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Deep Brain Stimulation

Deep Brain Stimulation (DBS) is a neurosurgical procedure involving the implantation of a medical device that delivers electrical stimulation to specific targets in the brain.
This technique is used to treat a variety of neurological disorders, such as Parkinson's disease, essential tremor, and obsessive-compulsive disorder.
DBS has been shown to be an effective treatment option, but the optimization of research protocols is crucial for enhancing reproducibility and accuracy.
PubCompare.ai offers a suite of AI-driven tools and analytics to help streamline the DBS research process.
Users can locate the best protocols from literature, pre-prints, and patents, and identify the most effective DBS treatments and products.
This comprehensive platform supports researchers in navigating the complexities of DBS research, ultimately contributing to the advancement of this important medical intervention. [Typo: 'pre-prints' instead of 'preprints']

Most cited protocols related to «Deep Brain Stimulation»

1
Cognitive Profiles in Parkinson's Disease
Cited 9 times
We reviewed the medical records of patients with PD who visited a tertiary referral center. We selected patients who had their cognitive status assessed by a comprehensive neuropsychological battery from Jan 2014 to Dec 2015. PD was diagnosed according to the clinical criteria of the UK PD Brain Bank [12 (link)], and patients who underwent deep brain stimulation or were aged less than 50 or more than 85 were excluded from the study. To rule out patients with dementia with Lewy bodies, we also excluded patients who had visual hallucinations or dementia occurring before or within 1 year following the onset of parkinsonism [13 (link)]. Patients who showed abnormalities in thyroid function test or vitamin B 12 levels; subjects who were treated with drugs affecting cognitive status such as benzodiazepines or antipsychotics were also excluded. Subjects having focal brain lesions or white matter hyperintensity corresponding to grade 2 or 3 of the Fazekas scale on a MRI scan were also excluded from this study [14 (link)].
This study was approved by the Institutional Review Board (IRB) and was exempt from the requirement for informed consent by the IRB because of its retrospective design.
Kim J.I., Sunwoo M.K., Sohn Y.H., Lee P.H, & Hong J.Y. (2016). The MMSE and MoCA for Screening Cognitive Impairment in Less Educated Patients with Parkinson’s Disease. Journal of Movement Disorders, 9(3), 152-159.
Publication 2016
Antipsychotic Agents Benzodiazepines Brain Cobalamins Cognition Congenital Abnormality Deep Brain Stimulation Ethics Committees, Research Hallucinations, Visual Lewy Bodies MRI Scans Outpatients Parkinsonian Disorders Patients Pharmaceutical Preparations Presenile Dementia Thyroid Function Tests White Matter
2
Idiopathic Parkinson's Disease Protocol
Cited 8 times
One-hundred and ten patients with idiopathic PD were recruited from our databases, referrals from specialists at the outpatient movement disorders unit, and from other affiliated clinics. Subjects were included if they were diagnosed by a movement disorders specialist as having idiopathic PD (as defined by the UK Brain Bank criteria [53] (link)), were between 40 and 85 of age, and were not demented. Subjects were excluded if they had brain surgery in the past including implanted deep brain stimulation or had significant co-morbidities likely to affect gait, e.g., acute illness, orthopedic disease, or history of stroke. In addition, subjects who could not walk independently in the off medication cycle, patients with claustrophobia, and patients who could not undergo MRI testing (e.g., if they had large metal implants) were excluded.
Herman T., Rosenberg-Katz K., Jacob Y., Auriel E., Gurevich T., Giladi N, & Hausdorff J.M. (2013). White Matter Hyperintensities in Parkinson’s Disease: Do They Explain the Disparity between the Postural Instability Gait Difficulty and Tremor Dominant Subtypes?. PLoS ONE, 8(1), e55193.
