Journal
Articles
Mattar AAG, Darainy M, Ostry DJ (2013) Motor learning and its sensory effects: The time course of
perceptual change, and its presence with gradual introduction of load. J. Neurophysiol. 109:782-91.
Abstract
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A complex interplay has been demonstrated between motor and sensory systems. We showed recently that motor learning leads to changes in the sensed position of the limb (Ostry DJ, Darainy M, Mattar AA, Wong J, Gribble PL. J Neurosci 30: 5384–5393, 2010). Here, we document further the links between motor learning and changes in somatosensory perception. To study motor learning, we used a force field paradigm in which subjects learn to compensate for forces applied to the hand by a robotic device. We used a task in which subjects judge lateral displacements of the hand to study somatosensory perception. In a first experiment, we divided the motor learning task into incremental phases and tracked sensory perception throughout. We found that changes in perception occurred at a slower rate than changes in motor performance. A second experiment tested whether awareness of the motor learning process is necessary for perceptual change. In this experiment, subjects were exposed to a force field that grew gradually in strength. We found that the shift in sensory perception occurred even when awareness of motor learning was reduced. These experiments argue for a link between motor learning and changes in somatosensory perception, and they are consistent with the idea that motor learning drives sensory change.
Mattar AAG, Nasir SM, Darainy M, Ostry DJ (2011) Sensory change following motor learning. in Green AM,
Chapman CE, Kalaska JF and Lepore F (Eds), Progress in Brain Research, Volume 191
(pp 29-42).
Abstract
PDF
Here we describe two studies linking perceptual change with motor learning. In the first, we
document persistent changes in somatosensory perception that occur following force field learning. Subjects learned to control a robotic device that applied forces to the hand during arm movements. This led to a change in the sensed position of the limb that lasted at least 24 h. Control experiments revealed that the sensory change depended on motor learning. In the second study, we describe changes in the perception of speech sounds that occur following speech motor learning. Subjects adapted control of speech movements to compensate for loads applied to the jaw by a robot. Perception of speech sounds was measured before and after motor learning. Adapted subjects showed a consistent shift in perception.
In contrast, no consistent shift was seen in control subjects and subjects that did not adapt to the load. These studies suggest that motor learning changes both sensory and motor function.
Mattar AAG, Ostry DJ (2010) Generalization of dynamics learning across changes in
movement amplitude. J Neurophysiol
104:426-438.
Abstract
PDF
Studies on generalization show the nature of how
learning is encoded
in the brain. Previous studies have shown rather limited generalization
of dynamics learning across changes in movement direction, a finding
that is consistent with the idea that learning is primarily local. In
contrast, studies show a broader pattern of generalization across
changes in movement amplitude, suggesting a more general form of
learning. To understand this difference, we performed an experiment
in which subjects held a robotic manipulandum and made movements
to targets along the body midline. Subjects were trained in a
velocitydependent
force field while moving to a 15 cm target. After training,
subjects were tested for generalization using movements to a 30 cm
target. We used force channels in conjunction with movements to the
30 cm target to assess the extent of generalization. Force channels
restricted lateral movements and allowed us to measure force production
during generalization. We compared actual lateral forces to the
forces expected if dynamics learning generalized fully. We found that,
during the test for generalization, subjects produced reliably less
force
than expected. Force production was appropriate for the portion of the
transfer movement in which velocities corresponded to those experienced
with the 15 cm target. Subjects failed to produce the expected
forces when velocities exceeded those experienced in the training
task. This suggests that dynamics learning generalizes little beyond
the range of one’s experience. Consistent with this result, subjects
who trained on the 30 cm target showed full generalization to the 15
cm target. We performed two additional experiments that show that
interleaved trials to the 30 cm target during training on the 15 cm
target can resolve the difference between the current results and those
reported previously.
Ostry DJ, Darainy M, Mattar AAG, Wong J, Gribble PL (2010) Somatosensory plasticity and motor
learning. J Neurosci 30:5384-5393.
