Deep Brain Stimulation Techniques Research Articles

Neuromodulation with Ultrasound: Hypotheses on the Directionality of Effects and a Community Resource.

Low-intensity Transcranial Ultrasound Stimulation (TUS) is a promising non-invasive technique for deep-brain stimulation and focal neuromodulation. Research with animal models and computational modelling has raised the possibility that TUS can be biased towards enhancing or suppressing neural function. Here, we first conduct a systematic review of human TUS studies for perturbing neural function and alleviating brain disorders. We then collate a set of hypotheses on the directionality of TUS effects and conduct an initial meta-analysis on the human TUS study reported outcomes to date (n = 32 studies, 37 experiments). We find that parameters such as the duty cycle show some predictability regarding whether the targeted area's function is likely to be enhanced or suppressed. Given that human TUS sample sizes are exponentially increasing, we recognize that results can stabilize or change as further studies are reported. Therefore, we conclude by establishing an Iowa-Newcastle (inTUS) resource for the systematic reporting of TUS parameters and outcomes to support further hypothesis testing for greater precision in brain stimulation and neuromodulation with TUS.

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills.

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. In particular, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, we exploited a recently developed non-invasive deep brain stimulation technique called transcranial temporal interference stimulation (tTIS) during reinforcement motor learning with concurrent neuroimaging, in a randomized, sham-controlled, double-blind study. Striatal tTIS applied at 80 Hz, but not at 20 Hz, abolished the benefits of reinforcement on motor learning. This effect was related to a selective modulation of neural activity within the striatum. Moreover, 80 Hz, but not 20 Hz, tTIS increased the neuromodulatory influence of the striatum on frontal areas involved in reinforcement motor learning. These results show that tTIS can non-invasively and selectively modulate a striatal mechanism involved in reinforcement learning, expanding our tools for the study of causal relationships between deep brain structures and human behaviour.

CLINICAL AND SURGICAL APPROACH TO EPILEPSY REFRACTORY

Refractory epilepsy is characterized by the persistence of epileptic seizures even after adequate use of at least two antiepileptic drugs. This condition represents a significant challenge in the treatment of epilepsy, requiring a more assertive clinical and, in some cases, surgical approach. This study aims to review and explore the clinical and surgical approach to refractory epilepsy, highlighting the available treatment options, indications, benefits and challenges faced by patients and health professionals. This is a bibliographic review, using qualitative premises, with the PubMed, Scopus, Web of Science and Scielo databases. To better refine the research, the health descriptors “epilepsy”, “surgical treatment”, “neurostimulation” and “refractory epilepsy” were used. The clinical approach to refractory epilepsy involves careful assessment of the patient, including a detailed clinical history, complete physical examination and complementary tests such as electroencephalogram (EEG), magnetic resonance imaging (MRI) and computed tomography (CT) of the brain. The aim is to identify the origin of the epileptic seizures and determine the best therapeutic strategy. Clinical treatment usually involves optimizing drug therapy, with adjustments to the doses of existing drugs or the introduction of new drugs. However, in many cases, the response to drug treatment is unsatisfactory, leading to consideration of surgical options. Surgery for refractory epilepsy can include removing the brain tissue responsible for epileptic seizures (temporal lobectomy, focal resection, etc.), deep brain stimulation or other less invasive techniques. These procedures aim to reduce the frequency and severity of epileptic seizures, improving the patient’s quality of life. The approach to refractory epilepsy requires a multidisciplinary and individualized assessment, taking into account the clinical characteristics and specific needs of each patient. Although clinical treatment is the first line of approach, surgery can be a viable option for those who do not respond adequately to antiepileptic drugs. It is essential that patients with refractory epilepsy are referred to specialized centers for a complete and appropriate evaluation of their case.

MRI-Guided Focused Ultrasound for the Treatment of Dystonia: A Narrative Review.

