The advancement of science depends heavily upon the ability of researchers to collect, store, analyze and share their data efficiently. In order to help achieve these goals, informatics research has been playing an increasingly important role in various scientific communities. These new tools have allowed researchers, in this scientific community as well as other communities, to efficiently store, analyze and share their sequence data. In the last decade attention has also focused on the development of informatics tools for the neuroscience community. One of the problems encountered by many neuroscientists is the coherent storage, organization, and retrieval of extremely diverse and large datasets.
Current technology allows neuroscientists to collect massive amounts of data.
In order to help the neuroscientist manage these complex datasets we have developed a novel database schema and implementation that allows datasets from di verse labs to be stored coherently in a single framework. The formal structure of that framework, called NeuroCore, will be detailed in Chapter 3.1, while various applications devised to help interact with NeuroCore databases will be described in Chapter 3.2. The data collected from each of these neurons or synapses typically consists of data from multiple individual training trials. In this experiment recordings are made from cerebellar cortex and nuclei and other structures while the animal performs certain behaviors as various external stimuli are presented. The data consists of unit recordings from various brain regions as well as recordings of the subject's behavioral response.