Guosong Liu, a neuroscientist at the Picower Center
for Learning and Memory at MIT, reports new information on
neuron design and function in the March 7 issue of Nature
Neuroscience that he says could lead to new directions in
how computers are made.
While computers get faster all the
time, they continue to lack any form of human intelligence.
While a computer may beat us at
balancing a checkbook or dominating a chessboard, it still
cannot easily drive a car or carry on a conversation. Computers lag in
raw processing power--even the most powerful
components are dwarfed by 100 billion brain cells--but
their biggest deficit may be that they are designed without
knowledge
of how the brain itself computes.
While computers process
information using a binary system of zeros and ones,
the neuron, Liu discovered, communicates
its electrical
signals in trinary--utilizing not only zeros and
ones, but also minus ones. This allows additional interactions
to occur
during processing. For instance, two signals can add
together
or cancel each other out, or different pieces of information
can link up or try to override one another.
One reason
the brain might need the extra complexity of another
computation component is that it has the
ability to ignore
information when necessary; for instance, if you
are concentrating on something,
you can ignore your surroundings. "Computers
don't
ignore information," Liu said. "This
is an evolutionary advantage that's unique
to the brain."
Liu, associate professor of
brain and cognitive sciences, said an important
element of how brain
circuits work
involves wiring
the correct positive, or "excitatory" wires,
with the correct negative, or "inhibitory" wires.
His work demonstrates that brain cells contain
many individual processing
modules that each collects a set number of
excitatory and inhibitory inputs. When the
two types of inputs
are correctly connected together,
powerful processing can occur at each module.
This work provides the first experimental
evidence supporting a theory proposed more
than 20 years
ago by MIT neuroscientist
Tomaso Poggio, the Eugene McDermott Professor
in the Brain Sciences, in which he proposed
that neurons
use
an excitatory/inhibitory
form to process information.
By demonstrating
the existence of tiny excitation/inhibition modules
within brain cells, the work also
addresses a huge question in
neuroscience: What is the brain's
transistor, or fundamental processing
unit? For many years,
neuroscientists believed that
this basic unit of computing was the
cell itself, which collects and processing
signals
from other cells. By showing that each
cell is built from hundreds of tiny modules,
each of which computes independently,
Liu's
work adds to a growing view that there
might be something even smaller than
the cell at
the heart of
computation.
Once all the modules have
completed their processing, they funnel
signals to the
cell body, where all
of the signals
are integrated
and passed on. "With cells composed
of so many smaller computational parts,
the complexity attributed to the nervous
system begins
to make more sense," Liu said.
Liu found that these microprocessors
automatically form all along the surface
of the cell as
the brain develops.
The
modules also
have their own built-in intelligence
that seems to allow them to accommodate
defects
in the wiring
or electrical
storms in the
circuitry: if any of the connections
break, new ones automatically form to
replace the
old ones.
If the positive, "excitatory" connections
are overloading, new negative, "inhibitory" connections
quickly form to balance out the signaling,
immediately restoring the capacity to
transmit information.
The discovery of
this balancing act, which occurs
repeatedly all over the
cell, provides
new insight
into the mechanisms
by which
our neural circuits adapt to changing
conditions.
This work is funded
by the National Institutes of Health and the RIKEN-MIT
Neuroscience
Research Center.
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