This case presents the situation of a 66-year-old woman diagnosed with Multiple System Atrophy Parkinsonian Type who underwent deep brain stimulation (DBS) therapy and subsequently made two suicide attempts. Despite receiving treatment and extensive psychotherapy, her condition did not improve, leading to suicidal behavior over the course of a year. Notably, she held unrealistic beliefs about the effectiveness of DBS therapy, expressing dissatisfaction with its outcomes. Family dynamics were complex, with the patient concealing her psychological distress while coping with her worsening health condition. This severe distress culminated in two suicide attempts within a relatively short timeframe. Our psychiatric team promptly intervened, implementing a suicidality protocol and adjusting her medication regimen. Despite a documented prevalence of suicidal ideation and attempts post-DBS in the literature, the exact causes remain uncertain, with the suggested involvement of neuroimmune or neurological pathways. This case contributes to scientific understanding by shedding light on suicide attempts following ineffective DBS interventions, emphasizing the patient\'s right to be informed about potential suicide risks and the possibility of assisted suicide through a neuroethical analysis. Therefore, our case underlines the importance of psychiatric evaluation and intervention in DBS patients to prevent further suicidality, focusing on a multidisciplinary approach tailored to the patient\'s autonomy and neuroethical principles.

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Implanting deep brain stimulation (DBS) electrodes in patients with Parkinson\'s disease often results in the appearance of a non-infectious, delayed-onset edema that disappears over time. However, the time window between the DBS electrode and DBS stimulating device implant is often used to record local field potentials (LFPs) which are used both to better understand basal ganglia pathophysiology and to improve DBS therapy. In this work, we investigated whether the presence of post-surgery edema correlates with the quality of LFP recordings in eight patients with advanced Parkinson\'s disease implanted with subthalamic DBS electrodes. The magnetic resonance scans of the brain after 8.5 ± 1.5 days from the implantation surgery were segmented and the peri-electrode edema volume was calculated for both brain hemispheres. We found a correlation (ρ = -0.81, p < 0.0218, Spearman\'s correlation coefficient) between left side local field potentials of the low beta band (11-20 Hz) and the edema volume of the same side. No other significant differences between the hemispheres were found. Despite the limited sample size, our results suggest that the effect on LFPs may be related to the edema localization, thus indicating a mechanism involving brain networks instead of a simple change in the electrode-tissue interface.

Implantable neurotechnology devices such as Brain Computer Interfaces (BCIs) and Deep Brain Stimulators (DBS) are an increasing part of treating or exploring potential treatments for neurological and psychiatric disorders. While only a few devices are approved, many promising prospects for future devices are under investigation. The decision to participate in a clinical trial can be challenging, given a variety of risks to be taken into consideration. During the consent process, prospective participants might lack the language to consider those risks, feel unprepared, or simply not know what questions to ask. One tool to help empower participants to play a more active role during the consent process is a Question Prompt List (QPL). QPLs are communication tools that can prompt participants and patients to articulate potential concerns. They offer a structured list of disease, treatment, or research intervention-specific questions that research participants can use as support for question asking. While QPLs have been studied as tools for improving the consent process during cancer treatment, in this paper, we suggest they would be helpful in neurotechnology research, and offer an example of a QPL as a template for an informed consent tool in neurotechnology device trials.

Recent advances in wireless data transmission technology have the potential to revolutionize clinical neuroscience. Today sensing-capable electrical stimulators, known as \"bidirectional devices\", are used to acquire chronic brain activity from humans in natural environments. However, with wireless transmission come potential failures in data transmission, and not all available devices correctly account for missing data or provide precise timing for when data losses occur. Our inability to precisely reconstruct time-domain neural signals makes it difficult to apply subsequent neural signal processing techniques and analyses. Here, our goal was to accurately reconstruct time-domain neural signals impacted by data loss during wireless transmission. Towards this end, we developed a method termed Periodic Estimation of Lost Packets (PELP). PELP leverages the highly periodic nature of stimulation artifacts to precisely determine when data losses occur. Using simulated stimulation waveforms added to human EEG data, we show that PELP is robust to a range of stimulation waveforms and noise characteristics. Then, we applied PELP to local field potential (LFP) recordings collected using an implantable, bidirectional DBS platform operating at various telemetry bandwidths. By effectively accounting for the timing of missing data, PELP enables the analysis of neural time series data collected via wireless transmission-a prerequisite for better understanding the brain-behavior relationships underlying neurological and psychiatric disorders.

