Definition
Algorithmic reconstruction of neuronal morphology is the process of parameterizing neurite branching patterns, quantifying the parameters for a given population of experimentally reconstructed neurons, and then feeding the data into an algorithm which computationally generates populations of “virtual” neurons.
Detailed Description
Background
Digitization of neuronal morphology is important for computational neuroscience because neuronal morphology affects synaptic integration and firing behavior within individual neurons as well as determining potential connectivity with other neurons (Ascoli 2002). However, experimental reconstruction techniques are still largely manual or, at best, semiautomated, requiring time and skill to accurately capture neuronal morphology. As computational models of the nervous system grow in scale...
References
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Graham, J. (2014). Algorithmic Reconstruction of Motoneuron Morphology. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_372-2
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DOI: https://doi.org/10.1007/978-1-4614-7320-6_372-2
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