Seeking to shed light on inconsistent brain activation patterns observed in previous studies of smell, a team of researchers in Lyon, France, used data mining techniques to analyze the pleasant or unpleasant odor sensations and corresponding brain scans of a group of 42 participants. They found characteristic patterns in the piriform cortex and amygdala. The group's research was published August 1 in Intelligent Computing .
The exceptional model mining method of data analysis, which looks for "exceptions" in data patterns, showed not only which specific brain areas responded to pleasant and unpleasant smells, it also allowed the analysis of differences in brain response between individuals and between subgroups split according to age and sex. In future studies, the same approach could be used for analysis of brains in healthy and pathological states to understand and treat disease. Everyone is different, thus there are individual differences in brain responses to pleasant and unpleasant smells.
However, such differences can be erased or overlooked when data are considered in the aggregate, thus the researchers used exceptional model mining "to identify partitions of data where a model fitted to the target variables is significantly different from this same model applied to the entire dataset." To collect the dataset, functional magnetic resonance imaging was conducted on 42 experimental participants in three different age groups while they reacted to six different smells. A d.
