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Neuroscience studies entail the generation of massive collections of heterogeneous data (e.g. demographics, clinical records, medical images). Integration and analysis of such data in research centers is pivotal for elucidating disease mechanisms and improving clinical outcomes. However, data collection in clinics often relies on non-standardized methods, such as paper-based documentation. Moreover, diverse data types are collected in different departments hindering efficient data organization, secure sharing and compliance to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. Henceforth, in this manuscript we present a specialized data management system designed to enhance research workflows in Deep Brain Stimulation (DBS), a state-of-the-art neurosurgical procedure employed to treat symptoms of movement and psychiatric disorders. The system leverages REDCap to promote accurate data capture in hospital settings and secure sharing with research institutes, Brain Imaging Data Structure (BIDS) as image storing standard and a DBS-specific SQLite database as comprehensive data store and unified interface to all data types. A self-developed Python tool automates the data flow between these three components, ensuring their full interoperability. The proposed framework has already been successfully employed for capturing and analyzing data of 107 patients from 2 medical institutions. It effectively addresses the challenges of managing, sharing and retrieving diverse data types, fostering advancements in data quality, organization, analysis, and collaboration among medical and research institutions. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a neurodegenerative disorder that involves the loss of dopaminergic neurons, which leads to motor and non-motor symptoms that have a significant impact. The pathophysiology of PD is complex and involves environmental and genetic factors that contribute to alpha-synuclein aggregation, mitochondrial dysfunction, oxidative stress, and neuroinflammation. The current treatments of PD primarily focus on symptom management and have limitations in addressing disease progression and non-motor symptoms. Epidemiological data indicates a rise in PD cases worldwide, which highlights the need for effective treatments. Pathophysiological insights point out the involvement of various factors in PD progression, such as dopamine dysregulation, genetic mutations, oxidative stress, mitochondrial damage, alpha-synuclein aggregation, and neuroinflammation. Although current treatments, which include dopamine precursors, monoamine oxidase (MAO) inhibitors, and non-dopaminergic drugs, can alleviate motor symptoms, they are not effective in preventing disease progression or managing non-motor symptoms. Additionally, they can lead to adverse effects and become less effective over time. Novel therapeutic approaches, including cell-based therapies, gene therapies, targeted drug delivery therapies, and magnetic field therapies, are promising in improving symptom management and providing personalized treatment. Additionally, emerging therapies that target alpha-synuclein aggregation, mitochondrial dysfunction, and neuroinflammation may have potential disease-modifying effects. To sum up, for dealing with the multiple aspects of PD, there is a great need to come up with new and creative therapeutic approaches that not only relieve symptoms, but also prevent the progression of disease and non-motor symptoms. The progress made in comprehending the underlying mechanisms of PD provides optimism for developing successful treatments that can enhance the outcomes and quality of life.

Abstract Background Woodhouse-Sakati Syndrome (WSS) is a rare autosomal recessive condition caused by biallelic pathogenic variants in the DCAF17 gene, with fewer than 200 cases reported in the literature. Symptoms first emerge in middle-late adolescence with a spectrum of hypogonadal and progressive neurological features. Case presentation We present a case of WSS with no reportable T2-weighted, apparent diffusion coefficient mapping and susceptibility weighted MRI findings. This differs from cases reported in the current literature. Our patient developed abnormal movements in both legs, clumsiness of the hands, dysarthria, and swallowing difficulties. Moreover, she presented with alopecia manifesting as frontal and temporal balding, severe dystonia with painful dystonic spasms primarily in the left upper limb, as well as primary amenorrhea. She was not independently ambulatory on presentation, requiring wheelchair assistance. Genetic testing, the crucial test for a definitive diagnosis, was undertaken in Qatar and confirmed WSS. Treatment provided includes botulinum toxin injections and deep brain stimulation, providing better dystonia control, with progress in walking and strength exercises, and overall remarkable improvement. Intensive neurorehabilitation regimes were also deployed from admission, including physiotherapy, occupational therapy and speech and language therapy. Conclusion This case adds to the current literature on WSS manifestations, with all previously reported cases having positive MRI findings, unlike our case.

Abstract A large-scale biophysical network model for the isolated striatal body is developed to optimise potential intrastriatal deep brain stimulation applied to, e.g. obsessive-compulsive disorder. The model is based on modified Hodgkin–Huxley equations with small-world connectivity, while the spatial information about the positions of the neurons is taken from a detailed human atlas. The model produces neuronal spatiotemporal activity patterns segregating healthy from pathological conditions. Three biomarkers were used for the optimisation of stimulation protocols regarding stimulation frequency, amplitude and localisation: the mean activity of the entire network, the frequency spectrum of the entire network (rhythmicity) and a combination of the above two. By minimising the deviation of the aforementioned biomarkers from the normal state, we compute the optimal deep brain stimulation parameters, regarding position, amplitude and frequency. Our results suggest that in the DBS optimisation process, there is a clear trade-off between frequency synchronisation and overall network activity, which has also been observed during in vivo studies.

A large-scale biophysical network model for the isolated striatal body is developed to optimise potential intrastriatal deep brain stimulation applied to, e.g. obsessive-compulsive disorder. The model is based on modified Hodgkin–Huxley equations with small-world connectivity, while the spatial information about the positions of the neurons is taken from a detailed human atlas. The model produces neuronal spatiotemporal activity patterns segregating healthy from pathological conditions. Three biomarkers were used for the optimisation of stimulation protocols regarding stimulation frequency, amplitude and localisation: the mean activity of the entire network, the frequency spectrum of the entire network (rhythmicity) and a combination of the above two. By minimising the deviation of the aforementioned biomarkers from the normal state, we compute the optimal deep brain stimulation parameters, regarding position, amplitude and frequency. Our results suggest that in the DBS optimisation process, there is a clear trade-off between frequency synchronisation and overall network activity, which has also been observed during in vivo studies. [ABSTRACT FROM AUTHOR]

