Title

In Vitro Modeling Of Nervous System: Engineering Of The Reflex Arc

Keywords

Cantilever; In vitro; Microelectrode array; Neural engineering; Neuromuscular junction; Reflex arc; Surface patterning

Abstract

Neural models are invaluable for understanding the physiology and pathology of the nervous system as well as for developing therapeutic strategies targeting relevant injury and diseases. New developments in the field of stem cells enable great feasibility and potential for generating in vitro models of the nervous system, especially human-based models to study diseases and for drug screening. The reflex arc has been a popular model system for studying neural regulation and circuit modulation. Numerous in vitro models of this system have been generated, among which modeling of the efferent portion of the reflex arc, the connection between motoneurons and skeletal muscles, or the neuromuscular junction (NMJ), has been the central focus. To a lesser extent, the afferent portion, or intrafusal fiber to sensory neuron segment, has also been studied as well as the sensory neuron to motoneuron connections. Furthermore, the integration of interdisciplinary technologies such as surface patterning, microelectrode arrays, and cantilever systems is driving biological NMJ systems more toward in vitro platforms for high content and high throughput capabilities which are suitable for drug screening. To better mimic the in vivo condition, inclusions of other components are also in progress, such as the blood-brain barrier, Bio-MEMs technologies and multi-organ-on-a-chip systems. The concurrent progress in integration of biology and engineering will accelerate the development of these in vitro nervous system models which have an increasing suitability for studying physiology and pathology of the human nervous system as well as for use in drug discovery research.

Publication Date

1-1-2016

Publication Title

Neural Engineering: From Advanced Biomaterials to 3D Fabrication Techniques

Number of Pages

261-298

Document Type

Article; Book Chapter

Personal Identifier

scopus

DOI Link

https://doi.org/10.1007/978-3-319-31433-4_9

Socpus ID

85008881377 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85008881377

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