Quantifying muscle alterations in a Parkinson's disease animal model using electromyographic biomarkers

In Vivo Assays for Amyloid-Related Diseases

Amyloid-related diseases, such as Alzheimer's and Parkinson's disease, are devastating conditions caused by the accumulation of abnormal protein aggregates known as amyloid fibrils. While assays involving animal models are essential for understanding the pathogenesis and developing therapies, a wide array of standard analytical techniques exists to enhance our understanding of these disorders. These techniques provide valuable information on the formation and propagation of amyloid fibrils, as well as the pharmacokinetics and pharmacodynamics of candidate drugs. Despite ethical concerns surrounding animal use, animal models remain vital tools in the search for treatments. Regardless of the specific animal model chosen, the analytical methods used are usually standardized. Therefore, the main objective of this review is to categorize and outline the primary analytical methods used in in vivo assays for amyloid-related diseases, highlighting their critical role in furthering our understanding of these disorders and developing effective therapies.

Digital biomarkers in Parkinson's disease

Digital biomarker (DB) assessments provide objective measures of daily life tasks and thus hold promise to improve diagnosis and monitoring of Parkinson's disease (PD) patients especially those with advanced stages. Data from DB studies can be used in advanced analytics such as Artificial Intelligence and Machine Learning to improve monitoring, treatment and outcomes. Although early development of inertial sensors as accelerometers and gyroscopes in smartphones provided encouraging results, the use of DB remains limited due to lack of standards, harmonization and consensus for analytical as well as clinical validation. Accordingly, a number of clinical trials have been developed to evaluate the performance of DB vs traditional assessment tools with the goal of monitoring disease progression, improving quality of life and outcomes. Herein, we update current evidence on the use of DB in PD and highlight potential benefits and limitations and provide suggestions for future research study.

Electrophysiology Methods for Assessing of Neurodegenerative and Post-Traumatic Processes as Applied to Translational Research

Electrophysiological studies have long established themselves as reliable methods for assessing the functional state of the brain and spinal cord, the degree of neurodegeneration, and evaluating the effectiveness of therapy. In addition, they can be used to diagnose, predict functional outcomes, and test the effectiveness of therapeutic and rehabilitation programs not only in clinical settings, but also at the preclinical level. Considering the urgent need to develop potential stimulators of neuroregeneration, it seems relevant to obtain objective data when modeling neurological diseases in animals. Thus, in the context of the application of electrophysiological methods, not only the comparison of the basic characteristics of bioelectrical activity of the brain and spinal cord in humans and animals, but also their changes against the background of neurodegenerative and post-traumatic processes are of particular importance. In light of the above, this review will contribute to a better understanding of the results of electrophysiological assessment in neurodegenerative and post-traumatic processes as well as the possibility of translating these methods from model animals to humans.

Decision-Making Time Analysis for Assessing Processing Speed in Athletes during Motor Reaction Tasks

Reaction time (RT) is a widely used measure for testing physical performance in motor tasks. This study focused on assessing the processing speed in athletes. Twenty-five healthy volunteers were assigned to the control (n = 16) or athletes groups (n = 9). They were evaluated during motor reaction tasks based on visual stimuli and three difficulty conditions. Physiological measures were obtained from motion capture and electromyography recordings of several muscles. Two RT phases, decision-making (DMK) and electromechanical delay (EMD), were used to analyze the processing speed. The results show significant RT differences between groups. The athletes were ~30% faster compared to the control group. Despite the fact that all participants were right-handed, RT did not show any differences between hands performances in any group. However, DMK time revealed significant differences between the hands. Controls showed a longer DMK time for the right-hand election, ~20% more than the left, while athletes showed no such disparity. These findings reveal that quantifying the decision-making component of reaction time is crucial to assessing processing speed in sport. This approach could facilitate the monitoring of adaptations in both motor-cognitive and neuromuscular processes. The theoretical implications presented in this study offer perspectives on handedness research.