The concomitant stimulation of the subthalamic nucleus and the substantia nigra pars reticulata is a promising approach to improve treatment of refractory axial symptoms in Parkinson's disease. While dual stimulation of the subthalamic nucleus and the substantia nigra pars reticulata has previously shown beneficial effects on gait, the role of the substantia nigra, a crucial component of the basal ganglia circuitry, in cognitive functions such as attention and executive control remains underexplored. This study aimed to investigate the impact of selective substantia nigra pars reticulata stimulation on attentional performance in patients receiving standard deep brain stimulation of the subthalamic nucleus. Twelve patients with bilateral subthalamic nucleus stimulation underwent computerized assessment of attention using a simple reaction time task. Reaction times were assessed under standard stimulation of the subthalamic nucleus versus simultaneous stimulation of the subthalamic nucleus and the substantia nigra pars reticulata. The results revealed a significant improvement in reaction times during the simple reaction time task when patients received dual stimulation compared to standard stimulation. Our findings provide further evidence for the pivotal role of the substantia nigra pars reticulata in cognitive functions such as attention. Despite the limitations of the study, including a small sample size, our results suggest potential benefits of simultaneous deep brain stimulation of the subthalamic nucleus and the substantia nigra pars reticulata on attentional performance in patients with Parkinson's disease. Further research with larger cohorts is warranted to confirm these findings and better understand the underlying mechanisms. [ABSTRACT FROM AUTHOR]

Background: Subthalamic deep brain stimulation (STN‐DBS) reduces antiparkinsonian medications in Parkinson's disease (PD) compared with the preoperative state. Longitudinal and comparative studies on this effect are lacking. Objective: To compare longitudinal trajectories of antiparkinsonian medication in STN‐DBS treated patients to non‐surgically treated control patients. Methods: We collected retrospective information on antiparkinsonian medication from PD patients that underwent subthalamic DBS between 1999 and 2010 and control PD patients similar in age at onset and baseline, sex‐distribution, and comorbidities. Results: In 74 DBS patients levodopa‐equivalent daily dose (LEDD) were reduced by 33.9–56.0% in relation to the preoperative baseline over the 14‐year observational period. In 61 control patients LEDDs increased over approximately 10 years, causing a significant divergence between groups. The largest difference amongst single drug‐classes was observed for dopamine agonists. Conclusion: In PD patients, chronic STN‐DBS was associated with a lower LEDD compared with control patients over 14 years. [ABSTRACT FROM AUTHOR]

When pharmaceutical treatments for Parkinson's Disease (PD) are no longer effective, Deep Brain Stimulation (DBS) surgery, a procedure that entails the stimulation of the Subthalamic Nucleus (STN), is another treatment option. However, the success rate of this surgery heavily relies on the precise location of the STN, as well as the correct positioning of the stimulation electrode. In order to ensure the correct location, Micro-Electrode Recordings (MERs) are analyzed. During surgery, MERs capture brain signals while inserted in the brain, receiving different brain activity depending on the crossed brain area. The location of the STN is guaranteed when brain signals from MERs meet certain criteria. Nevertheless, MER signals are sensitive to various artifacts coming from machinery or other electrical equipment in the operating theater; patient activity; and electrode motion. These all lower the signal-to-noise ratio of the MER signals. MER signals are stochastic, multicomponent, transient, and non-stationary in nature, and they contain multi-unit neural activity in the form of spikes and artefacts. Thus, accurately defining that MERs are located in the STN is not an easy task. This work analyzes relevant features from MER, based on analyzing spike activity and local field signals. Six different classification algorithms are used, together with the optimal input feature selection. The algorithms are trained using supervised Leave-One-Out Cross-Validation. MER data were collected in a real scenario from 14 PD patients during DBS implantation surgery. The dataset is publicly available. The results derived from the use of this method show an accuracy of up to 100% in detecting where the MER electrode is located in the STN brain area. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a progressive neurological disorder that is typically characterized by a range of motor dysfunctions, and its impact extends beyond physical abnormalities into emotional well-being and cognitive symptoms. The loss of dopaminergic neurons in the substantia nigra pars compacta (SNc) leads to an array of dysfunctions in the functioning of the basal ganglia (BG) circuitry that manifests into PD. While active research is being carried out to find the root cause of SNc cell death, various therapeutic techniques are used to manage the symptoms of PD. The most common approach in managing the symptoms is replenishing the lost dopamine in the form of taking dopaminergic medications such as levodopa, despite its long-term complications. Another commonly used intervention for PD is deep brain stimulation (DBS). DBS is most commonly used when levodopa medication efficacy is reduced, and, in combination with levodopa medication, it helps reduce the required dosage of medication, prolonging the therapeutic effect. DBS is also a first choice option when motor complications such as dyskinesia emerge as a side effect of medication. Several studies have also reported that though DBS is found to be effective in suppressing severe motor symptoms such as tremors and rigidity, it has an adverse effect on cognitive capabilities. Henceforth, it is important to understand the exact mechanism of DBS in alleviating motor symptoms. A computational model of DBS stimulation for motor symptoms will offer great insights into understanding the mechanisms underlying DBS, and, along this line, in our current study, we modeled a cortico-basal ganglia circuitry of arm reaching, where we simulated healthy control (HC) and PD symptoms as well as the DBS effect on PD tremor and bradykinesia. Our modeling results reveal that PD tremors are more correlated with the theta band, while bradykinesia is more correlated with the beta band of the frequency spectrum of the local field potential (LFP) of the subthalamic nucleus (STN) neurons. With a DBS current of 220 pA, 130 Hz, and a 100 microsecond pulse-width, we could found the maximum therapeutic effect for the pathological dynamics simulated using our model using a set of parameter values. However, the exact DBS characteristics vary from patient to patient, and this can be further studied by exploring the model parameter space. This model can be extended to study different DBS targets and accommodate cognitive dynamics in the future to study the impact of DBS on cognitive symptoms and thereby optimize the parameters to produce optimal performance effects across modalities. Combining DBS with rehabilitation is another frontier where DBS can reduce symptoms such as tremors and rigidity, enabling patients to participate in their therapy. With DBS providing instant relief to patients, a combination of DBS and rehabilitation can enhance neural plasticity. One of the key motivations behind combining DBS with rehabilitation is to expect comparable results in motor performance even with milder DBS currents. [ABSTRACT FROM AUTHOR]

