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When young children learn
to write a signature, their brains generate motor commands
that are different from the commands needed to do the same
thing as adults. And yet, we do not need to relearn handwriting
as our bones and muscles change. Our sensory-motor is equipped
with a powerful machinery that modifies the previously acquired
motor programs so as to compensate for changes in the body
and in the surrounding environment. The activities of our
research group are directed at understanding the biological
and computational mechanisms underlying this remarkable
ability to learn and adapt. At the same time, we wish to
take advantage of the knowledge we have acquired for designing
new procedures and technologies for facilitating the recovery
of motor functions lost to stroke and other injuries.
A neuro-robotic learning system
Both the processes of learning and of adaptation take place
through the plastic modification of synaptic transmission.
To study how neural plasticity relates to the acquisition
and adaptation of behaviors, we are developing a new experimental
framework based on the interaction of a neural system with
a small mobile robot. The robot and the neural system form
a closed sensory-motor loop, whose observable outcome is
an artificial motor behavior- for example, the robot tracking
the motion of a light source. This hybrid neuro-robotic
system allows us to develop and test computational models
of learning and plasticity. We directly compare the artificial
behaviors generated by the biological neural system with
the artificial behavior generated by a mathematical model
of the same system in combination with the mobile robot.
Computational primitives for sensory-motor
learning A number of electrophysiological studies
have revealed a modular organization within the structure
of the spinal cord. When a small electrical stimulation
is delivered to a site in the lumbar spinal cord, a group
of muscle is activated. The result of this activation is
a field of forces that tend to drive the ipsilateral hindlimb
toward a stable posture. Most remarkably, the simultaneous
stimulation of multiple sites leads to a vectorial summation
of the force fields generated by each site. These studies
have suggested that the brain may generate complex motor
behaviors by adding the force fields produced by multiple
modules in the spinal cord. We are developing a theory of
motor control based of the superposition of these force
fields, which we consider as "motor primitives" in analogy
with the language primitives used to generate unlimited
sentences out of a finite vocabulary of words.
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| Figure:
Motor adaptation to changes in arm dynamics.
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To generate even the simplest
movements of the arm, the brain must solve a complex problem
of dynamics. The relation between the forces generated by
the muscles of the arm and the ensuing movement is expressed
by a system of complex nonlinear differential equations.
A number of studies have suggested that the brain maintains
an internal representation of this dynamical relation, not
in the form of a mathematical expression but in the form
of a transformation from desired movement to corresponding
command. This type of representation has been called an
"internal model". We are investigating the properties of
internal models by observing how subjects interact with
a robotic manipulator that applies a preprogrammed force
field to their hand. This force fields constitutes a change
in the dynamics that the subject's motor system must represent
in order to move the hand as desired. The current experimental
evidence indicate that the subjects have an accurate representation
of the dependence of the force upon the state of motion
of the limb. However, there is a surprising inability to
represent correctly a perturbation that depends explicitly
upon time. We wish to pursue this analysis to understand
what are the mechanisms and the limitations of our ability
to adapt to changes in limb dynamics.
How we learn to handle unstable
objects Many activities of our daily lives involve
handling objects which are unstable or marginally stable,
such as a ladle filled with hot soup. The safe transport
of the soup to one's cup is just one of the many challenges
that disabled individuals Ð such as many survivors of cerebral
stroke - must cope with. Handling silverware and cups, replacing
light bulbs, holding a toothpaste-loaded toothbrush, hanging
a shirt with a dress hanger, driving a car, all are tasks
that require one to cope with some degree of instability
in the manipulated object. The term ``instability'' refers
to the fact that small deviations from the correct behavior
of the manipulated object may lead to complete disruption
of performance. For example, if because of an inappropriate
movement of the wrist, the toothpaste falls off the brush,
one must re-initiate the operation from scratch, which is
obviously annoying. In other instances, the consequences
of object instability can lead to serious damage or injury.
In our laboratory we reproduce some significant features
of object instability in a specially designed manipulandum.
The manipulandum is programmed to generate "virtual objects"
that emulate the physical presence of real objects. Looking
at the performance of human subjects in transporting different
virtual objects we hope to understand what mechanism are
used to by the motor system to cope with mechanical instability.
Designing force fields for motor
rehabilitation When subjects adapt to a new mechanical
environment, they learn to compensate for the disturbing
forces so as to restore previously learned movements. For
example, if a force disturbs our hand when we try to move
it in a straight line we may produce an undesired curved
movement. However, if we keep repeating the movement and
the perturbation does not change, we eventually succeed
in making a straight hand movement. If, at this point, the
force is suddenly removed the hand will be displaced in
a direction opposite to the initial curvature. This is called
an "after-effect". After effects are visible manifestations
of the fact that subjects have learned to anticipate the
forces produced by the external perturbation. We are now
investigating how after-effects may be artificially induced
by specifically designed force perturbations so as to facilitate
motor learning in people with motor impairments that do
not involve their ability to adapt to an external force
field.
Go to:Mussa-Ivaldi
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