Highlighted Publications
Ebrahimi S, van der Voort B, Ostry DJ (2024)
The Consolidation of Newly Learned Movements Depends
upon the Somatosensory Cortex in Humans. Journal
of Neuroscience, 44(32):e0629242024.
Abstract
PDF
Studies using magnetic brain stimulation indicate
the involvement of somatosensory regions in the
acquisition and retention of newly learned
movements. Recent work found an impairment in motor
memory when retention was tested shortly after the
application of continuous theta-burst stimulation
(cTBS) to the primary somatosensory cortex, compared
with stimulation of the primary motor cortex or a
control zone. This finding suggests that the
somatosensory cortex is involved in motor memory
retention, whereas the motor cortex is not. This
study tests the idea that the somatosensory cortex's
plasticity underlies newly learned movements,
challenging the common belief that adaptation
learning updates a motor controller. Participants
trained on a visuomotor adaptation task with a
gradually shifted visual feedback. Post-training,
cTBS was applied to M1, S1, or an occipital cortex
control area, and participants were tested for
retention after 24 hours. S1 stimulation led to
reduced retention, unlike M1 or the control.
Applying cTBS to S1 after unrotated feedback
training showed no effect, suggesting
learning-specific impacts. Findings support the S1's
role in encoding learning-related movement changes
and motor memory retention.
Ebrahimi S, Ostry DJ (2024) The human somatosensory
cortex contributes to the encoding of newly learned
movements. Proc Natl Sci USA
121:e2316294121.
Abstract
PDF
Recent studies indicate somatosensory cortex
involvement in motor learning and retention. This
study explores whether this involvement is transient
or leads to lasting learning-related changes,
suggesting the encoding of learned movements. By
applying cTBS post-training, we aimed to disrupt
learning-related changes in the somatosensory
cortex. Participants trained with rotated visual
feedback and were tested after stimulation to M1,
S1, or a control area. S1 disruption impaired motor
memory retention, unlike M1. Learning without
feedback changes did not show movement impairment
post-S1 stimulation, indicating learning-specific
disruptions. Results suggest S1 is part of a circuit
encoding movement-related learning changes.
Darainy M, Manning TF (2023) Disruption of
somatosensory cortex impairs motor learning and
retention. Journal of Neurophysiology
130:1521–1528.
Abstract
PDF
This study tests the somatosensory cortex's
function beyond processing somatic afferent
information, suggesting its involvement in motor
learning and memory stabilization. cTBS was applied
before force-field training to disrupt activity in
S1, M1, or an occipital control area. Retention and
relearning tests after 24 hours showed that cTBS to
S1 impaired learning and retention, while M1
disruption mainly affected retention. Basic movement
remained unaffected by cTBS, implying specific
disruption to learning-related cortical changes.
Relearning in a new force field post-retention
testing indicated cognitive learning was independent
of the cortical zones tested, highlighting the
somatosensory cortex's learning-related role.
Kumar N, Sidarta A, Smith C, Ostry DJ, (2022)
Ventrolateral prefrontal cortex contributes to human
motor learning. eNeuro
Abstract
PDF
This study
assesses the involvement in human motor learning, of
the ventrolateral prefrontal cortex (BA 9/46v), a
somatic region in the middle frontal gyrus. The
potential involvement of this cortical area in motor
learning is suggested by studies in nonhuman
primates which have found anatomic connections
between this area and sensorimotor regions in
frontal and parietal cortex, and also with basal
ganglia output zones. It is likewise sug- gested by
electrophysiological studies which have shown that
activity in this region is implicated in somatic
sensory memory and is also influenced by reward. We
directly tested the hypothesis that area 9/46v is
in- volved in reinforcement-based motor learning in
humans. Participants performed reaching movements to
a hidden target and received positive feedback when
successful. Before the learning task, we applied
continu- ous theta burst stimulation (cTBS) to
disrupt activity in 9/46v in the left or right
hemisphere. A control group received sham cTBS. The
data showed that cTBS to left 9/46v almost entirely
eliminated motor learning, whereas learning was not
different from sham stimulation when cTBS was
applied to the same zone in the right hemisphere.
Additional analyses showed that the basic
reward-history-dependent pattern of movements was
preserved but more variable following left
hemisphere stimulation, which suggests an overall
deficit in so- matic memory for target location or
target directed movement rather than reward
processing per se. The re- sults indicate that area
9/46v is part of the human motor learning circuit.
Kumar N, van Vugt FT,
Ostry DJ (2021) Recognition memory for human motor
learning. Curr Biol 31:1678-1686.
Abstract
PDF
Motor skill retention is typically
measured by asking participants to reproduce
previously learned movements from memory. The analog
of this retention test (recall memory) in human
verbal memory is known to under-estimate how much
learning is actually retained. Here we asked whether
information about previously learned movements,
which can no longer be reproduced, is also retained.