• Delayed-onset seizures after deep brain stimulation (DBS) surgery were seldom reported in previous studies. We studied 341 PD patients who underwent STN-DBS surgery from 2006 to 2021 in our department retrospectively. • Five patients experienced seizures after DBS surgery with an incidence of 1.47 %. All 5 seizures cases were characterized as delayed-onset with an average time of 12 days postoperatively, which was different from the previous studies. In the further risk factors analysis of seizures, we found that the average diameter of peri -electrode edema of patients with seizures was larger than the average diameter of patients without seizures, which indicated that peri -electrode edema was risk factor for delayed-onset seizures after DBS surgery. • Further multivariate analysis confirmed the result. Our study is the first report focusing on clinical characteristics and risk factors of delayed-onset seizures after DBS surgery based on a case series. • Although DBS related seizure is uncommon complication, patients who experienced seizures are still exposed in risks of trauma and damage to the implanted simulator. We believe that these findings were useful for prevention and management of seizures associated with DBS surgery. Delayed-onset seizures after deep brain stimulation (DBS) surgery were seldom reported. This study summarized the clinical characteristics of delayed-onset seizures after subthalamic nucleus (STN) DBS surgery for Parkinson's disease (PD) and analyzed risk factors. A single-center retrospective study containing consecutive STN-DBS PD patients from 2006 to 2021 was performed. Seizures occurred during the DBS surgery or within one month after DBS surgery were identified based on routine clinical records. Patients with postoperative magnetic resonance imaging (MRI) were included to further analyze the risk factors for postoperative seizures with univariate and multivariate statistical methods. 341 consecutive PD patients treated with bilateral STN-DBS surgery wereidentified, and five patients experienced seizures after DBS surgery with an incidence of 1.47 %. All seizures of the five cases were characterized as delayed onset with average 12 days post-operatively. All seizures presented as generalized tonic-clonic seizures and didn't recur after the first onset. In those seizures cases, peri -electrode edema was found in both hemispheres without hemorrhage and infarction. The average diameter of peri -electrode edema of patients with seizures was larger than those without seizures (3.15 ± 1.00 cm vs 1.57 ± 1.02 cm, p = 0.005). Multivariate risk factor analysis indicated that seizures were only associated with the diameter of peri -electrode edema (OR 4.144, 95 % CI 1.269–13.530, p = 0.019). Delayed-onset seizures after STN-DBS surgery in PD patients were uncommon with an incidence of 1.47 % in this study. The seizures were transient and self-limiting, with no developing into chronic epilepsy. Peri-electrode edema was a risk factor for delayed-onset seizures after DBS surgery. Patients with an average peri -electrode edema diameter > 2.70 cm had a higher risk to develop seizures. [ABSTRACT FROM AUTHOR]

Neuroscience studies entail the generation of massive collections of heterogeneous data (e.g. demographics, clinical records, medical images). Integration and analysis of such data in research centers is pivotal for elucidating disease mechanisms and improving clinical outcomes. However, data collection in clinics often relies on non-standardized methods, such as paper-based documentation. Moreover, diverse data types are collected in different departments hindering efficient data organization, secure sharing and compliance to the FAIR (Findable, Accessible, Interoperable, Reusable) principles. Henceforth, in this manuscript we present a specialized data management system designed to enhance research workflows in Deep Brain Stimulation (DBS), a state-of-the-art neurosurgical procedure employed to treat symptoms of movement and psychiatric disorders. The system leverages REDCap to promote accurate data capture in hospital settings and secure sharing with research institutes, Brain Imaging Data Structure (BIDS) as image storing standard and a DBS-specific SQLite database as comprehensive data store and unified interface to all data types. A self-developed Python tool automates the data flow between these three components, ensuring their full interoperability. The proposed framework has already been successfully employed for capturing and analyzing data of 107 patients from 2 medical institutions. It effectively addresses the challenges of managing, sharing and retrieving diverse data types, fostering advancements in data quality, organization, analysis, and collaboration among medical and research institutions.

This educational review article aims to discuss growing evidence from PET studies in the diagnosis and treatment of depression. PET has been used in depression to explore the neurotransmitters involved, the alterations in neuroreceptors, non-neuroreceptor targets (e.g., microglia and astrocytes), the severity and duration of the disease, the pharmacodynamics of various antidepressants, and neurobiological mechanisms of non-pharmacological therapies like psychotherapy, electroconvulsive therapy, and deep brain stimulation therapy, by showing changes in brainmetabolismand receptor and non-receptor targets. Studies have revealed alterations in neurotransmitter systems such as serotonin, dopamine, GABA, and glutamate, which are linked to the pathophysiology of depression. Overall, PET imaging has furthered the neurobiological understanding of depression. Despite these advancements, PET findings have not yet led to significant changes in evidence-based practices. Addressing the reasons behind inconsistencies in PET imaging results, conducting large sample size studies with a more standardized methodological approach, and investigating further the genetic and neurobiological aspects of depression may better leverage PET imaging in future studies. [ABSTRACT FROM AUTHOR]

The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9--11, 2023 in Gainesville, Florida with the theme of "Pushing the Forefront of Neuromodulation". The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic DBS. The DBS Think Tank was founded in 2012 and provides an open platformwhere clinicians, engineers, and researchers (from industry and academia) can freely discuss current and emerging DBS technologies, as well as logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a common degenerative neurological disorder, characterized by static tremor, bradykinesia, myotonia and postural abnormalities. Dopaminergic drugs are the main drugs in the treatment of PD, but long-term use will lead to drug efficacy loss, and even cause some adverse reactions such as dyskinesia and "on-off" phenomenon. Neuromodulation is a kind of biomedical engineering technology that can stimulate or inhibit the activity of brain neurons and regulate the changes of neuroplasticity by means of electric energy, magnetic field, ultrasound and other methods, so as to achieve treatment and improvement of diseases. In the non-drug treatment of PD, neuromodulation, as a new therapeutic means, has shown good efficacy, and has the advantages of small adverse reactions and easy tolerance. Based on this, this article reviews the research progress of several common neuromodulation in PD, including deep brain stimulation, transcranial magnetic stimulation, transcranial direct current stimulation and transcranial focused ultrasound.