UNASSIGNED: Pathological anxiety is responsible for major functional impairments and resistance to conventional treatments in anxiety disorders (ADs), posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). Focal neuromodulation therapies such as transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS) and deep brain stimulation (DBS) are being developed to treat those disorders.
UNASSIGNED: We performed a dimensional systematic review and meta-analysis to assess the evidence of the efficacy of TMS, tDCS and DBS in reducing anxiety symptoms across ADs, PTSD and MDD. Reports were identified through systematic searches in PubMed/Medline, Scopus and Cochrane library (inception to November 2020), followed by review according to the PRISMA guidelines. Controlled clinical trials examining the effectiveness of brain stimulation techniques on generic anxiety symptoms in patients with ADs, PTSD or MDD were selected.
UNASSIGNED: Nineteen studies (RCTs) met inclusion criteria, which included 589 participants. Overall, focal brain activity modulation interventions were associated with greater reduction of anxiety levels than controls [SMD: -0.56 (95% CI, -0.93 to-0.20, I 2 = 77%]. Subgroup analyses revealed positive effects for TMS across disorders, and of focal neuromodulation in generalized anxiety disorder and PTSD. Rates of clinical responses and remission were higher in the active conditions. However, the risk of bias was high in most studies.
UNASSIGNED: There is moderate quality evidence for the efficacy of neuromodulation in treating pathological anxiety.
UNASSIGNED: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=233084, identifier: PROSPERO CRD42021233084. It was submitted on January 29th, 2021, and registered on March 1st, 2021. No amendment was made to the recorded protocol. A change was applied for the subgroup analyses based on target brain regions, we added the putative nature (excitatory/inhibitory) of brain activity modulation.

Neuromodulation is a key therapeutic tool for clinicians managing patients with drug-resistant epilepsy. Multiple devices are available with long-term follow-up and real-world experience. The aim of this review is to give a practical summary of available neuromodulation techniques to guide the selection of modalities, focusing on patient selection for devices, common approaches and techniques for initiation of programming, and outpatient management issues. Vagus nerve stimulation (VNS), deep brain stimulation of the anterior nucleus of the thalamus (DBS-ANT), and responsive neurostimulation (RNS) are all supported by randomized controlled trials that show safety and a significant impact on seizure reduction, as well as a suggestion of reduction in the risk of sudden unexplained death in epilepsy (SUDEP). Significant seizure reductions are observed after 3 months for DBS, RNS, and VNS in randomized controlled trials, and efficacy appears to improve with time out to 7 to 10 years of follow-up for all modalities, albeit in uncontrolled follow-up or retrospective studies. A significant number of patients experience seizure-free intervals of 6 months or more with all three modalities. Number and location of epileptogenic foci are important factors affecting efficacy, and together with comorbidities such as severe mood or sleep disorders, may influence the choice of modality. Programming has evolved-DBS is typically initiated at lower current/voltage than used in the pivotal trial, whereas target charge density is lower with RNS, however generalizable optimal parameters are yet to be defined. Noninvasive brain stimulation is an emerging stimulation modality, although it is currently not used widely. In summary, clinical practice has evolved from those established in pivotal trials. Guidance is now available for clinicians who wish to expand their approach, and choice of neuromodulation technique may be tailored to individual patients based on their epilepsy characteristics, risk tolerance, and preferences.

