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Attributes of The Future of the Mind PDF
The Future of the Mind PDF-New York: Doubleday, 2014. First Edition and First Printing. Octavo, illustrated jacket, blue and black boards with silver spine imprinting, xviii + 377 pp. +1. As New, and better than that; completely flawless and pristine. Even the spine ends – book and jacket – are military straight and untouched, and will stay that way in archival protection. A collector copy if there ever was one of the 1st/1st of Michio Kaku’s remarkable adventure into understanding – scientifically and analytically – consciousness. Tall order, but he’s up for giving it a scholarly yet engaging go. Neither Kaku nor any scientist at this point will be able to cross the last river and explain what “self-awareness” is, as opposed to what happens physically when it goes on; but then they aren’t philosophers, and philosophers can’t even do that yet. When it will happens, it will arise from a new, blended discipline. You heard that here first. Please see scans, though I have limited those in the interest of not doing a
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The Writers
MICHIO KAKU is a professor of physics at the City University of New York, cofounder of string field theory, and the author of several widely acclaimed science books, including Hyperspace, Beyond Einstein, Physics of the Impossible, and Physics of the Future. He is the science correspondent for CBS’s This Morning and host of the radio programs Science Fantastic and Explorations in Science.
Proportions of The Future of the Mind PDF
- Publisher : Doubleday; 1st edition (February 25, 2014)
- Language : English
- Hardcover : 400 pages
- International Standard Book Number-10 : 038553082X
- International Standard Book Number-13 : 978-0385530828
- Item Weight : 1.51 pounds
- Dimensions : 6.45 x 1.34 x 9.51 inches
- The Future of the Mind PDF
Reviews From Customers
The epicenter for much of this research is the University of California at
Berkeley, where I received my own Ph.D. in theoretical physics years ago. I
had the pleasure of touring the laboratory of Dr. Gallant, whose group has
accomplished a feat once considered to be impossible: videotaping people’s
thoughts. “This is a major leap forward reconstructing internal imagery. We
are opening a window into the movies in our mind,” says Gallant.
When I visited his laboratory, the first thing I noticed was the team of
young, eager postdoctoral and graduate students huddled in front of their
computer screens, looking intently at video images that were reconstructed
from someone’s brain scan. Talking to Gallant’s team, you feel as though you
are witnessing scientific history in the making.
Gallant explained to me that first the subject lies flat on a stretcher, which
is slowly inserted headfirst into a huge, state- of- the- art MRI machine, costing
upward of $3 million. The subject is then shown several movie clips (such
as movie trailers readily available on YouTube). To accumulate enough data,
the subject has to sit motionless for hours watching these clips, a truly arduous
task. I asked one of the postdocs, Dr. Shinji Nishimoto, how they found
volunteers who were willing to lie still for hours on end with only fragments
of video footage to occupy the time. He said the people in the room, the grad
students and postdocs, volunteered to be guinea pigs for their own research.
As the subject watches the movies, the MRI machine creates a 3- D image
of the blood flow within the brain. The MRI image looks like a vast collection
of thirty thousand dots, or voxels. Each voxel represents a pinpoint of neural energy, and the color of the dot corresponds to the intensity of the signal and blood flow. Red dots represent points of large neural activity, while blue dots represent points of less activity. (The final image looks very much like thousands of Christmas lights in the shape of the brain. Immediately you can see that the brain is concentrating most of its mental energy in the visual cortex, which is located at the back of the brain, while watching these videos.)
Gallant’s MRI machine is so powerful it can identify two to three hundred distinct regions of the brain and, on average, can take snapshots that have one hundred dots per region of the brain. (One goal for future generations of MRI technology is to provide an even sharper resolution by increasing the number of dots per region of the brain.)
At first, this 3- D collection of colored dots looks like gibberish. But after
years of research, Dr. Gallant and his colleagues have developed a mathematical
formula that begins to find relationships between certain features of a picture (edges, textures, intensity, etc.) and the MRI voxels. For example, if you look at a boundary, you’ll notice it’s a region separating lighter and darker areas, and hence the edge generates a certain pattern of voxels. By having subject after subject view such a large library of movie clips, this mathematical formula is refined, allowing the computer to analyze how all sorts of images are converted into MRI voxels. Eventually the scientists were able to ascertain a direct correlation between certain MRI patterns of voxels
and features within each picture.
At this point, the subject is then shown another movie trailer. The computer
analyzes the voxels generated during this viewing and re- creates a rough approximation of the original image. (The computer selects images from one hundred movie clips that most closely resemble the one that the subject just saw and then merges images to create a close approximation.) In this way, the computer is able to create a fuzzy video of the visual imagery going through your mind. Dr. Gallant’s mathematical formula is so versatile that it can take a collection of MRI voxels and convert it into a picture, or it can do the reverse, taking a picture and then converting it to MRI voxels.
I had a chance to view the video created by Dr. Gallant’s group, and it was
very impressive. Watching it was like viewing a movie with faces, animals,
street scenes, and buildings through dark glasses. Although you could not
see the details within each face or animal, you could clearly identify the kind
of object you were seeing.
Not only can this program decode what you are looking at, it can also
decode imaginary images circulating in your head. Let’s say you are asked to
think of the Mona Lisa. We know from MRI scans that even though you’re
not viewing the painting with your eyes, the visual cortex of your brain will
light up. Dr. Gallant’s program then scans your brain while you are thinking
of the Mona Lisa and flips through its data files of pictures, trying to find the
closest match. In one experiment I saw, the computer selected a picture of
the actress Salma Hayek as the closest approximation to the Mona Lisa. Of
course, the average person can easily recognize hundreds of faces, but the
fact that the computer analyzed an image within a person’s brain and then
picked out this picture from millions of random pictures at its disposal is
still impressive.
The goal of this whole process is to create an accurate dictionary that
allows you to rapidly match an object in the real world with the MRI pattern
in your brain. In general, a detailed match is very difficult and will take years,
but some categories are actually easy to read just by flipping through some
photographs. Dr. Stanislas Dehaene of the Collège de France in Paris was
examining MRI scans of the parietal lobe, where numbers are recognized,
when one of his postdocs casually mentioned that just by quickly scanning
the MRI pattern, he could tell what number the subject was looking at. In
fact, certain numbers created distinctive patterns on the MRI scan. He notes,
“If you take 200 voxels in this area, and look at which of them are active
and which are inactive, you can construct a machine-learning device that
decodes which number is being held in memory.”
This leaves open the question of when we might be able to have picture quality
videos of our thoughts. Unfortunately, information is lost when a
person is visualizing an image. Brain scans corroborate this. When you compare
the MRI scan of the brain as it is looking at a flower to an MRI scan
as the brain is thinking about a flower, you immediately see that the second
image has far fewer dots than the first. So although this technology will
vastly improve in the coming years, it will never be perfect. (I once read a
short story in which a man meets a genie who offers to create anything that
the person can imagine. The man immediately asks for a luxury car, a jet
plane, and a million dollars. At first, the man is ecstatic. But when he looks at
these items in detail, he sees that the car and the plane have no engines, and
the image on the cash is all blurred. Everything is useless. This is because our
memories are only approximations of the real thing.)
But given the rapidity with which scientists are beginning to decode the
MRI patterns in the brain, will we soon be able to actually read words and
thoughts circulating in the mind?
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