BigNeuron: Unlocking the Secrets of the Human Brain

Thousands of detailed neuron images, from different organisms, currently sit in individual data collections across the world, comprising several petabytes of data altogether. Despite this plethora of data, made possible with advancements in cellular brain imaging, data standardization is still a major hurdle to gaining an accurate understanding of how neurons work. Over the years, dozens of imaging paradigms and algorithms have been created for visualizing the 3D structure of neurons — leading to a variety of unequal datasets in the field. However, neuroscientists widely agree that to solve the mysteries of the brain, they need to cross-compare these datasets. That’s why many of the field’s brightest minds are participating in BigNeuron, a community effort to define and advance the state of single-neuron reconstruction, analysis and create a common platform for analyzing 3D neuronal structures. In an attempt to find a standard neuron reconstruction algorithm, BigNeuron will sponsor a series of international hackathons and workshops where contending algorithms will be ported onto a common software platform in order to analyze neuronal physical structures using the same core dataset. The data generated by these benchmark runs will be used to develop a comprehensive annotated database of complex neuronal morphology, generate a searchable tool for discovering annotated and unique characteristics of neuronal morphology and lay the groundwork for potentially integrating this tool, with large-scale data sets, linking form to neuronal function. To read more about this, click here.