Following visuomotor adaptation,we used tests of
recall that involved reproduction of previously
learned movements and tests of recognition in which
participants were asked whether a candidate limb
displacement, produced by a robot arm held by the
subject, corresponded to a movement direction that
was experienced during active training. The main
finding was that 24 h after training, estimates of
recognition memory were about twice as accurate as
those of recall memory. Thus, there is information
about previously learned movements that is not
retrieved using recall testing but can be accessed
in tests of recognition. We conducted additional
tests to assess whether,24 h after learning, recall
for previously learned movements could be improved
by presenting passive movements as retrieval cues.
These tests were conducted immediately prior to
recall testing and involved the passive playback of
a small number of movements, which were spread
across the workspace and included both adapted and
baseline movements, without being marked as such.
This technique restored recall memory for movements
to levels close to those of recognition memory
performance. Thus, somatic information may enable
retrieval of otherwise inaccessible motor memories.
Kumar N,
Manning TF, Ostry DJ (2019) Somatosensory cortex
participates in the consolidation of human motor
memory. PLOS Biol 17(10).
Abstract
PDF
Newly learned motor skills are
initially labile and then consolidated to permit
retention. The circuits that enable the
consolidation of motor memories remain uncertain.
Most work to date has focused on primary motor
cortex, and although there is ample evidence of
learning-related plasticity in motor cortex, direct
evidence for its involvement in memory consolidation
is limited. Learning-related plasticity is also
observed in somatosensory cortex, and accordingly,
it may also be involved in memory consolidation.
Here, by using transcranial magnetic stimulation
(TMS) to block consolidation, we report the first
direct evidence that plasticity in somatosensory
cortex participates in the consolidation of motor
memory. Participants made movements to targets while
a robot applied forces to the hand to alter
somatosensory feedback. Immediately following
adaptation, continuous theta-burst transcranial
magnetic stimulation (cTBS) was delivered to block
retention; then, following a 24-hour delay, which
would normally permit consolidation, we assessed
whether there was an impairment. It was found that
when mechanical loads were introduced gradually to
engage implicit learning processes, suppression of
somatosensory cortex following training almost
entirely eliminated retention. In contrast, cTBS to
motor cortex following learning had little effect on
retention at all; retention following cTBS to motor
cortex was not different than following sham TMS
stimulation. We confirmed that cTBS to somatosensory
cortex interfered with normal sensory function and
that it blocked motor memory consolidation and not
the ability to retrieve a consolidated motor memory.
In conclusion, the findings are consistent with the
hypothesis that in adaptation learning,
somatosensory cortex rather than motor cortex is
involved in the consolidation of motor memory.
Ohashi H,
Gribble PL, Ostry DJ (2019) Somatosensory cortical
excitability changes precede those in motor cortex
during human motor learning. J Neurophysiol 122:1397-1405.
Abstract
PDF
One of the puzzles of learning to
talk or play a musical instrument is how we learn
which movement produces a particular sound: an
audiomotor map. The initial stages of map
acquisition can be studied by having participants
learn arm movements to auditory targets. The key
question is what mechanism drives this early
learning. Three learning processes from previous
literature were tested: map learning may rely on
active motor outflow, (target) error correction and
on the correspondence between sensory and motor
distances (i.e. that similar movements map to
similar sounds). Alternatively, we hypothesized that
map learning can proceed without these. Participants
made movements which were mapped to sounds in a
number of different conditions that each precluded
one of the potential learning processes. We tested
whether map learning relies on assumptions about
topological continuity by exposing participants to a
permuted map that did not preserve distances in
auditory and motor space. Further groups were tested
who passively experienced the targets, kinematic
trajectories produced by a robot arm, and auditory
feedback as a yoked active participant (hence
without active motor outflow). Another group made
movements without receiving targets (thus without
experiencing errors). In each case we observed
substantial learning, therefore none of the three
hypothesized processes is required for learning.
Instead early map acquisition can occur with free
exploration without target error correction, is
based on sensory-to-sensory correspondences, and
possible even for discontinuous maps. The findings
are consistent with the idea that early sensorimotor
map formation can involve instance-specific
learning.
Ostry DJ, Gribble PL (2016) Sensory plasticity in human
motor learning. Trends Neurosci 39:114-123.
Abstract
PDF
There is accumulating evidence from
behavioral, neurophysiological, and neuroimaging
studies that the acquisition of motor skills
involves both perceptual and motor learning.
Perceptual learning alters movements, motor
learning, and motor networks of the brain. Motor
learning changes perceptual function and the sensory
circuits of the brain. Here, we review studies of
both human limb movement and speech that indicate
that plasticity in sensory and motor systems is
reciprocally linked. Taken together, this points to
an approach to motor learning in which perceptual
learning and sensory plasticity have a fundamental
role. Trends Sensorimotor adaptation results in
changes to sensory systems and sensory networks in
the brain. Perceptual learning modifies sensory
systems and directly alters the motor networks of
the brain. Perceptual changes associated with
sensorimotor adaptation are durable and occur in
parallel with motor learning.
Bernardi NF, Darainy M, Ostry DJ (2015) Somatosensory
contribution to the early stages of motor skill
learning. J Neurosci 35: 14316 -14326.
