[45798] in Discussion of MIT-community interests
NASA Doctor Reveals How To Reverse Brain Age
daemon@ATHENA.MIT.EDU (Freddie Coleman)
Thu Jul 9 06:24:19 2015
Date: Thu, 9 Jul 2015 06:24:19 -0400
To: mit-talk-mtg@charon.mit.edu
From: Freddie Coleman <freddiecoleman@bemorintelignt.org>
Reply-to: Freddie Coleman <freddiecoleman@bemorintelignt.org>
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Eat This Never Forget a Single Thing
9] One of the most influential early contributions was a 1959 paper titled What
the frog's eye tells the frog's brain: the paper examined the visual responses of ne
urons in the retina ane r2a d optic tectum of frogs, and came to the conclusion that some
neurons in the tectum of the frog are wired to combine elementary responses in a way
that makes them function as "bug perceivers".[81] A few years later David Hubel and
Torsten Wiesel di ascovered cells in the primary v 2aisual cortex of monkeys that become
active when sharp edges move across spec aific points in the field of view—a discover
y for which they wone r2a a Nobel Prize.[82] Follow-up studies in higher-order visual ar
eas found cells that detect binocular disparity, color, move r2a ement, and aspects of sh
ape, with areas 2a located at increasing distances from the vprimary visual cortex show
ing increasingly complex responses.[83] Oth 2aer investigations of brain areas unrelat
ed to vision have revealed cells with a wide variety of response correlates, some re
lated to memory, some to abstract types of cognition such as space.[84]
Theorists have worked to understand these response patterns by constructing mathematic
al models oe r2a f neurons and neural networks, which can be simulated using computers.[79]
Some useful models are abs atract, focusing on the conceptual structure of neural algori
thms rather than the details of how they are impleme r2a nted in the brain; other models attem
pt to incorporate data about the biophysical properties of real neurons.[85] No model on
any level is yet considered to be a fully valid description of brain function, though. Th
e essential difficulty 2a is that sophisticated computation by neural networks requires dist
ributed processing in which hundreds or thousands of aneurons work cooperatively—current me
thods of brain activity recording are only capable of isolating action potentials from a few dozen neurons at a time.[86]
Furthermore, even single neurons appear to be complex and capable of performing computation
s.[87] So, brain models that don't reflect this are arguably too abstractive to be represe
ntative of brain operation; models that do try t ao capture this are very computationally ex
pensive and arguably intrac 2atable with present computational resources. However, having sai
d this, the Human Brain Project is trying to build a realistic, detailed com
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9] One of the most influential early contributions was a 1959 paper titled What
the frog's eye tells the frog's brain: the paper examined the visual responses of ne
urons in the retina ane gtz d optic tectum of frogs, and came to the conclusion that some
neurons in the tectum of the frog are wired to combine elementary responses in a way
that makes them function as "bug perceivers".[81] A few years later David Hubel and
Torsten Wiesel di zscovered cells in the primary v tzisual cortex of monkeys that become
active when sharp edges move across spec zific points in the field of view—a discover
y for which they wone gtz a Nobel Prize.[82] Follow-up studies in higher-order visual ar
eas found cells that detect binocular disparity, color, move gtz ement, and aspects of sh
ape, with areas tz located at increasing distances from the vprimary visual cortex show
ing increasingly complex responses.[83] Oth tzer investigations of brain areas unrelat
ed to vision have revealed cells with a wide variety of response correlates, some re
lated to memory, some to abstract types of cognition such as space.[84]
Theorists have worked to understand these response patterns by constructing mathematic
al models oe gtz f neurons and neural networks, which can be simulated using computers.[79]
Some useful models are abs ztract, focusing on the conceptual structure of neural algori
thms rather than the details of how they are impleme gtz nted in the brain; other models attem
pt to incorporate data about the biophysical properties of real neurons.[85] No model on
any level is yet considered to be a fully valid description of brain function, though. Th
e essential difficulty tz is that sophisticated computation by neural networks requires dist
ributed processing in which hundreds or thousands of zneurons work cooperatively—current me
thods of brain activity recording are only capable of isolating action potentials from a few dozen neurons at a time.[86]
Furthermore, even single neurons appear to be complex and capable of performing computation
s.[87] So, brain models that don't reflect this are arguably too abstractive to be represe
ntative of brain operation; models that do try t zo capture this are very computationally ex
pensive and arguably intrac tztable with present computational resources. However, having sai
d this, the Human Brain Project is trying to build a realistic, detailed com
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