Brain-computer interfaces (BCIs) provide a communication interface between the brain and external devices and have the potential to restore communication and control in patients with neurological injury or disease. For the invasive BCIs, most studies recruited participants from hospitals requiring invasive device implantation. Three widely used clinical invasive devices that have the potential for BCIs applications include surface electrodes used in electrocorticography (ECoG) and depth electrodes used in Stereo-electroencephalography (SEEG) and deep brain stimulation (DBS). This review focused on BCIs research using surface (ECoG) and depth electrodes (including SEEG, and DBS electrodes) for movement decoding on human subjects. Unlike previous reviews, the findings presented here are from the perspective of the decoding target or task. In detail, five tasks will be considered, consisting of the kinematic decoding, kinetic decoding,identification of body parts, dexterous hand decoding, and motion intention decoding. The typical studies are surveyed and analyzed. The reviewed literature demonstrated a distributed motor-related network that spanned multiple brain regions. Comparison between surface and depth studies demonstrated that richer information can be obtained using surface electrodes. With regard to the decoding algorithms, deep learning exhibited superior performance using raw signals than traditional machine learning algorithms. Despite the promising achievement made by the open-loop BCIs, closed-loop BCIs with sensory feedback are still in their early stage, and the chronic implantation of both ECoG surface and depth electrodes has not been thoroughly evaluated.

Background: Additional stimulation of the substantia nigra (SNr) has been proposed to target axial symptoms and gait impairment in patients with Parkinson's disease (PD). Objective: This study aimed to characterize effects of combined deep brain stimulation (DBS) of the subthalamic nucleus (STN) and SNr on gait performance in PD and to map stimulation sites within the SNr. Methods: In a double-blinded crossover design, 10 patients with PD and gait impairment underwent clinical examination and kinematic assessment with STN DBS, combined STN+SNr DBS and OFF DBS 30 minutes after reprogramming. To confirm stimulation within the SNr, electrodes, active contacts, and stimulation volumes were modeled in a common space and overlap with atlases of SNr was computed. Results: Overlap of stimulation volumes with dorsolateral SNr was confirmed for all patients. UPDRS III, scoring of freezing during turning and transitioning, stride length, stride velocity, and range of motion of shank, knee, arm, and trunk as well as peak velocities during turning and transitions and turn duration were improved with STN DBS compared to OFF. On cohort level, no further improvement was observed with combined STN+SNr DBS but additive improvement of spatiotemporal gait parameters was observed in individual subjects. Conclusions: Combined high frequency DBS of the STN and dorsolateral SNr did not consistently result in additional short-term kinematic or clinical benefit compared to STN DBS. Stimulation intervals, frequency, and patient selection for target symptoms as well as target region within the SNr need further refinement in future trials. [ABSTRACT FROM AUTHOR]

Background: Transcutaneous vagus nerve stimulation (VNS) showed early evidence of efficacy for the gait treatment of Parkinson's disease (PD). Objectives: Providing data on neurophysiological and clinical effects of transauricular VNS (taVNS). Methods: Ten patients with recording deep brain stimulation (DBS) have been enrolled in a within participant design pilot study, double‐blind crossover sham‐controlled trial of taVNS. Subthalamic local field potentials (β band power), Unified Parkinson's Disease Rating Scales (UPDRS), and a digital timed‐up‐and‐go test (TUG) were measured and compared with real versus sham taVNS during medication‐off/DBS‐OFF condition. Results: The left taVNS induced a reduction of the total β power in the contralateral (ie, right) subthalamic nucleus and an improvement of TUG time, speed, and variability. The taVNS‐induced β reduction correlated with the improvement of gait speed. No major clinical changes were observed at UPDRS. Conclusions: taVNS is a promising strategy for the management of PD gait, deserving prospective trials of chronic neuromodulation. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a common degenerative neurological disorder, characterized by static tremor, hradykinesia, myotonia and postural abnormalities. Dopaminergic drugs are the main drugs in the treatment of PD, but long-term use will lead to drug efficacy loss, and even cause some adverse reactions such as dyskinesia and "on-off phenomenon. Neuromodulation is a kind of biomedical engineering technology that can stimulate or inhibit the activity of brain neurons and regulate the changes of neuroplasticity by means of electric energy, magnetic field, ultrasound and other methods, so as to achieve treatment and improvement of diseases. In the non-drug treatment of PD, neuromodulation, as a new therapeutic means, has shown good efficacy, and has the advantages of small adverse reactions and casy tolerance. Based on this, this article reviews the research progress of several common neuromodulation in PD, including deep brain stimulation, transcranial magnetic stimulation, transcranial direct current stimulation and transcranial focused ultrasound. [ABSTRACT FROM AUTHOR]

Prefrontal circuits in the human brain play an important role in cognitive and affective processing. Neuromodulation therapies delivered to certain key hubs within these circuits are being used with increasing frequency to treat a host of neuropsychiatric disorders. However, the detailed neurophysiological effects of stimulation to these hubs are largely unknown. Here, we performed intracranial recordings across prefrontal networks while delivering electrical stimulation to two well-established white matter hubs involved in cognitive regulation and depression: the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS). We demonstrate a shared frontotemporal circuit consisting of the ventromedial prefrontal cortex, amygdala, and lateral orbitofrontal cortex where gamma oscillations are differentially modulated by stimulation target. Additionally, we found participant-specific responses to stimulation in the dorsal anterior cingulate cortex and demonstrate the capacity for further tuning of neural activity using current-steered stimulation. Our findings indicate a potential neurophysiological mechanism for the dissociable therapeutic effects seen across the SCC and VC/VS targets for psychiatric neuromodulation and our results lay the groundwork for personalized, network-guided neurostimulation therapy. [ABSTRACT FROM AUTHOR]

Introduction: Deep brain stimulation (DBS) is utilized to treat pediatric refractory dystonia and its use in pediatric patients is expected to grow. One important question concerns the impact of hope and unrealistic optimism on decision-making, especially in "last resort" intervention scenarios such as DBS for refractory conditions. Objective: This study examined stakeholder experiences and perspectives on hope and unrealistic optimism in the context of decision-making about DBS for childhood dystonia and provides insights for clinicians seeking to implement effective communication strategies. Materials and Methods: Semi-structured interviews with clinicians (n = 29) and caregivers (n = 44) were conducted, transcribed, and coded. Results: Using thematic content analysis, four major themes from clinician interviews and five major themes from caregiver interviews related to hopes and expectations were identified. Clinicians expressed concerns about caregiver false hopes (86%, 25/29) and desperation (68.9%, 20/29) in light of DBS being a last resort. As a result, 68.9% of clinicians (20/29) expressed that they intentionally tried to lower caregiver expectations about DBS outcomes. Clinicians also expressed concern that, on the flip side, unrealistic pessimism drives away some patients who might otherwise benefit from DBS (34.5%, 10/29). Caregivers viewed DBS as the last option that they had to try (61.3%, 27/44), and 73% of caregivers (32/44) viewed themselves as having high hopes but reasonable expectations. Fewer than half (43%, 19/44) expressed that they struggled setting outcome expectations due to the uncertainty of DBS, and 50% of post-DBS caregivers (14/28) expressed some negative feelings post treatment due to unmet expectations. 43% of caregivers (19/44) had experiences with clinicians who tried to set low expectations about the potential benefits of DBS. Conclusion: Thoughtful clinician-stakeholder discussion is needed to ensure realistic outcome expectations. [ABSTRACT FROM AUTHOR]

