Artificial neural network for brain-machine interface consistently produces more naturalistic finger movements than linear methods.

Brain-machine interfaces (BMI) aim to restore function to persons living with spinal cord injuries by 'decoding' neural signals into behavior. Recently, nonlinear BMI decoders have outperformed previous state-of-the-art linear decoders, but few studies have investigated what specific improvements these nonlinear approaches provide. In this study, we compare how temporally convolved feedforward neural networks (tcFNNs) and linear approaches predict individuated finger movements in open and closed-loop settings. We show that nonlinear decoders generate more naturalistic movements, producing distributions of velocities 85.3% closer to true hand control than linear decoders. Addressing concerns that neural networks may come to inconsistent solutions, we find that regularization techniques improve the consistency of tcFNN convergence by 194.6%, along with improving average performance, and training speed. Finally, we show that tcFNN can leverage training data from multiple task variations to improve generalization. The results of this study show that nonlinear methods produce more naturalistic movements and show potential for generalizing over less constrained tasks. Teaser: A neural network decoder produces consistent naturalistic movements and shows potential for real-world generalization through task variations.

Effect of anisotropic brain conductivity on patient-specific volume of tissue activation in deep brain stimulation for Parkinson disease.

OBJECTIVE: Deep brain stimulation (DBS) modeling can improve surgical targeting by quantifying the spatial extent of stimulation relative to subcortical structures of interest. A certain degree of model complexity is required to obtain accurate predictions, particularly complexity regarding electrical properties of the tissue around DBS electrodes. In this study, the effect of anisotropy on the volume of tissue activation (VTA) was evaluated in an individualized manner. METHODS: Tissue activation models incorporating patient-specific tissue conductivity were built for 40 Parkinson disease patients who had received bilateral subthalamic nucleus (STN) DBS. To assess the impact of local changes in tissue anisotropy, one VTA was computed at each electrode contact using identical stimulation parameters. For comparison, VTAs were also computed assuming isotropic tissue conductivity. Stimulation location was considered by classifying the anisotropic VTAs relative to the STN. VTAs were characterized based on volume, spread in three directions, sphericity, and Dice coefficient. RESULTS: Incorporating anisotropy generated significantly larger and less spherical VTAs overall. However, its effect on VTA size and shape was variable and more nuanced at the individual patient and implantation levels. Dorsal VTAs had significantly higher sphericity than ventral VTAs, suggesting more isotropic behavior. Contrastingly, lateral and posterior VTAs had significantly larger and smaller lateral-medial spreads, respectively. Volume and spread correlated negatively with sphericity. CONCLUSION: The influence of anisotropy on VTA predictions is important to consider, and varies across patients and stimulation location. SIGNIFICANCE: This study highlights the importance of considering individualized factors in DBS modeling to accurately characterize the VTA.

Impact of subthalamic nucleus stimulation on urinary dysfunction and constipation in Parkinson's disease.

OBJECTIVE: The effect of subthalamic nucleus (STN) deep brain stimulation (DBS) on urinary dysfunction and constipation in Parkinson's disease (PD) is variable. This study aimed to identify potential surgical and nonsurgical variables predictive of these outcomes. METHODS: The authors used the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part I to assess urinary dysfunction (item 10) and constipation (item 11) preoperatively and at 6-12 months postoperatively. A multiple linear regression model was used to investigate the impact of global cerebral atrophy (GCA) and active electrode contact location on the urinary dysfunction and constipation follow-up scores, controlling for age, disease duration, baseline score, motor improvement, and levodopa-equivalent dose changes. An electric field model was applied to localize the maximal-effect sites for constipation and urinary dysfunction compared with those for motor improvement. RESULTS: Among 74 patients, 23 improved, 28 deteriorated, and 23 remained unchanged for urinary dysfunction; 25 improved, 15 deteriorated, and 34 remained unchanged for constipation. GCA score and age significantly predicted urinary dysfunction follow-up score (R2 = 0.36, p < 0.001). Increased GCA and age were independently associated with worsening urinary symptoms. Disease duration, baseline constipation score, and anterior active electrode contacts in both hemispheres were significant predictors of constipation follow-up score (R2 = 0.31, p < 0.001). Higher baseline constipation score and disease duration were associated with worsening constipation; anterior active contact location was associated with improvement in constipation. CONCLUSIONS: Anterior active contact location was associated with improvement in constipation in PD patients after STN DBS. PD patients with greater GCA scores before surgery were more likely to experience urinary deterioration after DBS.

