Influence on neuron function

Research has supported a relationship between the morphological and functional properties of neurons. For instance, the accordance between the morphology and the functional classes of cat retinal ganglion cells has been studied to show the relationship between neuron shape and function. Orientation sensitivity and dendritic branching patterns are a few other common characteristics of neurons that researchers have noted as having an effect on neuron function.^[5] Ian A. Meinertzhagen et al. have recently established a connection between the genetic factors that underlie a specific neuronal structure and how these two factors then pertain to the neuron's function by examining the optic nerves in Drosophila melanogaster. They assert the structure of the neuron is able to determine its function by dictating synapse formation.^[6]

The geometry of neurons often depends on the cell type and the history of received stimuli that is processed through the synapses. The shape of a neuron often directs the neuron's function by establishing its synaptic partnerships. However, there is also a growing evidence for volume transmission, a process that involves electrochemical interactions from the whole cell membrane.^[5]

The axonal tree morphology is instrumental in activity modulation and information coding.^[7]

Development

The development of the morphological features of neurons is governed by both intrinsic and extrinsic factors. The neuromorphology of nervous tissue is dependent upon genes and other factors, such as electric fields, ionic waves, and gravity. Developing cells additionally impose geometrical and physical constraints upon each other. These interactions affect the neural shape and synaptogenesis.^[8] Morphological measures and imaging applications are important for further understanding the developmental process.

General morphology

Since there is a broad range of functions performed by different types of neurons in diverse parts of the nervous system, there is a wide variety in the size, shape, and electrochemical properties of neurons. Neurons can be found in different shapes and sizes and can be classified based upon their morphology. The Italian scientist Camillo Golgi grouped neurons into type I and type II cells. Golgi type I neurons have long axons that can move signals over long distances, such as in Purkinje cells, whereas Golgi type II neurons generally have shorter axons, such as granule cells, or are anaxonic.^[9]

Neurons can be morphologically characterized as unipolar, bipolar, or multipolar. Unipolar and pseudounipolar cells have only one process extending from the cell body. Bipolar cells have a two processes extending from the cell body and multipolar cells have three or more processes extending towards and away from the cell body.

Theoretical neuromorphology

Theoretical neuromorphology is a branch of neuromorphology focused on the mathematical description of the shape, structure and connectivity of the nervous system.

Gravitational neuromorphology

Gravitational neuromorphology studies the effects of altered gravity on the architecture of the central, peripheral, and autonomic nervous systems. This subfield aims to expand the current understanding of the adaptive capabilities of nervous systems, and specifically examines how environmental effects can alter nervous system structure and function. In this case environmental manipulations generally include exposing neurons to either hypergravity or microgravity. It is a subset of gravitational biology.^[10]

Design-based stereology

Design-based stereology is one of the most prominent methods for mathematically extrapolating a 3-D form from a given 2-D form. It is currently the leading technique in biomedical research for analyzing 3-D structures.^[13] Design-based stereology is a newer stereology technique that examines morphology that has been predefined and designed. This technique contrasts with the older method, model-based stereology, which utilized previously determined models as a guide. The more current design-based stereology allows researchers to probe the morphology of neurons without having to make assumptions about their size, shape, orientation or distribution. Design-based stereology also gives researchers more freedom and flexibility as model-based stereology is only effective if the models are truly representative of the object being studied, while design-based stereology is not constrained in this way.^[14]

Confocal microscopy

Confocal microscopy is the microscopic procedure of choice for examining neuron structures as it produces sharp images with improved resolution and decreased signal-to-noise ratio. The specific way this microscopy works allows one to look at one confocal plane at a time, which is optimal when viewing neuronal structures. Other more conventional forms of microscopy simply do not allow one to visualize all neuronal structures, especially those that are subcellular. Recently, some researchers have actually been combining design-based stereology and confocal microscopy to further their investigations into the specific neuronal cellular structures.

Cortical mapping

Cortical mapping is defined as the process of characterizing specific regions in the brain based on either anatomical or functional features. Current brain atlases are not definitive or homogenous enough to portray specific structural details. Recent advances in functional brain imaging and statistical analysis may however prove to be sufficient in the future. A recent development in this field called the Gray Level Index (GLI) method allows for more objective identification of cortical regions via algorithms. The GLI is a standardized method that allows researchers to determine neuron density. It is specifically defined as the ratio of area covered by Nissl-stained elements to area covered by unstained elements.^[15] More sophisticated cortical mapping techniques are still in the process of being developed and this field will most likely see an exponential growth in mapping methods in the near future.

Computational neuromorphology

Computational neuromorophology examines neurons and their substructures by cutting them into slices and studying these different subsections. It also describes the neuromorphological space as a 3-D space. This allows researchers to understand the size of specific neuronal components. Additionally, the 3-D imaging helps researchers comprehend how the neuron transmits information within itself.^[17]

Virtual microscopy

Virtual microscopy would allow researchers to obtain images with a decreased amount of imaging sessions, thus preserving the integrity of the tissue and decrease the possibility the fluorescent dyes fading during imaging. This method would additionally give researchers abilities to visualize currently unobtainable data, such as rare cell types and the spatial allocation of cells in a specific brain region.^[13] Virtual microscopy would essentially allow for the digitization of all images obtained, therefore preventing deterioration of the data. This digitization could also potentially permit researchers to create a database to share and store their data.