Background: Deep brain stimulation (DBS) in the centromedian-parafascicular complex (CM-pf) has been reported as a potential therapeutic option for disorders of consciousness (DoC). However, the lack of understanding of its electrophysiological characteristics limits the improvement of therapeutic effect. Objective: To investigate the CM-pf electrophysiological characteristics underlying disorders of consciousness (DoC) and its recovery. Methods: We collected the CM-pf electrophysiological signals from 23 DoC patients who underwent central thalamus DBS (CT-DBS) surgery. Five typical electrophysiological features were extracted, including neuronal firing properties, multiunit activity (MUA) properties, signal stability, spike-MUA synchronization strength (syncMUA), and the background noise level. Their correlations with the consciousness level, the outcome, and the primary clinical factors of DoC were analyzed. Results: 11 out of 23 patients (0/2 chronic coma, 5/13 unresponsive wakefulness syndrome/vegetative state (UWS/VS), 6/8 minimally conscious state minus (MCS-)) exhibited an improvement in the level of consciousness after CT-DBS. In CM-pf, significantly stronger gamma band syncMUA strength and alpha band normalized MUA power were found in MCS- patients. In addition, higher firing rates, stronger high-gamma band MUA power and alpha band normalized power, and more stable theta oscillation were correlated with better outcomes. Besides, we also identified electrophysiological properties that are correlated with clinical factors, including etiologies, age, and duration of DoC. Conclusion: We provide comprehensive analyses of the electrophysiological characteristics of CM-pf in DoC patients. Our results support the ‘mesocircuit’ hypothesis, one proposed mechanism of DoC recovery, and reveal CM-pf electrophysiological features that are crucial for understanding the pathogenesis of DoC, predicting its recovery, and explaining the effect of clinical factors on DoC.

Due to the prevalence of chronic pain worldwide, there is an urgent need to improve pain management strategies. While opioid drugs have long been used to treat chronic pain, their use is severely limited by adverse effects and abuse liability. Neurostimulation techniques have emerged as a promising option for chronic pain that is refractory to other treatments. While different neurostimulation strategies have been applied to many neural structures implicated in pain processing, there is variability in efficacy between patients, underscoring the need to optimize neurostimulation techniques for use in pain management. This optimization requires a deeper understanding of the mechanisms underlying neurostimulation-induced pain relief. Here, we discuss the most commonly used neurostimulation techniques for treating chronic pain. We present evidence that neurostimulation-induced analgesia is in part driven by the release of endogenous opioids and that this endogenous opioid release is a common endpoint between different methods of neurostimulation. Finally, we introduce technological and clinical innovations that are being explored to optimize neurostimulation techniques for the treatment of pain, including multidisciplinary efforts between neuroscience research and clinical treatment that may refine the efficacy of neurostimulation based on its underlying mechanisms.

When pharmaceutical treatments for Parkinson’s Disease (PD) are no longer effective, Deep Brain Stimulation (DBS) surgery, a procedure that entails the stimulation of the Subthalamic Nucleus (STN), is another treatment option. However, the success rate of this surgery heavily relies on the precise location of the STN, as well as the correct positioning of the stimulation electrode. In order to ensure the correct location, Micro-Electrode Recordings (MERs) are analyzed. During surgery, MERs capture brain signals while inserted in the brain, receiving different brain activity depending on the crossed brain area. The location of the STN is guaranteed when brain signals from MERs meet certain criteria. Nevertheless, MER signals are sensitive to various artifacts coming from machinery or other electrical equipment in the operating theater; patient activity; and electrode motion. These all lower the signal-to-noise ratio of the MER signals. MER signals are stochastic, multicomponent, transient, and non-stationary in nature, and they contain multi-unit neural activity in the form of spikes and artefacts. Thus, accurately defining that MERs are located in the STN is not an easy task. This work analyzes relevant features from MER, based on analyzing spike activity and local field signals. Six different classification algorithms are used, together with the optimal input feature selection. The algorithms are trained using supervised Leave-One-Out Cross-Validation. MER data were collected in a real scenario from 14 PD patients during DBS implantation surgery. The dataset is publicly available. The results derived from the use of this method show an accuracy of up to 100% in detecting where the MER electrode is located in the STN brain area.

