Neuroscience Data and Neuroinformatics

January 31, 2013
by Pharm Tao

Neuroscience Data and Neuroinformatics

 

Neuroscience Data

 

At least 50% genes of the mammalian genome are expressed by the nervous system (Sutcliffe et al., 1991). To understand brain-related diseases, it is necessary to map and study the expression patterns of these genes in the brain. Challenges remain in the collection, management, and analyses of neuroanatomic data. It is also important to compare data between different mouse strains from various aspects including stress reactions and drug responses (Moskowitz et al., 1985; Lucki et al., 2001).

 

To achieve these goals, neuroinformatics supports are needed for data management and gene expression analysis about the brain. Such data include those from the laboratory experiments, as well as the published reports from the literature including peer-reviewed journals and textbooks. Knowledge bases and encyclopedic collection of key concepts and facts would be very helpful (Bloom et al., 2006).

 

To facilitate systems biology studies of the brain, neuroscience data at various levels should be included in such knowledge bases or databases. At the molecular level, data about these fields would be needed: neurotransmitters; relevant enzymes, receptors, and ion channels; drug binding sites; structural and functional biomarkers (Bloom et al., 2006). At the cellular level, data about these fields would be needed: neurons, glial cells, and brain areas in nuclei or laminar brain macro-regions; structural data of shapes, sizes; functional data of classes, developmental stages, and aging conditions (Bloom et al., 2006).

 

Three-dimensional brain maps and atlases would also be useful. Data should be organized for circuitry and connections, including the bidirectional connections between nuclear or laminar neuronal areas, synaptic connections, the pathways, and detailed descriptions of structures (e.g., densities, numbers) and functions (e.g., excitatory and inhibitory) (Bloom et al., 2006). Data about the functional systems such as the endocrine and emotional systems, as well as the physiological and behavioral data about the cells and circuits should also be included. In addition, it is necessary to study the associations between nuclei or cortical areas and behaviors. Images should be included to analyze the structural and functional aspects of the mental activities in humans.

 

Neuroinformatics and the Wiki Technology

 

Databases play an important role in neuroinformatics. New Web 2.0 technologies such as the wiki technology can be very helpful for building universal coordinate databases (Nielsen, 2009), knowledge bases, and encyclopedias. The Wiki technology allows the editing of the database at different locations.

 

Many developments have been made with such efforts. For example, the MediaWiki-based Brede Wiki (http://neuro.imm.dtu.dk/wiki/) provides links to various databases including MaND (http://neuro.imm.dtu.dk/wiki/MaND), the neuroimaging database on major depressive disorder. It also has links to BiND (http://neuro.imm.dtu.dk/wiki/BiND), the neuroimaging database on bipolar disorder, and the neuroimaging database Brede Database (http://neuro.imm.dtu.dk/services/brededatabase/).

 

The common wiki technology provides simple text searches. To support more complicated and semantic studies, semantic wikis in neuroinformatics have been built, such as NeuroLex (http://neurolex.org/), a dynamic lexicon of more than 20,000 neuroscience terms. The site can be searched and also browsed by hierarchies such as behavioral activity and brain regions. More work would still be needed.

 

References:

 

Bloom FE, Morrison JH, Young WG. Neuroinformatics: a new tool for studying the brain. J Affect Disord. 2006 May;92(1):133-8.

 

Lucki I, Dalvi A, Mayorga AJ. Sensitivity to the effects of pharmacologically

selective antidepressants in different strains of mice. Psychopharmacology

(Berl). 2001 May;155(3):315-22.

 

Moskowitz AS, Terman GW, Liebeskind JC. Stress-induced analgesia in the mouse: strain comparisons. Pain. 1985 Sep;23(1):67-72.

 

Nielsen FA. Lost in localization: a solution with neuroinformatics 2.0? Neuroimage. 2009 Oct 15;48(1):11-3. doi: 10.1016/j.neuroimage.2009.05.073.

 

Sutcliffe JG, Travis GH, Danielson PE, Wong KK, Ottiger HP, Burton FH, Hasel KW, Bloom FE, Forss-Petter S. Molecular approaches to genes of the CNS. Epilepsy Res Suppl. 1991;4:213-23.

 

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