ReviewNeuroinformatics analysis of molecular expression patterns and neuron populations in gray matter regions: The rat BST as a rich exemplar
Introduction
The bed nuclei of the stria terminalis (BST) is a part of the cerebral nuclei (basal ganglia; Bota and Swanson, 2010; for a standard nomenclature see Swanson and Bota, 2010) that was first named as such in the rat forebrain by Johnston (1923) and Gurdjian (1925). The first parcellation of the BST as a stand-alone gray matter region was provided by de Groot (1959). Since then, the BST has been frequently subdivided in different subparts, divisions, or nuclei by different authors (for a review on nomenclatures of the rat BST, see Bota and Swanson, 2010). However, there are currently only two main topographically distinct classification schemas: medial–lateral and anterior–posterior. The classical medial–lateral parcellation schema is based on cytoarchitecture, chemoarchitecture, and input connections from the amygdalar region (de Olmos and Heimer, 1999, de Olmos et al., 1985, de Olmos et al., 2010, Geeraedts et al., 1990, Paxinos and Watson, 1986, Paxinos and Watson, 1998). This schema usually includes BST as part of the “extended amygdala” (de Olmos et al., 2010) and the number of component nuclei is variable. The modern anterior–posterior classification schema is based on a) ontogeny of neuron populations in gray matter regions (Bayer, 1987), as a criterion for demarcation from the preoptic region of the hypothalamus and for distinguishing internal divisions; b) cytoarchitecture and gene expression patterns (Ju and Swanson, 1989, Ju et al., 1989); and most importantly c) complex input connection patterns from the amygdalar region (Dong et al., 2001) and output connection patterns from component nuclei to many parts of the brain (Dong and Swanson, 2003, Dong and Swanson, 2004, Dong and Swanson, 2006, Swanson, 2004). Even though these two dominant parcellation schemes may appear as topographically orthogonal, they also include common nuclei, such as the juxtacapsular nucleus (BSTju; Moga et al., 1989). However the most common results of qualitative (topological) comparison performed by us (Bota and Swanson, 2010) lead to the relation of “partial correspondence” (Swanson and Bota, 2010) between the BST nuclei of these two parcellations.
The set of molecules known to be expressed in the rat BST nuclei increased with each relevant study there or in neighboring regions (de Olmos et al., 2010, Gray and Magnuson, 1987, Hammack et al., 2007, Ju et al., 1989, Moga et al., 1989, Poulin et al., 2006, Puente et al., 2010, Rainnie, 1999, Swanson et al., 1983, Zaborszky et al., 2005). Moreover, some molecular expression patterns are sex-specific (Polston and Simerly, 2003). However, there are very few reviews or surveys of the molecular architecture of rat BST nuclei (de Olmos et al., 2010)—and the same is true for neuron populations, classes, and types in the BST. Although the literature concerning BST neuron classification is more than 30 years old, few studies have used multiple classification schemas, the polythetic approach (see Bota and Swanson, 2010 for a review). Most studies reviewed here classify BST neurons according to one criterion, usually cytoarchitecture (unithetic approach), or several criteria at most. Moreover, the lack of agreement across neuroanatomical nomenclatures, accompanied by equivocal relations between gray matter regions, makes the results of experimental connection analyses difficult to interpret, compare, and integrate.
Proposed functions of the rat BST range from modulation of basic autonomic responses (Moga et al., 1989, Swanson and Sharpe, 1973), large sets of motor behaviors (Dong and Swanson, 2003, Dong and Swanson, 2006), and circadian rhythmicity (Amir et al., 2004), to stress- and anxiety-related behaviors (Choi et al., 2009, Levita et al., 2004, Walker et al., 2003), and behaviors related to drugs of abuse (Aston-Jones and Harris, 2004). This large set of functions can be explained only by complex patterns of connections, and a large set of expressed molecules. This in turn implies multiple neuron populations in the rat BST that can be distinguished using the multiple criteria (polythetic) approach for their classification (Bota and Swanson, 2010). Hence, a survey of molecules differentially expressed in the rat BST nuclei, and of identified neuron types, is not only valuable for a comprehensive description of this cerebral nuclei region, but is also necessary for establishing the structure–function relationships of each of the BST nuclei.
In this paper we survey comprehensively the published literature on molecular expression patterns and neuron populations, classes, and types identified in the rat BST. It can be viewed as a companion to an earlier paper (Bota and Swanson, 2010) where we proposed a methodology for collating and curating neuroanatomical nomenclatures in online neuroinformatic systems, and reviewed the literature on rat BST parcellation schemes. Because large scale efforts are greatly facilitated by neuroinformatics systems, we collated the molecular expression pattern and neuron population information in the Brain Architecture Knowledge Management System (BAMS). This allowed us to manage the inserted data in tabular formats and to analyze it statistically. Moreover, all the collated data and metadata is publicly available to the neuroscience community.
First, we briefly describe BAMS and its new interfaces and inference engine, created to integrate the results of different experiments and data types. This is accompanied by a description of the methodology used to map and collate data from the published literature. Second, we present the results of our survey of molecular expression data collated in BAMS, and the results of relevant statistical analyses. We then review the published literature on neuron populations identified in the BST, and on relations between them. Finally, we discuss the results of our survey and analysis, and propose several possible future experiments. This series of papers is meant to provide a general approach to collating information about the organization of neural systems from the legacy neuroscience literature and extracting knowledge from this information.
Section snippets
Results
The BAMS user interface includes different neuron population and molecule search options, described in detail in Bota and Swanson (2006), and Bota and Swanson (2010). The neuron populations and molecules associated with a gray matter region in BAMS can be directly accessed from the Menu of the system, along with information associated with the results of online searches about gray matter regions. Typical results of a gray matter region search that returns associated neuron populations and
Discussion
The rat BST is a very complex part of the cerebral nuclei (basal ganglia), in terms both of molecular expression patterns and of neuron populations, classes, and types. It is therefore not surprising that functions assigned to the various BST nuclei also cover a broad spectrum, and the associated literature is far too extensive to review here. In addition, these nuclei have not yet been analyzed and described in as much detail as many other regions of the mammalian CNS, and the integration of
BAMS presentation
BAMS (http://brancusi.usc.edu/bkms) has been under development since 2002 (Bota et al., 2003) and is an online neuroinformatics workbench for handling neuroanatomical information as collated from the published literature. The structure of BAMS is modular (Bota et al., 2003, Bota et al., 2005) and its five inter-related modules handle information related to four levels of nervous system organization. This structure allows insertion of data and metadata associated with the nervous system of any
Acknowledgments
M.B. and L.W.S. are supported by supported by the National Institutes of Health Grant NS050792. O.S. is supported by the James S. McDonnell Foundation.
We thank Dr. Clifford Saper for his valuable suggestions and feedback.
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