Contemporary surgical management of dystonia includes neuromodulation via deep brain stimulation (DBS) or ablative techniques such as radiofrequency (RF) ablation. MRI-guided focused ultrasound (MRgFUS) is an emerging modality that uses high-intensity ultrasound to precisely ablate targets in the brain; this is incisionless, potentially avoiding the surgical risks of a burr hole and transcortical tract to reach the anatomical target. There is some evidence of efficacy in essential tremor and Parkinson's disease (PD), but, to date, there is no study aggregating the evidence of MRgFUS in dystonia. In this narrative review, we searched Medline, Embase, CINAHL, EBSCO, and ClinicalTrials.gov for primary studies and clinical trials on MRgFUS in the treatment of dystonia. Data were analyzed concerning dystonia phenotype, reported outcomes, and complications. PD-related dystonia was also included within the scope of the review. Using our search criteria, six articles on the use of MRgFUS in adult dystonia and three articles on the use of FUS in dystonia in PD were included. Four trials on the use of FUS in dystonia were also found on ClinicalTrials.gov, one of which was completed in December 2013. All included studies showed evidence of symptomatic improvement, mostly in focal hand dystonia; improvements were also found in dystonia-associated tremor, cervicobrachial dystonia, and dystonia-associated chronic neuropathic painas well as PD-related dystonia. Reported complications included transient neurological deficits and persistent arm pain in one study. However, the evidence is limited to level-4 case series at present. MRgFUS is an emerging modality that appears to be safe and effective, particularly in focal hand dystonia, without major adverse effects. However, the quality of evidence is low at present, and long-term outcomes are unknown. High-quality prospective studies comparing MRgFUS to other surgical techniques will be useful in determining its role in the management of dystonia.

Evolution of Deep Brain Stimulation Techniques for Complication Mitigation.

Complication mitigation in deep brain stimulation has been a topic matter of much discussion in the literature. In this article, we examine how neurosurgeons as individuals and as a field generated and adapted techniques to prevent infection, lead fracture/lead migration, and suboptimal outcomes in both the acute period and longitudinally. The authors performed a MEDLINE search inclusive of articles from 1987 to June 2023 including human studies written in English. Using the Rayyan platform, two reviewers (J.P. and R.M.) performed a title screen. Of the 776 articles, 252 were selected by title screen and 172 from abstract review for full-text evaluation. Ultimately, 124 publications were evaluated. We describe the initial complications and inefficiencies at the advent of deep brain stimulation and detail changes instituted by surgeons that reduced them. Furthermore, we discuss the trend in both undesired short-term and long-term outcomes with emphasis on how surgeons recognized and modified their practice to provide safer and better procedures. This scoping review adds to the literature as a guide to both new neurosurgeons and seasoned neurosurgeons alike to understand better what innovations have been trialed over time as we embark on novel targets and neuromodulatory technologies.

Deep Brain Stimulation - Efficacy and Safety for Neurological Treatments

Though Deep Brain Stimulation (DBS) has been a popular technology in medicine with constantly reported innovation for many years, there are only limited studies that summarize its efficacy and safety. To compensate, this article thoroughly analyses these topics of DBS as treatments for multiple neurological diseases. Initially, the history and mechanism of DBS are introduced. Then, studies targeting different neurological conditions review the general efficacy of DBS. For traditional DBS targets like Parkinson’s Disease (PD), substantial disability rating improvements in patients of large-scale clinical reports are evidence of efficacy. Whereas for novel DBS targets like Obsessive-compulsive Disorder (OCD) and Huntington’s Disease (HD), evidence mainly comes from improvements in small-scale patient case studies and thus require further studies. Next, studies covering various complications discuss the safety consideration of DBS. While intra-operational (including hemorrhage and infection) and post-operational complications (including device malfunction, psychiatric impact, motor disorder, and cognitive impairment) of DBS are proven, change in patient personality, identity, autonomy, authenticity, agency, and self (PIAAAS) after DBS operation requires further information. Finally, though current DBS technique carries multiple risk concerns and needs improvements, potential prospects and solutions are explored for this potent and thriving technology.

