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Quantitative assessment of cortical somatosensory digit representations after median and ulnar nerve injury in rats.

ABSTRACT: Incomplete recovery of sensory function is common after peripheral nerve injury (PNI). Despite reinnervation following injury, disorganized cortical representations persist and may contribute to functional deficits. There is a dearth of literature characterizing cortical responses after PNI in rodent models. Here we develop a quantitative electrophysiological method for mapping forepaw digit responses in primary somatosensory cortex (S1) of rats. We tested the hypothesis that PNI in the forelimb would generate significant, long lasting sensory deficits, and corresponding disorganization in S1. Rats underwent a transection of the proximal segment of the median and ulnar nerves in the forelimb followed by tubular repair. 4-12 months after nerve injury, we tested mechanosensory withdrawal thresholds and mapped S1 responses to mechanical stimulation of the digits. PNI produces persistent elevation of mechanical withdrawal thresholds, consistent with an impairment in sensory function. Assessment of cortical neurophysiology reveals a substantial disorganization of S1 somatotopy. Additionally, we document degraded timing and digit specificity of cortical responses. This quantitative measurement of long-term changes in S1 digit representations after forelimb nerve injury in rodents provides a framework for further studies focused on the development of therapeutic strategies to restore cortical and sensory function.

SUBMITTER: Hulsey DR

PROVIDER: S-EPMC6679757 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Quantitative assessment of cortical somatosensory digit representations after median and ulnar nerve injury in rats.

Hulsey Daniel R DR Mian Tabarak M TM Darrow Michael J MJ Hays Seth A SA

Experimental brain research 20190704 9

Incomplete recovery of sensory function is common after peripheral nerve injury (PNI). Despite reinnervation following injury, disorganized cortical representations persist and may contribute to functional deficits. There is a dearth of literature characterizing cortical responses after PNI in rodent models. Here we develop a quantitative electrophysiological method for mapping forepaw digit responses in primary somatosensory cortex (S1) of rats. We tested the hypothesis that PNI in the forelimb ...[more]

PMID: 31273391

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Project description:BackgroundRadial, ulnar, or median nerve injuries are common peripheral nerve injuries. They usually present specific abnormal signs on the hands as evidence for hand surgeons to diagnose. However, without specialized knowledge, it is difficult for primary healthcare providers to recognize the clinical meaning and the potential nerve injuries through the abnormalities, often leading to misdiagnosis. Developing technologies for automatically detecting abnormal hand gestures would assist general medical service practitioners with an early diagnosis and treatment.MethodsBased on expert experience, we selected three hand gestures with predetermined features and rules as three independent binary classification tasks for abnormal gesture detection. Images from patients with unilateral radial, ulnar, or median nerve injuries and healthy volunteers were obtained using a smartphone. The landmark coordinates were extracted using Google MediaPipe Hands to calculate the features. The receiver operating characteristic curve was employed for feature selection. We compared the performance of rule-based models with logistic regression, support vector machine and of random forest machine learning models by evaluating the accuracy, sensitivity, and specificity.ResultsThe study included 1,344 images, twenty-two patients, and thirty-four volunteers. In rule-based models, eight features were finally selected. The accuracy, sensitivity, and specificity were (1) 98.2, 91.7, and 99.0% for radial nerve injury detection; (2) 97.3, 83.3, and 99.0% for ulnar nerve injury detection; and (3) 96.4, 87.5, and 97.1% for median nerve injury detection, respectively. All machine learning models had accuracy above 95% and sensitivity ranging from 37.5 to 100%.ConclusionOur study provides a helpful tool for detecting abnormal gestures in radial, ulnar, or median nerve injuries with satisfying accuracy, sensitivity, and specificity. It confirms that hand pose estimation could automatically analyze and detect the abnormalities from images of these patients. It has the potential to be a simple and convenient screening method for primary healthcare and telemedicine application.