Parkinson’s disease (PD) is a progressive neurological disorder that is typically characterized by a range of motor dysfunctions, and its impact extends beyond physical abnormalities into emotional well-being and cognitive symptoms. The loss of dopaminergic neurons in the substantia nigra pars compacta (SNc) leads to an array of dysfunctions in the functioning of the basal ganglia (BG) circuitry that manifests into PD. While active research is being carried out to find the root cause of SNc cell death, various therapeutic techniques are used to manage the symptoms of PD. The most common approach in managing the symptoms is replenishing the lost dopamine in the form of taking dopaminergic medications such as levodopa, despite its long-term complications. Another commonly used intervention for PD is deep brain stimulation (DBS). DBS is most commonly used when levodopa medication efficacy is reduced, and, in combination with levodopa medication, it helps reduce the required dosage of medication, prolonging the therapeutic effect. DBS is also a first choice option when motor complications such as dyskinesia emerge as a side effect of medication. Several studies have also reported that though DBS is found to be effective in suppressing severe motor symptoms such as tremors and rigidity, it has an adverse effect on cognitive capabilities. Henceforth, it is important to understand the exact mechanism of DBS in alleviating motor symptoms. A computational model of DBS stimulation for motor symptoms will offer great insights into understanding the mechanisms underlying DBS, and, along this line, in our current study, we modeled a cortico-basal ganglia circuitry of arm reaching, where we simulated healthy control (HC) and PD symptoms as well as the DBS effect on PD tremor and bradykinesia. Our modeling results reveal that PD tremors are more correlated with the theta band, while bradykinesia is more correlated with the beta band of the frequency spectrum of the local field potential (LFP) of the subthalamic nucleus (STN) neurons. With a DBS current of 220 pA, 130 Hz, and a 100 microsecond pulse-width, we could found the maximum therapeutic effect for the pathological dynamics simulated using our model using a set of parameter values. However, the exact DBS characteristics vary from patient to patient, and this can be further studied by exploring the model parameter space. This model can be extended to study different DBS targets and accommodate cognitive dynamics in the future to study the impact of DBS on cognitive symptoms and thereby optimize the parameters to produce optimal performance effects across modalities. Combining DBS with rehabilitation is another frontier where DBS can reduce symptoms such as tremors and rigidity, enabling patients to participate in their therapy. With DBS providing instant relief to patients, a combination of DBS and rehabilitation can enhance neural plasticity. One of the key motivations behind combining DBS with rehabilitation is to expect comparable results in motor performance even with milder DBS currents.

The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9–11, 2023 in Gainesville, Florida with the theme of “Pushing the Forefront of Neuromodulation”. The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic 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 logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices.

Prefrontal circuits in the human brain play an important role in cognitive and affective processing. Neuromodulation therapies delivered to certain key hubs within these circuits are being used with increasing frequency to treat a host of neuropsychiatric disorders. However, the detailed neurophysiological effects of stimulation to these hubs are largely unknown. Here, we performed intracranial recordings across prefrontal networks while delivering electrical stimulation to two well-established white matter hubs involved in cognitive regulation and depression: the subcallosal cingulate (SCC) and ventral capsule/ventral striatum (VC/VS). We demonstrate a shared frontotemporal circuit consisting of the ventromedial prefrontal cortex, amygdala, and lateral orbitofrontal cortex where gamma oscillations are differentially modulated by stimulation target. Additionally, we found participant-specific responses to stimulation in the dorsal anterior cingulate cortex and demonstrate the capacity for further tuning of neural activity using current-steered stimulation. Our findings indicate a potential neurophysiological mechanism for the dissociable therapeutic effects seen across the SCC and VC/VS targets for psychiatric neuromodulation and our results lay the groundwork for personalized, network-guided neurostimulation therapy.

Objective: Spinocerebellar ataxia type 3 (SCA3), also known as Machado-Joseph disease (MJD), is a rare neurodegenerative disease for which there is no specific treatment. Very few cases have been treated with single-target deep brain stimulation (DBS), and the results were not satisfactory. We applied multi-target DBS to an SCA3/MJD patient and performed positron emission computed tomography (PET) before and after DBS to explore the short-term clinical therapeutic effect. Materials andmethods: A 26-year-old right-hand-dominant female with a family history of SCA3/MJD suffered from cerebellar ataxia and dystonia. Genetic testing indicated an expanded CAGtrinucleotide repeat in the ATXN3 gene and a diagnosis of SCA3/MJD. Conservative treatment had no obvious effect; therefore, leads were implanted in the bilateral dentate nucleus (DN) and the globus pallidus internus (GPi) and connected to an external stimulation device. The treatment effect was evaluated in a double-blind, randomized protocol in five phases (over a total of 15 days): no stimulation, GPi, DN, or sham stimulation, and combined GPi and DN stimulation. 18F-fluoro-2-deoxy-d-glucose and dopamine transporter PET, Scale for the Assessment and Rating of Ataxia, Fahn-Tolosa-Marin Clinical Rating Scale for Tremor (FTM), Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS), and SF-36 quality of life scores were compared before and after DBS. Results: The Total Scale for the Assessment and Rating of Ataxia scores improved by ~42% (from 24 to 14). The BFMDRS movement scores improved by ~30% (from 40.5 to 28.5). The BFMDRS disability scores improved by ~12.5% (from 16 to 14). Daily living activities were not noticeably improved. Compared with the findings in pre-DBS imaging, 18F-fluoro-2-deoxy-d-glucose uptake increased in the cerebellum, while according to dopamine transporter imaging, there were no significant differences in the bilateral caudate nucleus and putamen. Conclusion: Multi-target acute stimulation (DN DBS and GPi DBS) in SCA3/MJD can mildly improve cerebellar ataxia and dystonia and increase cerebellar metabolism. [ABSTRACT FROM AUTHOR]

Cerebrotendinous xanthomatosis (CTX) is a rare autosomal recessive disorder caused by a deficiency of the sterol 27-hydroxylase enzyme. This deficiency results in excess production and accumulation of cholestanol, which can lead to many clinical findings within the first three decades of life, including progressive neurological dysfunction. This is a treatable condition with improvements in neurological and non-neurological symptoms upon the early initiation of replacement therapy. This case report details a 42 years-old left-handed male in whom deep brain stimulation (DBS) intervention was pursued due to a limiting tremor related to delayed diagnosis and treatment of CTX at 22 years old. The application of DBS in treating tremors in a CTX patient has not previously been reported. For our patient, application of DBS led to meaningful and longstanding tremor control benefits that have required minimal changes to stimulation parameters post-DBS. These improvements to tremor were achieved without negative impact to his other CTX related comorbidities. [ABSTRACT FROM AUTHOR]