Current Study on Deep Brain Stimulation for Parkinson's Disease

This paper emphasizes the evolution and application of neural electrical stimulation in the context of Parkinson's disease. During the last several decades, Deep Brain Stimulation (DBS) has become a highly successful viable treatment choice for patients with advanced stages of PD and other motor disorders. DBS utilizes a device similar to a pacemaker to administer constant electrical signals to targeted regions within the brain to help patient relieve the symptoms. The DBS has been involved in the rehabilitation process of more than 80000 people, and most of them are patients with PD. Based on the specific symptoms show by patients, several targets have been approved as effective DBS targets for patients with PD. These include subthalamic nucleus (STN), globus pallidus internus (GPi), ventral intermediate nucleus (Vim), and pedunculopontine nucleus (PPN). Hence, understanding the applications and evolution of DBS techniques have significant importance for future studies of PD and brain functions.

Reduced neural connectivity in the caudate anterior head predicts hallucination severity in schizophrenia.

Caudate functional abnormalities have been identified as one critical neural substrate underlying sensory gating impairments that lead to auditory phantom hallucinations in both patients with schizophrenia (SZ) and tinnitus, characterized by the perception of internally generated sounds in the absence of external environmental auditory stimuli. In this study, we tested the hypothesis as to whether functional connectivity abnormalities in distinct caudate subdivisions implicated in sensory gating and auditory phantom percepts in tinnitus, which are currently being localized for neuromodulation targeting using deep brain stimulation techniques, would be associated with auditory phantom hallucination severity in SZ. Twenty five SZ and twenty eight demographically-matched healthy control (HC) participants, completed this fMRI resting-state study and clinical assessments. Between-group seed-to-voxel analyses revealed only one region, the caudate anterior head, which showed reduced functional connectivity with the thalamus that survived whole-brain multiple comparison corrections. Importantly, connectivity between the caudate anterior head with thalamus negatively correlated with hallucination severity. In the present study, we deliver the first evidence of caudate subdivision specificity for the neural pathophysiology underlying hallucinations in schizophrenia within a sensory gating framework that has been developed for auditory phantoms in patients with tinnitus. Our findings provide transdiagnostic convergent evidence for the role of the caudate in the gating of auditory phantom hallucinations, observed across patients with SZ and tinnitus by specifying the anterior caudate division is key to mediation of hallucinations, and creating a path towards personalized treatment approaches to arrest auditory phantom hallucinations from reaching perceptual awareness.

Long-term safety and efficacy of frameless subthalamic deep brain stimulation in Parkinson’s disease

BackgroundBilateral deep brain stimulation (DBS) of the subthalamic nucleus (STN) is standard of care for Parkinson’s disease (PD) patients and a correct lead placement is crucial to obtain good clinical outcomes. Evidence demonstrating the targeting accuracy of the frameless technique for DBS, along with the advantages for patients and clinicians, is solid, while data reporting long-term clinical outcomes for PD patients are still lacking.ObjectivesThe study aims to assess the clinical safety and efficacy of frameless bilateral STN-DBS in PD patients at 5 years from surgery.MethodsConsecutive PD patients undergoing bilateral STN-DBS with a frameless system were included in this single-center retrospective study. Clinical features, including the Unified Parkinson’s Disease Rating Scale (UPDRS) in its total motor score and axial sub-scores, and pharmacological regimen were assessed at baseline, 1 year, 3 years, and 5 years after surgery. The adverse events related to the procedure, stimulation, or the presence of the hardware were systematically collected.ResultsForty-one PD patients undergone bilateral STN-DBS implantation were included in the study and fifteen patients already completed the 5-year observation. No complications occurred during surgery and the perioperative phase, and no unexpected serious adverse event occurred during the entire follow-up period. At 5 years from surgery, there was a sustained motor efficacy of STN stimulation: STN-DBS significantly improved the off-stim UPDRS III score at 5 years by 37.6% (P < 0.001), while the dopaminergic medications remained significantly reduced compared to baseline (− 21.6% versus baseline LEDD; P = 0.036).ConclusionsOur data support the use of the frameless system for STN-DBS in PD patients, as a safe and well-tolerated technique, with long-term clinical benefits and persistent motor efficacy at 5 years from the surgery.