Project description:Recent studies have suggested that cortical gamma-oscillations are tightly linked with various forms of physiological activity. In the present study, the dynamic changes of intracranially recorded median-nerve somatosensory-evoked potentials (SEPs) and somatosensory-induced gamma-oscillations were animated on a three-dimensional MR image, and the temporal and spatial characteristics of these activities were analysed in 10 children being evaluated for epilepsy surgery. Visual and quantitative assessments revealed that short-latency SEPs and somatosensory-induced gamma-oscillations predominantly involved the post-central gyrus and less intensely involved the pre-central gyrus and the anterior parietal lobule. Formation of a dipole of N20 peak with opposite polarities across the central sulcus was well delineated in animation movies. High-frequency (100-250 Hz) somatosensory-induced gamma-oscillations emerged in the post-central gyrus at 13.6-17.5 ms after median-nerve stimulation, gradually slowed down in frequency around and below 100 Hz, and progressively involved the neighbouring areas. A substantial proportion of somatosensory-induced gamma-oscillations was initially phase-locked and the proportion of a non-phase-locked component gradually increased over time. The primary motor hand areas proven by cortical stimulation frequently coincided with the sites showing the largest N20 peak and the largest somatosensory-induced gamma oscillations. In vivo animation of SEPs and somatosensory-induced gamma oscillations both may be utilized to localize the primary sensory-motor hand area in pre-surgical evaluation. The dipole on SEPs is consistent with the previously accepted notion that the cortices along the central sulcus are activated. The high-frequency somatosensory-induced gamma-oscillations in the post-central gyrus may represent the initial neural processing for external somatosensory stimuli, whereas the subsequent lower-frequency oscillations might represent the reafferent cortical activity occurring in larger cortical networks.

Project description:BackgroundAccurate predictors of neurological recovery after cervical spinal cord injury are needed. Particularly, to tailor adequate rehabilitation plans. However, objective and quantifiable predictors are sparse.MethodsWithin the prospective European Multicenter Study about Spinal Cord Injury (EMSCI) registry, cervical spinal cord injury patients are monitored at fixed follow up visits (2, 4, 12, 24, and 48 weeks after injury) clinically and with ulnar nerve electroneurography. Associations of ulnar nerve compound muscle action potential amplitudes (CMAP) with American Spinal Cord Injury Association (ASIA) impairment scale (AIS) grades over time were analyzed using linear mixed modeling. Applying logistic regression, the prognostic value of within 4-week ulnar nerve CMAP for 1-year AIS was analyzed. To account for missing data, (1) last observation carried forward and (2) multiple imputation methods were applied. For model derivation, our centers' cohort (EMSCI-HD) was analyzed. For model validation the cohort of other centers (EMSCI-nonHD) was used.ResultsIn the EMSCI-HD cohort, the median age (interquartile range (IQR)) was 52 (34-67) years. 58% were male. The initial AIS distribution was: A = 31%, B = 17%, C = 30%, and D = 22%). In the EMSCI-nonHD cohort, the median age was 49 (32-65) years. Compared to the EMSCI-HD cohort more patients were male (79%, p = 0.0034). The AIS distribution was: A = 33%, B = 13%, C = 21%, and D = 33%).In complete-case mixed model analyses (EMSCI-HD: n = 114; EMSCI-nonHD: n = 508) higher ulnar nerve CMAP were associated with better AIS grades over the entire follow up period. In complete-case logistic regression (EMSCI-HD: n = 90; EMSCI-nonHD: n = 444) higher ulnar nerve CMAP was an independent predictor of better AIS grades. The odds ratio for within 4-week ulnar nerve CMAP to predict 1-year AIS grade D versus A-C in the EMSCI-HD cohort was 1.24 per millivolt (confidence interval 1.07-1.44). The model was validated in an independent cervical spinal cord injury (EMSCI-nonHD) cohort (odds ratio 1.09, confidence interval 1.03-1.17).ConclusionsIn cervical spinal cord injury, the consideration of early ulnar nerve CMAP improves prognostic accuracy, which is of particular importance in patients with clinical grading uncertainties.

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Quantitative assessment of cortical somatosensory digit representations after median and ulnar nerve injury in rats.

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Quantitative assessment of cortical somatosensory digit representations after median and ulnar nerve injury in rats.

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