Abstract
The connectomes of nervous systems or parts there of are becoming important subjects of study as the amount of connectivity data increases. Because most tract-tracing studies are performed on the rat, we conducted a comprehensive analysis of the amygdala connectome of this species resulting in a meta-study. The data were imported into the neuroVIISAS system, where regions of the connectome are organized in a controlled ontology and network analysis can be performed. A weighted digraph represents the bilateral intrinsic (connections of regions of the amygdala) and extrinsic (connections of regions of the amygdala to non-amygdaloid regions) connectome of the amygdala. Its structure as well as its local and global network parameters depend on the arrangement of neuronal entities in the ontology. The intrinsic amygdala connectome is a small-world and scale-free network. The anterior cortical nucleus (72 in- and out-going edges), the posterior nucleus (45), and the anterior basomedial nucleus (44) are the nuclear regions that posses most in- and outdegrees. The posterior nucleus turns out to be the most important nucleus of the intrinsic amygdala network since its Shapley rate is minimal. Within the intrinsic amygdala, regions were determined that are essential for network integrity. These regions are important for behavioral (processing of emotions and motivation) and functional (memory) performances of the amygdala as reported in other studies.
Highlights
A connectome is a level-dependent representation of connections between biological entities
In addition to the definitions, descriptions and interpretations of parameters and statistical procedures that are used in the results subsection, the supplement contains a complete list of definitions
The heterogeneity of 0.68 suggests that each node has a sum of inputs and outputs in the same range (Estrada, 2010)
Summary
A connectome is a level-dependent representation of connections between biological entities. Amygdala connectome and its extrinsic efferent targets as well as extrinsic afferent sources at the meso level of nuclei and their subdivisions. One rationale of this study is to uncover the connectivity of the intrinsic amygdala network of the rat based on high-resolution tract-tracing data. The connectome of the intrinsic amygdala network has not been investigated in terms of network measures, graph theoretical quantities, and multivariate statistics. After making these connectome data accessible through a weighted connectivity matrix, specific questions concerning motifs, reciprocity, and most strongly connected regions upon others can be addressed
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