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Graph theoretical comparison of functional connectivity between cLTP treated and untreated microelectrode arrays

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Analyzing graph properties of neural networks has recently gained much attention in attempts to understand how information is processed in the brain... Using in-vitro techniques to form neural networks has increased in popularity as it allows one to develop small, easy to record networks that maintain many of the graph properties of larger brain networks... MEAs can be used to grow neural networks from disassociated cells to understand how neurons spontaneously connect to create networks and how these networks then evolve over time... To understand the network formation of MEA cultured neurons, we study the graph theoretical properties of two MEAs networks, the control MEA network and the MEA network treated with chemical Long Term Potentiation (cLTP)... We find that the synchronization and average node degree increase dramatically for the cLTP treated networks while the untreated network shows no obvious change... We will determine how cLTP affects these properties... The graphical analysis will enable us to identify what type of network each is (such as a small-world or a scale free network) and determine whether cLTP has an effect on the network development or merely on the strength of connectivity... We conjecture that cLTP treated networks have more efficient and quicker communication between nodes... Therefore, the cLTP treated networks show greater clustering as well as shorter path length than the untreated networks... Information flow is another important aspect of such graph model... We intend to develop directed graphs using transfer entropy to study how information flow of the network may change during its development.

No MeSH data available.


Graph models. (a) cLTP treated MEA network at baseline; (b) cLTP treated MEA network at 5 days past baseline.
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Figure 1: Graph models. (a) cLTP treated MEA network at baseline; (b) cLTP treated MEA network at 5 days past baseline.


Graph theoretical comparison of functional connectivity between cLTP treated and untreated microelectrode arrays
Graph models. (a) cLTP treated MEA network at baseline; (b) cLTP treated MEA network at 5 days past baseline.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4697556&req=5

Figure 1: Graph models. (a) cLTP treated MEA network at baseline; (b) cLTP treated MEA network at 5 days past baseline.

View Article: PubMed Central - HTML

AUTOMATICALLY GENERATED EXCERPT
Please rate it.

Analyzing graph properties of neural networks has recently gained much attention in attempts to understand how information is processed in the brain... Using in-vitro techniques to form neural networks has increased in popularity as it allows one to develop small, easy to record networks that maintain many of the graph properties of larger brain networks... MEAs can be used to grow neural networks from disassociated cells to understand how neurons spontaneously connect to create networks and how these networks then evolve over time... To understand the network formation of MEA cultured neurons, we study the graph theoretical properties of two MEAs networks, the control MEA network and the MEA network treated with chemical Long Term Potentiation (cLTP)... We find that the synchronization and average node degree increase dramatically for the cLTP treated networks while the untreated network shows no obvious change... We will determine how cLTP affects these properties... The graphical analysis will enable us to identify what type of network each is (such as a small-world or a scale free network) and determine whether cLTP has an effect on the network development or merely on the strength of connectivity... We conjecture that cLTP treated networks have more efficient and quicker communication between nodes... Therefore, the cLTP treated networks show greater clustering as well as shorter path length than the untreated networks... Information flow is another important aspect of such graph model... We intend to develop directed graphs using transfer entropy to study how information flow of the network may change during its development.

No MeSH data available.