Publication 2013
Brain Cerebrovascular Accident Claustrophobia Deep Brain Stimulation Metals Movement Disorders Operative Surgical Procedures Outpatients Patients Pharmaceutical Preparations
3
Parkinson's Disease Patient Characteristics
Cited 8 times

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Publication 2013
Deep Brain Stimulation Diagnosis Patients Pharmaceutical Preparations Woman
4
Evaluating Balance and Mobility in Parkinson's Disease
Cited 8 times
Ninety-seven participants with idiopathic PD participated in the study. These participants were part of either a larger clinical study examining prospective fall risk or an exercise efficacy study. Therefore, the group here represents a convenience sample of participants with PD, and the data for this paper was taken from their baseline visits. Inclusion criteria: all people in the study were diagnosed with idiopathic PD by a movement disorders neurologist. People were excluded from the study if they presented with cognitive impairment, prior orthopedic injuries, or impairments that could interfere with mobility such as artificial joints or peripheral neuropathy or prior brain surgery such as a pallidotomy or deep brain stimulation. All participants signed informed consent forms approved by the Oregon Health & Science University Institutional Review Board. All work was conducted in accordance with the declaration of Helsinki (1964).
All participants came in for an assessment of their balance and mobility which included both clinical and instrumented testing. The data presented in this paper is taken from the clinical scales: the Unified Parkinson's Disease Rating Scale (UPDRS) III Motor section, Hoehn & Yahr (H&Y) disease severity classification, and the Berg and the Mini-BESTest. The testing was performed in the same order for each participant, and rest breaks were given as needed to avoid fatigue. Other balance and gait assessments conducted during testing that were not included in this analysis included gait and sway analysis using wearable inertial sensors. Testing was conducted at the Oregon Clinical Translational Research Institute at Oregon Health & Science University. All participants took their PD medication as normally indicated and were tested in the ON state. All of the participants except for two were currently taking some form of PD medication. The testing was administered by a trained examiner, overseen by a physical therapist. Participant characteristics are outlined in Table 1.
King L.A., Priest K.C., Salarian A., Pierce D, & Horak F.B. (2011). Comparing the Mini-BESTest with the Berg Balance Scale to Evaluate Balance Disorders in Parkinson's Disease. Parkinson's Disease, 2012, 375419.
Publication 2011
Brain Deep Brain Stimulation Disorders, Cognitive Ethics Committees, Research Fatigue Injuries Joints Movement Disorders Neurologists Operative Surgical Procedures Pallidotomy Peripheral Nervous System Diseases Pharmaceutical Preparations Physical Therapist Protein Biosynthesis Range of Motion, Articular
5
Neuropsychological Evaluation of Non-Demented Parkinson's Patients
Cited 7 times
Participants included 161 non-demented patients with idiopathic PD who underwent clinical neuropsychological evaluation between 2004 and 2009 at the University of Florida’s Psychology Clinic. All PD patients had been referred by the UF Movement Disorders Center. Informed consent was obtained according to university and federal guidelines. To be included, PD patients had to be between 40 and 90 years of age and meet UK Brain Bank diagnostic criteria (Hughes, Ben-Shlomo, Daniel, & Lees, 1992 (link); Hughes, Daniel, Kilford, & Lees, 1992 ). These criteria are based on the presence of bradykinesia plus at least one other cardinal motor symptom: muscular rigidity, resting tremor, or postural instability. Patients must demonstrate marked improvement in response to dopaminergic therapy to differentiate idiopathic PD from Parkinson’s plus syndromes. Exclusion criteria were co-morbid neurological illnesses, previous neurosurgical treatments (i.e., deep brain stimulation or pallidotomy), or evidence of dementia based on scores less than 130 on the Dementia Rating Scale II (DRS-II; Jurica, Leitten & Mattis, 2001 ). Dementia was excluded because the intent was to capture primary apathy. Including demented patients creates a confound that apathy may be secondary to cognitive impairment (Marin, 1991 (link)).
Participant information and disease characteristics are shown in Table 1. As a group, the PD patients were well educated, predominantly men (68.9%), Caucasian (95%), and ranged in age from 42 to 84 years. On average, they had been experiencing parkinsonian symptoms for 8.5 years and were in the mid-stages of their disease (i.e., Unified Parkinson’s Disease Rating Scale (UPDRS) motor score = 25.5, SD = 8.6). Approximately one third of the patients were pre-surgical candidates for Deep Brain Stimulation (DBS). The majority of patients were tremor-predominant subtype (77%) or akinetic–rigid subtype (17.4%). Between 25 and 30% of the PD participants were taking antidepressants and/or anxiolytic medications. Importantly, rates of apathy were not significantly different between individuals who were taking antidepressants or anxiolytics and those who were not taking them (p = .098 for antidepressants and p = .17, for anxiolytics). There were no significant differences in apathy (p = .69) or depression (p = .76) between patients with tremor predominant versus akinetic rigid subtypes of PD. Additional information is shown in Table 1.
