Extraction of structural and functional information from large scale reconstruction of basal forebrain-cortical networks
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1
Rutgers University, United States
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2
California Institute of Technology, United States
The term basal forebrain (BF) refers to a heterogeneous collection of structures located close to the medial and ventral surfaces of the cerebral hemispheres. BF areas, including the medial septum, ventral pallidum, diagonal band nuclei and the substantia innominata contain cell types that differ in transmitter content and projection pattern. Among the different neuronal populations, the cholinergic corticopetal neurons have received particular emphasis due to their prominent demise in Alzheimers disease. This highly complex brain region has been implicated in cortical activation, attention, and memory. Part of the difficulty in understanding the role of the BF in these functions, as well as the processing characteristics of this disease state lies in the anatomical complexity of the region. The neuronal architecture of the BF cholinergic system (BFC) is considered to be a diffuse population of neurons. However, recently we have shown that the 3D distributions of cholinergic and non-cholinergic neurons are inhomogeneous, suggesting a clustered organization. Neuronal clusters in many brain systems have been suggested as sites of integrative operation since neurons in a cluster most likely would share input and interact via local collaterals.
Driven by our needs for analysis of large-scale mapped neurons, we developed a new software environment (www.ratbrain.org) in which point loci of mapped neurons are represented by vectorial datasets. The software tools are developed in Java, with cross platform support. A special XML format (MorphML) is used for data modeling. For quantification and statistical analysis of clusters we implemented an algorithm that determines the number of cell bodies within a spherical volume around each neuron (cell-centered density approach). If the total number of cells contained increases linearly with the diameter of spheres, the cell population is considered to be homogeneously distributed (Null hypothesis). In contrast, any deviation from the linear function is an indicative of clusters (alternative hypothesis). The critical diameters and cell counts at which deviations occur represent the critical density and cluster size. Applying the critical density and cluster size as thresholds, the program is able to select and visualize neurons which are part of a putative cluster. The various BFC cluster parameters (cell density, number of clusters, location) show a remarkably consistency among individuals of rats.
In order to understand the function of clusters, we compared the spatial overlap between individual clusters of cholinergic neurons with retrogradely labeled cell populations in the BF defined by their cortical targets. To combine different datasets, BF mapped cells from 18 Fast Blue or Fluoro Gold deposits in various cortical regions (in 9 rat brains) were warped into a master file using affine transformation. Multiple binomial tests were applied to determine the significance of the spatial overlap of the various retrograde cell populations with specific cholinergic clusters. The high selectivity of overlap suggests specific projection pattern of the spatially segregated clusters. This is consistent with the hypothesis that BF clusters may be part of a forebrain modular architecture that interconnect functionally distinct posterior cortical and prefrontal networks, thus may coordinate interaction between them. USPHS Grant NS023945.
Conference:
Neuroinformatics 2008, Stockholm, Sweden, 7 Sep - 9 Sep, 2008.
Presentation Type:
Poster Presentation
Topic:
Neuroimaging
Citation:
Zaborszky
L,
Csordas
A,
Varsanyi
P and
Nadasdy
Z
(2008). Extraction of structural and functional information from large scale reconstruction of basal forebrain-cortical networks.
Front. Neuroinform.
Conference Abstract:
Neuroinformatics 2008.
doi: 10.3389/conf.neuro.11.2008.01.068
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Received:
28 Jul 2008;
Published Online:
28 Jul 2008.
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Correspondence:
Laszlo Zaborszky, Rutgers University, Newark, United States, laszloz@andromeda.rutgers.edu