Structural connectivity of low-frequency subthalamic stimulation for improving stride length in Parkinson's disease

BACKGROUND

A reduction in stride length is considered a key characteristic of gait kinematics in Parkinson's disease (PD) and has been identified as a predictor of falls. Although low-frequency stimulation (LFS) has been suggested as a method to improve gait characteristics, the underlying structural network is not well understood.

OBJECTIVE

This study aims to investigate the structural correlates of changes in stride length during LFS (85 Hz).

METHODS

Objective gait performance was retrospectively evaluated in 19 PD patients who underwent deep brain stimulation (DBS) at 85 Hz and 130 Hz. Individual DBS contacts and volumes of activated tissue (VAT) were computed using preoperative magnetic resonance imaging (MRI) and postoperative computed tomography (CT) scans. Structural connectivity profiles to predetermined cortical and mesencephalic areas were estimated using a normative connectome.

RESULTS

LFS led to a significant improvement in stride length compared to 130 Hz stimulation. The intersection between VAT and the associative subregion of the subthalamic nucleus (STN) was associated with an improvement in stride length and had structural connections to the supplementary motor area, prefrontal cortex, and pedunculopontine nucleus. Conversely, we found that a lack of improvement was linked to stimulation volumes connected to cortico-diencephalic fibers bypassing the STN dorsolaterally. The robustness of the connectivity model was verified through leave-one-patient-out, 5-, and 10-fold cross cross-validation paradigms.

CONCLUSION

These findings offer new insights into the structural connectivity that underlies gait changes following LFS. Targeting the non-motor subregion of the STN with LFS on an individual level may present a potential therapeutic approach for PD patients with gait disorders.

Subthalamic 85 Hz deep brain stimulation improves walking pace and stride length in Parkinson's disease patients

BACKGROUND

Mobile gait sensors represent a compelling tool to objectify the severity of symptoms in patients with idiopathic Parkinson's disease (iPD), but also to determine the therapeutic benefit of interventions. In particular, parameters of Deep Brain stimulation (DBS) with its short latency could be accurately assessed using sensor data. This study aimed at gaining insight into gait changes due to different DBS parameters in patients with subthalamic nucleus (STN) DBS.

METHODS

An analysis of various gait examinations was performed on 23 of the initially enrolled 27 iPD patients with chronic STN DBS. Stimulation settings were previously adjusted for either amplitude, frequency, or pulse width in a randomised order. A linear mixed effects model was used to analyse changes in gait speed, stride length, and maximum sensor lift.

RESULTS

The findings of our study indicate significant improvements in gait speed, stride length, and leg lift measurable with mobile gait sensors under different DBS parameter variations. Notably, we observed positive results at 85 Hz, which proved to be more effective than often applied higher frequencies and that these improvements were traceable across almost all conditions. While pulse widths did produce some improvements in leg lift, they were less well tolerated and had inconsistent effects on some of the gait parameters. Our research suggests that using lower frequencies of DBS may offer a more tolerable and effective approach to enhancing gait in individuals with iPD.

CONCLUSIONS

Our results advocate for lower stimulation frequencies for patients who report gait difficulties, especially those who can adapt their DBS settings remotely. They also show that mobile gait sensors could be incorporated into clinical practice in the near future.

Prediction of Movement Ratings and Deep Brain Stimulation Parameters in Idiopathic Parkinson's Disease

BACKGROUND

Deep brain stimulation (DBS) parameter fine-tuning after lead implantation is laborious work because of the almost uncountable possible combinations. Patients and practitioners often gain the perception that assistive devices could be beneficial for adjusting settings effectively.

OBJECTIVE

We aimed at a proof-of-principle study to assess the benefits of noninvasive movement recordings as a means to predict best DBS settings.

MATERIALS AND METHODS

For this study, 32 patients with idiopathic Parkinson's disease, under chronic subthalamic nucleus stimulation with directional leads, were recorded. During monopolar review, each available contact was activated with currents between 0.5 and 5 mA, and diadochokinesia, rigidity, and tapping ability were rated clinically. Moreover, participants' movements were measured during four simple hand movement tasks while wearing a commercially available armband carrying an inertial measurement unit (IMU). We trained random forest models to learn the relations between clinical ratings, electrode settings, and movement features obtained from the IMU.

