Two-dimensional Networks
Two-dimensional Networks - Related Videos
02:39
Building Three-Dimensional Neuronal Networks Coupled to Micro-Electrode Arrays
0 Views •
2025
This video demonstrates the development of a 3D neuronal culture coupled to a planar microelectrode array with hippocampal neurons. The isolated neurons form a 2D network on the microelectrode array's active area and adhere to glass microbeads in a multi-well plate with a membrane insert. Upon transferring these neuron-coated microbeads to the electrode, they organize into an interconnected 3D neural network.
02:18
Network Covalent Solids
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2020
Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds. To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...
09:01
A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
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Cited by 1 •
2014
This video presents a method of examining age-related changes in functional connectivity of cognitive control networks engaged by targeted tasks/processes. The technique is based on multi-variate analysis of fMRI data.
10:45
Anatomically Inspired Three-dimensional Micro-tissue Engineered Neural Networks for Nervous System Reconstruction, Modulation, and Modeling
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Cited by 40 •
2017
This manuscript details the fabrication of micro-tissue engineered neural networks: three-dimensional micron-sized constructs comprised of long aligned axonal tracts spanning aggregated neuronal population(s) encased in a tubular hydrogel. These living scaffolds can serve as functional relays to reconstruct or modulate neural circuitry or as biofidelic test-beds mimicking gray-white matter neuroanatomy.
02:26
Protein Networks
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2020
An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions. These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...
FAQs
Spatial arrangement shows not only which biological components are connected, but also where those connections occur across a plane. This distinction helps researchers relate local organization to tissue architecture, cell-to-cell proximity, or molecular patterns. Two systems with similar connectivity may therefore display different biological behavior if their links are distributed differently in space.
The meaning of each element depends on the biological question. Nodes can represent cells, proteins, genes, or ecological components, while edges can encode contact, communication, regulation, or other associations. Defining these elements explicitly allows the same network framework to describe different biological systems while preserving the distinction between entities and their relationships.
Connectivity describes how readily components are linked through the network, whereas clustering indicates whether connections concentrate into locally organized groups. Examining both properties helps reveal whether biological organization is dispersed, tightly grouped, or shaped by local neighborhoods. These structural measures support analysis of how small-scale interactions may contribute to broader biological patterns.
A network can connect local events to system-level organization by showing how interactions accumulate across neighboring components. Repeated contacts, communication, or regulation may create organized spatial patterns rather than isolated effects. In biology, this perspective supports investigation of how cell organization, tissue architecture, or molecular interactions contribute to pattern formation across a larger region.
Researchers first select the biological entities to represent as nodes and determine which relationships should become edges. They then preserve the entities’ organization across a plane and examine properties such as connectivity, clustering, and spatial arrangement. The resulting model can be used to interpret organization and compare patterns among biological systems.
Such comparisons are useful when biological differences may involve organization as well as the presence or absence of individual components. Applying the same network perspective to healthy, developing, and diseased systems can reveal changes in cell-to-cell organization, tissue architecture, or molecular interaction patterns. This supports analysis of how biological structure shifts across conditions.
The framework can address questions about how cells are arranged, how tissues acquire architecture, how proteins or genes interact, and how ecological components are associated in space. It is especially valuable when researchers need to connect spatial relationships with network structure, allowing local organization and larger-scale biological behavior to be examined together.