Abstract
PDF
- J Neurosci Journal Club
Commentary PDF format (210 KB)
- J Neurophysiol Neuro Forum Commentary PDF format (106 KB)
Motor learning is dependent upon plasticity in motor areas of the brain, but does it occur in isolation, or does it also result in changes to sensory systems? We examined changes to somatosensory function that occur in conjunction with motor learning. We found that even after periods of training as brief as 10 min, sensed limb position was altered and the perceptual change persisted for 24 h. The perceptual change was reflected in subsequent movements; limb movements following learning deviated from the prelearning trajectory by an amount that was not different in magnitude and in the same direction as the perceptual shift. Crucially, the perceptual change was dependent upon motor learning. When the limb was displaced passively such that subjects experienced similar kinematics but without learning, no sensory change was observed. The findings indicate that motor learning affects not only motor areas of the brain but changes sensory function as well.
Darainy
M, Mattar AAG, Ostry DJ (2009) Effects of human arm impedance on dynamics
learning and generalization. J Neurophysiol 101:3158–3168.
Abstract PDF
Previous studies have demonstrated anisotropic
patterns of hand impedance under static conditions and during movement.
Here we show that the pattern of kinematic error observed in studies of
dynamics learning is associated with this anisotropic impedance
pattern. We also show that the magnitude of kinematic error associated
with this anisotropy dictates the amount of motor learning and,
consequently, the extent to which dynamics learning generalizes.
Subjects were trained to reach to visual targets while holding a
robotic device that applied forces during movement. On infrequent
trials, the load was removed and the resulting kinematic error was
measured. We found a strong correlation between the pattern of
kinematic error and the anisotropic pattern of hand stiffness. In a
second experiment subjects were trained under force-field conditions to
move in two directions: one in which the dynamic perturbation was in
the direction of maximum arm impedance and the associated kinematic
error was low and another in which the perturbation was in the
direction of low impedance where kinematic error was high.
Generalization of learning was assessed in a reference direction that
lay intermediate to the two training directions. We found that transfer
of learning was greater when training occurred in the direction
associated with the larger kinematic error. This suggests that the
anisotropic patterns of impedance and kinematic error determine the
magnitude of dynamics learning and the extent to which it generalizes.
Mattar AAG, Ostry
DJ (2007) Neural
averaging in motor learning. J Neurophysiol 97:220-228.
Abstract PDF
The capacity for skill development over multiple training episodes is
fundamental to human motor function. We have studied the process by
which skills evolve with training by progressively modifying a
series of motor learning tasks that subjects performed over a 1-mo
period. In a series of empirical and modeling studies, we show that
performance undergoes repeated modification with new learning. Each
in a series of prior training episodes contributes such that present
performance reflects a weighted average of previous learning.
Moreover, we have observed that the relative weighting of skills
learned wholly in the past changes with time. This suggests that the
neural substrate of skill undergoes modification after
consolidation.
Mattar AAG, Ostry DJ
(2007) Modifiability of generalization in dynamics learning. J
Neurophysiol 98:3321-3329.
Abstract PDF
Studies on plasticity in motor function have shown that motor learning
generalizes, such that movements in novel situations are affected by
previous training. It has been shown that the pattern of
generalization for visuomotor rotation learning
changes when training movements are made to a wide distribution of
directions. Here we have found that for dynamics learning, the shape
of the generalization gradient is not similarly modifiable by theextent of training within the workspace. Subjects learned to control
a robotic device during training and we measured how subsequent
movements in a reference direction were affected. Our results show
that as the angular separation between training and test directions
increased, the extent of generalization was reduced. When training
involved multiple targets throughout the workspace, the extent of
generalization was no greater than following training to the nearest
target alone. Thus a wide range of experience compensating for a
dynamics perturbation provided no greater benefit than localized
training. Instead, generalization was complete when training
involved targets that bounded the reference direction. This suggests
that broad generalization of dynamics learning to movements in novel
directions depends on interpolation between instances of localized
learning.
Lametti
DR, Mattar AAG (2006) Mirror neurons and the
lateralization of human language. J Neurosci 26:6666-6667.
Abstract PDF
Mattar
AAG, Gribble PL (2005) Motor learning by observing. Neuron
46:153-160.
