Dataset Information

Reflex-based grasping, skilled forelimb reaching, and electrodiagnostic evaluation for comprehensive analysis of functional recovery-The 7-mm rat median nerve gap repair model revisited.

ABSTRACT: INTRODUCTION:The rat median nerve injury and repair model gets increasingly important for research on novel bioartificial nerve grafts. It allows follow-up evaluation of the recovery of the forepaw functional ability with several sensitive techniques. The reflex-based grasping test, the skilled forelimb reaching staircase test, as well as electrodiagnostic recordings have been described useful in this context. Currently, no standard values exist, however, for comparison or comprehensive correlation of results obtained in each of the three methods after nerve gap repair in adult rats. METHODS:Here, we bilaterally reconstructed 7-mm median nerve gaps with autologous nerve grafts (ANG) or autologous muscle-in-vein grafts (MVG), respectively. During 8 and 12 weeks of observation, functional recovery of each paw was separately monitored using the grasping test (weekly), the staircase test, and noninvasive electrophysiological recordings from the thenar muscles (both every 4 weeks). Evaluation was completed by histomorphometrical analyses at 8 and 12 weeks postsurgery. RESULTS:The comprehensive evaluation detected a significant difference in the recovery of forepaw functional motor ability between the ANG and MVG groups. The correlation between the different functional tests evaluated precisely displayed the recovery of distinct levels of forepaw functional ability over time. CONCLUSION:Thus, this multimodal evaluation model represents a valuable preclinical model for peripheral nerve reconstruction approaches.

SUBMITTER: Stoßel M

PROVIDER: S-EPMC5651396 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Reflex-based grasping, skilled forelimb reaching, and electrodiagnostic evaluation for comprehensive analysis of functional recovery-The 7-mm rat median nerve gap repair model revisited.

Stößel Maria M Rehra Lena L Haastert-Talini Kirsten K

Brain and behavior 20170906 10

<h4>Introduction</h4>The rat median nerve injury and repair model gets increasingly important for research on novel bioartificial nerve grafts. It allows follow-up evaluation of the recovery of the forepaw functional ability with several sensitive techniques. The reflex-based grasping test, the skilled forelimb reaching staircase test, as well as electrodiagnostic recordings have been described useful in this context. Currently, no standard values exist, however, for comparison or comprehensive ...[more]

PMID: 29075572

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Project description:BACKGROUND:Active upper-limb prostheses are used to restore important hand functionalities, such as grasping. In conventional approaches, a pattern recognition system is trained over a number of static grasping gestures. However, training a classifier in a static position results in lower classification accuracy when performing dynamic motions, such as reach-to-grasp. We propose an electromyography-based learning approach that decodes the grasping intention during the reaching motion, leading to a faster and more natural response of the prosthesis. METHODS AND RESULTS:Eight able-bodied subjects and four individuals with transradial amputation gave informed consent and participated in our study. All the subjects performed reach-to-grasp motions for five grasp types, while the elecromyographic (EMG) activity and the extension of the arm were recorded. We separated the reach-to-grasp motion into three phases, with respect to the extension of the arm. A multivariate analysis of variance (MANOVA) on the muscular activity revealed significant differences among the motion phases. Additionally, we examined the classification performance on these phases. We compared the performance of three different pattern recognition methods; Linear Discriminant Analysis (LDA), Support Vector Machines (SVM) with linear and non-linear kernels, and an Echo State Network (ESN) approach. Our off-line analysis shows that it is possible to have high classification performance above 80% before the end of the motion when with three-grasp types. An on-line evaluation with an upper-limb prosthesis shows that the inclusion of the reaching motion in the training of the classifier importantly improves classification accuracy and enables the detection of grasp intention early in the reaching motion. CONCLUSIONS:This method offers a more natural and intuitive control of prosthetic devices, as it will enable controlling grasp closure in synergy with the reaching motion. This work contributes to the decrease of delays between the user's intention and the device response and improves the coordination of the device with the motion of the arm.

Project description:Classically, it has been hypothesized that reach-to-grasp movements arise from two discrete parietofrontal cortical networks. As part of these networks, the dorsal premotor cortex (PMd) has been implicated in the control of reaching movements of the arm, whereas the ventral premotor cortex (PMv) has been associated with the control of grasping movements of the hand. Recent studies have shown that such a strict delineation of function along anatomical boundaries is unlikely, partly because reaching to different locations can alter distal hand kinematics and grasping different objects can affect kinematics of the proximal arm. Here, we used chronically implanted multielectrode arrays to record unit-spiking activity in both PMd and PMv simultaneously while rhesus macaques engaged in a reach-to-grasp task. Generalized linear models were used to predict the spiking activity of cells in both areas as a function of different kinematic parameters, as well as spike history. To account for the influence of reaching on hand kinematics and vice versa, we applied demixed principal components analysis to define kinematics synergies that maximized variance across either different object locations or grip types. We found that single cells in both PMd and PMv encode the kinematics of both reaching and grasping synergies, suggesting that this classical division of reach and grasp in PMd and PMv, respectively, does not accurately reflect the encoding preferences of cells in those areas.SIGNIFICANCE STATEMENT For reach-to-grasp movements, the dorsal premotor cortex (PMd) has been implicated in the control of reaching movements of the arm, whereas the ventral premotor cortex (PMv) has been associated with the control of grasping movements of the hand. We recorded unit-spiking activity in PMd and PMv simultaneously while macaques performed a reach-to-grasp task. We modeled the spiking activity of neurons as a function of kinematic parameters and spike history. We applied demixed principal components analysis to define kinematics synergies. We found that single units in both PMd and PMv encode the kinematics of both reaching and grasping synergies, suggesting that the division of reach and grasp in PMd and PMv, respectively, cannot be made based on their encoding properties.

Dataset Information

Reflex-based grasping, skilled forelimb reaching, and electrodiagnostic evaluation for comprehensive analysis of functional recovery-The 7-mm rat median nerve gap repair model revisited.

Publications

Reflex-based grasping, skilled forelimb reaching, and electrodiagnostic evaluation for comprehensive analysis of functional recovery-The 7-mm rat median nerve gap repair model revisited.

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