rate, the art or science of capturing an image from brainwave
activity took an important step forward thanks to new research from
the University of California, Berkeley. Researchers at U of C
used functional magnetic
resonance imaging (fMRI) to peek at a subject's brain activity
and attempt to read their thoughts.
A previous study had
looked at using fMRI scans of parts of the brain linked to shape
identification to correctly guess the a viewed image from a series of
stock images. Jack Gallant, a University of California,
Berkeley neuroscientist who led the current effort, describes
this previous work as similar to "the magician's card trick
where you pick a card from a deck, and he guesses which card you
picked. The magician knows all the cards you could have seen."
new study expands this approach greatly by also scanning parts of the
brain used for general classifications like "person",
"car", or "building". Utilizing Bayesian
probabilistic math, researchers armed with a database of over 6
million possible results and the new scans were able to go beyond
identification into the realm of reconstruction, coming up with an
image corresponding to what the person was thinking of, after an
initial calibration to adjust for mental differences.
Professor Gallant, "[In the new study] the card could be a
photograph of anything in the universe. The magician has to figure it
out without ever seeing it."
The new study is
reported in the journal Neuron and was coauthored by
Berkeley postdoctoral researcher Thomas Naselaris.
current study researchers can get a general idea of what the person
is thinking about, but lack the ability to literally draw a
picture-perfect scene of the what the subject is visualizing.
This is because imaging techniques such as fMRI lump millions of
neurons into single output blocks. Frank Tong, a Vanderbilt
University neuroscientist who evaluated the study describes, "At
the finer level, there is a ton of information. We just don't have a
way to tap into that without opening the skull and accessing it
Supplementary scanning techniques, though,
like optical laser scans or EEG readings could help improve the
fidelity of the current information. Professor Gallant states,
"[In a few decades] you could use algorithms like this to decode
other things than vision. In theory, you could analyze internal
speech. You could have someone talk to themselves, and have it come
out in a machine." (Such devices currently exist, but not by
tapping brainwaves... they tap neurons going to the voicebox)
thoughts certainly are not without alarming privacy and safety
implications. Still, such issues have seldom been able to hold
back the progress of science and it looks like for better or worse,
we're heading towards being able to read each others' minds, given
the proper (expensive) tools.