Abstract PDF
Learning complex motor behaviours like riding a bicycle or swinging a golf
club is based on acquiring neural representations of the mechanical requirements
of movement (e.g. coordinating muscle forces to control the club). Here
we provide evidence that mechanisms matching observation and action facilitate
motor learning. Subjects who observed a video depicting another person learning
to reach in a novel mechanical environment (imposed by a robot arm) performed
better, when later tested in the same environment, than subjects who observed
similar movements but no learning; moreover subjects who observed learning
of a different environment performed worse. We show that this effect is
not based on conscious strategies but instead depends on the implicit engagement
of neural systems for movement planning and control.
Gribble
PL, Mullin LI, Cothros N, Mattar AAG (2003) Role of
cocontraction in arm movement accuracy. J Neurophysiol 89:2396-2405.
Abstract PDF
Cocontraction (the simultaneous activation of antagonist muscles around
a joint) provides the nervous system with a way to adapt the mechanical
properties of the limb to changing task requirements- both in statics and
during movement. However, relatively little is known about the conditions
under which the motor system modulates limb impedance through cocontraction.
The goal of this study was to test for a possible relationship between cocontraction
and movement accuracy in multi-joint limb movements. The electromyographic
activity of seven single- and double-joint shoulder and elbow muscles was
recorded using surface electrodes while subjects performed a pointing task
in a horizontal plane to targets that varied randomly in size. Movement
speed was controlled by providing subjects with feedback on a trial-to-trial
basis. Measures of cocontraction were estimated both during movement and
during a 200-ms window immediately following movement end. We observed an
inverse relationship between target size and cocontraction: as target size
was reduced, cocontraction activity increased. In addition, trajectory variability
decreased and endpoint accuracy improved. This suggests that, although energetically
expensive, cocontraction may be a strategy used by the motor system to facilitate
multi-joint arm movement accuracy. We also observed a general trend for
cocontraction levels to decrease over time, supporting the idea that cocontraction
and associated limb stiffness are reduced over the course of practice.
Gribble
PL, Everling S, Ford K, Mattar AAG (2002) Hand-eye
coordination for rapid pointing movements: Arm movement direction and
distance are specified prior to saccade onset. Exp Brain Res
145:372-382.
Abstract PDF
Visually guided arm movements such as reaching or pointing are accompanied
by saccadic eye movements that typically begin prior to motion of the arm.
In the past, some degree of coupling between the oculomotor and limb motor
systems has been demonstrated by assessing the relative onset times of eye
and arm movement, and by the demonstration of a gap effect for arm movement
reaction times. However, measures of limb movement onset time based on kinematics
are affected by factors such as the relatively high inertia of the limb
and neuromechanical delays. The goal of the present study was thus to assess
the relative timing of rapid eye and arm movements made to visual targets
by examining electromyographic (EMG) activity of limb muscles in conjunction
with eye and arm position measures. The observation of a positive correlation
between eye and limb EMG onset latencies, and the presence of a gap effect
for limb EMG onset times (a reduction in reaction time when a temporal gap
is introduced between the disappearance of a central fixation point and
the appearance of a new target) both support the idea that eye and arm movement
initiation are linked. However, limb EMG onset in most cases precedes saccade
onset, and the magnitude of EMG activity prior to eye movement is correlated
with both the direction and amplitude of the upcoming arm movement. This
suggests that, for the rapid movements studied here, arm movement direction
and distance are specified prior to the onset of saccades.
Conference presentations / published abstracts
Gribble PL, Mattar AA, Brown LE, Malfait N, Wilson ET, Obhi SS, Valyear KF, Culham JC, Anton JL, Williams A. Motor learning by observing. Poster presented at the 21st Annual Meeting of the Society for the Neural Control of Movement, San Juan, Puerto Rico, April 26 - May 1, 2011.