Electrical Stimulation of Regenerative Peripheral Nerve Interfaces (RPNIs) Induces Referred Sensations in People With Upper Limb Loss.

Individuals with upper limb loss lack sensation of the missing hand, which can negatively impact their daily function. Several groups have attempted to restore this sensation through electrical stimulation of residual nerves. The purpose of this study was to explore the utility of regenerative peripheral nerve interfaces (RPNIs) in eliciting referred sensation. In four participants with upper limb loss, we characterized the quality and location of sensation elicited through electrical stimulation of RPNIs over time. We also measured functional stimulation ranges (sensory perception and discomfort thresholds), sensitivity to changes in stimulation amplitude, and ability to differentiate objects of different stiffness and sizes. Over a period of up to 54 months, stimulation of RPNIs elicited sensations that were consistent in quality (e.g. tingling, kinesthesia) and were perceived in the missing hand and forearm. The location of elicited sensation was partially-stable to stable in 13 of 14 RPNIs. For 5 of 7 RPNIs tested, participants demonstrated a sensitivity to changes in stimulation amplitude, with an average just noticeable difference of 45 nC. In a case study, one participant was provided RPNI stimulation proportional to prosthetic grip force. She identified four objects of different sizes and stiffness with 56% accuracy with stimulation alone and 100% accuracy when stimulation was combined with visual feedback of hand position. Collectively, these experiments suggest that RPNIs have the potential to be used in future bi-directional prosthetic systems.

Clinical and immunological responses to COVID-19 vaccination in rheumatoid arthritis patients on disease modifying antirheumatic drugs: a cross-sectional study.

Objective: This study was conducted to investigate the immunological and clinical response to COVID-19 vaccination in rheumatoid arthritis (RA) patients receiving disease modifying antirheumatic drugs (DMARDs). Methods: A cross-sectional study was conducted among RA patients who received two doses of COVID-19 vaccine within 6 months to one year. Demographic information, comorbidities, vaccination details, and past COVID-19 infection details were collected. Hemoglobin (Hb), erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and interleukin-6 (IL-6) levels were estimated. Disease Activity Score-28 (DAS-28) was calculated for RA patients. Anti-spike antibody (ASA) concentrations were measured, and compared with a healthy control population. Correlations of ASA with age, sex, disease parameters, medication use, and comorbidities were assessed. Results: A total of 103 RA patients and 185 controls were included in the study. RA patients had higher mean age, lower mean Hb, higher ESR, and elevated IL-6 levels. Both groups showed positive results for anti-spike antibodies, with a higher percentage in controls. Among RA patients majority had low DAS-28 score. The number of DMARDs used showed a negative correlation with antibody levels. There was a slight positive correlation between ASA concentration and DAS-28 score. Comorbidities did not significantly influence antibody concentration. No significant differences were found in antibody levels based on the type of COVID-19 vaccine or previous COVID-19 infection or booster dose vaccination among RA patients. Conclusion: The study revealed that RA patients showed a reduced antibody response following COVID-19 vaccination compared to the control group and potentially influenced by immunosuppressive treatments and disease-related factors.

Tranexamic acid (class I drug) reduced and capped gold nanoparticles as a potential hemostatic agent with enhanced performance.