RESULTS

Firstly, we could show that clinical mobility ratings can be predicted from IMU features with correlations of up to r = 0.68 between true and predicted values. Secondly, these features also enabled a prediction of DBS parameters, which showed correlations of up to approximately r = 0.8 with clinically optimal DBS settings and were associated with congruent volumes of tissue activated.

CONCLUSION

Movement recordings from customer-grade mobile IMU carrying devices are promising candidates, not only for remote symptom assessment but also for closed-loop DBS parameter adjustment, and could thus extend the list of available aids for effective programming beyond imaging techniques.

Diffusion magnetic resonance imaging connectome features are predictive of functional lateralization of semantic processing in the anterior temporal lobes

Assessment of regional language lateralization is crucial in many scenarios, but not all populations are suited for its evaluation via task-functional magnetic resonance imaging (fMRI). In this study, the utility of structural connectome features for the classification of language lateralization in the anterior temporal lobes (ATLs) was investigated. Laterality indices for semantic processing in the ATL were computed from task-fMRI in 1038 subjects from the Human Connectome Project who were labeled as stronger rightward lateralized (RL) or stronger leftward to bilaterally lateralized (LL) in a data-driven approach. Data of unrelated subjects (n = 432) were used for further analyses. Structural connectomes were generated from diffusion-MRI tractography, and graph theoretical metrics (node degree, betweenness centrality) were computed. A neural network (NN) and a random forest (RF) classifier were trained on these metrics to classify subjects as RL or LL. After classification, comparisons of network measures were conducted via permutation testing. Degree-based classifiers produced significant above-chance predictions both during cross-validation (NN: AUC-ROC[CI] = 0.68[0.64-0.73], accuracy[CI] = 68.34%[63-73.2%]; RF: AUC-ROC[CI] = 0.7[0.66-0.73], accuracy[CI] = 64.81%[60.9-68.5]) and testing (NN: AUC-ROC[CI] = 0.69[0.53-0.84], accuracy[CI] = 68.09[53.2-80.9]; RF: AUC-ROC[CI] = 0.68[0.53-0.84], accuracy[CI] = 68.09[55.3-80.9]). Comparison of network metrics revealed small effects of increased node degree within the right posterior middle temporal gyrus (pMTG) in subjects with RL, while degree was decreased in the right posterior cingulate cortex (PCC). Above-chance predictions of functional language lateralization in the ATL are possible based on diffusion-MRI connectomes alone. Increased degree within the right pMTG as a right-sided homologue of a known semantic hub, and decreased hubness of the right PCC may form a structural basis for rightward-lateralized semantic processing.

Prediction of motor Unified Parkinson's Disease Rating Scale scores in patients with Parkinson's disease using surface electromyography

OBJECTIVE

Parkinson's disease (PD) is a chronic neurodegenerative disorder with increasing prevalence in the elderly. Especially patients with advanced PD often require complex medication regimens due to fluctuations, that is abrupt transitions from ON to OFF or vice versa. Current gold standard to quantify PD-patients' motor symptoms is the assessment of the Unified Parkinson's Disease Rating Scale (UPDRS), which, however, is cumbersome and may depend upon investigators. This work aimed at developing a mobile, objective and unobtrusive measurement of motor symptoms in PD.

METHODS

Data from 45 PD-patients was recorded using surface electromyography (sEMG) electrodes attached to a wristband. The motor paradigm consisted of a tapping task performed with and without dopaminergic medication. Our aim was to predict UPDRS scores from the sEMG characteristics with distinct regression models and machine learning techniques.

RESULTS

A random forest regression model outnumbered other regression models resulting in a correlation of 0.739 between true and predicted UPDRS values.

CONCLUSIONS

PD-patients' motor affection can be extrapolated from sEMG data during a simple tapping task. In the future, such records could help determine the need for medication changes in telemedicine applications.

SIGNIFICANCE

Our findings support the utility of wearables to detect Parkinson's symptoms and could help in developing tailored therapies in the future.

Machine Learning Techniques for Parkinson’s Disease Detection using Wearables during a Timed-up-and-Go-Test

In this paper, the classification models for Idiopathic Parkinson's syndrome (iPS) detection through timed-up-and-go test performed on iPS-patients are given. The models are based on the supervised learning. The data are extracted via Myo gesture armband worn on two hands. The corresponding models are based on extracted features from signal data and raw signal data respectively. The achieved accuracy from both models are 0.91 and 0.93 with reasonable specificity and sensitivity.