Kirsch-Darrow L., Marsiske M., Okun M.S., Bauer R, & Bowers D. (2011). Apathy and Depression: Separate Factors in Parkinson’s Disease. Journal of the International Neuropsychological Society, 17(6), 1058-1066.
Publication 2011
Anti-Anxiety Agents Antidepressive Agents Apathy Bradykinesia Brain Caucasoid Races Deep Brain Stimulation Dementia Diagnosis Disorders, Cognitive Hydrochloride, Dopamine Motor Disorders Movement Disorders Muscle Rigidity Neuropsychological Tests Neurosurgical Procedures Operative Surgical Procedures Pallidotomy Parkinsonian Disorders Patients Resting Tremor Syndrome Therapeutics Tranquilizing Agents Tremor

Most recents protocols related to «Deep Brain Stimulation»

1
Multimodal Brain MRI Dataset for Segmentation
Cited 2 times
Our experiments feature three datasets. The first one comprises 15,346 clinical scans from the PACS of Massachusetts General Hospital (see detailed information in SI Appendix, Appendix 1). Briefly, these scans are from 1,367 MRI sessions of distinct subjects with memory complaints, between 18 and 90 years of age: 749 males (age =62.2 ± 15.2) and 618 females (age = 58.1 ± 17.2). Importantly, all scans are uncurated, and span a huge range of MR contrasts (T1-weighted, T2-weighted, FLAIR, diffusion MRI, etc.). Acquisitions are isotropic (11%) and anisotropic in axial (81%), coronal (4%), and sagittal (4%) orientations. The resolution of isotropic scans varies between 0.3 and 4.7 mm. For anisotropic scans, in-plane resolution ranges between 0.2 and 4.7 mm, while slice spacing varies between 0.8 and 10.5 mm. Ground truths for whole-brain segmentation, cortex parcellation, and ICV estimation were obtained for a subset of scans as follows. First, we isolated all sessions (N = 62) with 1 mm isotropic T1-weighted scans. These were then labeled using FreeSurfer (3 (link)), and the obtained segmentations were rigidly registered (47 ) to the other scans of the corresponding sessions. Note that we also obtained ICVs for all these scans by reporting the estimations given by FreeSurfer on the T1-weighted scans. Finally, we conducted a visual QC on the results and removed all scans where even a small segmentation error could be seen, either due to FreeSurfer or registration errors (138 scans) and/or poor image quality (94 cases with, e.g., insufficient coverage of the brain, wrong organ). In total, this provided us with ground truth segmentations for 520 scans, that we split between validation (20), and testing (500). All the other 14,752 scans were held-out for indirect evaluation.
The second dataset consists of 66 scans from three subdatasets: 20 T1-weighted scans from OASIS database (43 (link)); 18 subjects imaged twice with T2-weighted acquisitions and a sequence typically used in deep brain stimulation (DBS) (48 (link)); and 8 proton density scans (49 ). All scans are at 1 mm isotropic resolution and are available with manual or semiautomated segmentations for 31 brain regions (45 ). Labels for cortex parcellation were obtained by running FreeSurfer on the T1-weighted scans or on companion 1 mm T1-weighted acquisitions for the T2-weighted, DBS, and proton density scans.
The last dataset is another subset of 100 scans from ADNI (7 (link)), including 47 males and 53 females, aged 72.9 ± 7.6 y. Half of the subjects are healthy, while the others are diagnosed with Alzheimer’s Disease. All subjects are imaged with two acquisitions: 1 mm isotropic T1-weighted scans and FLAIR scans at 5 mm axial resolution. Volumetric measurements for individual regions and ICVs are retrieved for all subjects by processing the T1-weighted scans with FreeSurfer.
Billot B., Magdamo C., Cheng Y., Arnold S.E., Das S, & Iglesias J.E. (2023). Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets. Proceedings of the National Academy of Sciences of the United States of America, 120(9), e2216399120.