Assessing Cognitive Workload in Motor Decision-Making through Functional Connectivity Analysis: Towards Early Detection and Monitoring of Neurodegenerative Diseases

Neurodegenerative diseases (NDs), such as Alzheimer's, Parkinson's, amyotrophic lateral sclerosis, and frontotemporal dementia, among others, are increasingly prevalent in the global population. The clinical diagnosis of these NDs is based on the detection and characterization of motor and non-motor symptoms. However, when these diagnoses are made, the subjects are often in advanced stages where neuromuscular alterations are frequently irreversible. In this context, we propose a methodology to evaluate the cognitive workload (CWL) of motor tasks involving decision-making processes. CWL is a concept widely used to address the balance between task demand and the subject's available resources to complete that task. In this study, multiple models for motor planning during a motor decision-making task were developed by recording EEG and EMG signals in n=17 healthy volunteers (9 males, 8 females, age 28.66±8.8 years). In the proposed test, volunteers have to make decisions about which hand should be moved based on the onset of a visual stimulus. We computed functional connectivity between the cortex and muscles, as well as among muscles using both corticomuscular and intermuscular coherence. Despite three models being generated, just one of them had strong performance. The results showed two types of motor decision-making processes depending on the hand to move. Moreover, the central processing of decision-making for the left hand movement can be accurately estimated using behavioral measures such as planning time combined with peripheral recordings like EMG signals. The models provided in this study could be considered as a methodological foundation to detect neuromuscular alterations in asymptomatic patients, as well as to monitor the process of a degenerative disease.

Assays of Tongue Force, Timing, and Dynamics in Rat and Mouse Models

Communication and swallowing are highly complex sensorimotor events that are tightly linked to respiration and vital to health and well-being. The tongue is a complex organ, often described as a muscular hydrostat, that is crucial for maintaining airway patency, preparing and safely transporting food/liquid, and rapidly changing position and shape for speech. As with any complex behavior, tongue function can be compromised with aging, diseases/conditions, trauma, or as a pharmacologic side effect. As such, modeling lingual function and dysfunction for basic and translational research is paramount; understanding how the nervous system controls tongue function for complex behavior is foundational to this work. Non-invasive access to tongue tissues and kinematics during awake behavior has been historically challenging, creating a critical need to measure tongue function in model systems. Germane to this field of study are the instruments and assays of licking/lapping and drinking, including tongue force and timing measures, many of which were designed or modified by Dr. Stephen C. Fowler. The focus of this paper is to review some of the important contributions of measuring tongue behaviors in awake rats and mice and how these have been modified by other researchers to advance translational science.

Muscle function alterations in a Parkinson's disease animal model: Electromyographic recordings dataset

Parkinson's disease (PD) is currently diagnosed based on characteristic motor dysfunctions induced by the loss of dopaminergic neurons in the substantia nigra pars compacta [1], [2]. The animal model most commonly used to reproduce PD-related motor deficits in rats is the massive degeneration of nigrostriatal neurons by using intracerebral infusion of 6-hydroxydopamine (6-OHDA) [3], [4].

This article presents data related to the research article “Quantifying muscle alterations in a Parkinson's disease animal model using electromyographic biomarkers” [5]. This study evaluated the effect of PD neurotoxic lesion model on muscle function of freely moving rats. The effects on muscle function considering the time post-lesion have never been described for this Parkinson's disease model. Electromyographic recordings were obtained from control and hemiparkinsonian rats walking in a circular treadmill. Chronic EMG electrodes were implanted subcutaneously in a hindlimb muscle - the biceps femoris muscle - for evaluating muscular activity during the gait. Five dataset of EMG recordings are presented in this article corresponding to control animals and four groups of lesioned animals at different time post-injury (three to six weeks after lesion). Stationarity of the EMG signals were established and the effective muscular contractions were detected by using signal processing methods described in [5]. Power spectrum density was characterized through the mean and median frequencies and signals probability distribution function analysis was also performed.These analyses have shown that PSD frequency contents progressively fall with time post-lesion suggesting muscle function changes along this enclosed time.

This dataset could be reused to investigate muscular activation parameters under control and lesioned conditions in freely moving rats and for evaluating different signal processing methods for EMG patterns detection.