Quantitative methods for analyzing neuronal numbers have fueled advances in our knowledge of the brain but methods to study spatial organization have lagged. The microcolumn is a distinct vertical spatial organization that characterizes cerebral cortex. To quantitatively assess microcolumnar structure, we will adapt methods derived from statistical physics to analyze local spatial relationships among neurons as they are organized into microcolumns. Tissue for these studies will be obtained at no cost from young, middle aged and elderly rhesus monkeys that, as part of an NIA funded Program Project, have been behaviorally tested on tasks sensitive to age-related cognitive decline. Preliminary data confirms an age-related reduction in the strength of microcolumns in the prefrontal cortex. We will test the following hypotheses: (1) spatial organization of neurons into microcolumns is disrupted in normal aging despite of the lack of neuronal death; and (2) disruption of microcolumns will be associated with age-related cognitive decline. Hence, in Aim 1 we will develop a fully automated density map method to quantify the average """"""""microcolumnar"""""""" structure across diverse interconnected cortical regions which are part of the circuitry of the pertinent cognitive functions. To do this efficiently we will apply our method to standard whole brain coronal series of 30 micron thick frozen sections stained with thionin. Because such sections shrink dramatically in the z plane, they only provide spatial neuronal locations in two dimensions (2D).
In Aim 2 we will extend our analysis to 3D to validate the 2D density map method by acquiring x,y,z neuronal locations from thick celloidin sections that don't differentially shrink in the z dimension, as well as immunocytochemically stained sections analyzed with the confocal microscope. We will then extend our method to generate 3D density maps and determine if """"""""correction"""""""" factors can be applied to the 2D density maps of Aim 1.
In Aim 3 we will identify regions showing age-related changes in microcolumnar organization and then determine if these disruptions are associated with age-related cognitive decline. The importance of these investigations derives from two factors. First, currently available methods can only partially test the hypotheses proposed, so the methods we develop and validate will provide efficient and reliable new ways to quantify local spatial relationships. Second, the application of these methods to neuroanatomy of normal aging may allow us to detect subtle, sublethal, changes in cortical structure that reflect progressive neuronal dysfunction when neuronal loss is not a factor.
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