External hemostatic agents play a crucial role in stabilizing an impaired process during pathological conditions. The idea is to stabilize thein vivosystem as soon as possible. This study uses a class I hemostatic drug tranexamic acid as a reducing and capping agent for synthesizing the gold nanoparticles (Tr-AuNPs). Being the synthetic analogue of lysine and a biologically inspired alkylamine molecule, the chemistry can be fine-tuned for stable material that can simultaneously target the intrinsic and extrinsic hemostatic pathway, making it promising for hemostatic applications. The Tr-AuNPs of hydrodynamic diameter ∼46 nm were synthesized and evaluated physio-chemically using various analytical techniques wherein they showed hemocompatibility and increased thrombus weight compared to the native drug. The decrease in prothrombin time (PT) and international normalized ratio supported by the dynamic thromboelastography (TEG) study indicates the prepared nano-conjugate's potential in reducing time for attaining hemostasis as compared to the native tranexamic acid drug. At a 9µg ml-1concentration, Tr-AuNPs had a procoagulant effect, shown by decreased reaction time (R) and coagulation time (K) with improvedαangle and MA. There was a significant increase in the rate of coagulationin vivoby Tr-AuNPs, i.e. (52 s) compared to the native tranexamic acid (360 s). Radiolabelling studies ascertained thein vivobiocompatibility (non-invasive distribution, residence, clearance, and stability) of the Tr-AuNPs. The short-term toxicity studies were conducted to establish a proof of concept for the biomedical application of the material. The results highlighted the use of biologically alkyl amine molecules as capping and reducing agents for the synthesis of nanoparticles, which have shown a synergistic effect on the coagulation cascade while holding the potential for also acting as potential theranostic agents.

Dorsal subthalamic deep brain stimulation improves pain in Parkinson's disease.

Introduction: Inconsistent effects of subthalamic deep brain stimulation (STN DBS) on pain, a common non-motor symptom of Parkinson's disease (PD), may be due to variations in active contact location relative to some pain-reducing locus of stimulation. This study models and compares the loci of maximal effect for pain reduction and motor improvement in STN DBS. Methods: We measured Movement Disorder Society Unified PD Rating Scale (MDS-UPDRS) Part I pain score (item-9), and MDS-UPDRS Part III motor score, preoperatively and 6-12 months after STN DBS. An ordinary least-squares regression model was used to examine active contact location as a predictor of follow-up pain score while controlling for baseline pain, age, dopaminergic medication, and motor improvement. An atlas-independent isotropic electric field model was applied to distinguish sites of maximally effective stimulation for pain and motor improvement. Results: In 74 PD patients, mean pain score significantly improved after STN DBS (p = 0.01). In a regression model, more dorsal active contact location was the only significant predictor of pain improvement (R2 = 0.17, p = 0.03). The stimulation locus for maximal pain improvement was lateral, anterior, and dorsal to that for maximal motor improvement. Conclusion: STN stimulation, dorsal to the site of optimal motor improvement, improves pain. This region contains the zona incerta, which is known to modulate pain in humans, and may explain this observation.

Assessment of the Number of Phlebotomists in a Newly Established Sample Collection Center.

INTRODUCTION: Phlebotomy, i.e., the collection of blood samples, is one of the most commonly performed procedures in almost all hospital settings. The phlebotomy center is the first point of contact for patient samples with the laboratory services. The patient load visiting the phlebotomy center of a rapidly developing hospital is very variable and unpredictable. This leads to staffing issues related to a number of phlebotomists. The actual phlebotomy procedure requires only a few minutes, but the total time includes the patient's arrival to departure from the phlebotomy center. In this study, we have attempted to assess the adequacy of the number of phlebotomists in our sample collection center and to determine how many patients can be attended to comfortably by each phlebotomist. As the sample load increases, the burden on phlebotomists also increases, and they may or may not express the strain of it. We attempted to determine the cut-off patient numbers above which request for additional personnel has to be put into the hospital administration. MATERIALS AND METHODS: This was a prospective, hospital-based, observational study carried out in the outpatient sample collection center section at the All India Institute of Medical Sciences, Bibinagar, Telangana, over a period of one month, i.e., December 2022. The movement of 1200 patients was observed for the phlebotomy procedure. Patient details, the time taken for registration, waiting time, and phlebotomy time were noted, along with the hindering factors in the phlebotomy center. OBSERVATIONS AND RESULTS: There were 680 males and 520 females. The mean time for patient arrival to departure from the phlebotomy center and the mean waiting time was 9.8 minutes and 6.5 minutes, respectively. Various reasons for increased phlebotomy time were pediatric patients, anxious patients, postprandial sample patients, difficulty in finding veins, etc. Though the estimated capacity of the phlebotomy center is apparently satisfactory with four personnel, many hidden causes for time loss were observed.  Conclusion: An adequate number of trained and effective phlebotomists is the first step in ensuring the success of any laboratory service, and while deciding on this "adequate number," not only the direct effort, but also the indirect effort, operational needs and emergencies have to be kept in mind. Each phlebotomist in a six-hour shift can comfortably attend 30 to 35 outpatients for phlebotomy. When this number exceeds it, additional staff has to be added. Adopting measures to reduce the waiting time for phlebotomy procedures will improve the phlebotomy center's service. The study provides a basis for the modification of a number of phlebotomists in order to ensure optimal patient service.