Publication 2023
Alzheimer's Disease Anisotropy ARID1A protein, human Atrial Premature Complexes Brain Contrast Media Cortex, Cerebral CREB3L1 protein, human Deep Brain Stimulation Diffusion Magnetic Resonance Imaging Females Males Memory Mental Orientation Pets Protons Radionuclide Imaging Vision
2
Observational and Interventional Studies on Mood Disorders
We retrieved all observational studies and clinical trials related to patients with mood disorders or to their caregivers. In the case of clinical trials, we included all interventions, such as drugs, lifestyle modification, psycho-educational treatments, and behavioral treatments. We extracted data for studies registered in the CTRI database between June 15, 2009 and December 31, 2019. We used the three advanced search options at the CTRI website: ‘scientific title of the study,’ ‘health condition/problem studied,’ and ‘intervention and comparator agent’ to identify relevant observational studies and interventional clinical trials.
For the first two options, we searched the database using disorder keywords such as “depression”, “depressive disorder”, “major depressive disorder”, “treatment-resistant depression”, “mania”, “bipolar disorder”, and “bipolar depression”, entered individually. For the third option, we searched using names of psychotropic drugs and other treatments, such as “olanzapine”, “risperidone”, “cognitive behaviour therapy”, “electroconvulsive therapy”, repetitive transcranial magnetic stimulation, and deep brain stimulation, again entered individually. Two authors (NV, RJ) independently searched the CTRI database using these strategies, after which a final list of studies satisfying the eligibility criteria was made by removing duplicates. We excluded studies involving interventions related to Ayurveda, Unani, and other alternative systems of medicine because the results of such studies tend to be published in journals and other destinations that might not have been accessible to us in our literature search. We also excluded studies that were not conducted primarily in patients with the disorders listed above.
Menon V., Varadharajan N., Joseph R., Praharaj S.K, & Andrade C. (2023). Publication of studies registered in Clinical Trials Registry of India: An audit of mood disorder research protocols from 2009-2019. Indian Journal of Psychiatry, 65(1), 68-74.
Publication 2023
Behavior Therapy Bipolar Disorder Cognitive Therapy Deep Brain Stimulation Depression, Bipolar Depressive Disorder, Treatment-Resistant Disorder, Depressive Electroconvulsive Therapy Eligibility Determination Major Depressive Disorder Mania Mood Disorders Olanzapine Patients Pharmaceutical Preparations Psychotropic Drugs Risperidone Transcranial Magnetic Stimulation, Repetitive
3
Factors Influencing Epilepsy Surgery Utilization
Data from responses were described using frequency (percentage of nonmissing totals) for categorical variables and median (interquartile range) for continuous variables. Missing values of treatments were set to zero if meeting certain conditions. If all procedure volumes were missing from a given center, no imputation was performed. If only some procedure volumes were missing, those left blank were recorded as zero.
Separate regression models were built for each of the surgical treatments as dependent variables, which included temporal lobectomy, extratemporal resection, hemispherotomy/ectomy, LITT, corpus callosotomy, VNS implantation, and responsive neurostimulation (RNS) implantation. Deep brain stimulation cases were excluded because of lack of reliable reporting. Potential model independent variables included organization accreditation level (level 3 vs 4), center director demographic (pediatric vs adult patients), institution type (academic, private practice, or teaching affiliate), US geographic region (South, Midwest, Northeast, or West), number of epileptologists with 2 or more years of fellowship training, percent of resections performed with electrocorticography (ECOG; by 10% incremental increase), availability of image-guided robotics (yes vs no), availability of magnetoencephalography (MEG; yes vs no), availability of positron emission tomography (PET; yes vs no), and availability of single-photon emission computed tomography (SPECT; yes vs no). Variables that were highly imbalanced were not used in the multivariable models, and this most commonly was the distribution of treatment by the organization accreditation level.
Many centers reported performing none of any given treatment type (count = 0). Therefore, we used zero-inflated (ZIF) Poisson regression models18 (link) for these highly skewed count data. These multivariable models had 2 components: one for modeling the count of treatments with Poisson regression and another for modeling excess zeros in the data. There are 2 sources of zeros in a ZIF Poisson model: excess zeros that come from the binary component and zeros that come from the count component.
Estimates from the first component (ZIF) of the ZIF Poisson model are presented as ORs. The original binary model captures the probability of no treatment. For ease of interpretation, we present inverted ORs to interpret odds of performing any of a given procedure. An OR greater than 1 indicates increased odds of performing the procedure; an OR less than 1 indicates decreased odds of performing that procedure. Estimates from the second component (Poisson regression) are presented as incidence rate ratios (IRRs). An IRR greater than 1 indicates a factor by which the treatment rate for a given surgery is higher than the rate for the reference category; an IRR less than 1 indicates the factor by which the rate is decreased compared with the reference category.
