Synthetic Brains
Researchers study the feasibility of brains made from carbon nanotubes
http://www.nsf.gov/discoveries/disc_summ.jsp?cntn_id=112947&org=NSF
Researchers are building mathematical models that accurately reflect neuron connections.
January 27, 2009
Synthetic brains are a long way from reality, but researchers at the University of Southern
California, funded by the National Science Foundation, are taking the first steps to build
neurons from carbon nanotubes that emulate human brain function.
"At this point we still don't know if building a synthetic brain is feasible," said Alice Parker,
professor of electrical engineering. "It may take decades to realize anything close to the
human brain but emulating pieces of the brain, such as a synthetic vision system or
synthetic cochlea that interface successfully with a real brain may be available quite soon,
and synthetic parts of the brain's cortex within decades."
The challenges to creating a synthetic brain are staggering. Unlike computer software that
simulates brain function, a synthetic brain will include hardware that emulates brain cells,
their amazingly complex connectivity and a concept Parker calls "plasticity," which allows
the artificial neurons to learn through experience and adapt to changes in their
environment the way real neurons do.
There is also the matter of scale. By 2022, with conventional technology, if the team could
construct a synthetic brain that emulated real brain function, even crudely, it would take
100 billion artificial neurons and a very a large room to hold them.
"Obviously the technology will have to be downsized to aid a human being or be feasible as a
robot brain," Parker said. Power is another consideration. The power requirements for a
synthetic brain are staggering because a human brain never turns off. "In a transistor things
are on or off so it's a black-or-white situation, but in the brain there are also many shades of
gray and power is continuously being consumed," Parker noted.
But before the researchers can tackle concerns of power and scale, they are building
mathematical models that accurately reflect the Byzantine connections of all the neurons
and demonstrate how the connections allow neurons to communicate with each other.
Each neuron in the cortex--a part of the brain that contributes significantly to conscious
thought and intelligence--is connected to tens of thousands of other neurons. The
researchers are also implementing the complex computations carried out by each neuron on
all the inputs it receives from other neurons.
"It's a nonlinear phenomenon and almost impossible to model but that's what we're
attempting to do," Parker said.
The researchers have shown that portions of a neuron can be modeled electronically using
carbon nanotube circuit models and have performed detailed simulations of the circuit
models. A single archetypical neuron, including excitatory and inhibitory synapses, has
been modeled electronically and simulated. Parker and her co-researcher Chongwu Zhou
are in the process of combining these circuit models of neurons to create a functional
carbon nanotube circuit model of a small network of neurons. This small network of
interconnected neurons will be simulated using the carbon nanotube models. This network
demonstrates an interesting neural circuit that detects moving edges in a selected direction.
Parker believes carbon nanotubes are an ideal material to emulate brain function because
their three-dimensional structure allows connectivity in all directions on all planes and
because a carbon-based prosthesis is less likely to be rejected by the human body than one
made from inorganic materials. But their invasive nature could result in them invading
surrounding tissue and prompting lesions and cancers.
"It's a possibility and something else that needs to be addressed for the technology to be
feasible," Parker said.
As the researchers move ahead with their mathematical modeling and neuron construction,
beginning with a single synapse, they ponder "plasticity," neuroscientists' term for the
brain's ability to learn and adapt to change. "Our brains can grow new neurons and the
synapses between them in an hour--a remarkable biological feature that is difficult to
emulate from an engineering perspective," Parker said.
Emulating such plasticity in a synthetic brain will require a major leap in technology,
similar to the leap from cathode ray tubes to transistors. "We don't know what the new
technology will look like yet, but it will be a technology that can self-assemble and reshape
itself.
As we work in the lab building neurons or constructing mathematical models, we must
consider the requirement of plasticity, even if we don't yet know what it looks like."
Aside from the daunting technological challenges, a synthetic brain or brain components
will also raise ethical and environmental issues. The role of emotions in learning are just
beginning to be understood, and it appears they are incredibly important to brain function.
"Based on what I know right now, emotions would have to be included for a synthetic brain
to be able to learn," Parker said. "It's important to understand their cause and effect."
