Posted: 27 Dec 2017 07:30 AM PST
The cosmos in your cranium: "The human brain is the most complex
organized matter in the universe (pending more complex brains that exist
elsewhere in the cosmos)."
Cracking the German Enigma code is considered to be one of the decisive
factors that hastened Allied victory in World War II. Now researchers
have used similar techniques to crack some of the brain’s mysterious
code. By statistically analyzing clues intercepted
through espionage, computer science pioneers in the 1940s were able to
work out the rules of the Enigma code, turning a string of gibberish
characters into plain language to expose German war communications.
Today, a team that included computational neuroscientist Eva Dyer,
who recently joined the Georgia Institute of Technology, used
cryptographic techniques inspired by Enigma’s decrypting to predict,
from brain data alone, which direction subjects will move
their arms
The work by researchers from the University of Pennsylvania, Georgia
Tech, and Northwestern University could eventually help decode the
neural activity underpinning more complex muscle movements and become
useful in prosthetics, or even speech, to aid patients
with paralysis.
During the war, the team that cracked Enigma, led by Alan Turing,
considered the forebear of modern computer science, analyzed the
statistical prevalence of certain letters of the alphabet to understand
how they were distributed in messages like points on
a map. That allowed the code breakers to eventually decipher whole
words reliably.
LISTEN TO THE PODCAST: The Brain, Cosmos in the Cranium, Part I - when the brain's fate hangs by a few
molecules
In a similar manner, the neurological research team has now mapped
the statistical distribution of more prevalent and less prevalent
activities in populations of motor neurons to arrive at the specific
hand movements driven by that neural activity.
The research team was led by University of Pennsylvania professor
Konrad Kording, and Eva Dyer, formerly a postdoctoral researcher in
Kording’s lab and now an assistant professor at Georgia Tech. They
collaborated with the group of Lee Miller, a professor
at Northwestern University. They published their study on December 12,
2017, in the journal Nature Biomedical Engineering.
Neuron firing pattern
In an experiment conducted in animal models, the researchers took data
from more than one hundred neurons associated with arm movement. As the
animals reached for a target that appeared at different locations around
a central starting point, sensors recorded
spikes of neural activity that corresponded with the movement of the
subject’s arm.
“Just looking at the raw neural activity on a visual level tells you
basically nothing about the movements it corresponds to, so you have to
decode it to make the connection,” Dyer said. “We did it by mapping
neural patterns to actual arm movements using
machine learning techniques inspired by cryptography.”
The statistical prevalence of certain neurons’ firings paired up
reliably and repeatedly with actual movements the way that, in the
Enigma project, the prevalence of certain code symbols paired up with
the frequency of use of specific letters of the alphabet
in written language. In the neurological experiment, an algorithm
translated the statistical patterns into visual graphic patterns, and
eventually, these aligned with the physical hand movements that they
aimed to decode.
“The algorithm tries every possible decoder until we get something
where the output looks like typical movements,” Kording said. “There are
issues scaling this up — it’s a hard computer science problem — but
this is a proof-of-concept that cryptanalysis
can work in the context of neural activity.
“At this point, the cryptanalysis approach is very new and needs
refining, but fundamentally, it’s a good match for this kind of brain
decoding,” Dyer said.
Brain decoding does face a fundamental challenge that code-breaking doesn't.
In cryptography, code-breakers have both the encrypted and
unencrypted messages, so all they need to do is to figure out which
rules turn one into the other. "What we wanted to do in this experiment
was to be able to decode the brain from the encrypted message
alone,” Kording said.
Hear PODCAST: The Brain, Cosmos in the Cranium, Part II -- neurons' secrets and how they make the brain compute
Brain-computer interfaces
A cryptanalysis approach to decoding neural activity is particularly
attractive when it comes to brain-computer interfaces that control
prosthetics.
Existing brain-computer interfaces can already use such data to move a
robotic prosthesis, but Kording and Dyer’s experiment has achieved a
significant innovation. Existing technology uses a process known as
supervised learning, in which the interface can
be trained to recognize which neural firings correspond to which
intended physical movements, and can thus “replay” those movements when
the subject's motor neurons produce a pattern the device has been
trained to recognize.
The new research could do away with the training period required for
existing brain-computer interfaces to function and allow robotic limbs
to directly interpret their user’s thoughts without even having to be
calibrated. It would represent a significant
quality-of-life improvement for patients wearing them.
“Supervised training may sound simple, but actually, it can be long
and troublesome, and in the end, it can even fail,” Dyer said. “For
example, if the patient’s arm is not paralyzed but instead is missing,
it’s really hard for the training to work.”
The researchers’ innovation could mean the difference between a
patient straining to mentally picture how the arm should move with
possibly cumbersome results, and willfully moving the arm in a virtually
natural way.
Doorway to mindreading
This cryptanalysis approach also offers promise for brain-computer
interfaces to achieve literal mind-reading, the way decoding Enigma
allowed for reading encrypted texts.
A patient repeatedly thinking the same sentences would generate
neural patterns. “We could build a decoder that transforms those
patterns until they look like language,” Kording said. “I think we
should be able to do this within the next decade.”
A consistent improvement in brain recording technology could help put
this goal within reach. This could become useful for patients unable to
speak but could also possibly be abused in espionage, Kording warned.
But there's still time to work out the direction
future applications take on.
An evolutionary stroke of luck has made this cryptanalysis approach
possible. “The brain ended up with this encryption system through
natural selection,” Kording said. “So, it’s essentially making the same
kind of ‘mistakes’ that allowed us to crack Enigma
in the first place.”
Modern encryption systems are so refined they’re impossible to crack.
Enigma, on the other hand, was new enough during World War II that it
had small imperfections that gave decrypters a pathway into its secrets,
making its cracking a fitting inspiration
for brain decoding.
The Daily Galaxy via
Georgia Tech
Hacking the Human Brain's Enigma Code --"The Most Complex Organized Matter in the Universe"
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