Brain (2001), 124, 67–82
Characterizing the neural mechanisms of skill
learning and repetition priming
Evidence from mirror reading
Russell A. Poldrack1,2 and John D. E. Gabrieli2
1MGH-NMR
Center and Harvard Medical School,
Charlestown, Massachusetts and 2Department of
Psychology, Stanford University, Stanford, California, USA
Correspondence to: Russell A. Poldrack, MGH-NMR
Center Building 149, 13th Street, Charlestown, MA 02129,
USA
E-mail: [email protected]
Summary
The changes in brain activity related to skill learning and
repetition priming in a mirror-reading task were examined
using functional MRI. Subjects exhibited significant
learning across five training sessions and this learning
generalized significantly to different spatial transformations (inverted-mirror reversed text and normal
letters spelled backwards). Mirror reading, compared with
reading normal text, was associated with extensive
activation in occipital, temporal, parietal and frontal
regions. Learning to read mirror-reversed (MR) text was
associated with increased activation in left inferior
temporal, striatal, left inferior prefrontal and right
cerebellar regions and with decreased activity in the left
hippocampus and left cerebellum. Short-term repetition
priming was associated with reduced activity in many of
the regions active during mirror reading and extensive
item-specific practice (long-term repetition priming)
resulted in a virtual elimination of activity in those regions.
Short- and long-term repetition priming thus appeared to
rely upon common neural mechanisms. Nearly all of the
regions exhibiting significant learning-related changes also
exhibited increased repetition priming effects, suggesting
common neural substrates for priming and skill learning
in this task. Comparison of MR items with other spatially
transformed typographies showed that the learningrelated changes were general to all of the spatial
transformations. The results confirm the importance of
striatofrontal neural networks for the acquisition of skills,
and suggest that skill learning and repetition priming may
have common substrates within a particular task.
Keywords: basal ganglia; mirror reading; skill learning; repetition priming
Abbreviations: BA ⫽ Brodmann area; fMRI ⫽ functional MRI; IR ⫽ inverted-reversed; MR ⫽ mirror-reversed; ROI ⫽
region of interest; SB ⫽ spelled-backwards
Introduction
The ability of humans and other animals to learn from
experience, once thought to be a unitary function, is now
recognized to be supported by multiple memory systems
with different functional characteristics and neural bases
(Squire, 1992; Cohen and Eichenbaum, 1993). A fundamental
distinction in memory is between the declarative and nondeclarative (or procedural) memory systems. Declarative
memory supports explicit recollection of events and facts
and is thought to rely upon the medial temporal lobe and
diencephalic structures; damage to these regions leads to
amnesia, a global impairment of declarative memory. Nondeclarative memory comprises a number of memory functions
that are independent of the medial temporal lobe, as evidenced
by their sparing in people with amnesia, and are thought to
rely upon a number of cortical and subcortical structures.
© Oxford University Press 2001
Non-declarative memory functions include skill learning
(the acquisition of general task procedures with practice),
repetition priming (item-specific learning) and classical
conditioning.
Skill learning and repetition priming: common
systems?
Some previous work has suggested that non-declarative
memory may include independent systems specialized for
skill learning and repetition priming. In particular,
dissociations between skill learning and repetition priming
have been demonstrated in studies of patient groups. For
example, Heindel and colleagues examined priming (using a
word-stem completion task) and skill learning (using a
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R. A. Poldrack et al.
rotary pursuit task) in patients with Huntington’s disease and
Alzheimer’s disease (Heindel et al., 1989). They found a
double dissociation, in which Huntington’s disease patients
exhibited normal repetition priming on the stem completion
task but impaired motor learning on the rotary pursuit task,
whereas Alzheimer’s disease patients showed the opposite
pattern. However, because skill learning and repetition
priming were measured using different tasks these results are
equally consistent with a dissociation between different types
of knowledge (e.g. lexical/semantic versus perceptual versus
motor learning) than a dissociation between skill learning
and repetition priming per se. Dissociations between skill
learning and repetition priming have also been demonstrated
within a single task in normal subjects. For example, Schwartz
and Hashtroudi (1991) found that skill learning and repetition
priming were uncorrelated in both word identification and
inverted-reading tasks. Although these findings seem to
suggest separate skill learning and repetition priming systems,
others (Poldrack et al., 1999b) have argued on the basis of
behavioural and computational evidence that these data can
be accommodated by a single mechanism for both skill
learning and repetition priming (in any particular task).