[Remote assessment of idiopathic Parkinson's disease : Developments in diagnostics, monitoring and treatment]

The idiopathic Parkinson's disease (iPD) is a progressive neurodegenerative disorder primarily resulting in impaired movement execution. In the course of the disease symptom fluctuation is common and makes adequate treatment difficult. In this overview the current approaches using modern and especially mobile technologies for diagnosis, monitoring and treatment of iPD are presented. Currently, there are no medical aids ready for point of care application; however, the development of these technologies has great potential for improving care for patients suffering from iPD.

Standard value of ultrasound elastography using acoustic radiation force impulse imaging (ARFI) in healthy liver tissue of children and adolescents

PURPOSE

Ultrasound elastography by acoustic radiation force impulse imaging (ARFI) is used in adults for non invasive measurement of liver stiffness, indicating liver diseases like fibrosis. To establish ARFI in children and adolescents we determined standard values of healthy liver tissue and analysed potentially influencing factors.

MATERIALS AND METHODS

132 patients between 0 and 17 years old were measured using ARFI. None of them had any liver disease or any other disease that could affect the liver secondarily. All patients had a normal ultrasound scan, a normal BMI and normal liver function tests. The mean value of all ARFI measurements was calculated and potentially influencing factors were analysed.

RESULTS

The mean value of all ARFI elastography measurements was 1.16 m/sec (SD ± 0.14 m/sec). Neither age (p = 0.533) nor depth of measurement (p = 0.066) had no significant influence on ARFI values, whereas a significant effect of gender was found with lower ARFI values in females (p = 0.025), however, there was no significant interaction between age groups (before or after puberty) and gender (p = 0.276). There was an interlobar difference with lower values in the right liver lobe compared to the left (p = 0.036) and with a significantly lower variance (p < 0.001). Consistend values were measured by different examiners (p = 0.108), however, the inter examiner variance deviated significantly (p < 0.001).

CONCLUSION

ARFI elastography is a reliable method to measure liver stiffness in children and adolescents. In relation to studies which analyse liver diseases, the standard value of 1.16 m/sec (± 0.14 m/sec) allows a differentiation of healthy versus pathological liver tissue.

Does bimanual grasping of the Müller-Lyer illusion provide evidence for a functional segregation of dorsal and ventral streams?

Studies claiming a differential processing of visual illusions for perception and action have been subjected to many challenges. One criticism is that attentional demands were mismatched between the perception and action tasks. Dewar and Carey (2006) reexamined this argument by comparing bimanual grasping to bimanual size estimation and concluded that manual size estimation (ManEst) was affected by the illusion to a greater extent than grasping, supporting the case for two functionally distinct streams of visual processing. We tested whether this result may be due to their use of closed loop visual conditions by replicating their study under both closed and open loop conditions. We found that the difference in illusion effects between grasping and ManEst disappeared under open loop conditions, indicating that Dewar and Carey's findings can be explained by the availability of visual feedback and not a perception/action dissociation. We also discuss potential shortcomings of bimanual designs.

Grasping isoluminant stimuli

We used a virtual reality setup to let participants grasp discs, which differed in luminance, chromaticity and size. Current theories on perception and action propose a division of labor in the brain into a color proficient perception pathway and a less color-capable action pathway. In this study, we addressed the question whether isoluminant stimuli, which provide only a chromatic but no luminance contrast for action planning, are harder to grasp than stimuli providing luminance contrast or both kinds of contrast. Although we found that grasps of isoluminant stimuli had a slightly steeper slope relating the maximum grip aperture to disc size, all other measures of grip quality were unaffected. Overall, our results do not support the view that isoluminance of stimulus and background impedes the planning of a grasping movement.

Grasping trapezoidal objects

When grasping rectangular or circular objects with a precision grip the digits close in on the object in opposite directions. In doing so the digits move perpendicular to the local surface orientation as they approach opposite sides of the object. This perpendicular approach is advantageous for accurately placing the digits. Trapezoidal objects have non-parallel surfaces so that moving the digits in opposite directions would make the digits approach the contact surfaces at an angle that is not 90°. In this study we examined whether this happens, or whether subjects tend to approach trapezoidal objects’ surfaces perpendicularly. We used objects of different sizes and with different surface slants. Subjects tended to approach the object’s surfaces orthogonally, suggesting that they aim for an optimal precision of digit placement rather than simply closing their hand as it reaches the object.