Neuromorphology
Neuromorphology (from Greek νεῦρον, neuron, "nerve"; μορφή, morphé, "form"; -λογία, -logia, “study of”[1][2]) is the study of nervous system form, shape, and structure. The study involves looking at a particular part of the nervous system from a molecular and cellular level and connecting it to a physiological and anatomical point of view. The field also explores the communications and interactions within and between each specialized section of the nervous system. Morphology is distinct from morphogenesis. Morphology is the study of the shape and structure of biological organisms, while morphogenesis is the study of the biological development of the shape and structure of organisms. Therefore, neuromorphology focuses on the specifics of the structure of the nervous system and not the process by which the structure was developed. Neuromorphology and morphogenesis, while two different entities, are nonetheless closely linked.
History
Progress in defining the morphology of nerve cells has been slow in its development. It took nearly a century after the acceptance of the
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
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
Subfields
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
Neurons can be morphologically characterized as
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
Research methods and techniques
A variety of techniques have been used to study neuromorphology, including confocal microscopy, design-based stereology, neuron tracing[11] and neuron reconstruction. Current innovations and future research include virtual microscopy, automated stereology, cortical mapping, map guided automated neuron tracing, microwave techniques, and network analysis. Of the currently used techniques for studying neuromorphology, design-based stereology and confocal microscopy are the two most preferred methods. A complete database of neuronal morphology called the NeuroMorpho Database also exists.[12]
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
Clinical applications
Neuromorphology has been used as a new method of exploring the underlying cause of many
Current and future research
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
See also
References
- ^ Morphology
- ^ Neuron
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- ^ Oztas, Emin (2003). "Neuronal tracing". Neuroanatomy. 2: 2–5.
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- ^ "What is design-based stereology". Retrieved 7 November 2011.
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- ^ Trinidad, Pablo. "Computational Neuromorphology". University of Texas at Dallas. Archived from the original on 2 January 2009. Retrieved 2 November 2011.