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Learning How To Build A Neural Network Model Of The Tactile Periphery, Vicky Chang

Undergraduate Student Research Internships Conference

First order neurons in the hairless skin of human hands have spatially complex receptive fields that allow for the detection of spatial details. These spatially complex receptive fields arise from the branching of mechanoreceptors, which converge and connect to first order neurons. This arrangement allows us to process our sensory environment through detecting the edge orientation of a touched object for instance, and do things like read braille.

These spatially complex receptive fields can studied by using a feedforward neural network to model the tactile periphery. By understanding the processing at the level of the tactile periphery, we can better …