All statistical analyses were performed in R version 4.0 (R Core Team, Vienna, Austria) with reproducible programing in R Markdown. p values ≤ 0.05 were considered statistically significant. ZIF Poisson models were constructed with the zeroinfl function from R package pscl.19 (link) Backward stepwise model selection based on the Akaike information criterion (AIC) was performed using the stepAIC function from R package MASS.20 (link)
Arredondo K.H., Ahrens S.M., Bagić A.I., Bai S., Chapman K.E., Ciliberto M.A., Clarke D.F., Eisner M., Fountain N.B., Gavvala J.R., Perry M.S., Rossi K.C., Wong-Kisiel L.C., Herman S.T, & Ostendorf A.P. (2023). Association Between Characteristics of National Association of Epilepsy Centers and Reported Utilization of Specific Surgical Techniques. Neurology, 100(7), e719-e727.
Publication 2023
A-factor (Streptomyces) Adult Deep Brain Stimulation Electrocorticography Fellowships Operative Surgical Procedures Ovum Implantation Patients Positron-Emission Tomography Tomography, Emission-Computed, Single-Photon
4
Retrospective Analysis of Parkinson's Disease
The research group was recruited from the Neurology Ward and the Single-Day Ward of the Neurology Clinic of the Silesian Medical University in Katowice between the 1 August 2019 and the 30 October 2022. The research was carried out retrospectively based on the medical data analysis and EEG recordings performed during the diagnostic process. The study was conducted according to the guidelines of the Declaration of Helsinki. Ethical review and approval were waived for this study due to the retrospective character of the work and data anonymization. The Ethics Committee of the Medical University of Silesia waived the requirement to obtain ethical approval for this study. The patients with PD were diagnosed according to the Movement Disorder Society clinical diagnostic criteria for Parkinson’s disease 2015 [3 (link)]. The diagnosis of PD-MCI was performed in line with the Movement Disorder Society Task Force Guidelines 2012 [11 (link)], and the PD-D was made according to Clinical Diagnostic Criteria for Dementia associated with Parkinson’s disease formed by MDS Task Force in 2007 [12 (link)]. A total of 453 patients with PD were hospitalized at the chosen time. To be included in the study, patients must have met the aforementioned disease criteria: undergo a brain neuroimaging examination (computer tomography or MRI of the brain), undergo an EEG examination, and have a neuropsychological consultation. Exclusion criteria included: atypical and secondary parkinsonism, implantation of deep brain stimulation, the presence of other neurological or psychiatric conditions, other secondary causes of cognitive impairment that were significant according to the evaluator (e.g., decompensated, advanced hypothyroidism, significant electrolyte disturbance), and any other severe illnesses. Figure 1 depicts the participants’ recruitment flow chart. Based on the neuropsychological examination and the currently applicable PD-D and PD-MCI diagnosis criteria, 25 patients with PD-D, 30 patients with PD-MCI, and 43 patients without cognitive impairment were selected for the study. Detailed data of the clinical characterization are summarized in Table 1.
Zawiślak-Fornagiel K., Ledwoń D., Bugdol M., Romaniszyn-Kania P., Małecki A., Gorzkowska A, & Mitas A.W. (2023). The Increase of Theta Power and Decrease of Alpha/Theta Ratio as a Manifestation of Cognitive Impairment in Parkinson’s Disease. Journal of Clinical Medicine, 12(4), 1569.
Publication 2023
Brain Character Deep Brain Stimulation Dementia Diagnosis Disorders, Cognitive Electrolytes Ethical Review Ethics Committees Hypothyroidism Mental Disorders Movement Disorders Neuropsychological Tests Ovum Implantation Patients Secondary Parkinson Disease Tomography
5
Wearable Device for Parkinson's Wearing-Off Detection
This prospective study was carried out at the Pacific Parkinson’s Research Center, University of British Columbia. Following approval by the Ethics Board, all subjects had provided written, informed consent.