Desynchronizing oscillators coupled in multi-cluster networks through adaptively controlling partial networks.

This article introduces an adaptive control scheme with a feedback delay, specifically designed for controlling partial networks, to achieve desynchronization in a coupled network with two or multiple clusters. The proposed scheme's effectiveness is validated through several representative examples of coupled neuronal networks with two interconnected clusters. The efficacy of this scheme is attributed to the rigorous and numerical analyses on the corresponding transcendental characteristic equation, which includes time delay and other network parameters. In addition to investigating the impact of time delay and inter-connectivity on the stability of an incoherent state, we also rigorously find that controlling only one cluster cannot realize the desynchronization in the coupled oscillators within three or more clusters. All these, we believe, can deepen the understanding of the deep brain stimulation techniques presently used in the clinical treatment of neurodegenerative diseases and suggest future avenues for enhancing these clinical techniques through adaptive feedback settings.

Adaptive Stimulations in a Biophysical Network Model of Parkinson’s Disease

Deep brain stimulation (DBS)-through a surgically implanted electrode to the subthalamic nucleus (STN)-has become a widely used therapeutic option for the treatment of Parkinson's disease and other neurological disorders. The standard conventional high-frequency stimulation (HF) that is currently used has several drawbacks. To overcome the limitations of HF, researchers have been developing closed-loop and demand-controlled, adaptive stimulation protocols wherein the amount of current that is delivered is turned on and off in real-time in accordance with a biophysical signal. Computational modeling of DBS in neural network models is an increasingly important tool in the development of new protocols that aid researchers in animal and clinical studies. In this computational study, we seek to implement a novel technique of DBS where we stimulate the STN in an adaptive fashion using the interspike time of the neurons to control stimulation. Our results show that our protocol eliminates bursts in the synchronized bursting neuronal activity of the STN, which is hypothesized to cause the failure of thalamocortical neurons (TC) to respond properly to excitatory cortical inputs. Further, we are able to significantly decrease the TC relay errors, representing potential therapeutics for Parkinson's disease.

Frameless Robot-Assisted Asleep Centromedian Thalamic Nucleus Deep Brain Stimulation Surgery in Patients with Drug-Resistant Epilepsy: Technical Description and Short-Term Clinical Results.

This purpose of this work is to give a detailed description of a surgical technique for frameless robot-assisted asleep deep brain stimulation (DBS) of the centromedian thalamic nucleus (CMT) in drug-resistant epilepsy (DRE). Ten consecutively enrolled patients who underwent CMT-DBS were included in the study. The FreeSurfer "Thalamic Kernel Segmentation" module and experience target coordinates were used for locating the CMT, and quantitative susceptibility mapping (QSM) images were used to check the target. The patient's head was secured with a head clip, and electrode implantation was performed with the assistance of the neurosurgical robot Sinovation®. After opening the dura, the burr hole was continuously flushed with physiological saline to stop air from entering the skull. All procedures were performed under general anesthesia without intraoperative microelectrode recording (MER). The mean age of the patients at surgery and onset of seizures was 22years (range 11-41years) and 11years (range 1-21years), respectively. The median duration of seizures before CMT-DBS surgery was 10years (2-26years). CMT was successfully segmented, and its position was verified by experience target coordinates and QSM images in all ten patients. The mean surgical time for bilateral CMT-DBS in this cohort was 165 ± 18min. The mean pneumocephalus volume was 2 cm3. The median absolute errors in the x-, y-, and z-axes were 0.7mm, 0.5mm, and 0.9mm, respectively. The median Euclidean distance (ED) and radial error (RE) was 1.3 ± 0.5mm and 1.0 ± 0.3mm, respectively. No significant difference was found between right- and left-sided electrodes regarding the RE nor the ED. After a mean 12-month follow-up, the average reduction in seizures was 61%, and six patients experienced a ≥ 50% reduction in seizures, including one patient who had no seizures after the operation. All patients tolerated the anesthesia operation, and no permanent or serious complications were reported. Frameless robot-assisted asleep surgery is a precise and safe approach for placing CMT electrodes in patients with DRE, shortening the surgery time. The segmentation of the thalamic nuclei enables the precise location of the CMT, and the flow of physiological saline to seal the burr holes is a good way to reduce the influx of air. CMT-DBS is an effective method to reduce seizures.