UNASSIGNED: The onset of the COVID-19 pandemic in March of 2020 forced a rapid pivot to telehealth and compelled a use-case experiment in specialty telehealth neurology movement disorders care. The aims of this study were to quantify the potential benefit of telehealth as an option to the Parkinson\'s disease community as shown by the first 9 months of the COVID-19 pandemic, and to quantify the potential impact of the absence of a deep brain stimulation (DBS) telehealth option on DBS patient follow-up.
UNASSIGNED: New patient visits to the Inova Parkinson\'s and Movement Disorder\'s Center from April to December 2020 (9 months) were retrospectively reviewed for telehealth vs. in-person, demographics (age, gender, race, primary insurance), chief complaint, prior movement disorders specialist (MDS) consultation, imaging tests ordered, and distance/travel time from primary zip code to clinic. Additionally, DBS programming visit volume from April to December 2020 was compared to DBS programming visit volume from April to December 2019.
UNASSIGNED: Of the 1,097 new patients seen, 85% were via telehealth (N = 932) and 15% in person (N = 165). In the telehealth cohort, 97.75% had not consulted with an MDS before (N = 911), vs. 87.9% of in-person (N = 145). Age range was 61.8 +/- 17.9 years (telehealth), 68.8 +/- 16.0 years (in-person). Racial breakdown for telehealth was 60.7% White (N = 566), 10.4% Black (N = 97), 7.4% Asian (N = 69) and 4.5% Hispanic (N = 42); in-person was 70.9% White (N = 117), 5.5% Black (N = 9), 7.9% Asian (N = 13) and 5.5% Hispanic (N = 9). Top 5 consultation reasons, top 10 primary insurance providers and imaging studies ordered between the two cohorts were similar. Distance/travel time between primary zip code and clinic were 33.8 +/- 104.8 miles and 42.2 +/- 93.4 min (telehealth) vs. 38.1 +/- 114.7 miles and 44.1 +/- 97.6 min (in-person). DBS programming visits dropped 24.8% compared to the same period the year before (254 visits to 191 visits).
UNASSIGNED: Telehealth-based new patient visits to a Movement Disorders Center appeared successful at increasing access to specialty care. The minimal difference in supporting data highlights the potential parity to in-person visits. With no telehealth option for DBS visits, a significant drop-off was seen in routine DBS management.

OBJECTIVE: Freezing of gait is detrimental to patients with idiopathic Parkinson\'s disease (PD). Its pathophysiology represents a multilevel failure of motor processing in the cortical, subcortical, and brainstem circuits, ultimately resulting in ineffective motor output of the spinal pattern generator. Electrophysiological studies pointed to abnormalities of oscillatory activity in freezers that covered a broad frequency range including the theta, alpha, and beta bands. We explored muscular frequency domain activity with respect to freezing, and used deep brain stimulation to modulate these rhythms thereby evaluating the supraspinal contributions to spinal motor neuron activity.
METHODS: We analyzed 9 PD freezers and 16 healthy controls (HC). We studied the patients after overnight withdrawal of dopaminergic medication with stimulation off, stimulation of the subthalamic nucleus (STN-DBSonly) or the substantia nigra pars reticulate (SNr-DBSonly), respectively. Patients performed a walking paradigm passing a narrow obstacle. We analyzed the frequency-domain spectra of the tibialis anterior (TA) and gastrocnemius (GA) muscles in \'regular gait\' and during the \'freezing\' episodes.
RESULTS: In stimulation off, PD freezers showed increased muscle activity of the alpha and low-beta band compared to HC in both TA and GA. This activity increase was present during straight walking and during the freezes to similar extent. STN- but not SNr-DBS decreased this activity and paralleled the clinical improvement of freezing.
CONCLUSIONS: We found increased muscle activation of the alpha and lower beta band in PD freezers compared to HC, and this was attenuated with STN-DBS. Future studies may use combined recordings of local field potentials, electroencephalography (EEG), and electromyography (EMG) to interrogate the supraspinal circuit mechanisms of the pathological activation pattern of the spinal pattern generator.

Adaptive deep brain stimulation (aDBS) is a promising new technology with increasing use in experimental trials to treat a diverse array of indications such as movement disorders (Parkinson\'s disease, essential tremor), psychiatric disorders (depression, OCD), chronic pain and epilepsy. In many aDBS trials, a neural biomarker of interest is compared with a predefined threshold and stimulation amplitude is adjusted accordingly. Across indications and implant locations, potential biomarkers are greatly influenced by sleep. Successful chronic embedded adaptive detectors must incorporate a strategy to account for sleep, to avoid unwanted or unexpected algorithm behavior. Here, we show a dual algorithm design with two independent detectors, one used to track sleep state (wake/sleep) and the other used to track parkinsonian motor state (medication-induced fluctuations). Across six hemispheres (four patients) and 47 days, our detector successfully transitioned to sleep mode while patients were sleeping, and resumed motor state tracking when patients were awake. Designing \"sleep aware\" aDBS algorithms may prove crucial for deployment of clinically effective fully embedded aDBS algorithms.