Cortical and STN spectral changes during limb movements in PD patients with and without dystonia

Background: Dystonia is a prevalent yet under-studied motor feature of Parkinson disease (PD). Although considerable efforts have focused on brain oscillations related to the cardinal symptoms of PD, whether dystonia is associated with specific electrophysiological features is unclear. Objectives: To investigate subcortical and cortical field potentials at rest and during contralateral hand and foot movements in PD patients with versus without dystonia. Methods: We examined the prevalence and somatotopy of dystonia in PD patients undergoing deep brain stimulation (DBS) surgery. We recorded intracranial electrophysiology from sensorimotor cortex and directional DBS electrodes in subthalamic nucleus (STN), during both rest and voluntary contralateral limb movements. We used wavelet transforms and linear mixed models to characterize spectral content in patients with and without dystonia (n=25). Results: Dystonia was highly prevalent at enrollment (61%) and most common in the foot (78%). PD patients with dystonia display greater subthalamic theta and alpha power during movement (p < 0.05) but not at rest. Regardless of dystonia status, cortical recordings display prominent beta desynchronization (13-30 Hz) during movement, whereas STN signals show increases in spectral power at lower frequencies (4-20 Hz), with peaks at 6.0 +/- 3.3 and 4.2 +/- 2.9 Hz during hand and foot movements, respectively (p < 0.03). Conclusions: Whereas cortex was characterized by beta desynchronization during hand and foot movements similarly, STN showed limb-specific low frequency activity which was increased in PD patients with dystonia. These findings may help elucidate why PD-related dystonia is most common in the foot and help guide future closed-loop DBS devices.

Trunk in Stroke

The trunk is the part of the human body that provides basic mechanical stabilization. It provides strength transmission between the upper and lower body regions. Body control is the ability of the body muscles to maintain the upright posture, to adapt to weight transfers, and to maintain selective trunk and limb movements by maintaining the support surface in static and dynamic postural adjustments. Good proximal trunk control provides better distal limb movements, balance, and functional motion. There are many evaluation methods, devices, and scales for trunk function and performance. 3D kinematic, electromyography, hand-held dynamometer, isokinetic dynamometer, trunk accelerometer are some devices that measure trunk function. The motor assessment scale-trunk subscale, the stroke impairment assessment set- trunk control subscale, trunk control test, trunk impairment scale are the most used scales. This chapter explores the effect of strokes on the trunk.

Parasite defensive limb movements enhance signal attraction in male little torrent frogs: insight into the evolution of multimodal signals

Many animals rely on complex sexual signals that target multiple senses to attract mates and repel rivals. These multimodal mating displays can however also attract unintended receivers, which can be an important driver of signal complexity. Despite being taxonomically widespread, we often lack insight into how multimodal signals evolve from unimodal signals and in particular what roles unintended eavesdroppers play. Here we assess whether the physical movements of parasite defense behavior increase the complexity and attractiveness of an acoustic sexual signal in the little torrent frog (Amolops torrentis). Calling males of this species often display limb movements in order to defend against blood sucking parasites such as frog biting midges that eavesdrop on their acoustic signal. Through mate choice tests we show that some of these midge evoked movements influence female preference for acoustic signals. Our data suggest that midge induced movements may be incorporated into a sexual display, targeting both hearing and vision in the intended receiver. Females may play an important role in incorporating these multiple components because they prefer signals which combine multiple programs. Our results thus help to understand the relationship between ecological and sexual selection pressure operating on signalers and how in turn this may influence multimodal signal evolution.

Bayesian optimization of peripheral intraneural stimulation protocols to evoke distal limb movements

Objective. Motor neuroprostheses require the identification of stimulation protocols that effectively produce desired movements. Manual search for these protocols can be very time-consuming and often leads to suboptimal solutions, as several stimulation parameters must be personalized for each subject for a variety of target movements. Here, we present an algorithm that efficiently tunes peripheral intraneural stimulation protocols to elicit functionally relevant distal limb movements. Approach. We developed the algorithm using Bayesian Optimization and defined multi-objective functions based on the coordinated recruitment of multiple muscles. We implemented different multi-output Gaussian Processes to model our system and compared their functioning by applying the algorithm offline to data acquired in rats for walking control and in monkeys for hand grasping control. We then performed a preliminary online test in a monkey to experimentally validate the functionality of our method. Main results. Offline, optimal intraneural stimulation protocols for various target motor functions were rapidly identified in both experimental scenarios. Using the model that performed best, the algorithm converged to stimuli that evoked functionally consistent movements with an average number of actions equal to 20% (13% unique) and 20% (16% unique) of the search space size in rats and monkeys, respectively. Online, the algorithm quickly guided the observations to stimuli that elicited functional hand gestures, although more selective motor outputs could have been achieved by refining the objective function used. Significance. These results demonstrate that Bayesian Optimization can reliably and efficiently automate the tuning of peripheral neurostimulation protocols, establishing a translational framework to configure peripheral motor neuroprostheses in clinical applications. The proposed method can potentially be applied to optimize motor functions using other stimulation modalities.