Understanding Model Experimental and Population Level Variance in Cognitive and Neuron Simulations
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This report summarizes accomplishments of a three-year project focused on developing technical capabilities for measuring and modeling neuronal processes at the nanoscale. It was successfully demonstrated that nanoprobes could be engineered that were biocompatible, and could be biofunctionalized, that responded within the range of voltages typically associated with a neuronal action potential. Furthermore, the Xyce parallel circuit simulator was employed and models incorporated for simulating the ion channel and cable properties of neuronal membranes. The ultimate objective of the project had been to employ nanoprobes in vivo, with the nematode C elegans, and derive a simulation based on the resulting data. Techniques were developed allowing the nanoprobes to be injected into the nematode and the neuronal response recorded. To the authors's knowledge, this is the first occasion in which nanoparticles have been successfully employed as probes for recording neuronal response in an in vivo animal experimental protocol.
The purpose of this work was to help develop a research roadmap and small proof ofconcept for addressing key problems and gaps from the perspective of using text analysis methods as a primary tool for detecting when a group is undergoing a phase change. Self- rganizing map (SOM) techniques were used to analyze text data obtained from the tworld-wide web. Statistical studies indicate that it may be possible to predict phase changes, as well as detect whether or not an example of writing can be attributed to a group of interest.
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