Diffusional Landscapes for the Study of Neural Differentiation

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During early development of the central nervous system, the global landscape and concentration of chemical species within the spinal cord serve to direct neuron differentiation and development. The chemical constituency and concentrations of myriad chemical stimulants within the spinal cord signals both the type of neural cells that will develop as well as provide a "trail of breadcrumbs" to direct the precise synaptic connections to other neurons. This research presents a microsystem that generates specific concentration profiles of multiply relevant chemical species to study the development and differentiation of neurons. Using micro and nanofabrication, a microsystem will be designed, fabricated, characterized, and used to generate chemical profiles of known chemicals that affect spinal cord development. An anthology of four mouse spinal cord chemical mediators will be studied: sonic hedgehog (Shh), bone morphogenic protein (BMP), retinoic acid (RA), and noggin, and the spatial and temporal histological distributions of resulting neural cells will be mapped to the imposed chemical mediator concentrations. The advantage of this approach is that cells can be studied in biologically relevant environments without the introduction of the myriad unknown and uncontrolled parameters found in vivo. This project will support the education and laboratory research training of both graduate and undergraduate students at the University of Maine in a collaborative, multi-disciplinary research project involving biological, micro/nano fabrication, and engineering methods in instrumentation and techniques. The project will also be highlighted in UMaine's "Consider Engineering" summer program for high school students and in several undergraduate and graduate level courses to introduce science & engineering initiates to interdisciplinary research. The microsystem will be extended within these programs/courses to encompass applications involving: cognition models, artificial intelligence, biocomputing, and neural networks.