Surface electromyography pattern of human swallowing

<p>Abstract</p> <p>Background</p> <p>The physiology of swallowing is characterized by a complex and coordinated activation of many stomatognathic, pharyngeal, and laryngeal muscles. Kinetics and electromyographic studies have widely investigated the pharyngeal and laryngeal pattern of deglutition in order to point out the differences between normal and dysphagic people. In the dental field, muscular activation during swallowing is believed to be the cause of malocclusion.</p> <p>Despite the clinical importance given to spontaneous swallowing, few physiologic works have studied stomatognathic muscular activation and mandibular movement during spontaneous saliva swallowing.</p> <p>The aim of our study was to investigate the activity patterns of the mandibular elevator muscles (masseter and anterior temporalis muscles), the submental muscles, and the neck muscles (sternocleidomastoid muscles) in healthy people during spontaneous swallowing of saliva and to relate the muscular activities to mandibular movement.</p> <p>Methods</p> <p>The spontaneous swallowing of saliva of 111 healthy individuals was analyzed using surface electromyography (SEMG) and a computerized kinesiography of mandibular movement.</p> <p>Results</p> <p>Fifty-seven of 111 patients swallowed without occlusal contact (SNOC) and 54 individuals had occlusal contact (SOC). The sternocleidomastoid muscles showed a slight, but constant activation during swallowing. The SEMG of the submental and sternocleidomastoid muscles showed no differences between the two groups. The SEMG of the anterior temporalis and masseter muscles showed significant differences (p < 0.0001). The duration of swallowing was significantly higher in the SNOC subjects. Gender and age were not related to electromyographic activation. Healthy SOC and SNOC behaved in different ways.</p> <p>Conclusion</p> <p>The data suggest that there is not a single "normal" or "typical" pattern for spontaneous saliva swallowing. The polygraph seemed a valuable, simple, non-invasive and reliable tool to study the physiology of swallowing.</p

Ultrasound evaluation in combination with finger extension force measurements of the forearm musculus extensor digitorum communis in healthy subjects

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to evaluate the usefulness of an ultrasound-based method of examining extensor muscle architecture, especially the parameters important for force development. This paper presents the combination of two non-invasive methods for studying the extensor muscle architecture using ultrasound simultaneously with finger extension force measurements.</p> <p>Methods</p> <p>M. extensor digitorum communis (EDC) was examined in 40 healthy subjects, 20 women and 20 men, aged 35–73 years. Ultrasound measurements were made in a relaxed position of the hand as well as in full contraction. Muscle cross-sectional area (CSA), pennation angle and contraction patterns were measured with ultrasound, and muscle volume and fascicle length were also estimated. Finger extension force was measured using a newly developed finger force measurement device.</p> <p>Results</p> <p>The following muscle parameters were determined: CSA, circumference, thickness, pennation angles and changes in shape of the muscle CSA. The mean EDC volume in men was 28.3 cm³and in women 16.6 cm³. The mean CSA was 2.54 cm²for men and 1.84 cm²for women. The mean pennation angle for men was 6.5° and for women 5.5°. The mean muscle thickness for men was 1.2 cm and for women 0.76 cm. The mean fascicle length for men was 7.3 cm and for women 5.0 cm. Significant differences were found between men and women regarding EDC volume (p < 0.001), CSA (p < 0.001), pennation angle (p < 0.05), muscle thickness (p < 0.001), fascicle length (p < 0.001) and finger force (p < 0.001). Changes in the shape of muscle architecture during contraction were more pronounced in men than women (p < 0.01). The mean finger extension force for men was 96.7 N and for women 39.6 N. Muscle parameters related to the extension force differed between men and women. For men the muscle volume and muscle CSA were related to extension force, while for women muscle thickness was related to the extension force.</p> <p>Conclusion</p> <p>Ultrasound is a useful tool for studying muscle architectures in EDC. Muscle parameters of importance for force development were identified. Knowledge concerning the correlation between muscle dynamics and force is of importance for the development of new hand training programmes and rehabilitation after surgery.</p

Measurement of pharyngeal sensory cortical processing: technique and physiologic implications

