The principal goal of this application is to accelerate the development of brain imaging methods that can link complex gene expression dynamics in single cells to the function of populations of neurons known to be responsible for cognition. With new technology developed by the applicants (termed cellular compartment analysis of temporal activity by FISH, or catFISH), it is possible to detect and compare the neural populations activated by two distinct behavioral experiences within the same brain. The temporal resolution properties of catFISH derive from the temporally precise transcriptional regulation of different immediate-early genes (lEGs) following periods of neuronal activity. Using fluorescence in situ hybridization (FISH) and confocal microscopy to reveal the subcellular location of specific lEG RNAs, the activity history of individual neurons throughout the brain can be determined at two or more time points. catFISH has the promise of providing a connectivity map that bridges what we know about the activity characteristics of cell ensembles recorded during behavior, and what we know about multiple genes that are activated by these behaviors. This proposal exploits the potential of the temporal and cellular precision of the catFISH method, combined with novel transgenic mouse models, to offer unique insights into the cellular basis of information processing for large numbers of cells across widely-distributed brain structures. We propose three aims to achieve these goals.
Aim 1 combines the catFISH method in cell-specific GFP-expressing mice, along with circuit tracing techniques, to provide functional maps of cells in circuits activated by specific behaviors.
Aim 2 uses Arc promoter BAC - GFP transgenic mice in combination with catFISH to increase the number of behaviorally-activated neural networks that can be compared within a single mouse brain.
Aim 3 takes two approaches to further our ability to achieve large-scale neural circuit visualization and quantification: development of state-of-the-art, computer-assisted, 3-dimensional cell segmentation and classification software for confocal images; and development of hyperspectral slide scanning technologies for application to large regions of brain tissue. The co-P.I.s of this grant represent the laboratories from which the molecular imaging (JG, CB, PW, BM), genetic methodologies (PW), parallel electrophysiological recording methods (CB, BM), computer-assisted confocal quantitative image analysis (BR) and hyperspectral analysis (JT) were developed. This interdisciplinary team has a history of productive collaboration, and our goals are driven by the fundamental question posed in this Program Announcement: how to visualize large-scale, behavior-driven, genetically-manipulated, functional connectivity maps of the mammalian central nervous system.
