- Poster presentation
- Open Access
Development of avalanches and efficient communication in neuronal networks
© Thivierge and Tauskela; licensee BioMed Central Ltd. 2014
- Published: 21 July 2014
- Neural Development
- Cortical Network
- Gradual Development
- Artificial Data
- Microelectrode Array
To examine the implications of this trend, we evaluated communication between pairs of neurons using a measure of transfer entropy that quantifies the amount of information (in bits) in a neuron found in the past history of another neuron . Transfer entropy increased over development, and its distribution followed a power law with a slope approaching α≈1.5 towards 30 days in vitro (Figure 1C). Next, we generated artificial data whose distribution matched the power law of transfer entropy observed experimentally. Using graph-theoretical analyses, we show that a power law with an exponent of α≈1.5 maximizes network efficiency by facilitating rapid communication across neurons while minimizing the overall traffic burden (Figure 1D).
In sum, this study links the gradual development of power law scaling with increased communication efficiency in networks of cortical neurons. Incremental changes in network dynamics suggest that power scaling of avalanches and communication are shaped concurrently over the course of in vitro development, and may arise from a common origin. This developmental trend poses a particular challenge for computational models of avalanches that typically focus on the endpoint of development , and therefore merits the attention of further experimental and theoretical work.
This work was funded by grants to J.P.T. from NSERC Discovery and CIHR operating funds, as well as intramural funds from the National Research Council. Authors are thankful to Amy Aylsworth for technical assistance.
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