Error detection and correction in intracortical brain-machine interfaces controlling two finger groups.

Objective.While brain-machine interfaces (BMIs) are promising technologies that could provide direct pathways for controlling the external world and thus regaining motor capabilities, their effectiveness is hampered by decoding errors. Previous research has demonstrated the detection and correction of BMI outcome errors, which occur at the end of trials. Here we focus on continuous detection and correction of BMI execution errors, which occur during real-time movements.Approach.Two adult male rhesus macaques were implanted with Utah arrays in the motor cortex. The monkeys performed single or two-finger group BMI tasks where a Kalman filter decoded binned spiking-band power into intended finger kinematics. Neural activity was analyzed to determine how it depends not only on the kinematics of the fingers, but also on the distance of each finger-group to its target. We developed a method to detect erroneous movements, i.e. consistent movements away from the target, from the same neural activity used by the Kalman filter. Detected errors were corrected by a simple stopping strategy, and the effect on performance was evaluated.Mainresults.First we show that including distance to target explains significantly more variance of the recorded neural activity. Then, for the first time, we demonstrate that neural activity in motor cortex can be used to detect execution errors during BMI controlled movements. Keeping false positive rate below5%, it was possible to achieve mean true positive rate of28.1%online. Despite requiring 200 ms to detect and react to suspected errors, we were able to achieve a significant improvement in task performance via reduced orbiting time of one finger group.Significance.Neural activity recorded in motor cortex for BMI control can be used to detect and correct BMI errors and thus to improve performance. Further improvements may be obtained by enhancing classification and correction strategies.

Evaluation of Citrated Plasma After Thawing for Routine Coagulation Testing.

OBJECTIVE: We aim to find the time in which a thawed citrate plasma sample that was preserved can be analyzed for routine coagulation testing without losing precision. METHODS: Whole blood samples from 30 healthy volunteers were collected in 3.2% sodium citrate vacutainer and centrifuged to separate platelet-poor plasma. Each sample was then aliquoted, one aliquot was used immediately for prothrombin time (PT)-international normalized ratio (INR) and activated partial thromboplastin time (APTT), four were stored at -20°C, and four were stored at -80°C for 24 hours. After 24 hours, the aliquots were taken out and thawed at 37°C in water bath and analyzed after 15, 30, 60, and 120 minutes. STATISTICAL ANALYSIS: Data were presented as mean with standard deviation (SD). Repeated measures ANOVA with Tukey post-hoc test was performed for multiple comparisons. All analysis was done using GraphPAD Prism 8.0 software (GraphPad Software, San Diego, California, USA).  Results: In the case of PT and INR, no statistically significant difference was found between the mean values after thawing for 120 minutes when compared with the mean baseline value. However, the APTT showed a statistically significant difference (p = 0.0232) after 30 minutes of thawing when the sample was stored at -20°C. Furthermore, a statistically significance difference (p = 0.0001) was found after 60 minutes of thawing when the samples were stored at -80°C. CONCLUSION: Plasma samples for the PT and INR may be accepted for assessment up to 120 minutes, when stored at -20°C and -80°C for 24 hours. In the case of APTT, the plasma sample can be used for assessment up to 30 minutes after thawing when stored at -20°C and up to 60 minutes when stored at -80°C.