Mattar AAG, Darainy M and Ostry DJ. Generalization of sensory change following dynamics learning. Poster presented at the 40th Annual Meeting of the Society for Neuroscience, San Diego, CA, November 13-17, 2010
Darainy M, Mattar AAG and Ostry DJ. Exploring the links between motor learning and changes to somatosensory function. Poster presented at the 40th Annual Meeting of the Society for Neuroscience, San Diego, CA, November 13-17, 2010
Ostry DJ and Mattar AAG. Specificity of motor learning. Proceedings of the 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008
Ostry DJ and Mattar AAG. Generalization in motor learning. Proceedings of the 3rd International Symposium on Measurement, Analysis, and Modeling of Human Functions, 2007
Mattar AAG and Ostry DJ. Motor learning as a weighted average of past experience. Proceedings of the Annual Symposium Advances in Computational Motor Control, 2005
Mattar AAG, Ostry DJ.
Force production reveals limited generalization of dynamics learning
across changes in movement amplitude. Presented at the 39th Annual
Meeting of the Society for Neuroscience, Chicago, IL, 2009.
Darainy
M, Mattar AAG, Wong JD, Gribble PL, Ostry
DJ. The sensed position of the limb changes following dynamics
learning. Presented at the 39th Annual Meeting of the Society for
Neuroscience, Chicago, IL, 2009.
Wong JD, Gribble
PL, Darainy M, Mattar AAG, Ostry DJ.
Proprioception is modified following dynamics learning. Presented at
the 39th Annual Meeting of the Society for Neuroscience, Chicago, IL,
2009.
Ostry DJ, Darainy M, Mattar
AAG, Nasir SM, Wong J, Gribble PL. Sensory plasticity
and motor learning. Presented at the 19th Annual Meeting of the Society
for the Neural Control of Movement, Waikoloa, HI, 2009.
Darainy
M, Mattar AAG, Ostry DJ. The anisotropic
pattern of hand impedance affects dynamics learning and generalization.
Presented at the 38th Annual Meeting of the Society for Neuroscience,
Washington, DC, 2008.
Mattar AAG,
Ostry DJ. Motor learning modifies somatosensory
perception. Presented at the 37th Annual Meeting of the
Society for Neuroscience, San Diego, CA, 2007.
Ostry DJ, Mattar AAG. Generalization in motor
learning. Presented at the 3rd International Symposium on
Measurement, Analysis, and Modeling of Human Functions, Lisbon,
Portugal, 2007.
Mattar AAG,
Ostry DJ. Learned control of novel dynamics involves interpolation, not
extrapolation. Presented at the 17th Annual Meeting of the
Society for Neural Control of Movement, Seville,
Spain, 2007.
Mattar AAG, Ostry
DJ. The motor system learns by interpolation, not extrapolation.
Presented at the 36th Annual Meeting of the Society for Neuroscience,
Atlanta, GA, 2006.
Mattar AAG,
Ostry DJ. Motor learning as a weighted average of past experience.
Presented at the 35th Annual Meeting of the Society for Neuroscience,
Washington, DC, 2005.
Mattar AAG,
Ostry DJ. Motor learning as a weighted average of past experience.
Presented at Advances in Computational Motor Control IV, Washington,
DC, 2005.
Mattar AAG, Ostry DJ.
Recent dynamics learning can produce facilitation, interference and
everything in-between. Presented at Progress in Motor Control V, State
College, PA, 2005.
Mattar AAG,
Ostry DJ. The influence of recent motor learning: From facilitation to
interference. Presented at the 15th Annual Neural Control of Movement
Meeting, Key Biscayne, FL, 2005.
Mattar AAG,
Gribble PL. Motor learning by observing. Presented at the 15th Annual
Neural Control of Movement Meeting, Key Biscayne, FL, 2005.
Joanisse
MF, Melnyk L, Mattar AAG, Terry A, Gribble PL.
Procedural memory in children: A motor learning task reveals
developmental differences in learning but not interference. Presented
at the Biennial Meeting of the Society for Research in Child
Development, Atlanta, GA, 2005.
Mattar AAG,
Gribble PL. Motor learning by observing. Presented at the 34th Annual
Meeting of the Society for Neuroscience, San Diego, CA, 2004.
Gribble PL, Mattar AAG, Terry A, Melnyk L,
Joanisse MF. Development of motor learning and consolidation: Adaptive
representation of limb dynamics in children. Presented at the 11th
Annual Cognitive Neuroscience Society Meeting, San Francisco, CA, 2004.