HH model based smart deep brain stimulator to detect, predict and control epilepsy using machine learning algorithm

BackgroundEpilepsy is the most common neurological disorder in the world. To control epilepsy, deep brain stimulation is one of the widely accepted treatment techniques. However, conventional deep brain stimulation technique provides continuous stimulation without optimizing the stimulation parameters, resulting in adverse side effects and unexpected death. Hence, understanding the dynamic behavior of brain neural networks at a cellular level is required for patient-specific epilepsy treatment. Considering the underlying mechanism of a single neuronal shift in the brain neural network, computational model-based techniques have a new face for healthcare, which aims to develop effective medical devices for preclinical investigations. New methodThis paper discusses the design of a Smart Deep Brain Stimulator (SDBS) using the Hodgkin-Huxley (HH) conductance-based cellular model of brain neurons to automatically detect, predict and regulate epilepsy against patient-specific conditions. Epileptic activity is simulated as a spike train of action potential due to sodium and potassium channel conductance variations in the single-neuron HH model. The proposed SDBS consists of three components:- i) seizure detection using bagging and boosting-based ensemble machine learning classifiers, ii) channel conductance prediction using Long Short Term Memory-Recurrent Neural Network (LSTM-RNN) based Deep Neural Network (DNN) for updating model parameters of brain neuron, and iii) model-based intelligent control of epileptic seizure with Nonlinear Autoregressive Moving Average-L2 (NARMA-L2) Controller and Nonlinear Model Predictive Controller (NMPC). ResultsFor effective treatment, improving the overall accuracy and efficiency of SDBS is essential. For epilepsy detection, the ensemble bagging machine learning algorithm provides better accuracy of 92.7% compared to the ensemble boosting algorithm. LSTM-RNN deep neural network model with four layers predicts the variations in channel conductance with Root Mean Square Error (RMSE) of 0.00568 and 0.009081 for sodium and potassium channel conductance, respectively. From the closed-loop performances of SDBS with an intelligent control scheme, it is observed that SDBS with NMPC provides efficient and accurate stimulation with minimum energy consumption. From a stability point of view, SDBS with NMPC provides better stability than SDBS with NARMA-L2 Controller. Comparison with existing methodThe proposed SDBS is designed to generate accurate stimulation pulses for epilepsy patients with specific conditions depending on the neuronal activity of a single neuron. Moreover, it will also adapt to the dynamic condition of epilepsy patients. The existing deep brain stimulator continuously provides stimulation pulses without adapting to the patient’s conditions. ConclusionThe proposed SDBS could provide patient-specific treatment based on sodium/potassium channel conductance variations of brain neurons. It will help increase the use of deep brain stimulation techniques and reduce sudden death. Furthermore, the proposed technique will be extended to neural network models with larger neuronal populations to improve the practical feasibility.

A Novel Closed-Loop Deep Brain Stimulation Technique for Parkinson’s Patients Rehabilitation Utilizing Machine Learning

