Algorithmic Extraction of Morphological Statistics from Electronic Archives of Neuroanatomy

摘要: A large amount of digital data describing the 3D structure neuronal cells has been collected by many laboratories worldwide in past decade. Part these is made available to scientific community through internet-accessible archives. The potential such sharing great, that experimental acquisition high-resolution and complete tracing reconstructions extremely time consuming. Through electronic databases, scientists can reanalyze mine archived a fast inexpensive way. However, lack software tools for this purpose so far limited use shared neuroanatomical data. Here we introduce L-Measure (LM), free package extraction morphological from digitized reconstructions. LM consists user-friendly graphical interface flexible core engine. allows both single-neuron study statistical analysis sets neurons. Studies be specific regions dendrites; statistics returned as raw data, frequency histograms, or cross-parameter dependencies. current version (v1.0) runs under Windows its output compatible with MS-Excel.