Neuromagnetic investigations of mechanisms and effects of STN-DBS and medication in Parkinson's disease

Parkinson’s disease (PD) is a neurodegenerative disorder cardinally marked by motor symptoms, but also sensory symptoms and several other non-motor symptoms. PD patients are typically treated with dopaminergic medication for several years. Many patients eventually experience bouts of periods where medication might not be able to effectively control symptoms as well as experience side-effects of long-term dopaminergic treatments. Deep brain stimulation (DBS) is an option as the next therapeutic recourse for such patients. DBS treatment essentially involves placement of stimulating electrodes in the subthalamic nucleus (STN) or the globus pallidus internum (GPi) along with an implanted pulse generator (IPG) in the sub-clavicular space. STN-DBS alleviates motor symptoms and leads to substantial improvements in quality of life for PD patients. Although DBS is known to improve several classes of symptoms, the effect mechanism of DBS is still not clear. While there is a lack of electrophysiological investigation of sensory processing and the effects of treatments in PD altogether, the electrophysiological studies of the cortical dynamics during motor tasks and at rest lack consensus.We recorded magnetoencephalography (MEG) and electromyography (EMG) from PD patients in three studies: (i) at rest, (ii) during median nerve stimulation, and (iii) while performing phasic contractions (hand gripping). The three studies focused on cortical oscillatory dynamics at rest, during somatosensory processing and during movement, respectively. The measurements were conducted in DBS-treated, untreated (DBS washout) and dopaminergic-medicated states. While both treatments (DBS and dopaminergic medication) ameliorated motor symptoms similarly in all studies, they showed differentiated effects on: (i) increased sensorimotor cortical low-gamma spectral power (31-45 Hz) (but no changes in beta power (13-30 Hz)) at rest only during DBS, (ii) somatosensory processing with higher gamma augmentation (31-45 Hz, 20-60 ms) in the dopaminergic-medicated state compared to DBS-treated and untreated states, and (iii) hand gripping with increased motor-related beta corticomuscular coherence (CMC, 13-30 Hz) during dopaminergic medication in contrast to increased gamma power (31-45 Hz) during DBS.Firstly, we infer from the three studies that DBS and dopaminergic medication employ partially different anatomo-functional pathways and functional strategies when improving PD symptoms. Secondly, we suggest that treatments act on pathological oscillatory dynamics differently at cortical and sub-cortical levels and may do so through more sophisticated mechanisms than mere suppression of the pathological spectral power in a particular band. And thirdly, we urge exploring effect mechanisms of PD treatments beyond the motor system. The effects of dopaminergic medication on early somatosensory processing has opened the door for exploring the effects of treatments and studying their mechanisms using electrophysiology, especially in higher order sensory deficits. Integration of such research findings into a holistic view on mechanisms of treatments could pave way for better disease management paradigms. 

Using epidemic simulators for monitoring an ongoing epidemic

Prediction of infection trends, estimating the efficacy of contact tracing, testing or impact of influx of infected are of vital importance for administration during an ongoing epidemic. Most effective methods currently are empirical in nature and their relation to parameters of interest to administrators are not evident. We thus propose a modified SEIRD model that is capable of modeling effect of interventions and inward migrations on the progress of an epidemic. The tunable parameters of this model bear relevance to monitoring of an epidemic. This model was used to show that some of the commonly seen features of cumulative infections in real data can be explained by piecewise constant changes in interventions and population influx. We also show that the data of cumulative infections from twelve Indian states between mid March and mid April 2020 can be generated from the model by applying interventions according to a set of heuristic rules. Prediction for the next ten days based on this model, reproduced real data very well. In addition, our model also reproduced the time series of recoveries and deaths. Our work constitutes an important first step towards an effective dashboard for the monitoring of epidemic by the administration, especially in an Indian context

