High-resolution Mapping
High-resolution Mapping - Related Videos
11:07
High-resolution Optical Mapping of the Mouse Sino-atrial Node
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Cited by 17 •
2016
Here, we present a protocol for optical mapping of electrical activity from the mouse right atrium and especially the sino-atrial node, at a high spatial and temporal resolution.
10:36
Ultrasound Localization Microscopy for Super-Resolution Mapping of the Rodent Brain Microvasculature
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2025
Ultrasound Localization Microscopy (ULM) is a recently developed technique that allows for an unprecedented level of resolution in imaging the microvasculature in vivo. In this work, we describe in detail how to obtain super-resolved images of the brain microvasculature in rodents using a standardized functional ultrasound imaging platform designed for preclinical research.
09:48
Fiber Optic Distributed Sensors for High-resolution Temperature Field Mapping
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Cited by 8 •
2016
We demonstrate use of a fiber optic distributed sensor for mapping the temperature field of mixing air jets. The Rayleigh scattering-based sensor generates thousands of data points along a single fiber to provide exceptional spatial resolution that is unattainable with traditional sensors such as thermocouples.
10:26
AFM-based Mapping of the Elastic Properties of Cell Walls: at Tissue, Cellular, and Subcellular Resolutions
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Cited by 39 •
2014
We describe a method to map mechanical properties of plant tissues using an atomic force microscope (AFM). We focus on how to record mechanical changes that take place in cell walls during plant development at wide-field mesoscale, enabling these changes to be correlated with growth and morphogenesis.
09:17
High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation
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Cited by 20 •
2011
This report provides a detailed description of the methodology and results of simultaneous endocardial and epicardial optical mapping of electrical excitation in the intact left atrium of a Langendorff-perfused sheep heart during stretch-induced atrial fibrillation.
FAQs
Spatial coordinates are the key mechanism that turns biological signals into interpretable location-specific patterns. Microscopy and molecular labeling generate signals, while image acquisition records them and computational analysis links each signal to a defined position. This preserves relationships among cellular features and tissue regions, allowing researchers to examine where changes occur rather than only whether they occur.
The method can be applied to structures, molecules, and activities, then used to examine cell organization or gene-expression distributions within tissue. It can also track developmental changes and disease-associated remodeling. These categories connect what is detected at a location with biological processes that vary across a sample, expanding analysis beyond a single overall measurement.
High-resolution Mapping can expose localized patterns that disappear when signals are averaged across a larger region. Spatially separated features may show different organization, expression, or activity even when a broad measurement reports one combined value. This makes the approach useful for comparing normal and abnormal samples and for generating hypotheses about cellular interactions.
Computational analysis converts acquired image information into an organized spatial representation. By linking signals with coordinates and cellular features with tissue location, it helps researchers compare regions, recognize distributions, and relate observed patterns to developmental or disease-associated changes. Its role is therefore interpretive as well as organizational: it supports mechanistic hypotheses from spatial observations.
A typical workflow combines molecular labeling, microscopy, image acquisition, and computational analysis. Labeling provides detectable signals, microscopy captures their physical distribution, and image acquisition records the resulting view for analysis. The final computational step connects observations to spatial coordinates, producing a map that can be examined across cells, tissue regions, or samples.
Researchers may choose this approach when tissue location matters to the biological question, such as studying cell organization, gene-expression distributions, developmental change, or disease-associated remodeling. It is also relevant for examining therapeutic response. Preserving location helps distinguish whether a change is widespread or confined to particular cells or tissue regions.
In biology, these maps support more than visualization. They can connect cellular features with tissue function, reveal possible interactions among cells, and guide comparisons between normal and abnormal samples. The resulting spatial evidence helps formulate mechanistic hypotheses, which can then inform studies of tissue behavior and therapeutic response.