Not exact matches
The researchers fed the
data from the
scans into a machine - learning computer program, which eventually could identify which concept a volunteer was thinking about based
on his or her
brain activity.
Using two
data sets of functional MRI
brain scans from more than 350 adult and child siblings during resting state, Fair and colleagues applied an innovative technique to characterize functional connectivity and machine learning to successfully identify siblings based
on their connectotype.
Based
on the results of that test, Beaty and colleagues developed a predictive model and tested against
brain scan data collected for earlier studies
on creativity.
As the initial
brain -
scan data flooded in, it made her imagine the mind as a sort of muscle system that relied
on opposing forces.
Apparently in February 2008 Cedars - Sinai radiologists overrode the default settings
on a CT scanner used for the
brain scans, hoping to obtain clearer
data.