Real-time acquisition and analysis ofElectro-oculography signals

Electro-oculography signals are corneo-retinal potentials that carry informationpertaining to eye movements. This information can be used to estimate drowsinesslevel of the subject which could provide interesting insights into research of acci-dent prevention. Of all features present, blink duration has been proved to be aneffective measure of drowsiness. The aim of this thesis work is to build a portablesystem to acquire and analyze electro-oculographic (EOG) signals in real-time.The system contains two sub-systems; a hardware sub-system that consists of thefilters, amplifiers, data acquisition card and isolation and the software sub-systemthat contains the program to acquire and analyze the signal and present the resultsto the observer. The filters were designed starting with simulation, implementa-tion on the prototype board, culminating in the design of a printed circuit board(PCB) and packaging. The complete software was written in PythonTMusing sev-eral relevant libraries for data processing. A text-based user interface was createdto enable easy user interaction. The results are graphically displayed in real-time. Ex-situ tests were done with two volunteers while in-situ test was done onone subject. The data from the in-situ tests showed "good signal quality" in a"noisy" environment concurring with the design specifications. To motivate theimportance of calibration, two calibration paradigms were used during ex-situtests, where one paradigm records only normal blinks while the other records longblinks and the results showed differences in detection and error rates. The obser-vations made from performance tests at various levels gave "satisfactory results"and proved the usefulness of the system for experimental purposes in-situ

Effects of exercise anticipation on cardiorespiratory coherence

In this study, we explored the role of feedforward mechanisms in triggering cardiorespiratory adjustments before the onset of exercise. To isolate the feedforward aspects, we examined the effect of exercise anticipation on cardiorespiratory coherence. Twenty-nine healthy males (age = 18.8 [0.96] years) were subjected to bicycle (BE) and handgrip exercise (H) at two different intensities, viz., low and high. Bicycle exercise was performed in a unilateral (left- and right-sided) or bilateral mode, whereas handgrip was performed only in a unilateral mode. Single-lead ECG and respiratory rhythm, measured in the 5 min of anticipation phase before the onset of exercise, were used for analysis. Coherence was computed between ECG-derived instantaneous heart rate and respiratory signal. Average coherence in the high-frequency band (0.15-0.4 Hz) was used to estimate respiratory sinus arrhythmia (RSA). We found that coherence decreased with the anticipation of exercise relative to baseline (baseline = 0.54 [0.16], BE = 0.41 [0.12], H = 0.39 [0.12], p < 0.001). The decrease was greater for high intensity exercise (low = 0.42 [0.11], high = 0.37 [0.1], p < 0.001). The fall of coherence with intensity was stronger for bicycle exercise (BE: low = 0.44 [0.12], high = 0.37 [0.12], H: low = 0.4 [0.12], high = 0.37 [0.12], p = 0.00433). The expectation of bilateral exercise resulted in lower coherence compared to unilateral exercise (right-sided = 0.45 [0.16], left-sided = 0.4 [0.16], bilateral = 0.36 [0.15], unilateral vs. bilateral: p < 0.001), and the left-sided exercise had lower coherence compared to that of the right (left-sided vs. right-sided: p = 0.00925). Handgrip exercise showed similar trend (right-sided = 0.4 [0.15], left-sided = 0.37 [0.14], p = 0.0056). In conclusion, feedforward RSA adjustments in anticipation of exercise covaried with subsequent exercise-related features like intensity, muscle mass (unilateral vs. bilateral), and the exercise side (left vs. right). The left versus the right difference in coherence indicates autonomic asymmetry. Feedforward changes in RSA are like those seen during actual exercise and might facilitate the rapid phase transition between rest and exercise. © 2022 The Authors. Physiological Reports published by Wiley Periodicals LLC on behalf of The Physiological Society and the American Physiological Society

Worsening of Verbal Fluency After Deep Brain Stimulation in Parkinson's Disease: A Focused Review

Worsening of verbal fluency after treatment with deep brain stimulation in Parkinson's disease patients is one of the most often reported cognitive adverse effect. The underlying mechanisms of this decline are not well understood. The present focused review assesses the evidence for the reliability of the often-reported decline of verbal fluency, as well as the evidence for the suggested mechanisms including disease progression, reduced medication levels, electrode positions, and stimulation effect vs. surgical effects. Finally, we highlight the need for more systematic investigations of the large degree of heterogeneity in the prevalence of verbal fluency worsening after DBS, as well as provide suggestions for future research. Keywords: Deep brain stimulation, Parkinson's disease, Verbal fluenc

Feasibility of home-based tracking of insulin resistance from vascular stiffness estimated from the photoplethysmographic finger pulse waveform

