Why is NeuronBank Needed?
Despite the fundamental value of identifying neurons and mapping circuits, progress seems to have slowed in recent years. For example, the Aplysia abdominal ganglion has proven invaluable for basic research on learning and memory, yet only 247 of its estimated 1600 neurons (Coggeshall, 1976) have been identified, and no new identifications have been made in the past 10 years (full review is here). Similarly, only 324 of an estimated 8000 neurons have been identified in the Tritonia central ganglia, with nearly 300 neurons identified in the initial two publications (Getting, 1976; Willows et al., 1973).
Consolidate our Current Knowledge. Neuroscience has produced a wealth of data on identified neurons and the circuits they form, but this data is distributed over decades of journal articles. It is thus difficult to organize and increasingly fragmented over time. For example, a researcher interested in the siphon-withdrawal circuit in Aplysia californica would have to delve into 40 years of publications, some of which were subsequently shown to contain inaccuracies and nomenclature inconsistencies. Clearly, journal-based representation of neural circuitry is untenable. To facilitate progress, we need to develop systems for entering, storing, and mining information about identified neuron types and their connections. The NeuronBank project seeks to fill this need.
Unpublishable data. The impact of new neuron identifications diminishes in proportion to the number already known and has generally fallen below the level for journal-based publication. NeuronBank will help alleviate this problem by serving as a repository for new observations of identified neurons and their synaptic connections. Importantly, new observations will be uniquely citable and credited to the reporting lab.
Informatics tool for Identifying New Neurons. Identifying new neurons is the tedious task of ensuring that the suite of characteristics that describe a neuron is unique and will enable definitive identification for future experiments. NeuronBank will allow users to rapidly check the uniqueness of an observation and even will be able to suggest diagnostics for further clarifying if a neuron is a known type or novel. For new cell types, NeuronBank can compare neurons with neighboring identified types and suggest the qualities that would provide the most distinctive markers of identity. Thus, NeuronBank will function not only as a knowledge base but also as an innovative informatics approach to identifying new neuron types. This functionality could be particularly fruitful, as researchers regularly come across apparently novel cell types in the course of experimentation. Without a quick way to cross-reference the observation against other known types or a means of publishing the observation, these novel cells are usually abandoned and ignored. The availability of NeuronBank could help transform these un-utilized observations into a rapid expansion in the state of knowledge.
Coggeshall RE (1967) A light and electron microscope study of the abdominal ganglion of Aplysia californica. Journal of Neurophysiology 30:1263-1287.
Getting PA (1976) Afferent neurons mediating escape-swimming of the marine molusk, Tritonia diomedia. Journal of comparative physiology. A, Sensory, neural, and behavioral physiology . 110:271-386.
Willows AO, Dorsett DA, Hoyle G (1973) The neuronal basis of behavior in Tritonia. I. Functional organization of the central nervous system. Journal of Neurobiology 4:207-237.