Open Access. Powered by Scholars. Published by Universities.®
- Discipline
- Institution
- Keyword
- Publication Type
Articles 1 - 3 of 3
Full-Text Articles in Computational Neuroscience
Low Cost Neurochairs, Frankie Pike
Low Cost Neurochairs, Frankie Pike
Master's Theses
Electroencephalography (EEG) was formerly confined to clinical and research settings with the necessary hardware costing thousands of dollars. In the last five years a number of companies have produced simple electroencephalograms, priced below $300 and available direct to consumers. These have stirred the imaginations of enthusiasts and brought the prospects of "thought-controlled" devices ever closer to reality. While these new devices were largely targeted at video games and toys, active research on enabling people suffering from debilitating diseases to control wheelchairs was being pursued. A number of neurochairs have come to fruition offering a truly hands-free mobility solution, but whether …
Neural Synchrony In The Zebra Finch Brain, Sydney Pia Goings
Neural Synchrony In The Zebra Finch Brain, Sydney Pia Goings
Scripps Senior Theses
I am interested in discovering the role of field potential oscillations in producing synchrony within the song system of the male zebra finch brain. An important function attributed to neural synchrony is sensorimotor integration. In the production of birdsong, sensorimotor integration is crucial, as auditory feedback is necessary for the maintenance of the song. A cortical-thalamic-cortical feedback loop is thought to play a role in the integration of auditory and motor information for the purpose of producing song. Synchronous activity has been observed between at least two nuclei in this feedback loop, MMAN and HVC. Since low frequency field potential …
Derivation Of A Novel Efficient Supervised Learning Algorithm From Cortical-Subcortical Loops, Ashok Chandrashekar, Richard Granger
Derivation Of A Novel Efficient Supervised Learning Algorithm From Cortical-Subcortical Loops, Ashok Chandrashekar, Richard Granger
Dartmouth Scholarship
Although brain circuits presumably carry out powerful perceptual algorithms, few instances of derived biological methods have been found to compete favorably against algorithms that have been engineered for specific applications. We forward a novel analysis of a subset of functions of cortical-subcortical loops, which constitute more than 80% of the human brain, thus likely underlying a broad range of cognitive functions. We describe a family of operations performed by the derived method, including a non-standard method for supervised classification, which may underlie some forms of cortically dependent associative learning. The novel supervised classifier is compared against widely used algorithms for …