Use of 3D Neuronal Reconstructions for Carrying out Morphological Analyses
Mentor 1
James R. Moyer, Jr.
Location
Union Wisconsin Room
Start Date
5-4-2019 1:30 PM
End Date
5-4-2019 3:30 PM
Description
Numerous studies have attempted to relate variations in cellular structure (i.e., morphology) with variations in electrical firing properties (i.e., function). These cellular properties, such as dendritic complexity or electrical firing characteristics are plastic and can change not only across the lifespan, but also as a function of experience (e.g., learning or other adaptive/maladaptive behaviors). Our laboratory studies how the nervous system changes as a function of age as well as learning/memory. We use a several approaches, including whole-cell patch-clamp recordings (to study electrical properties) coupled with biocytin injections (to study morphology) in order to better understand structure-function relationships of neurons both within and between brain regions. Within the lab, my role has been to take the brain slice from which a recording was obtained and process it to (a) visualize the recorded neuron and then (b) create a digital, 3D reconstruction of the neuron. The purpose of this poster is to describe the procedures used to ultimately obtain a 3D reconstruction and illustrate some of the analyses used to study neuronal morphology. Briefly, the slice is fixed, then washed in various solutions, one of which contains streptavidin, which binds the biocytin molecule. We use a fluorescently-labeled streptavidin, which means that the molecule will fluoresce (or glow) when exposed to an appropriate wavelength of light. Confocal laser scanning microscopy (CSLM) uses laser light of an appropriate wavelength to visualize the fluorescently-labeled neuron. CSLM allows us to obtain a series of high-resolution image stacks that can then be combined and imported to our Neurolucida 360 software, which I use to create a 3D image. These images can be analyzed in a variety of ways to quantify the complex neuronal structure. Cells from specific regions and specific cell types can be averaged to help us understand how neurons change with age and experience.
Use of 3D Neuronal Reconstructions for Carrying out Morphological Analyses
Union Wisconsin Room
Numerous studies have attempted to relate variations in cellular structure (i.e., morphology) with variations in electrical firing properties (i.e., function). These cellular properties, such as dendritic complexity or electrical firing characteristics are plastic and can change not only across the lifespan, but also as a function of experience (e.g., learning or other adaptive/maladaptive behaviors). Our laboratory studies how the nervous system changes as a function of age as well as learning/memory. We use a several approaches, including whole-cell patch-clamp recordings (to study electrical properties) coupled with biocytin injections (to study morphology) in order to better understand structure-function relationships of neurons both within and between brain regions. Within the lab, my role has been to take the brain slice from which a recording was obtained and process it to (a) visualize the recorded neuron and then (b) create a digital, 3D reconstruction of the neuron. The purpose of this poster is to describe the procedures used to ultimately obtain a 3D reconstruction and illustrate some of the analyses used to study neuronal morphology. Briefly, the slice is fixed, then washed in various solutions, one of which contains streptavidin, which binds the biocytin molecule. We use a fluorescently-labeled streptavidin, which means that the molecule will fluoresce (or glow) when exposed to an appropriate wavelength of light. Confocal laser scanning microscopy (CSLM) uses laser light of an appropriate wavelength to visualize the fluorescently-labeled neuron. CSLM allows us to obtain a series of high-resolution image stacks that can then be combined and imported to our Neurolucida 360 software, which I use to create a 3D image. These images can be analyzed in a variety of ways to quantify the complex neuronal structure. Cells from specific regions and specific cell types can be averaged to help us understand how neurons change with age and experience.
