Imagine you have a massive jigsaw puzzle, but instead of just fitting together the pieces, each piece represents a neuron in the brain and the connections between them. That’s what scientists are tackling with connectomics – constructing a map of neural circuitry. The problem? The maps are getting bigger and more complex, with tens of thousands of neurons and millions of connections. So, researchers developed neuPrint, a handy tool that allows scientists to easily explore and analyze these connectomes. With a user-friendly web interface and powerful APIs for the tech-savvy, neuPrint makes it possible for researchers worldwide to ask important questions about neural networks. It even provides tools to assess the quality of these reconstructions. By sharing their data openly, the researchers found that many readers were more interested in examining the raw data rather than their analysis. This suggests that data-only papers could be a valuable resource for scientists. And by making the data accessible online, scientific discoveries can spread much more quickly. So, if you’re curious about delving into the intricate workings of the brain, check out neuPrint and start exploring the hidden connections within!

Due to advances in electron microscopy and deep learning, it is now practical to reconstruct a connectome, a description of neurons and the chemical synapses between them, for significant volumes of neural tissue. Smaller past reconstructions were primarily used by domain experts, could be handled by downloading data, and performance was not a serious problem. But new and much larger reconstructions upend these assumptions. These networks now contain tens of thousands of neurons and tens of millions of connections, with yet larger reconstructions pending, and are of interest to a large community of non-specialists. Allowing other scientists to make use of this data needs more than publication—it requires new tools that are publicly available, easy to use, and efficiently handle large data. We introduce neuPrint to address these data analysis challenges. Neuprint contains two major components—a web interface and programmer APIs. The web interface is designed to allow any scientist worldwide, using only a browser, to quickly ask and answer typical biological queries about a connectome. The neuPrint APIs allow more computer-savvy scientists to make more complex or higher volume queries. NeuPrint also provides features for assessing reconstruction quality. Internally, neuPrint organizes connectome data as a graph stored in a neo4j database. This gives high performance for typical queries, provides access though a public and well documented query language Cypher, and will extend well to future larger connectomics databases. Our experience is also an experiment in open science. We find a significant fraction of the readers of the article proceed to examine the data directly. In our case preprints worked exactly as intended, with data inquiries and PDF downloads starting immediately after pre-print publication, and little affected by formal publication later. From this we deduce that many readers are more interested in our data than in our analysis of our data, suggesting that data-only papers can be well appreciated and that public data release can speed up the propagation of scientific results by many months. We also find that providing, and keeping, the data available for online access imposes substantial additional costs to connectomics research.

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