Extensive research has been conducted about the 300 different kinds of neurons in the brain and their function, but this information has been spread across tens of thousands of research papers.
Now, researchers at Carnegie Mellon University have used data mining techniques to create a "one stop shop" for information about neurons in the brain in a format similar to the one used by Wikipedia, according a new report in the Journal of Neurophysiology.
If we want to think about building a brain or re-engineering the brain, we need to know what parts we're working with," said Nathan Urban, director of Carnegie Mellon's BrainHubSM neuroscience initiative. "We know a lot about neurons in some areas of the brain, but very little about neurons in others. To accelerate our understanding of neurons and their functions, we need to be able to easily determine whether what we already know about some neurons can be applied to others we know less about."
A dynamic environment
To create the online resource, the team picked over 10,000 published papers that included physiological information describing how neurons responded to various inputs. Text mining algorithms were then used to "read" each of the papers and find the portions of each paper that recognized the kind of neuron studied. The team then separated the electrophysiological information associated with the properties of that neuronal type. The team also recovered data on how each of the tests in the literature was performed and corrected the information to account for any inconsistencies that might be due to the format of the experiment. All around, the researchers were able to gather and standardize information for around 100 different kinds of neurons.
Since current text algorithms are not perfect when it comes to mining data, the new online resource - called NeuroElectro - allows users to flag information they believe is incorrect. Site users can also submit new data - a la Wikipedia.
"It's a dynamic environment in which people can collect, refine and add data," Urban said. "It will be a useful resource to people doing neuroscience research all over the world."
The same Carnegie Mellon scientists are now contrasting the information on NeuroElectro with other types of information, including information on neurons' patterns of gene expression. In one instance, Urban's group is using a different freely available resource, the Allen Brain Atlas, to find if groups of neurons with very similar electrical function have comparable gene expression.
"It would take a lot of time, effort and money to determine both the physiological properties of a neuron and its gene expression," Urban said. "Our website will help guide this research, making it much more efficient."