<p>Abstract</p> <p>Background</p> <p>Dysphagia is a major complication of different diseases affecting both the central and peripheral nervous system. Pharyngeal sensory impairment is one of the main features of neurogenic dysphagia. Therefore an objective technique to examine the cortical processing of pharyngeal sensory input would be a helpful diagnostic tool in this context. We developed a simple paradigm to perform pneumatic stimulation to both sides of the pharyngeal wall. Whole-head MEG was employed to study changes in cortical activation during this pharyngeal stimulation in nine healthy subjects. Data were analyzed by means of synthetic aperture magnetometry (SAM) and the group analysis of individual SAM data was performed using a permutation test.</p> <p>Results</p> <p>Our results revealed bilateral activation of the caudolateral primary somatosensory cortex following sensory pharyngeal stimulation with a slight lateralization to the side of stimulation.</p> <p>Conclusion</p> <p>The method introduced here is simple and easy to perform and might be applicable in the clinical setting. The results are in keeping with previous findings showing bihemispheric involvement in the complex task of sensory pharyngeal processing. They might also explain changes in deglutition after hemispheric strokes. The ipsilaterally lateralized processing is surprising and needs further investigation.</p

Sensory Input Pathways and Mechanisms in Swallowing: A Review

Over the past 20 years, research on the physiology of swallowing has confirmed that the oropharyngeal swallowing process can be modulated, both volitionally and in response to different sensory stimuli. In this review we identify what is known regarding the sensory pathways and mechanisms that are now thought to influence swallowing motor control and evoke its response. By synthesizing the current state of research evidence and knowledge, we identify continuing gaps in our knowledge of these mechanisms and pose questions for future research

Neuromuscular imaging in inherited muscle diseases

Driven by increasing numbers of newly identified genetic defects and new insights into the field of inherited muscle diseases, neuromuscular imaging in general and magnetic resonance imaging (MRI) in particular are increasingly being used to characterise the severity and pattern of muscle involvement. Although muscle biopsy is still the gold standard for the establishment of the definitive diagnosis, muscular imaging is an important diagnostic tool for the detection and quantification of dystrophic changes during the clinical workup of patients with hereditary muscle diseases. MRI is frequently used to describe muscle involvement patterns, which aids in narrowing of the differential diagnosis and distinguishing between dystrophic and non-dystrophic diseases. Recent work has demonstrated the usefulness of muscle imaging for the detection of specific congenital myopathies, mainly for the identification of the underlying genetic defect in core and centronuclear myopathies. Muscle imaging demonstrates characteristic patterns, which can be helpful for the differentiation of individual limb girdle muscular dystrophies. The aim of this review is to give a comprehensive overview of current methods and applications as well as future perspectives in the field of neuromuscular imaging in inherited muscle diseases. We also provide diagnostic algorithms that might guide us through the differential diagnosis in hereditary myopathies

Neural processing of natural sounds

Natural sounds include animal vocalizations, environmental sounds such as wind, water and fire noises and non-vocal sounds made by animals and humans for communication. These natural sounds have characteristic statistical properties that make them perceptually salient and that drive auditory neurons in optimal regimes for information transmission.Recent advances in statistics and computer sciences have allowed neuro-physiologists to extract the stimulus-response function of complex auditory neurons from responses to natural sounds. These studies have shown a hierarchical processing that leads to the neural detection of progressively more complex natural sound features and have demonstrated the importance of the acoustical and behavioral contexts for the neural responses.High-level auditory neurons have shown to be exquisitely selective for conspecific calls. This fine selectivity could play an important role for species recognition, for vocal learning in songbirds and, in the case of the bats, for the processing of the sounds used in echolocation. Research that investigates how communication sounds are categorized into behaviorally meaningful groups (e.g. call types in animals, words in human speech) remains in its infancy.Animals and humans also excel at separating communication sounds from each other and from background noise. Neurons that detect communication calls in noise have been found but the neural computations involved in sound source separation and natural auditory scene analysis remain overall poorly understood. Thus, future auditory research will have to focus not only on how natural sounds are processed by the auditory system but also on the computations that allow for this processing to occur in natural listening situations.The complexity of the computations needed in the natural hearing task might require a high-dimensional representation provided by ensemble of neurons and the use of natural sounds might be the best solution for understanding the ensemble neural code