We recruited 25 patients diagnosed with PD by certified movement disorder specialists according to the United Kingdom Parkinson’s Disease Society Brain Bank Criteria. Exclusion criteria included (i) atypical Parkinsonism, (ii) depressive mood identified by Beck Depression Inventory-II (BDI-II)>14 or concurrent treatment with antidepressants, (iii) cognitive impairment measured by Montreal Cognitive Assessment ≤ 22, (iv) history of epilepsy, polyneuropathy, spinal cord diseases, thyroid dysfunction, or severe dermatological conditions, and (v) history of deep brain stimulation, implantation of any medical devices, or anticholinergic medication use.
Demographic features including age, sex, duration of disease after initial diagnosis, and total daily L-dopa dose were obtained. Overall severity of Parkinsonism was assessed by Unified Parkinson’s Disease Rating Scale (UPDRS) part III in all participants. The “wearing off questionnaire-19 (WOQ-19)”, a clinical scale that measures the degree of fluctuations in both motor and non-motor symptoms, was assessed in all patients. A compact view of subjects’ responses to the questionnaire is plotted in Figure S1. Participants were considered to have WO if they experienced at least two or more symptoms in WOQ 19 that improved with L-dopa intake [28 (link),29 (link)]. The Scales for Outcomes in Parkinson’s disease-AUTonomic dysfunction (SCOPA-AUT) was used to assess any pre-existent autonomic system function [30 (link)]. Table 1 lists the main demographic features of each subject.
A wearable wristband, E4 wristband® (Empatica Inc., Milan, Italy), was used to obtain EDA, HR, BVP, and TEMP information. It carries out EDA measurements with two dry silver-plated electrodes that are attached to the inner surface of the watch with a sampling rate of 4 Hz and a range of skin conductance (SC) from 0.01 μS to 100 μS. BVP is measured by photoplethysmography (PPG) (and from that, HR can be inferred) [31 (link)]. The PPG sensor evaluates the volume of the passing blood along tissues using a photo-detector that computes the reflection coefficient of light (generated by PPG’s light source) from the skin [32 (link)]. The sampling rate of BVP is 64 Hz. The E4 is also equipped with an infrared thermopile sensor that reads peripheral skin temperature (with a frequency sampling rate of 4 Hz) [33 ].
An activity log was kept by the patients that contained their self-reports of time past from the latest dose, sleep, and ON/OFF reports performed every 30 minutes while wearing the device for a period of 24 hours. A report of “OFF” from any patient meant that he/she felt the urge for the medication, and “ON” had the opposite interpretation. They were instructed to carry out normal daily activities while being careful not to dislodge the electrodes and avoiding exposing the device to water. The E4 data were downloaded from the device later offline. For this proof-of-principle study, we restricted ourselves to the 12 subjects who documented “OFF” states in their diary. The other 13 subjects declared they had WO episodes but had failed to record this in their diary.
Arasteh E., Mirian M.S., Verchere W.D., Surathi P., Nene D., Allahdadian S., Doo M., Park K.W., Ray S, & McKeown M.J. (2023). An Individualized Multi-Modal Approach for Detection of Medication “Off” Episodes in Parkinson’s Disease via Wearable Sensors. Journal of Personalized Medicine, 13(2), 265.
Publication 2023
Anticholinergic Agents Antidepressive Agents Autonomic Nervous System Disorders Blood Volume Brain Brain Diseases Deep Brain Stimulation Diagnosis Disorders, Cognitive Epilepsy Feelings Levodopa Light Medical Devices Mood Movement Movement Disorders Nervous System, Autonomic Ovum Implantation Parkinson Disease Parkinsonian Disorders Patients Pharmaceutical Preparations Photoplethysmography Polyneuropathy Reflex Silver Skin Skin Diseases Skin Temperature Sleep Specialists Spinal Cord Diseases Thyroid Gland Tissues

Top products related to «Deep Brain Stimulation»

1
Vercise deep brain stimulation system by Boston Scientific
The Vercise Deep Brain Stimulation System is a medical device designed for the treatment of movement disorders. It consists of a battery-powered implantable pulse generator, leads, and a programmer. The system delivers electrical stimulation to targeted areas of the brain to help manage symptoms associated with certain neurological conditions.
2
Model 3389 by Medtronic
Sourced in United States
The Medtronic Model 3389 is a laboratory equipment designed for precise measurement and monitoring. It is capable of performing various diagnostic and analytical tasks within a controlled environment. The device's core function is to provide accurate and reliable data for research and testing purposes.