Balancing Memorization and Generalization in RNNs for High Performance Brain-Machine Interfaces.

Brain-machine interfaces (BMIs) can restore motor function to people with paralysis but are currently limited by the accuracy of real-time decoding algorithms. Recurrent neural networks (RNNs) using modern training techniques have shown promise in accurately predicting movements from neural signals but have yet to be rigorously evaluated against other decoding algorithms in a closed-loop setting. Here we compared RNNs to other neural network architectures in real-time, continuous decoding of finger movements using intracortical signals from nonhuman primates. Across one and two finger online tasks, LSTMs (a type of RNN) outperformed convolutional and transformer-based neural networks, averaging 18% higher throughput than the convolution network. On simplified tasks with a reduced movement set, RNN decoders were allowed to memorize movement patterns and matched able-bodied control. Performance gradually dropped as the number of distinct movements increased but did not go below fully continuous decoder performance. Finally, in a two-finger task where one degree-of-freedom had poor input signals, we recovered functional control using RNNs trained to act both like a movement classifier and continuous decoder. Our results suggest that RNNs can enable functional real-time BMI control by learning and generating accurate movement patterns.

The impact of task context on predicting finger movements in a brain-machine interface.

A key factor in the clinical translation of brain-machine interfaces (BMIs) for restoring hand motor function will be their robustness to changes in a task. With functional electrical stimulation (FES) for example, the patient's own hand will be used to produce a wide range of forces in otherwise similar movements. To investigate the impact of task changes on BMI performance, we trained two rhesus macaques to control a virtual hand with their physical hand while we added springs to each finger group (index or middle-ring-small) or altered their wrist posture. Using simultaneously recorded intracortical neural activity, finger positions, and electromyography, we found that decoders trained in one context did not generalize well to other contexts, leading to significant increases in prediction error, especially for muscle activations. However, with respect to online BMI control of the virtual hand, changing either the decoder training task context or the hand's physical context during online control had little effect on online performance. We explain this dichotomy by showing that the structure of neural population activity remained similar in new contexts, which could allow for fast adjustment online. Additionally, we found that neural activity shifted trajectories proportional to the required muscle activation in new contexts. This shift in neural activity possibly explains biases to off-context kinematic predictions and suggests a feature that could help predict different magnitude muscle activations while producing similar kinematics.

Anti-spike Antibody Status in Pre-vaccinated Healthy Participants and Rheumatoid Arthritis Patients During the Third Wave of COVID-19.

Introduction Anti-spike severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies produced after infection with the coronavirus disease of 2019 (COVID-19) will offer protection and prevent re-infection for a few months. Seroprevalence studies measuring the SARS­CoV-2 immunoglobulin G (IgG) levels will be helpful to know the herd immunity level that prevents community transmission. Very few studies have addressed the antibody titer among healthy participants and rheumatoid arthritis (RA) patients. The present study was conducted to determine the anti-spike SARS-CoV-2 antibody (Ab) status before COVID-19 vaccination in healthy participants and RA patients. Methodology A cross-sectional study was conducted at a tertiary care hospital to estimate the serum anti-spike antibody levels against COVID-19 among the pre-vaccinated healthy participants and patients with RA during the third wave of COVID-19. After receiving written informed consent, participants were recruited as per the inclusion and exclusion criteria. Demographic details, co-morbid status, and medication details were collected. Five milliliters of blood samples were collected, and anti-spike antibodies were estimated. The SARS-CoV-2 Ab positivity rate was expressed in percentage and was correlated with gender and age groups. Ab-positive participants were classified into three categories based on the neutralizing antibody titers (NAT). Results A total of 58 participants (49 healthy volunteers and nine RA patients) were recruited. Out of 58 participants, 40 were males, nine were females among healthy participants, and one male and eight females in the RA group were enrolled. Among the RA patients, one participant was found to have the chronic obstructive pulmonary disease (COPD), and two participants with hypothyroidism. Antibody positivity was found to be 83.6% among the healthy volunteers and 100% in the RA patients. About 48% had NAT between 50 and 90%. There was no significant difference for age and gender-specific positivity for SARS-CoV-2 neutralizing antibodies and neutralizing antibody titers among healthy participants. Conclusion Our study showed 84% positivity for anti-spike SARS-CoV-2 antibodies around the third wave (between November 2021 and February 2022). The majority had high neutralizing antibody titers. The probable reason for the SARS-CoV-2 antibody positivity before vaccination was either asymptomatic infection or herd immunity.

