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Full-Text Articles in Computational Neuroscience
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 …
The Possible Connection Of Gamma Oscillation And 3-D Object Representation, Thien N. Vu
The Possible Connection Of Gamma Oscillation And 3-D Object Representation, Thien N. Vu
Summer Research
We process and encode for different features of a particular object (shape, color, texture, etc.) in distinct areas of the brain. How we bind these attributes together into a unified perception of an object is unknown. Past research suggests that synchronized activity between brain areas, particularly induced gamma activity (~ 40 Hz), may account for this binding process and the basis of our conscious perceptual experience, specifically through object representation. In this study, participants were asked to look at a series of 2-D pictures of cars from distinctive rotations (00, 900, 1800) and were …