Segment Muscle Analysis
Segment Muscle Analysis - Related Videos
11:38
Volume Segmentation and Analysis of Biological Materials Using SuRVoS (Super-region Volume Segmentation) Workbench
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Cited by 10 •
2017
Segmentation of three-dimensional data from many imaging techniques is a major bottleneck in analysis of complex biological systems. Here, we describe the use of SuRVoS Workbench to semi-automatically segment volumetric data at various length-scales using example datasets from cryo-electron tomography, cryo soft X-ray tomography, and phase contrast X-ray tomography techniques.
08:42
Myo-mechanical Analysis of Isolated Skeletal Muscle
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Cited by 25 •
2011
To assess the in vivo effects of therapeutic interventions for muscle disease, methods are needed to quantitate force generation and fatigability in treated muscle. We detail an approach to evaluating myo-mechanical properties in explanted mouse hindlimb muscle. This analysis provides a robust approach to quantitating the effects of genetic modification on muscle function, as well as comparison of therapies in mouse models of muscle disease.
08:36
Semi-automated Analysis of Mouse Skeletal Muscle Morphology and Fiber-type Composition
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Cited by 26 •
2017
Immunohistochemical staining of myosin heavy chain isoforms has emerged as the state-of-the-art discriminator of skeletal muscle fiber-type (i.e., type I, type IIA, type IIX, type IIB). Here, we present a staining protocol along with a novel semi-automated algorithm that facilitates rapid assessment of fiber-type and fiber morphology.
10:27
Do's and Don'ts in the Preparation of Muscle Cryosections for Histological Analysis
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Cited by 44 •
2015
Here we demonstrate the most efficient methods for freezing, embedding, cryosectioning, and staining of muscle biopsies to avoid freezing artifacts.
06:12
Dissection of the Transversus Abdominis Muscle for Whole-mount Neuromuscular Junction Analysis
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Cited by 23 •
2014
In this video we demonstrate a protocol for dissection of the transversus abdominis muscle of the mouse and use immunofluorescence and microscopy to visualize neuromuscular junctions.
FAQs
Whole-muscle measurements can combine signals from regions that do not respond identically. Comparing defined segments separates regional differences in structure, activation, recruitment, or coordination, making localized patterns visible. This finer resolution helps researchers determine whether a measured muscle response reflects broadly shared activity or a change concentrated in a particular anatomical or temporal segment.
Anatomical segmentation compares different regions within a muscle, while temporal segmentation compares portions of a recording or movement-related dataset. The first emphasizes localized structural or activation differences; the second highlights changes across time. Using the appropriate segmentation scheme helps align measurements with questions about regional function, changing activity, or motor coordination.
Segment-level recruitment patterns show which muscle regions contribute to an observed response, whereas coordination patterns describe how activity is distributed among segments during a task. These measurements help link neural commands with localized muscular effects. They are therefore useful for examining how the nervous system organizes movement and posture rather than treating muscle activity as uniform.
Motor learning studies can use segment comparisons to identify changes in the distribution of muscle activity that a single whole-muscle value could conceal. Differences among segments may clarify whether learning is associated with altered recruitment, improved coordination, or a change in localized responses. This supports more detailed interpretation of how sensorimotor control develops.
A typical workflow begins by selecting meaningful anatomical or temporal boundaries, then dividing the muscle, recording, or dataset accordingly. Researchers measure features such as cross-sectional characteristics, activation patterns, or electromyographic signals within each segment. They then compare the resulting measurements to identify regional differences relevant to muscle function and neural control.
Depending on the research question, investigators can compare cross-sectional features, activation patterns, or electromyographic signals across defined segments. These measurements provide complementary information about muscle structure and activity. Examining them side by side can show whether segment differences involve physical organization, neural or muscular activation, or the timing and distribution of recorded activity.
The method is useful when a disorder or intervention may affect muscle regions differently, because segment comparisons can expose localized changes instead of reducing them to one whole-muscle result. In neuromuscular disorder and rehabilitation studies, these findings can help characterize altered muscle responses and evaluate questions about neuromuscular function, recovery, or motor control.
In neuroscience, segment-level measurements provide a way to examine the relationship between neural commands and localized muscle responses during movement, posture, and motor learning. By comparing activation or electromyographic patterns across segments, researchers can study how sensorimotor control is organized and how that organization may differ in experimental models or clinical contexts.