a 1-year grace period after trial completion, 34/169 (20.12%) had results reported on ClinicalTrials.gov, and 107/169 (63.31%) were published. ∼80% of published trials included details about stimulation parameters used. Published and unpublished trials did not significantly differ by trial characteristics.

CONCLUSION

We highlight key knowledge and performance gaps in DBS and RNS trial research. Over one-third of trials remain unpublished >1 year after completion; pediatric trials are scarce; most of the thalamus remains unexplored; about one-in-five trials fail to report stimulation parameters; and movement disorders comprise the most studied indications.

Neuroethical implications of focused ultrasound for neuropsychiatric illness

BACKGROUND

MR-guided focused ultrasound is a promising intervention for treatment-resistant mental illness, and merits contextualized ethical exploration in relation to more extensive ethical literature regarding other psychosurgical and neuromodulation treatment options for this patient population. To our knowledge, this topic has not yet been explored in the published literature.

OBJECTIVE

The purpose of this paper is to review and discuss in detail the neuroethical implications of MR-guided focused ultrasound for neuropsychiatric illness as an emerging treatment modality.

METHODS

Due to the lack of published literature on the topic, the approach involved a detailed survey and review of technical and medical literature relevant to focused ultrasound and established ethical issues related to alternative treatment options for patients with treatment-resistant, severe and persistent mental illness. The manuscript is structured according to thematic and topical findings.

RESULTS

This technology has potential benefits for patients suffering with severe mental illness, compared with established alternatives. The balance of technical, neuroscientific and clinical considerations should inform ethical deliberations. The nascent literature base, nuances in legal classification and permissibility depending upon jurisdiction, influences of past ethical issues associated with alternative treatments, tone and framing in media articles, and complexity of clinical trials all influence ethical assessment and evaluations of multiple stakeholders. Recommendations for future research are provided based on these factors.

CONCLUSION

Salient ethical inquiry should be further explored by researchers, clinicians, and ethicists in a nuanced manner methodologically, one which is informed by past and present ethical issues related to alternative treatment options, broader psychiatric treatment frameworks, pragmatic implementation challenges, intercultural considerations, and patients' ethical concerns.

Closed-Loop Deep Brain Stimulation for Psychiatric Disorders

ABSTRACT

Deep brain stimulation (DBS) is a well-established approach to treating medication-refractory neurological disorders and holds promise for treating psychiatric disorders. Despite strong open-label results in extremely refractory patients, DBS has struggled to meet endpoints in randomized controlled trials. A major challenge is stimulation "dosing"-DBS systems have many adjustable parameters, and clinicians receive little feedback on whether they have chosen the correct parameters for an individual patient. Multiple groups have proposed closed loop technologies as a solution. These systems sense electrical activity, identify markers of an (un)desired state, then automatically deliver or adjust stimulation to alter that electrical state. Closed loop DBS has been successfully deployed in movement disorders and epilepsy. The availability of that technology, as well as advances in opportunities for invasive research with neurosurgical patients, has yielded multiple pilot demonstrations in psychiatric illness. Those demonstrations split into two schools of thought, one rooted in well-established diagnoses and symptom scales, the other in the more experimental Research Domain Criteria (RDoC) framework. Both are promising, and both are limited by the boundaries of current stimulation technology. They are in turn driving advances in implantable recording hardware, signal processing, and stimulation paradigms. The combination of these advances is likely to change both our understanding of psychiatric neurobiology and our treatment toolbox, though the timeframe may be limited by the realities of implantable device development.

Offline Learning of Closed-Loop Deep Brain Stimulation Controllers for Parkinson Disease Treatment

Deep brain stimulation (DBS) has shown great promise toward treating motor symptoms caused by Parkinson's disease (PD), by delivering electrical pulses to the Basal Ganglia (BG) region of the brain. However, DBS devices approved by the U.S. Food and Drug Administration (FDA) can only deliver continuous DBS (cDBS) stimuli at a fixed amplitude; this energy inefficient operation reduces battery lifetime of the device, cannot adapt treatment dynamically for activity, and may cause significant side-effects (e.g., gait impairment). In this work, we introduce an offline reinforcement learning (RL) framework, allowing the use of past clinical data to train an RL policy to adjust the stimulation amplitude in real time, with the goal of reducing energy use while maintaining the same level of treatment (i.e., control) efficacy as cDBS. Moreover, clinical protocols require the safety and performance of such RL controllers to be demonstrated ahead of deployments in patients. Thus, we also introduce an offline policy evaluation (OPE) method to estimate the performance of RL policies using historical data, before deploying them on patients. We evaluated our framework on four PD patients equipped with the RC+S DBS system, employing the RL controllers during monthly clinical visits, with the overall control efficacy evaluated by severity of symptoms (i.e., bradykinesia and tremor), changes in PD biomakers (i.e., local field potentials), and patient ratings. The results from clinical experiments show that our RL-based controller maintains the same level of control efficacy as cDBS, but with significantly reduced stimulation energy. Further, the OPE method is shown effective in accurately estimating and ranking the expected returns of RL controllers.