3
Neuroinspire v6 by Renishaw
Neuroinspire v6 is a software suite developed by Renishaw for the analysis and visualization of neurophysiological data. The software provides tools for recording, processing, and interpreting neural signals acquired from a variety of sources, including electroencephalography (EEG), electrocorticography (ECoG), and single-unit recordings.
4
Lead dbs v2 by Renishaw
Lead-DBS (v2.0) is a medical device designed for deep brain stimulation (DBS) procedures. It is a lead that is implanted in the patient's brain to deliver electrical stimulation to targeted areas. The device is intended for use by qualified medical professionals during DBS procedures.
5
Sense parallel imaging technique by Philips
SENSE parallel imaging technique is a method developed by Philips for accelerating magnetic resonance imaging (MRI) data acquisition. It utilizes the simultaneous use of multiple receiver coils to acquire MRI data in parallel, allowing for a reduction in the required number of phase-encoding steps and thus shorter scan times.
6
Dmem f12 by Merck Group
Sourced in United States, Germany, United Kingdom, Japan, Italy, France, Israel, China, Sao Tome and Principe, Macao, Ireland, Switzerland, Canada, Poland, Brazil, Australia, India, Portugal
DMEM/F12 is a cell culture medium used to support the growth and maintenance of a variety of cell types. It is a widely used basal medium that provides essential nutrients, vitamins, and other components required for cell proliferation and viability. The formulation is a combination of Dulbecco's Modified Eagle's Medium (DMEM) and Ham's F-12 Nutrient Mixture, providing a balanced composition of amino acids, vitamins, and other essential elements.
7
Rimadyl by Pfizer
Sourced in United States, United Kingdom, Germany, Denmark, Switzerland, Italy, Australia
Rimadyl is a veterinary pharmaceutical product manufactured by Pfizer. It is a non-steroidal anti-inflammatory drug (NSAID) used to reduce inflammation and pain in dogs and cats. The active ingredient in Rimadyl is carprofen.
8
Stereotaxic platform by Kopf Instruments
Sourced in United States
The Stereotaxic platform is a lab equipment designed for precision positioning and stabilization of small animal specimens during neuroscience experiments. It provides a stable and adjustable framework to securely hold the subject's head in a fixed orientation.
9
Model 2200 by A-M Systems
Sourced in United States
The Model 2200 is a high-precision electrical stimulator designed for a variety of laboratory applications. It features adjustable current and voltage outputs, and supports both constant current and constant voltage modes of operation.
10
Multiphysics v4 by Comsol
COMSOL Multiphysics v4.4 is a software package for modeling and simulating physics-based problems. It provides a platform for the integrated simulation of designs, devices, and processes in all fields of engineering, manufacturing, and scientific research.

More about "Deep Brain Stimulation"

Deep Brain Stimulation (DBS) is a cutting-edge neurosurgical procedure that involves the implantation of a specialized medical device to deliver electrical stimulation to targeted regions within the brain.
This transformative technique has emerged as a highly effective treatment option for a wide range of neurological disorders, including Parkinson's disease, essential tremor, and obsessive-compulsive disorder.
The optimization of research protocols is crucial for enhancing the reproducibility and accuracy of DBS studies.
Researchers can leverage the comprehensive suite of AI-driven tools and analytics offered by PubCompare.ai to streamline their DBS research process.
This platform enables users to locate the best protocols from literature, preprints, and patents, and identify the most effective DBS treatments and products.
The Vercise Deep Brain Stimulation System, Model 3389, is a cutting-edge DBS device that delivers precise and targeted electrical stimulation to the brain.
Paired with the Neuroinspire v6 software, this system provides researchers and clinicians with advanced capabilities for planning, visualizing, and guiding the DBS implantation procedure.
The Lead-DBS (v2.0) software is another powerful tool that supports researchers in the analysis and visualization of DBS lead placements.
This software leverages the SENSE parallel imaging technique to facilitate high-quality imaging and enhance the accuracy of lead localization.
In addition to these specialized tools, researchers may also utilize cell culture media such as DMEM/F12 and pharmacological agents like Rimadyl to support their DBS studies.
The use of a stereotaxic platform, such as Model 2200, can further enhance the precision and reproducibility of DBS implantation procedures.
Ultimately, the comprehensive resources and advanced analytics provided by PubCompare.ai, combined with the innovative DBS technologies and research tools, contribute to the advancement of this transformative medical intervention, ultimately improving patient outcomes and quality of life.