Function Visualization
Function Visualization - Related Videos
07:41
Behavioral Assessment of Visual Function via Optomotor Response and Cognitive Function via Y-Maze in Diabetic Rats
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Cited by 17 •
2020
Neural degeneration in both eyes and brain as a result of diabetes can be observed through behavioral tests carried out on rodents. The Y-maze, a measure of spatial cognition, and the optomotor response, a measure of visual function, both provide insight into potential diagnoses and treatments.
08:59
Using the optokinetic response to study visual function of zebrafish
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Cited by 34 •
2010
Optokinetic response has been widely used to assess the visual functions of larval zebrafish. Nevertheless, the standard protocol for larval fish is not yet readily applicable in adults1-5. Here, we introduce how to measure the OKR of adult zebrafish using a new protocol which is established in our lab.
09:08
Combined SPECT and CT Imaging to Visualize Cardiac Functionality
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2023
Source: Alycia G. Berman, James A. Schaber, and Craig J. Goergen, Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana Here we will demonstrate the fundamentals of single-photon emission computed tomography/computed tomography (SPECT/CT) imaging using mice. The technique involves injecting a radionuclide into a mouse, imaging the animal after it is distributed throughout the body, and then reconstructing the produced images to create a volumetric dataset. This can...
08:34
A Simple Behavioral Assay for Testing Visual Function in Xenopus laevis
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Cited by 26 •
2014
Xenopus laevis tadpoles prefer swimming on the white side of a black/white tank. This behavior is guided by their vision. Based on this behavior, we present a simple assay to test the visual function of tadpoles.
11:49
Using High Resolution Computed Tomography to Visualize the Three Dimensional Structure and Function of Plant Vasculature
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Cited by 62 •
2013
High resolution x-ray computed tomography (HRCT) is a non-destructive diagnostic imaging technique that can be used to study the structure and function of plant vasculature in 3D. We demonstrate how HRCT facilitates exploration of xylem networks across a wide range of plant tissues and species.
FAQs
A graph makes slope visible through the direction and steepness of a curve, while intercepts identify where it meets the coordinate axes. Extrema, or local highest and lowest points, indicate changes in behavior that may be difficult to recognize in a symbolic expression alone. These visual cues connect algebraic form with geometric interpretation during mathematical analysis.
Function Visualization can show whether a curve appears to progress without a visible break and whether its values approach a boundary or trend without reaching it. These visual patterns provide geometric evidence about continuity and asymptotic behavior. Examining them helps students and researchers interpret how a function behaves across its plotted range rather than focusing only on its written expression.
Changing parameters produces visible transformations of the curve, allowing users to associate algebraic changes with geometric effects. An interactive display can make it easier to compare several parameter settings and identify which changes alter position, shape, or other graph features. This immediate visual feedback supports experimentation and strengthens intuition about relationships within mathematical expressions.
Plotting multiple functions in a shared visual setting makes differences in slope, intercepts, extrema, continuity, and asymptotic behavior easier to inspect. The comparison can reveal where models behave similarly or diverge, providing geometric context for symbolic or numerical reasoning. This is especially useful when selecting, examining, or communicating the behavior of alternative mathematical models.
Begin with the mathematical expression, determine corresponding input and output values, and represent those pairs on coordinate axes. Plotting the points produces a curve or graphical pattern whose features can then be examined. Reviewing slope, intercepts, extrema, continuity, and asymptotic behavior turns the plotted result into an interpretable mathematical representation rather than an isolated collection of points.
Interactive tools are particularly useful when the goal is to investigate how parameter changes transform a curve. A user can adjust a parameter, observe the resulting graph, and compare the new features with the original display. This process supports exploratory learning, helps connect symbolic expressions to geometric meaning, and makes changing relationships easier to communicate.
In algebra, graphs connect expressions with geometric features; in calculus, they help examine behavior such as extrema and continuity. Modeling uses visual comparisons to study relationships, while data analysis benefits from graphical interpretation of patterns. Across these areas, visualization supports intuition and provides a way to examine mathematical relationships that complements symbolic work.
A visualization can expose patterns, clarify relationships, and support the interpretation of slope, intercepts, extrema, continuity, and asymptotic behavior. It also gives students a clearer basis for developing intuition and gives researchers a means to inspect complex relationships. When presented alongside mathematical reasoning, the graph can communicate results more clearly to others.