Restoring continuous finger function with temporarily paralyzed nonhuman primates using brain-machine interfaces.

Objective.Brain-machine interfaces (BMIs) have shown promise in extracting upper extremity movement intention from the thoughts of nonhuman primates and people with tetraplegia. Attempts to restore a user's own hand and arm function have employed functional electrical stimulation (FES), but most work has restored discrete grasps. Little is known about how well FES can control continuous finger movements. Here, we use a low-power brain-controlled functional electrical stimulation (BCFES) system to restore continuous volitional control of finger positions to a monkey with a temporarily paralyzed hand.Approach.We delivered a nerve block to the median, radial, and ulnar nerves just proximal to the elbow to simulate finger paralysis, then used a closed-loop BMI to predict finger movements the monkey was attempting to make in two tasks. The BCFES task was one-dimensional in which all fingers moved together, and we used the BMI's predictions to control FES of the monkey's finger muscles. The virtual two-finger task was two-dimensional in which the index finger moved simultaneously and independently from the middle, ring, and small fingers, and we used the BMI's predictions to control movements of virtual fingers, with no FES.Main results.In the BCFES task, the monkey improved his success rate to 83% (1.5 s median acquisition time) when using the BCFES system during temporary paralysis from 8.8% (9.5 s median acquisition time, equal to the trial timeout) when attempting to use his temporarily paralyzed hand. In one monkey performing the virtual two-finger task with no FES, we found BMI performance (task success rate and completion time) could be completely recovered following temporary paralysis by executing recalibrated feedback-intention training one time.Significance.These results suggest that BCFES can restore continuous finger function during temporary paralysis using existing low-power technologies and brain-control may not be the limiting factor in a BCFES neuroprosthesis.

Localization of deep brain stimulation trajectories via automatic mapping of microelectrode recordings to MRI.

Objective. Suboptimal electrode placement during subthalamic nucleus deep brain stimulation (STN DBS) surgery may arise from several sources, including frame-based targeting errors and intraoperative brain shift. We present a computer algorithm that can accurately localize intraoperative microelectrode recording (MER) tracks on preoperative magnetic resonance imaging (MRI) in real-time, thereby predicting deviation between the surgical plan and the MER trajectories.Approach. Random forest (RF) modeling was used to derive a statistical relationship between electrophysiological features on intraoperative MER and voxel intensity on preoperative T2-weighted MR imaging. This model was integrated into a larger algorithm that can automatically localize intraoperative MER recording tracks on preoperative MRI in real-time. To verify accuracy, targeting error of both the planned intraoperative trajectory ('planned') and the algorithm-derived trajectory ('calculated') was estimated by measuring deviation from the final DBS lead location on postoperative high-resolution computed tomography ('actual').Main results. MR imaging and MERs were obtained from 24 STN DBS implant trajectories. The cross-validated RF model could accurately distinguish between gray and white matter regions along MER trajectories (AUC 0.84). When applying this model within the localization algorithm, thecalculatedMER trajectory estimate was found to be significantly closer to theactualDBS lead when compared to theplannedtrajectory recorded during surgery (1.04 mm vs 1.52 mm deviation,p< 0.002), with improvement shown in 19/24 cases (79%). When applying the algorithm to simulated DBS trajectory plans with randomized targeting error, up to 4 mm of error could be resolved to <2 mm on average (p< 0.0001).Significance. This work presents an automated system for intraoperative localization of electrodes during STN DBS surgery. This neuroengineering solution may enhance the accuracy of electrode position estimation, particularly in cases where high-resolution intraoperative imaging is not available.