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RSEISP
2007
Springer

Checking Brain Expertise Using Rough Set Theory

12 years 22 days ago
Checking Brain Expertise Using Rough Set Theory
Most information about the external world comes from our visual brain. However, it is not clear how this information is processed. We will analyze brain responses using machine learning methods based on rough set theory. We will test the expertise of the visual area V4, which is responsible for shape classifications. Characteristic of each stimulus are treated as a set of learning attributes. We assume that bottom-up information is related to hypotheses, while top-down information is related to predictions. Therefore, neuronal responses are divided into three categories. Category 0 occurs if cell response is below 20 spikes/s (sp/s), indicating that the hypothesis is not valid. Category 1 occurs if cell activity is higher than 20 spikes, implying the hypothesis is valid. Category 2 occurs if cell response is above 40 sp/s; in this case we conclude that the hypothesis and prediction are valid. By using experimental data we make a decision table for each cell, and generate equivalence c...
Andrzej W. Przybyszewski
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where RSEISP
Authors Andrzej W. Przybyszewski
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