Objective. In this study we explored the utility of post-prandial vascular stiffness as a surrogate measure for estimating insulin resistance, which is a pre-diabetic condition. Approach. A cohort of 51 healthy young adults with varying body mass index (BMI) values was studied using fasting plasma values of insulin and glucose, fasting and post-meal finger photoplethysmography (PPG) and electrocardiogram (ECG). Insulin resistance was estimated by homeostatic model assessment for insulin resistance 2 (HOMA-IR2) using fasting plasma insulin and glucose. Vascular stiffness was estimated by reciprocal of pulse arrival time (rPAT) from ECG and finger PPG at five time points from fasting to 2 h post-oral glucose ingestion. We examined if insulin resistance correlates with meal-induced vascular stiffness changes, supporting the feasibility of using finger PPG to estimate insulin resistance. Main results. HOMA-IR2 was positively correlated with an early rise (0 to 30 min post-meal) and delayed fall (30 to 120 min post-meal) of rPAT. Correlation persisted even after the effect of BMI has been partialled out in subgroup analysis. We conclude that finger PPG-based pulse waveform and single-lead ECG has the potential to be used as a non-invasive method for the assessment of insulin resistance. Significance. As both signals, namely ECG and PPG, can be easily acquired using wearable and other low-cost sensing systems, the present study can serve as a pointer to develop accessible strategies for monitoring and longitudinal tracking of insulin resistance in health and pathophysiological states. © 2022 Institute of Physics and Engineering in Medicine

How Does Deep Brain Stimulation Affect Magnetoencephalography Data?

Deep Brain Stimulation (DBS) is an established and effective neuromodulation technique preferred in treating several neurological and neuropsychiatric disorders such as Parkinson's Disease(PD), epilepsy, obsessive compulsive disorder, depression and several such disorders. Magnetoencephalography (MEG) is a widely used neuroimaging strategy to understand the pathology and the therapeutic effects of DBS in clinical cohorts. One of the significant limitations is the inability to differentiate the DBS stimulation artefact from actual neuronal excitations, especially in lower frequency bands of interest where sub-harmonics of DBS artefacts may obscure the biological response and is a confounder. The primary objective of this study is to understand how DBS stimulation artefacts affect MEG signals and to this end, we employ a phantom based on a water melon. Using this phantom, we record the spectral signature of the DBS stimulation artefact at various DBS frequencies and stimulation voltages, the effect of standard artefact rejection approaches like spatiotemporal signal space separation (tSSS). We present in this paper the results of the initial analysis. © 2021 IEEE

Tool for image annotation based on gaze

Supervised learning on image data demands availability of large amounts of annotated image data. Annotation is predominantly a tool assisted manual activity and increasingly accounts for a large share of budget in machine learning systems development. This is due to the time involved and the need for large manpower to annotate large databases. Instead of the predominantly bounding box drawing using mouse cursor, we propose a more natural human computer interface-the human gaze. We hereby propose a technique of image annotation by using a novel protocol for acquiring gaze data to create a polygon around the object rather than bounding boxes. In this study the method is outlined and the results are compared with manually created annotations. The technique can be used to annotate existing image databases or create new annotated databases by simultaneous image acquisition and annotation

Evaluation of a gamified upper-arm bimanual trainer for stroke patients - A healthy cohort study

The current study aims to evaluate the bimanual trainer, ArmAble, using electrophysiology and kinematic data from a healthy cohort, that can help in creating a reliable rehabilitation schema. We use muscle activation patterns recorded through electromyography in healthy subjects, in order to understand the effect on synergies and activation patterns while using a bimanual trainer. We recorded electromyography from six muscles on either side (including four anti-gravity muscles) and kinematic data, while the subject uses the bimanual trainer to understand the muscular activation in the upper limbs. Experimental conditions included different complexity of reaching tasks and different inclinations. We computed the muscle output as quantified by RMS values and intermuscular coherence, which denotes common cortical drive and coordination between muscles. While inclination did not have a significant effect on RMS, there was a marginal yet non-significant effect on IMC. Whereas the complexity of the reaching task did affect the RMS, while it did not affect IMC. We discuss these results in the context of game design principles for neuro-rehabilitation