-- Diane E. Banegas, (703) 292-8070 dbanegas@nsf.gov
Investigators
Alice Parker
Chongwu Zhou
Related Institutions/Organizations
University of Southern California
Next
Researchers study the feasibility of brains made from carbon nanotubes
http://www.nsf.gov/discoveries/disc_summ.jsp?cntn_id=112947&org=NSF
Researchers are building mathematical models that accurately reflect neuron connections.
January 27, 2009
Synthetic brains are a long way from reality, but researchers at the University of Southern
California, funded by the National Science Foundation, are taking the first steps to build
neurons from carbon nanotubes that emulate human brain function.
"At this point we still don't know if building a synthetic brain is feasible," said Alice Parker,
professor of electrical engineering. "It may take decades to realize anything close to the
human brain but emulating pieces of the brain, such as a synthetic vision system or
synthetic cochlea that interface successfully with a real brain may be available quite soon,
and synthetic parts of the brain's cortex within decades."
The challenges to creating a synthetic brain are staggering. Unlike computer software that
simulates brain function, a synthetic brain will include hardware that emulates brain cells,
their amazingly complex connectivity and a concept Parker calls "plasticity," which allows
the artificial neurons to learn through experience and adapt to changes in their
environment the way real neurons do.
There is also the matter of scale. By 2022, with conventional technology, if the team could
construct a synthetic brain that emulated real brain function, even crudely, it would take
100 billion artificial neurons and a very a large room to hold them.
"Obviously the technology will have to be downsized to aid a human being or be feasible as a
robot brain," Parker said. Power is another consideration. The power requirements for a
synthetic brain are staggering because a human brain never turns off. "In a transistor things
are on or off so it's a black-or-white situation, but in the brain there are also many shades of
gray and power is continuously being consumed," Parker noted.
But before the researchers can tackle concerns of power and scale, they are building
mathematical models that accurately reflect the Byzantine connections of all the neurons
and demonstrate how the connections allow neurons to communicate with each other.
Each neuron in the cortex--a part of the brain that contributes significantly to conscious
thought and intelligence--is connected to tens of thousands of other neurons. The
researchers are also implementing the complex computations carried out by each neuron on
all the inputs it receives from other neurons.
"It's a nonlinear phenomenon and almost impossible to model but that's what we're
attempting to do," Parker said.
The researchers have shown that portions of a neuron can be modeled electronically using
carbon nanotube circuit models and have performed detailed simulations of the circuit
models. A single archetypical neuron, including excitatory and inhibitory synapses, has
been modeled electronically and simulated. Parker and her co-researcher Chongwu Zhou
are in the process of combining these circuit models of neurons to create a functional
carbon nanotube circuit model of a small network of neurons. This small network of
interconnected neurons will be simulated using the carbon nanotube models. This network
demonstrates an interesting neural circuit that detects moving edges in a selected direction.
Parker believes carbon nanotubes are an ideal material to emulate brain function because
their three-dimensional structure allows connectivity in all directions on all planes and
because a carbon-based prosthesis is less likely to be rejected by the human body than one
made from inorganic materials. But their invasive nature could result in them invading
surrounding tissue and prompting lesions and cancers.
"It's a possibility and something else that needs to be addressed for the technology to be
feasible," Parker said.
As the researchers move ahead with their mathematical modeling and neuron construction,
beginning with a single synapse, they ponder "plasticity," neuroscientists' term for the
brain's ability to learn and adapt to change. "Our brains can grow new neurons and the
synapses between them in an hour--a remarkable biological feature that is difficult to
emulate from an engineering perspective," Parker said.
Emulating such plasticity in a synthetic brain will require a major leap in technology,
similar to the leap from cathode ray tubes to transistors. "We don't know what the new
technology will look like yet, but it will be a technology that can self-assemble and reshape
itself.
As we work in the lab building neurons or constructing mathematical models, we must
consider the requirement of plasticity, even if we don't yet know what it looks like."
Aside from the daunting technological challenges, a synthetic brain or brain components
will also raise ethical and environmental issues. The role of emotions in learning are just
beginning to be understood, and it appears they are incredibly important to brain function.
"Based on what I know right now, emotions would have to be included for a synthetic brain
to be able to learn," Parker said. "It's important to understand their cause and effect."
-- Diane E. Banegas, (703) 292-8070 dbanegas@nsf.gov
Investigators
Alice Parker
Chongwu Zhou
Related Institutions/Organizations
University of Southern California
Next
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