These two views of non-declarative memory make
opposing claims concerning the neural bases of skill learning
and repetition priming; the independence theory predicts that
separate brain regions should exhibit neural changes related
to skill learning and repetition priming, whereas the singlesystem theory predicts that similar areas should exhibit
learning-related and priming-related changes within a
particular task (although these areas would probably differ for
different tasks). We examined this question in a preliminary
fashion using functional MRI (fMRI) in a study of the mirrorreading task (Poldrack et al., 1998). In this task, subjects are
presented with mirror-reversed (MR) text to read. With
practice, subjects can become quite skilled at this task and
learning is persistent, lasting at least 1 year (Kolers, 1976).
Learning occurs normally in amnesic patients undertaking
the mirror-reading task (Cohen and Squire, 1980; Martone
et al., 1984), suggesting that it does not rely upon the medial
temporal lobe. Such skill learning appears to be impaired in
patients with Huntington’s disease (Martone et al., 1984),
suggesting that it may rely upon the striatum or striatofrontal
networks.
In our previous study, subjects were presented with novel
MR words and pseudowords, and asked to perform lexical
decisions on these items; the lexical decision task was used
instead of the usual reading-aloud procedure because of the
constraints of fMRI on overt speech. Subjects participated in
two scanning sessions, and in between these sessions were
trained for three sessions on the mirror-reading task. In
addition, they received extensive practice on a small set of
repeated items during training. During scanning, lexical
decisions on novel MR items were compared with those on
items presented in plain text, as well as comparing them in
the second session with items that had been practised during
training. Only the posterior portion of the brain was imaged
using fMRI. We found a network of occipital, superior
parietal and inferior temporal regions involved in mirror
reading compared with reading of plain text. Increased
activity following learning was observed in the left inferior
temporal cortex, while decreased activity was observed in
the lateral occipital and superior parietal cortex. Repetition
priming has generally been associated with decreased neural
activity for repeated compared with novel stimuli (Squire
et al., 1992; Demb et al., 1995; Gabrieli et al., 1996) and
we found such priming-related decreases in a number of
regions, including the left inferior temporal region that
exhibited a learning-related increase in activity, i.e. as this
region became more engaged in the task (evidenced by the
learning-related increase) it began to exhibit a greater priming
effect (evidenced by the priming-related decrease). These
data were taken as preliminary evidence for common neural
substrates in skill learning and repetition priming; however,
the study did not include the conditions necessary to test this
view strongly.
In the present study we examined short-term repetition
priming, both before and after training on the mirror-reading
task, by presenting sets of new MR items and then presenting
the same items soon after (within 24 s). This design allowed
us to examine directly how priming changed as a function
of skill learning. We also included a set of repeated items
during the training session in order to identify regions
showing long-term repetition priming effects. Thus, we were
able to determine whether short-term priming and long-term
priming had common neural substrates.
What is learned in mirror reading?
In our previous study (Poldrack et al., 1998) we found
decreasing activation with learning in regions of the right
dorsal visual path (superior parietal cortex) and increasing
activation in the left ventral visual path (inferior temporal
cortex). These changes were interpreted as reflecting a shift
from visuospatial transformation to direct recognition of the
MR stimuli, but there were no manipulations in the previous
study to test directly the nature of the processes underlying
these changes. There are, for example, several possible
explanations for the increasing inferior temporal activation
that are equally consistent with the previous data. First, the
increase in activation could reflect development of novel
representations for individual MR letters [consistent with the
results of Masson (1986)]. A second possibility is that
increase in activation reflected processes that were letterspecific but not specific to the MR typography, such as skill
in the recognition of transformed versions of particular letters.
Another possibility is that the increase reflected general
visual processing procedures that were specific to the MR
typography (as proposed by Kolers, 1975), but not letterspecific as argued by Masson (Masson, 1986). A fourth
possiblity is that the increase reflected processes that are
neither letter-specific nor specific to the MR typography.
The present study included two control conditions with
Neural basis of skill learning and priming
69
Fig. 1 Depiction of stimulus types.
different transformed typographies [inverted-reversed (IR)
and spelled-backwards (SB); see Fig. 1] to allow investigation
of the specificity of learning in the mirror-reading task.
Learning that is specific to the MR typography should result
in changes in activation for only MR items, whereas nonspecific changes in processing should result in equivalent
learning-related changes for all typographies. Differences in
activity between SB and IR items provide evidence about
the degree to which learning in the task is specific to
visuospatial transformation.
Material and methods
Participants
Sixteen volunteers from the Stanford community (seven
males, nine females; mean age 20.3 years, SD 1.7) participated
in the study. All subjects were right-handed [based on the
Briggs and Nebes (1975) handedness inventory] and were
native speakers of English. Informed consent was obtained
for each participant prior to the experiment in a manner
approved by the Stanford University Human Subjects
Committee, which also approved the study, and participants
were screened for any possible contraindications prior to
entering the MR suite.