Abstract PDF
The early stages of motor skill
acquisition are often marked by uncertainty about
the sensory and motor goals of the task, as is the
case in learning to speak or learning the feel of a
good tennis serve. Here we present an experimental
model of this early learning process, in which
targets are acquired by exploration and
reinforcement rather than sensory error. We use this
model to investigate the relative contribution of
motor and sensory factors to human motor learning.
Participants make active reaching movements or
matched passive movements to an unseen target using
a robot arm. We find that learning through passive
movements paired ith reinforcement is comparable
with learning associated with active movement, both
in terms of magnitude and durability, with
improvements due to training still observable at a 1
week retest. Motor learning is also accompanied by
changes in somatosensory perceptual acuity. No
stable changes in motor performance are observed for
participants that train, actively or passively, in
the absence of reinforcement, or for participants
who are given explicit information about target
position in the absence of somatosensory experience.
These findings indicate that the somatosensory
system dominates learning in the early stages of
motor skill acquisition.
Vahdat S, Darainy M, Ostry DJ (2014) Structure of
plasticity in human sensory and motor networks due to
perceptual learning. J Neurosci 34:2451-63.
Abstract PDF
As we begin to acquire a new motor
skill, we face the dual challenge of determining and
refining the somatosensory goals of our movements
and establishing the best motor commands to achieve
our ends. The two typically proceed in parallel, and
accordingly it is unclear how much of skill
acquisition is a reflection of changes in sensory
systems and how much reflects changes in the brain's
motor areas. Here we have intentionally separated
perceptual and motor learning in time so that we can
assess functional changes to human sensory and motor
networks as a result of perceptual learning. Our
subjects underwent fMRI scans of the resting brain
before and after a somatosensory discrimination
task. We identified changes in functional
connectivity that were due to the effects of
perceptual learning on movement. For this purpose,
we used a neural model of the transmission of
sensory signals from perceptual decision making
through to motor action. We used this model in
combination with a partial correlation technique to
parcel out those changes in connectivity observed in
motor systems that could be attributed to activity
in sensory brain regions. We found that, after
removing effects that are linearly correlated with
somatosensory activity, perceptual learning results
in changes to frontal motor areas that are related
to the effects of this training on motor behavior
and learning. This suggests that perceptual learning
produces changes to frontal motor areas of the brain
and may thus contribute directly to motor learning.
Darainy M, Vahdat S, Ostry DJ (2013) Perceptual
learning in sensorimotor adaptation. J Neurophysiol
110: 2152-2162.
Abstract
PDF
Motor learning often involves
situations in which the somatosensory targets of
movement are initially, poorly defined, as for
example, in learning to speak or learning the feel
of a proper tennis serve. Under these conditions,
motor skill acquisition presumably requires
perceptual as well as motor learning. That is, it
engages both the progressive shaping of sensory
targets and associated changes in motor performance.
In the present paper, we test the idea that
perceptual learning alters somatosensory function
and in so doing produces changes to motor
performance and sensorimotor adaptation. Subjects in
these experiments undergo perceptual training in
which a robotic device passively moves the arm on
one of a set of fan shaped trajectories. Subjects
are required to indicate whether the robot moved the
limb to the right or the left and feedback is
provided. Over the course of training both the
perceptual boundary and acuity are altered. The
perceptual learning is observed to improve both the
rate and extent of learning in a subsequent
sensorimotor adaptation task and the benefits
persist for at least 24 hours. The improvement in
the present studies is obtained regardless of
whether the perceptual boundary shift serves to
systematically increase or decrease error on
subsequent movements. The beneficial effects of
perceptual training are found to be substantially
dependent upon reinforced decision-making in the
sensory domain. Passive-movement training on its own
is less able to alter subsequent learning in the
motor system. Overall, this study suggests
perceptual learning plays an integral role in motor
learning.
Vahdat S, Darainy M, Milner TE, Ostry DJ
(2011) Functionally specific changes in
resting-state sensorimotor networks after motor
learning. J Neurosci 31:16907-16915.
Abstract
PDF
Motor learning changes the activity
of cortical motor and subcortical areas of the
brain, but does learning affect sensory systems as
well? We examined inhumansthe effects of motor
learning using fMRI measures of functional
connectivity under resting conditions and found
persistent changes in networks involving both motor
and somatosensory areas of the brain. We developed a
technique that allows us to distinguish changes in
functional connectivity that can be attributed to
motor learning from those that are related to
perceptual changes that occur in conjunction with
learning. Using this technique, we identified a new
network in motor learning involving second
somatosensory cortex, ventral premotor cortex, and
supplementary motor cortex whose activation is
specifically related to perceptual changes that
occur in conjunction with motor learning. We also
found changes in a network comprising cerebellar
cortex, primary motor cortex, and dorsal premotor
cortex that were linked to the motor aspects of
learning. In each network, we observed highly
reliable linear relationships between neuroplastic
changes and behavioral measures of either motor
learning or perceptual function. Motor learning thus
results in functionally specific changes to distinct
resting-state networks in the brain.
Ostry DJ, Darainy M, Mattar AAG, Wong J, Gribble PL
(2010) Somatosensory plasticity and motor learning. J
Neurosci 30:5384-5393.
Abstract
PDF
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.