Deep brain stimulation (DBS) in the centromedian-parafascicular complex (CM-pf) has been reported as a potential therapeutic option for disorders of consciousness (DoC). However, the lack of understanding of its electrophysiological characteristics limits the improvement of therapeutic effect. To investigate the CM-pf electrophysiological characteristics underlying disorders of consciousness (DoC) and its recovery. We collected the CM-pf electrophysiological signals from 23 DoC patients who underwent central thalamus DBS (CT-DBS) surgery. Five typical electrophysiological features were extracted, including neuronal firing properties, multiunit activity (MUA) properties, signal stability, spike-MUA synchronization strength (syncMUA), and the background noise level. Their correlations with the consciousness level, the outcome, and the primary clinical factors of DoC were analyzed. 11 out of 23 patients (0/2 chronic coma, 5/13 unresponsive wakefulness syndrome/vegetative state (UWS/VS), 6/8 minimally conscious state minus (MCS-)) exhibited an improvement in the level of consciousness after CT-DBS. In CM-pf, significantly stronger gamma band syncMUA strength and alpha band normalized MUA power were found in MCS- patients. In addition, higher firing rates, stronger high-gamma band MUA power and alpha band normalized power, and more stable theta oscillation were correlated with better outcomes. Besides, we also identified electrophysiological properties that are correlated with clinical factors, including etiologies, age, and duration of DoC. We provide comprehensive analyses of the electrophysiological characteristics of CM-pf in DoC patients. Our results support the 'mesocircuit' hypothesis, one proposed mechanism of DoC recovery, and reveal CM-pf electrophysiological features that are crucial for understanding the pathogenesis of DoC, predicting its recovery, and explaining the effect of clinical factors on DoC. [Display omitted] • Electrophysiological features related to diagnosis and outcome of DoC were found in CM-pf. • Provide additional electrophysiological evidence of CM-pf for the 'mesocircuit' hypothesis of DoC. • CM-pf electrophysiology helps explain the effect of clinical factors on DoC recovery. [ABSTRACT FROM AUTHOR]

Objective.Despite advances in the treatment of psychiatric diseases, currently available therapies do not provide sufficient and durable relief for as many as 30–40% of patients. Neuromodulation, including deep brain stimulation (DBS), has emerged as a potential therapy for persistent disabling disease, however it has not yet gained widespread adoption. In 2016, the American Society for Stereotactic and Functional Neurosurgery (ASSFN) convened a meeting with leaders in the field to discuss a roadmap for the path forward. A follow-up meeting in 2022 aimed to review the current state of the field and to identify critical barriers and milestones for progress.Design.The ASSFN convened a meeting on June 3, 2022 in Atlanta, Georgia and included leaders from the fields of neurology, neurosurgery, and psychiatry along with colleagues from industry, government, ethics, and law. The goal was to review the current state of the field, assess for advances or setbacks in the interim six years, and suggest a future path forward. The participants focused on five areas of interest: interdisciplinary engagement, regulatory pathways and trial design, disease biomarkers, ethics of psychiatric surgery, and resource allocation/prioritization. The proceedings are summarized here.Conclusion.The field of surgical psychiatry has made significant progress since our last expert meeting. Although weakness and threats to the development of novel surgical therapies exist, the identified strengths and opportunities promise to move the field through methodically rigorous and biologically-based approaches. The experts agree that ethics, law, patient engagement, and multidisciplinary teams will be critical to any potential growth in this area.

Introduction: Deep brain stimulation (DBS) studies in Parkinson's Disease (PD) targeting the subthalamic nucleus (STN) have characterized its spectral properties across cognitive processes. In emotional evaluation tasks, specific alpha frequency (8-12Hz) event-related de-synchronization (ERD) (reduced power) has been demonstrated. The time-locked stimulation of STN relative to stimuli onset has shown subjective positive valence shifts with 10Hz but not with 130Hz. However, neurophysiological effects of stimulation on power modulation have not been investigated. We aim to investigate effects of acute stimulation of the right STN on concurrent power modulation in the contralateral STN and frontal scalp EEG. Fromour previous study, we had a strong a priori hypothesis that negative imagery without stimulation would be associated with alpha ERD; negative imagery with 130Hz stimulation would be also associated with alpha ERD given the lack of its effect on subjective valence ratings; negative imagery with 10Hz stimulation was to be associated with enhanced alpha power given the shift in behavioral valence ratings. Methods: Twenty-four subjects with STN DBS underwent emotional picture-viewing tasks comprising neutral and negative pictures. In a subset of these subjects, the negative images were associated with time-locked acute stimulation at either 10 or 130Hz. Power of signals was estimated relative to the baseline and subjected to non-parametric statistical testing. Results: As hypothesized, in 130Hz stimulation condition, we show a decrease in alpha power to negative vs. neutral images irrespective of stimulation. In contrast, this alpha power decrease was no longer evident in the negative 10Hz stimulation condition consistent with a predicted increase in alpha power. Greater beta power in the 10Hz stimulation condition along with correlations between beta power across the 10Hz stimulation and unstimulated conditions suggest physiological and cognitive generalization effects. Conclusion: Acute alpha-specific frequency stimulation presumably was associated with a loss of this expected decrease or desynchronization in alpha power to negative images suggesting the capacity to facilitate the synchronization of alpha and enhance power. Acute time-locked stimulation has the potential to provide causal insights into the spectral frequencies and temporal dynamics of emotional processing. [ABSTRACT FROM AUTHOR]

Deep brain stimulation is a device-based neurosurgical technological method built into a well-known treatment distinctively and specifically for Parkinson's Disease movement-disorders. Its basic function is to reduce motor symptoms and restore the motor functioning. However, the insertion of small microelectrode in STN of the brain is a complicated-mission. Embedding microsensors (microelectrodes) and encoding the DBS devices are challenging and primly quantified significant factors for the end-results/clinical-outcome. This study presents the latest in science – the Parkinson's research and emphasizes the significance of the enveloping and all-encompassing well-known net works coupled with precisely DBS reaching targets. DBS also gives a unique-opportunity to study the electrical-activity (i.e., oscillating neural-activity) of various sub-cortical-structures in Parkinson's brain. Progressing the objective of anatomical–structural and, also functional-net works engrossed in the invention of pathological–neural–activity shall resolve and improve the clinical-outcome with DBS and lower the dyskinesia's. The study also experimentally investigates over the latest discovery on target sub-cortical-structures and targeting-methods, and presents the thorough and meticulous innovative technologies and inventive mechanisms which props up encoding DBS techniques and gears-up choosing the parameters expectations in built bio-feedback-signals, i.e., biomarkers and local-field-potentials incorporated in DBS which are now defined to as adaptive closed-loop DBS systems. These scientific advances are focused for achieving to the prevention of cardinal-motoric-features by the least/likely dyskinesia's. Enhancing the targeting of anatomical–structural and functional networks involved in the computationally generation of pathological neuronal and neural-activity will progress the DBS-effect clinically and prognostically and edge the dyskinesia's and dysarthria's (adverse-effects). [ABSTRACT FROM AUTHOR]