Materials
For the mirror-reading scans, a list of 1584 words was drawn
from the Kucera and Francis database (Kucera and Francis,
1967), with word frequency ranging from 10 to 100
occurrences (mean 29.8, SD 20.9) and word length from five
to eight letters (mean 6.5, SD 1.1). For each word, a matched
pseudoword was created by changing one consonant in the
word, with the constraint that the word remained
pronounceable. Words from this list were randomly assigned
to conditions in the experiment, with the constraint that word
frequency and word length did not differ between conditions.
Experimental design
The study consisted of two fMRI scanning sessions with five
training sessions in between. Figure 1 presents an overview
of the stimuli used in the fMRI scans and training and Fig. 2
presents a schematic representation of the experimental
design. In the first fMRI session, subjects participated in
three functional scans. The first scan, performed as part of a
Fig. 2 Depiction of study design.
separate study, is not reported here. In each of the two
following scans, subjects made lexical decisions based on
four different types of stimuli; the order of these scans and
the order of conditions within the scans were counterbalanced
across subjects. In one scan (Mirror Reading I), the stimuli
consisted of MR (new items, first presentation), MR repeated
(second presentation of MR items), MR practised (items to
be practised during training sessions) and plain text. In the
other scan (Mirror Reading II), the stimuli consisted of MR,
inverted-reversed, spelled backwards and plain text (items in
all conditions in Mirror Reading II were unique). A cue (‘⬍’
or ‘⬎’) was presented laterally to the stimulus 200 ms before
each stimulus in the Mirror Reading II scan to alert the
subject to the direction from which they should read, so that
items in the spelled-backward condition were not read as nonwords. In both mirror reading scans, items were presented for
2000 ms with an 800 ms interstimulus interval and subjects
were asked to press a response key as quickly as possible if
the item was a real word. Each mirror reading scan consisted
of four cycles through each of the four conditions and lasted
a total of 460.8 s (during which 160 images were collected);
an additional four images were collected at the beginning of
each scan and discarded. The order of the two scans (Mirror
Reading I and II) was counterbalanced across subjects.
Following the first fMRI session, subjects returned for five
training sessions over 2 weeks. In each session, the subject
was presented with four blocks of 96 MR items; half of the
items were pseudowords and half were real words. In each
block, 48 of the items were unique and were seen only once
during training, whereas 48 were repeated from the MR
practised condition in fMRI session 1; these repeated items
appeared in every block for a total of 20 repetitions. Unlike
the scanning session, in which subjects had only 2800 ms to
perform the task on each item, the stimulus remained on the
screen until a response was made during the training sessions.
Subjects pressed one button if the item was a word and a
different button if the item was a non-word. This differed
70
R. A. Poldrack et al.
from the go/no-go response that was peformed during fMRI
scanning.
Two weeks after the first fMRI scan and following
completion of all training sessions, subjects returned for a
second fMRI session. The scans performed in this session
were identical in design to those performed in session 1,
with the exception that all items were new (except those in
the MR practised condition, which were repeated across the
first scan session and all training sessions). Order of task
presentation within each scan was counterbalanced across
subjects and each item presented during scanning appeared
equally often in fMRI sessions 1 and 2 across subjects.
Stimuli were generated by a Macintosh computer and
back-projected onto a screen located above the subject’s neck
via a magnet-compatible projector. The projected image
appeared on a mirror mounted above the subject’s head.
Subjects responded by pressing a switch with the right index
finger and responses were collected by a computer interfaced
to the switch using the PsyScope button box.
MRI data acquisition
Imaging was performed on a 1.5 T GE Signa whole-body
MRI system. A prototype birdcage receive-only head coil
was used for signal reception. Head movement was minimized
using a bite-bar formed with the subject’s dental impression.
The onset of scanning was controlled by the experimental
presentation program via a pulse output for precise
synchronization of scanning and stimulus presentation.
Sixteen contiguous axial images were imaged (6 mm
thickness) parallel to the AC–PC (anterior–posterior
commissure) line. A T2*-sensitive gradient echo spiral pulse
sequence (Glover and Lai, 1998) was used for functional
imaging with parameters of repetition time ⫽ 1440 ms, echo
time ⫽ 40 ms, flip angle ⫽ 80°, field of view ⫽ 24 cm and
two spiral interleaves (for a total time per image of 2880 ms
and in-plane resolution of 2.9 mm). T1-weighted spin-echo
images were collected for the same set of slices. A highresolution three-dimensional SPGR (spoiled gradientrecalled) volume was also collected for use in spatial
normalization.