Deep brain stimulation (DBS) is an effective treatment for movement problems caused by a variety of neurodegenerative illnesses, including Parkinson’s disease (PD). Researchers have created closed-loop DBS (CL-DBS) techniques for reducing hand tremors in many disorders, notably Parkinson’s patients, in recent years. As shown in the studies, hand tremor and rigidity symptoms are two sides of the same coin, with hand tremor leading to rigidity fluctuations and vice versa. The following are the primary contributions of this study: 1) depicts the correlation between the two indicators and 2) the suggestion of a proximal policy optimization (PPO)-based non-integer proportional integral derivative (PID) control technique to reduce hand tremor and stiffness at the same time, where the reward function is developed to alter DBS settings when illness levels vary. The PPO technique is combined with the main controller to provide adaptive learning. The controller parameters of the non-integer PID scheme are regarded as changeable controller coefficients in the proposed strategy, which will be adaptively built by the PPO technique via online learning of its neural networks (NNs). In order to demonstrate the advantages and adaptability of the procedure with different models and patients, the recommended strategy is an analysis by computer simulation in a variety of contexts (performance, robustness, and noise) and compared to current methodologies like integer-order PID (IOPID) and fractional-order PID (FOPID). The simulation outcomes showed that the created system performed better and more effectively than previous approaches in coping with parameter changes and outside noise, in addition to simultaneously reducing hand tremor and stiffness.

Efficient suppression of parkinsonian beta oscillations in a closed-loop model of deep brain stimulation with amplitude modulation.

Parkinson's disease (PD) is a movement disorder characterized by the pathological beta band (15-30 Hz) neural oscillations within the basal ganglia (BG). It is shown that the suppression of abnormal beta oscillations is correlated with the improvement of PD motor symptoms, which is a goal of standard therapies including deep brain stimulation (DBS). To overcome the stimulation-induced side effects and inefficiencies of conventional DBS (cDBS) and to reduce the administered stimulation current, closed-loop adaptive DBS (aDBS) techniques were developed. In this method, the frequency and/or amplitude of stimulation are modulated based on various disease biomarkers. Here, by computational modeling of a cortico-BG-thalamic network in normal and PD conditions, we show that closed-loop aDBS of the subthalamic nucleus (STN) with amplitude modulation leads to a more effective suppression of pathological beta oscillations within the parkinsonian BG. Our results show that beta band neural oscillations are restored to their normal range and the reliability of the response of the thalamic neurons to motor cortex commands is retained due to aDBS with amplitude modulation. Furthermore, notably less stimulation current is administered during aDBS compared with cDBS due to a closed-loop control of stimulation amplitude based on the STN local field potential (LFP) beta activity. Efficient models of closed-loop stimulation may contribute to the clinical development of optimized aDBS techniques designed to reduce potential stimulation-induced side effects of cDBS in PD patients while leading to a better therapeutic outcome.

Complications of Deep Brain Stimulation for Movement Disorders: Literature Review and Personal Experience.

The contemporary technique of deep brain stimulation (DBS) is very effective for management of movement disorders-including Parkinson's disease, generalized dystonia, and tremors-and has also been successfully applied for novel indications (e.g., intractable epilepsy and chronic pain). As a result, growing numbers of DBS procedures have been performed worldwide; correspondingly, the incidence of associated morbidity has also increased. All complications of DBS can be divided into those associated with (1) the surgical procedure, (2) the device itself, and (3) the applied electrical stimulation. On the basis of an analysis of the available literature and the personal experience of the author, it may be concluded that implantation of a DBS device is a relatively safe procedure accompanied by very low risks of major morbidity or a permanent neurological deficit. Nevertheless, awareness of the possible complications and application of appropriate preventive measures for their avoidance are very important for providing safe and effective treatment.

Role of Gamma Knife Radiosurgery in the Management of Functional Disorders - A Literature Review.

Role of radiosurgical lesioning in functional disorders has been restricted because of development of deep brain stimulation (DBS) techniques. However, many elderly patients with comorbidities and coagulation abnormalities may not be eligible for DBS. Radiosurgical lesioning may be a good alternative in such cases. The objective of the study was to review the role of radiosurgical lesioning for functional targets in common functional disorders. Literature reports pertaining to common disorders were reviewed. Disorders included are tremors (essential tremors, tremor-dominant Parkinson's disease [PD], multiple sclerosis [MS] related refractory tremors), Parkinson's disease (for rigidity, bradykinesia, drug-induced dyskinesias), dystonia, and obsessive-compulsive disorder (OCD). The most commonly performed procedure was ventral intermediate nucleus (VIM) lesioning for essential tremors and tremor-dominant PD, with about 90% patients demonstrating improvement. Intractable OCD with 60% responders is a promising indication. Other disorders are less commonly treated, with dystonia being the least commonly treated entity. Subthalamic nucleus (STN) and globus pallidus interna/posteroventral pallidum (GPi) lesioning are very rarely reported, and the available literature suggests caution due to high rates of adverse effects. Outcomes for radiosurgical lesioning for essential tremors (VIM) and OCD (anterior limb of internal capsule [ALIC]) are encouraging. Radiosurgical lesioning offers a lower immediate risk profile in patient population with several comorbidities; however, long-term adverse effects due to radiation are a concern, especially for STN and GPi lesioning.

