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The integration of probabilistic information during sensorimotor estimation is unimpaired in children with Cerebral Palsy.

ABSTRACT: BACKGROUND:It is important to understand the motor deficits of children with Cerebral Palsy (CP). Our understanding of this motor disorder can be enriched by computational models of motor control. One crucial stage in generating movement involves combining uncertain information from different sources, and deficits in this process could contribute to reduced motor function in children with CP. Healthy adults can integrate previously-learned information (prior) with incoming sensory information (likelihood) in a close-to-optimal way when estimating object location, consistent with the use of Bayesian statistics. However, there are few studies investigating how children with CP perform sensorimotor integration. We compare sensorimotor estimation in children with CP and age-matched controls using a model-based analysis to understand the process. METHODS AND FINDINGS:We examined Bayesian sensorimotor integration in children with CP, aged between 5 and 12 years old, with Gross Motor Function Classification System (GMFCS) levels 1-3 and compared their estimation behavior with age-matched typically-developing (TD) children. We used a simple sensorimotor estimation task which requires participants to combine probabilistic information from different sources: a likelihood distribution (current sensory information) with a prior distribution (learned target information). In order to examine sensorimotor integration, we quantified how participants weighed statistical information from the two sources (prior and likelihood) and compared this to the statistical optimal weighting. We found that the weighing of statistical information in children with CP was as statistically efficient as that of TD children. CONCLUSIONS:We conclude that Bayesian sensorimotor integration is not impaired in children with CP and therefore, does not contribute to their motor deficits. Future research has the potential to enrich our understanding of motor disorders by investigating the stages of motor processing set out by computational models. Therapeutic interventions should exploit the ability of children with CP to use statistical information.

SUBMITTER: Chambers C

PROVIDER: S-EPMC5706703 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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The integration of probabilistic information during sensorimotor estimation is unimpaired in children with Cerebral Palsy.

Chambers Claire C Sokhey Taegh T Gaebler-Spira Deborah D Kording Konrad P KP

PloS one 20171129 11

<h4>Background</h4>It is important to understand the motor deficits of children with Cerebral Palsy (CP). Our understanding of this motor disorder can be enriched by computational models of motor control. One crucial stage in generating movement involves combining uncertain information from different sources, and deficits in this process could contribute to reduced motor function in children with CP. Healthy adults can integrate previously-learned information (prior) with incoming sensory inform ...[more]

PMID: 29186196

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Project description:Cerebral palsy is primarily an upper motor neuron disease that results in a spectrum of progressive movement disorders. Secondary to the neurological lesion, muscles from patients with cerebral palsy are often spastic and form debilitating contractures that limit range of motion and joint function. With no genetic component, the pathology of skeletal muscle in cerebral palsy is a response to aberrant neurological input in ways that are not fully understood. This study was designed to gain further understanding of the skeletal muscle response to cerebral palsy using microarrays and correlating the transcriptional data with functional measures. Hamstring biopsies from gracilis and semitendinosus muscles were obtained from a cohort of patients with cerebral palsy (n=10) and typically developing patients (n=10) undergoing surgery. Affymetrix HG-U133A 2.0 chips (n=40) were used and expression data was verified for 6 transcripts using quantitative real-time PCR, as well as for two genes not on the microarray. Chips were clustered based on their expression and those from patients with cerebral palsy clustered separately. Significant genes were determined conservatively based on the overlap of three summarization algorithms (n=1,398). Significantly altered genes were analyzed for over-representation among gene ontologies, transcription factors, pathways, microRNA and muscle specific networks. These results centered on an increase in extracellular matrix expression in cerebral palsy as well as a decrease in metabolism and ubiquitin ligase activity. The increase in extracellular matrix products was correlated with mechanical measures demonstrating the importance in disability. These data lay a framework for further studies and novel therapies. Skeletal muscle biopsies from both the gracilis and semitendinosus were obtained during surgery for 20 pediatric subjects for affymetrix microarray analysis. We obtained a group of 10 patients undergoing medial hamstring lengthening in the cerebral palsy group and 10 patients undergoing ACL reconstruction with hamstring autograft in the control group. This provided 40 microarrays in 4 groups to analyze the effect of cerebral palsy and also differences between muscles.

Project description:Background: Walking problems in children with cerebral palsy (CP) can in part be explained by limited selective motor control. Muscle synergy analysis is increasingly used to quantify altered neuromuscular control during walking. The early brain injury in children with CP may lead to a different development of muscle synergies compared to typically developing (TD) children, which might characterize the abnormal walking patterns. Objective: The overarching aim of this review is to give an overview of the existing studies investigating muscle synergies during walking in children with CP compared to TD children. The main focus is on how muscle synergies differ between children with CP and TD children, and we examine the potential of muscle synergies as a measure to quantify and predict treatment outcomes. Methods: Bibliographic databases were searched by two independent reviewers up to 22 April 2019. Studies were included if the focus was on muscle synergies of the lower limbs during walking, obtained by a matrix factorization algorithm, in children with CP. Results: The majority (n = 12) of the 16 included studies found that children with CP recruited fewer muscle synergies during walking compared to TD children, and several studies (n = 8) showed that either the spatial or temporal structure of the muscle synergies differed between children with CP and TD children. Variability within and between subjects was larger in children with CP than in TD children, especially in more involved children. Muscle synergy characteristics before treatments to improve walking function could predict treatment outcomes (n = 3). Only minimal changes in synergies were found after treatment. Conclusions: The findings in this systematic review support the idea that children with CP use a simpler motor control strategy compared to TD children. The use of muscle synergy analysis as a clinical tool to quantify altered neuromuscular control and predict clinical outcomes seems promising. Further investigation on this topic is necessary, and the use of muscle synergies as a target for development of novel therapies in children with CP could be explored.

Project description:Upper body movements during walking provide information about balance control and gait stability. Typically developing (TD) children normally present a progressive decrease of accelerations from the pelvis to the head, whereas children with cerebral palsy (CP) exhibit a general increase of upper body accelerations. However, the literature describing how they are transmitted from the pelvis to the head is lacking. This study proposes a multilevel motion sensor approach to characterize upper body accelerations and how they propagate from pelvis to head in children with CP, comparing with their TD peers. Two age- and gender-matched groups of 20 children performed a 10m walking test at self-selected speed while wearing three magneto-inertial sensors located at pelvis, sternum, and head levels. The root mean square value of the accelerations at each level was computed in a local anatomical frame and its variation from lower to upper levels was described using attenuation coefficients. Between-group differences were assessed performing an ANCOVA, while the mutual dependence between acceleration components and the relationship between biomechanical parameters and typical clinical scores were investigated using Regression Analysis and Spearman's Correlation, respectively (? = 0.05). New insights were obtained on how the CP group managed the transmission of accelerations through the upper body. Despite a significant reduction of the acceleration from pelvis to sternum, children with CP do not compensate for large accelerations, which are greater than in TD children. Furthermore, those with CP showed negative sternum-to-head attenuations, in agreement with the documented rigidity of the head-trunk system observed in this population. In addition, the estimated parameters proved to correlate with the scores used in daily clinical practice. The proposed multilevel approach was fruitful in highlighting CP-TD gait differences, supported the in-field quantitative gait assessment in children with CP and might prove beneficial to designing innovative intervention protocols based on pelvis stabilization.

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The integration of probabilistic information during sensorimotor estimation is unimpaired in children with Cerebral Palsy.

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The integration of probabilistic information during sensorimotor estimation is unimpaired in children with Cerebral Palsy.

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