Deep brain stimulation (DBS) and functional-neurosurgery has been driven by frontier technological innovations has evolved since 1993, plus a new line to surgical targeting, estimate and in the relief-of-therapy at the target. In spite of right targeting and precise point of DBS electrode, efficient coding and encoding (the programming) is vital for a successful-outcome. A precise point-of-electrode (PoE) in the target-region and the effectual-coding of DBS devices are considered the most significant-factors for the effective outcome. Unlike in usual computer programming, in the open-loop DBS-devices, the encoding is cumbersome due to its manual process without any automatic compilation and/or execution especially for standard parameters-setting. Present approach entails use of broad rules connecting tenacity-of-electrode technical specification/configuration, type, battery corroboration and impedance-test. However, the protocol in connection with coding is not established well. This study presents the modern-management and some current-trends in DBS-encoding which includes directional-steering-of-current, fractionated current, interleaving, and the use of new impulse-generators. These scientific advances are paying attention on attaining to the prevention of cardinal features by the least dyskinesia's. Current research on PD subjects emphasizes the significancy of wide spread networks coupled to precise-DBS-targets. Enhancing the targeting of anatomical—structural and functional net-works involved in the computationally generation of pathological neuronal and neural-activity will progress the DBS-effect clinically/prognostically and get rid of the dyskinesia's. Study also discusses the technicalities on target-structures, targeting-strategies in DBS, and presents a comprehensive outline of frontier-technologies which will support DBS-coding/encoding and choosing-parameters in the prospect, following linked biofeedback-signals closed-loop adaptive deep-brain-stimulus devices. [ABSTRACT FROM AUTHOR]

Background: Pharmacotherapy and psychotherapeutic approaches are still the mainstay first line of treatment for substance use disorder. However, the path to rehabilitation and cessation of dependence often proves uncertain and laborious, with risks of relapse being considerable despite exposure to current therapeutic modalities. For cases of treatment‐refractory addiction, deep brain stimulation (DBS) interventions can prove a more effective long term therapeutic solution for the patient. Objectives: The aim of the study will be to systematically assess whether attempts at correcting substance use disorder via DBS neurosurgical interventions have been successful in inducing remission or ameliorating relapse rates. Methods: The current study will analyze available literature from database inception up to 15th April 2023, reviewing all publications documenting results achieved with human patients undergoing DBS for substance use disorder in PubMed, Ovid, Cochrane, and Web of Science. The electronic database search will exclude animal studies in the field and focus solely on the application of DBS for the purposes of addressing addiction disorders. Results: The expectation is for a reduced number of trial results to have been reported, namely due to the relatively recent application of DBS to address severe addiction. Nonetheless, numbers should be in sufficient amount to inform about the efficacy of the intervention. Conclusion: This study will attempt to demonstrate the viability of DBS as a solution for tackling treatment‐refractory substance use disorder, proposing it as a valid therapeutic option that can deliver robust results and help combat an expanding societal plague that is drug dependence. [ABSTRACT FROM AUTHOR]

Background: New-onset refractory status epilepticus (NORSE) and its subset of febrile infection-related epilepsy syndrome (FIRES) are devastating clinical presentations with high rates of mortality and morbidity. The recently published consensus on the treatment of these conditions includes anesthetics, antiseizure drugs, antivirals, antibiotics, and immune therapies. Despite the internationally accepted treatment, the outcome remains poor for a significant percentage of patients. Methods: We conducted a systematic review of the use of neuromodulation techniques in the treatment of the acute phase of NORSE/FIRES using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Results: Our search strategy brought up 74 articles of which 15 met our inclusion criteria. A total of 20 patients were treated with neuromodulation. Thirteen cases represented FIRES and in 17 cases the NORSE remained cryptogenic. Ten had electroconvulsive therapy (ECT), seven had vagal nerve stimulation (VNS), and four had deep brain stimulation (DBS); one patient had initially VNS and later DBS. Eight patients were female and nine were children. In 17 out of 20 patients, the status epilepticus was resolved after neuromodulation, while three patients died. Conclusion: NORSE can have a catastrophic course and the first treatment goal should be the fastest possible termination of status epilepticus. The data presented are limited by the small number of published cases and the variability of neuromodulation protocols used. However, they show some potential clinical benefits of early neuromodulation therapy, suggesting that these techniques could be considered within the course of FIRES/NORSE. [ABSTRACT FROM AUTHOR]

Introduction: Decoding brain states from subcortical local field potentials (LFPs) indicative of activities such as voluntary movement, tremor, or sleep stages, holds significant potential in treating neurodegenerative disorders and offers new paradigms in brain-computer interface (BCI). Identified states can serve as control signals in coupled human-machine systems, e.g., to regulate deep brain stimulation (DBS) therapy or control prosthetic limbs. However, the behavior, performance, and efficiency of LFP decoders depend on an array of design and calibration settings encapsulated into a single set of hyper-parameters. Although methods exist to tune hyper-parameters automatically, decoders are typically found through exhaustive trial-and-error, manual search, and intuitive experience. Methods: This study introduces a Bayesian optimization (BO) approach to hyper-parameter tuning, applicable through feature extraction, channel selection, classification, and stage transition stages of the entire decoding pipeline. The optimization method is compared with five real-time feature extraction methods paired with four classifiers to decode voluntary movement asynchronously based on LFPs recorded with DBS electrodes implanted in the subthalamic nucleus of Parkinson’s disease patients. Results: Detection performance, measured as the geometric mean between classifier specificity and sensitivity, is automatically optimized. BO demonstrates improved decoding performance from initial parameter setting across all methods. The best decoders achieve a maximum performance of 0.74 ± 0.06 (mean ± SD across all participants) sensitivity-specificity geometric mean. In addition, parameter relevance is determined using the BO surrogate models. Discussion: Hyper-parameters tend to be sub-optimally fixed across different users rather than individually adjusted or even specifically set for a decoding task. The relevance of each parameter to the optimization problem and comparisons between algorithms can also be difficult to track with the evolution of the decoding problem. We believe that the proposed decoding pipeline and BO approach is a promising solution to such challenges surrounding hyper-parameter tuning and that the study’s findings can inform future design iterations of neural decoders for adaptive DBS and BCI. [ABSTRACT FROM AUTHOR]