Three-layer model with absorption for conservative estimation of the maximum acoustic transmission coefficient through the human skull for transcranial ultrasound stimulation

Transcranial ultrasound stimulation (TUS) has been shown to be a safe and effective technique for non-invasive superficial and deep brain stimulation. Safe and efficient translation to humans requires estimating the acoustic attenuation of the human skull. Nevertheless, there are no international guidelines for estimating the impact of the skull bone. A tissue independent, arbitrary derating was developed by the U.S. Food and Drug Administration to take into account tissue absorption (0.3 dB/cm-MHz) for diagnostic ultrasound. However, for the case of transcranial ultrasound imaging, the FDA model does not take into account the insertion loss induced by the skull bone, nor the absorption by brain tissue. Therefore, the estimated absorption is overly conservative which could potentially limit TUS applications if the same guidelines were to be adopted. Here we propose a three-layer model including bone absorption to calculate the maximum pressure transmission through the human skull for frequencies ranging between 100 kHz and 1.5 MHz. The calculated pressure transmission decreases with the frequency and the thickness of the bone, with peaks for each thickness corresponding to a multiple of half the wavelength. The 95th percentile maximum transmission was calculated over the accessible surface of 20 human skulls for 12 typical diameters of the ultrasound beam on the skull surface, and varies between 40% and 78%. To facilitate the safe adjustment of the acoustic pressure for short ultrasound pulses, such as transcranial imaging or transcranial ultrasound stimulation, a table summarizes the maximum pressure transmission for each ultrasound beam diameter and each frequency.

Effects of feedback control in small-world neuronal networks interconnected according to a human connectivity map

In this work, we consider a phenomenological two-dimensional discrete model coupled in a structure of a clustered network to investigate the suppression of neuronal synchronization in a complex network. We constructed a network according to a weighted human connectivity matrix and an adjacency matrix that carries small-world properties. The coupling between neurons is inserted through a chemical synapse term and a neuronal activation function. The neuronal synchronization is measured by the Kuramoto order parameter. We intend to achieve the suppression of burst phase synchronization, and for that, we use a mathematical tool, based on the technique of deep brain stimulation, which consists of applying an external signal to the network after a certain time, causing the bursts to desynchronize. Our results are efficient when applying the feedback method both in the global network and in the cortical regions. We have seen that for cortical regions, synchronization is more difficult to suppress, however, by slightly increasing the perturbation, we are able to achieve the desired effect. This shows that it is possible to use the control efficiently in isolated cortical areas, therefore, we present a new alternative to conventional methods, avoiding to apply the control to the entire network to obtain the same results.

Deep brain-machine interfaces: sensing and modulating the human deep brain.

Different from conventional brain-machine interfaces that focus more on decoding the cerebral cortex, deep brain-machine interfaces enable interactions between external machines and deep brain structures. They sense and modulate deep brain neural activities, aiming at function restoration, device control and therapeutic improvements. In this article, we provide an overview of multiple deep brain recording and stimulation techniques that can serve as deep brain-machine interfaces. We highlight two widely used interface technologies, namely deep brain stimulation and stereotactic electroencephalography, for technical trends, clinical applications and brain connectivity research. We discuss the potential to develop closed-loop deep brain-machine interfaces and achieve more effective and applicable systems for the treatment of neurological and psychiatric disorders.