Neuroinformatics is a multifaceted field. It is as broad as the field of neuroscience. The various domains of NI may also share some common features such as databases, data mining systems, and data modeling tools. NI projects are often coordinated by user groups or research organizations. Large-scale infrastructure supporting NI development is also a vital aspect of the field.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Brain coordinate systems are used to define a “standard brain” against which to describe the locus of neuroanatomic structures and activation patterns. They are necessary to imaging – data sets are “normalized” to the space defined by a particular coordinate system (a process of stereotaxic transformation) so that voxel-based computations can be carried out. One such system is the Talairach system that derives from the Talairach and Tournoux Atlas, which was based on the brain of a single individual (see Talairach and Tournoux 1988; 1993). Another is the MNI system developed at the Montreal Neurological Institute in collaboration with the International Consortium for Brain Mapping (see Section 2.2). This system was developed from a sample of 152 individuals and is currently the most commonly used template for brain imaging. Some imaging software suites can convert data between the Talairach and MNI systems.
- 2.
Computational modeling is the dominant method of simulating neuronal circuits and as such is briefly covered in this subsection. The outline of main concepts given here will also aid in better understanding a few of the NI examples that the reader will encounter in Section 3. A comprehensive description of neural modeling is well outside the scope of this book. The interested reader is referred to the original sources cited.
- 3.
Some readers may have encountered the term “Cognitive Informatics,” a term coined by Wang (2002). The claim has been made that cognitive informatics is a new, innovative, emerging discipline concerned with (a) mathematical and computational approaches to understanding neural and cognitive systems, especially in terms of how they represent abstract knowledge, and (b) how this understanding can potentially lead to new types of computer architecture (see Wang 2003a,b; 2006; 2007a,b). These two goals, however, have been at the core of cybernetics and neural modeling for more than five decades (see sources cited earlier on neural modeling). On closer inspection, “cognitive informatics” is largely an approach to modeling influenced by a bit of philosophy about knowledge representation. Specifically, it is an approach predicated on a set of descriptive mathematical (algebraic) methods around which an elaborate set of propositions, corollaries, and theorems have been built (see Wang 2003b; 2006; 2007b). This clarification is being made here as a caution to the reader not to confuse “cognitive informatics” with neuroinformatics for neuropsychology. “Cognitive informatics” is an approach to modeling, and the relevance of modeling to NI in neuropsychology is articulated in this subsection.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Jagaroo, V. (2009). Current Neuroinformatics Applications and Infrastructure. In: Neuroinformatics for Neuropsychology. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0060-9_2
Download citation
DOI: https://doi.org/10.1007/978-1-4419-0060-9_2
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-0059-3
Online ISBN: 978-1-4419-0060-9
eBook Packages: Behavioral ScienceBehavioral Science and Psychology (R0)