Spatial behavior and seizure-induced changes in c-fos mRNA expression in young and old rats.

The subcellular processes of gene induction and expression in the hippocampus are likely to underlie some of the known age-related impairments in spatial learning and memory. It is well established that immediate-early genes are rapidly and transiently induced in response to neuronal activity and this expression is required for stabilization of durable memories. To examine whether age-related memory impairment might be caused, in part, by differences in the level of cellular activation or subcellular processing, c-fos expression in CA1 pyramidal and dentate gyrus granule cells in the dorsal hippocampus of young and old rats was determined using fluorescence in situ hybridization and reverse transcription polymerase chain reaction.

Activation patterns in superficial layers of neocortex change between experiences independent of behavior, environment, or the hippocampus.

Previous work suggests that activation patterns of neurons in superficial layers of the neocortex are more sensitive to spatial context than activation patterns in deep cortical layers. A possible source of this laminar difference is the distribution of contextual information to the superficial cortical layers carried by hippocampal efferents that travel through the entorhinal cortex and subiculum. To evaluate the role that the hippocampus plays in determining context sensitivity in superficial cortical layers, behavior-induced expression of the immediate early gene Arc was examined in hippocampus-lesioned and control rats after exposing them to 2 distinct contexts.

A multi-model approach to simultaneous segmentation and classification of heterogeneous populations of cell nuclei in 3D confocal microscope images.

Automated segmentation and morphometry of fluorescently labeled cell nuclei in batches of 3D confocal stacks is essential for quantitative studies. Model-based segmentation algorithms are attractive due to their robustness. Previous methods incorporated a single nuclear model.

Hierarchical, model-based merging of multiple fragments for improved three-dimensional segmentation of nuclei.

Background: Automated segmentation of fluorescently labeled cell nuclei in three-dimensional confocal images is essential for numerous studies, e.g., spatiotemporal fluorescence in situ hybridization quantification of immediate early gene transcription.

3D-catFISH: a system for automated quantitative three-dimensional compartmental analysis of temporal gene transcription activity imaged by fluorescence in situ hybridization.

Fluorescence in situ hybridization (FISH) of neural activity-regulated, immediate-early gene (IEG) expression provides a method of functional brain imaging with cellular resolution. This enables the identification, in one brain, of which specific principal neurons were active during each of two distinct behavioral epochs. The unprecedented potential of this differential method for large-scale analysis of functional neural circuits is limited, however, by the time-intensive nature of manual image analysis.

A hybrid 3D watershed algorithm incorporating gradient cues and object models for automatic segmentation of nuclei in confocal image stacks.

Background: Automated segmentation of fluorescently-labeled cell nuclei in 3D confocal microscope images is essential to many studies involving morphological and functional analysis. A common source of segmentation error is tight clustering of nuclei. There is a compelling need to minimize these errors for constructing highly automated scoring systems.