Proceedings of the 10th annual deep brain stimulation think tank: Advances in cutting edge technologies, artificial intelligence, neuromodulation, neuroethics, interventional psychiatry, and women in neuromodulation

The deep brain stimulation (DBS) Think Tank X was held on August 17-19, 2022 in Orlando FL. The session organizers and moderators were all women with the theme women in neuromodulation. Dr. Helen Mayberg from Mt. Sinai, NY was the keynote speaker. She discussed milestones and her experiences in developing depression DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers and researchers (from industry and academia) can freely discuss current and emerging DBS technologies as well as the logistical and ethical issues facing the field. The consensus among the DBS Think Tank X speakers was that DBS has continued to expand in scope however several indications have reached the "trough of disillusionment." DBS for depression was considered as "re-emerging" and approaching a slope of enlightenment. DBS for depression will soon re-enter clinical trials. The group estimated that globally more than 244,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: neuromodulation in Europe, Asia, and Australia; cutting-edge technologies, closed loop DBS, DBS tele-health, neuroethics, lesion therapy, interventional psychiatry, and adaptive DBS.

Decision-making in stereotactic epilepsy surgery

Surgery can cure or significantly improve both the frequency and the intensity of seizures in patients with medication-refractory epilepsy. The set of diagnostic and therapeutic interventions involved in the path from initial consultation to definitive surgery is complex and includes a multidisciplinary team of neurologists, neurosurgeons, neuroradiologists, and neuropsychologists, supported by a very large epilepsy-dedicated clinical architecture. In recent years, new practices and technologies have emerged that dramatically expand the scope of interventions performed. Stereoelectroencephalography has become widely adopted for seizure localization; stereotactic laser ablation has enabled more focal, less invasive, and less destructive interventions; and new brain stimulation devices have unlocked treatment of eloquent foci and multifocal onset etiologies. This article articulates and illustrates the full framework for how epilepsy patients are considered for surgical intervention, with particular attention given to stereotactic approaches.

Towards network-guided neuromodulation for epilepsy

Epilepsy is well-recognized as a disorder of brain networks. There is a growing body of research to identify critical nodes within dynamic epileptic networks with the aim to target therapies that halt the onset and propagation of seizures. In parallel, intracranial neuromodulation, including deep brain stimulation and responsive neurostimulation, are well-established and expanding as therapies to reduce seizures in adults with focal-onset epilepsy; and there is emerging evidence for their efficacy in children and generalized-onset seizure disorders. The convergence of these advancing fields is driving an era of 'network-guided neuromodulation' for epilepsy. In this review, we distil the current literature on network mechanisms underlying neurostimulation for epilepsy. We discuss the modulation of key 'propagation points' in the epileptogenic network, focusing primarily on thalamic nuclei targeted in current clinical practice. These include (i) the anterior nucleus of thalamus, now a clinically approved and targeted site for open loop stimulation, and increasingly targeted for responsive neurostimulation; and (ii) the centromedian nucleus of the thalamus, a target for both deep brain stimulation and responsive neurostimulation in generalized-onset epilepsies. We discuss briefly the networks associated with other emerging neuromodulation targets, such as the pulvinar of the thalamus, piriform cortex, septal area, subthalamic nucleus, cerebellum and others. We report synergistic findings garnered from multiple modalities of investigation that have revealed structural and functional networks associated with these propagation points - including scalp and invasive EEG, and diffusion and functional MRI. We also report on intracranial recordings from implanted devices which provide us data on the dynamic networks we are aiming to modulate. Finally, we review the continuing evolution of network-guided neuromodulation for epilepsy to accelerate progress towards two translational goals: (i) to use pre-surgical network analyses to determine patient candidacy for neurostimulation for epilepsy by providing network biomarkers that predict efficacy; and (ii) to deliver precise, personalized and effective antiepileptic stimulation to prevent and arrest seizure propagation through mapping and modulation of each patients' individual epileptogenic networks.