Making Neuroinformatics Integral to Studying the Brain

The current issue of Science includes the special section Dealing with Data. In it there is a perspective paper on neuroscience and data titled “Challenges and Opportunities in Mining Neuroscience Data” (published February 11, 2011 in Science). The focus of the perspective is on the Human Connectome Project and the Neuroscience Information Framework. These important projects are familiar to those of you who have been following my posts (see “Other related blog posts” below). However, the authors point out a very important fact. Most neuroinformatics resources remain underused by the research community.

The authors conclude with eight suggestions on how to make neuroinformatics integral to studying the brain:

• Neuroscientists should share their data and in a form that is easily accessible.
• Neuroscience databases need to be created, populated, and sustained with adequate support from federal and other funding mechanisms.
• Databases become more useful as they are more densely populated so adding to existing databases may be preferable to creating new ones.
• Data consumption will increasingly involve machines first and humans second. Neuroscientists should annotate content using community ontologies and identifiers. Coordinates, atlas, and registration method should be specified when referencing spatial locations.
• Some types of published data should be reported in standardized table formats that facilitate data mining.
• Investment needs to occur in interdisciplinary research to develop computational, machine-learning, and visualization methods for synthesizing across spatial and temporal information tiers.
• Educational strategies from undergraduate through postdoctoral levels are needed to ensure that neuroscientists of the next generation are proficient in data mining and using the data-sharing tools of the future.
• Cultural changes in the neurosciences are needed to promote widespread participation in this endeavor.

These suggestions, if followed, would certainly move the neuroscience community in the right direction. They seem to assume, however, that human consumption of neuroscience data will remain primarily as it is. I don’t think this is the case. We will see radical changes in human data consumption as machines become able to do more with the data without human intervention. The suggestion to use “standardized table formats” in relational databases is good but what I think would even be better is to focus efforts on getting the data deployed to the Semantic Web. Nevertheless, these two goals are not mutually exclusive.

Other related blog posts:

Mapping the Brain’s Connections: the Connectome

NIF: When You’re Looking for Neuroscience Resources Including Data

NIF: Neurons, Models, and Grants

NIF: Better Literature Search