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Competition

Competition

When organisms require the same limited resources within an environment, they may have to compete for them. Competition is a net-negative interaction. Even if two competing individuals or populations do not interact directly, the overall fitness of both competitors is lowered as a result of not having full access to the limited resource.

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Internal Receptors

Many cellular signals are hydrophilic and therefore cannot pass through the plasma membrane. However, small or hydrophobic signaling molecules can cross the hydrophobic core of the plasma membrane and bind to internal, or intracellular, receptors that reside within the cell. Many mammalian steroid hormones use this mechanism of cell signaling, as does nitric oxide (NO) gas.

Diffusion

Diffusion

Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...

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Diffusion

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Internal Energy

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The total of all possible kinds of energy present in a substance is called the internal energy (U), sometimes symbolized as E. Suppose a system with initial internal energy, Uinitial, undergoes a change in energy (transfer of work or heat), and the final internal energy of the system is Ufinal. Change in internal energy equals the difference between Ufinal and Uinitial.

Internal Energy

Internal Energy

The internal energy of a thermodynamic system is the sum of the kinetic and potential energies of all the molecules or entities in the system. The kinetic energy of an individual molecule includes contributions due to its rotation and vibration, as well as its translational energy. The potential energy is associated only with the interactions between one molecule and the other molecules of the system. Neither the system's location nor its motion is of any consequence as far as the internal...

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Related Experiment Video

Updated: Feb 1, 2026

Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery

Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery

Published on: July 5, 2021

Challenges in diffusion MRI tractography - Lessons learned from international benchmark competitions.

Kurt G Schilling¹, Alessandro Daducci², Klaus Maier-Hein³

¹Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States of America.

Magnetic Resonance Imaging

|December 4, 2018

Summary

Diffusion MRI (dMRI) fiber tractography is crucial for mapping brain connectivity. A decade of challenges highlights the need to validate dMRI tractography methods for accuracy and reproducibility in clinical and research settings.

Keywords:

Accuracy Algorithms Challenges Diffusion MRI Tractography Validation

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Last Updated: Feb 1, 2026

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Area of Science:

Neuroimaging
Biomedical Engineering
Computational Neuroscience

Background:

Diffusion MRI (dMRI) fiber tractography is widely used for noninvasive brain structural connectivity mapping.
Current dMRI tractography methods have limitations impacting accuracy and reproducibility.
Validation is critical for reliable scientific conclusions and clinical applications.

Purpose of the Study:

To summarize key lessons learned from a decade of diffusion MRI tractography challenges.
To provide perspective on the past, present, and future challenges in the field.
To evaluate common and emerging tractography algorithms.

Main Methods:

International benchmark competitions ('challenges') were organized.
A platform was provided to compare algorithms and results fairly.
Common and emerging dMRI tractography algorithms were evaluated.

Main Results:

Lessons from ten years of tractography challenges have been summarized.
Insights into the reliability of the tractography process were gained.
The evaluation advanced the understanding of common and emerging algorithms.

Conclusions:

A decade of challenges has provided valuable insights into dMRI tractography.
Addressing current and future challenges is essential for advancing the field.
Continued validation efforts are crucial for clinical and research applications.