MRI data analysis
Functional data were reconstructed by gridding to a Cartesian
matrix before two-dimensional Fourier transform and a
correction for blurring resulting from off-resonance
(Irarrazabal et al., 1996) was applied. After reconstruction,
functional images were motion-corrected using AIR 3.0 with
interpolation to 3 mm cubic voxels. Images were then spatially
normalized to the MNI305 space (which approximates the
stereotactic space of Talairach and Tournoux, 1988) with
SPM99 using a 12 parameter affine transformation followed
by non-linear warping using 7⫻8⫻7 discrete cosine basis
functions. Data were smoothed with a Gaussian filter (8 mm
full-width at half-maximum).
Data were analysed in SPM99 using an initial analysis
treating subjects as a fixed effect (i.e. including all images
for each subject). One subject was excluded from the analysis
of Mirror Reading I and two subjects were excluded from
the analysis of Mirror Reading II because extensive artefacts
were evident in the individual subject analyses. Global signal
variation was removed using proportional scaling and lowfrequency signal components were removed by including
low-frequency covariates in the design matrix. Regions were
identified in which activity was either significantly greater
(i.e. activation) or significantly less (i.e. deactivation) during
all of the transformed text conditions compared with the
plain text condition across both scans in each scanning
session, providing an estimate of active regions that is not
biased towards any of the particular conditions. This analysis
was performed separately across the two sessions to avoid
exclusion of regions exhibiting learning-related changes.
Regions of significant activation were first identified by
thresholding the statistical parametric map at P ⫽ 0.001
(uncorrected for multiple comparisons) along with a cluster
extent threshold of at least 10 voxels. The activations
identified by this analysis were characterized further
according to the theory of Gaussian random fields in order
to provide a correction for multiple comparisons (P ⫽ 0.05).
Multiple maxima within a cluster of activation were identified
if they were at least 8 mm apart.
Because global signal normalization can result in spurious
deactivations if the global signal level is correlated with the
task, we performed a correlation analysis to rule this out so
that deactivations and session⫻condition interactions could
be confidently interpreted. For each session and subject,
the correlation was measured between a delayed boxcar
representing the task conditions and the global signal level
for Mirror Reading I. Two such analyses were performed
using delayed boxcar reference functions, one representing
only new MR and plain text, and another representing all
MR conditions compared with plain text. These correlations
were compared with zero using a one-sample t test across
subjects. There was no significant correlation between global
signal and the task function (rs ranging from –0.09 to
0.06, Ps ⬎ 0.1). This suggests that the deactivations and
session⫻condition interactions observed in this study reflect
true signal changes rather than artefacts of global signal
normalization.
The regions identified in this initial fixed-effect analysis
were then used to perform region-of-interest (ROI) analyses
treating subjects as a random effect [using repeated measures
analysis of variance (ANOVA) with the Huyhn–Feldt
correction for non-sphericity]. The ROI was determined using
contrasts that were orthogonal to those examined in the ROI
analysis to ensure unbiased comparisons. For each maximum
voxel location identified in the unbiased comparison, the
adjusted magnetic resonance signal was summed over that
voxel and all voxels that were connected to that voxel (using
an 18-connectivity scheme) in which there was significant
activation in the unbiased analysis (P ⬍ 0.001). This resulted
Neural basis of skill learning and priming
71
Fig. 3 Behavioural data during scanning and training. In the bottom row open boxes ⫽ new non-words, open circles ⫽ practised nonwords, filled boxes ⫽ new words, filled circles ⫽ practised words. Error bars reflect within-subject standard error.
in a maximum of 19 voxels being included in each ROI.
Specific comparisons between conditions were performed
using linear contrasts.
scanning were unavailable for two of the 16 subjects due to
malfunction of the button box. Correct responses for each scan
were analysed using a 2 (session) ⫻4 (condition) repeated
measures ANOVA with the Huyhn–Feldt correction for nonsphericity.
Results
Behavioural results
Mirror Reading I
Response times and accuracy for subjects during fMRI
scanning are presented in Fig. 3. Behavioural data during
For response times, there were significant main effects of
session and condition, along with a significant interaction
72
R. A. Poldrack et al.
(all Ps ⬍ 0.001). Paired comparisons (contrasts) were used
to examine differences between conditions. In both sessions,
MR items were read more slowly than plain text (Ps ⬍
0.001) and new MR items were read more slowly than
repeated MR items (Ps ⬍ 0.001). Performance on new MR
items was faster in session 2 than session 1 (P ⬍ 0.001),
whereas there was only a marginally significant difference
between sessions 1 and 2 for plain text (P ⫽ 0.09). There
was a larger absolute increase for MR compared with plain
text, but the proportional change in response time was
similar (13.0% speed-up for MR versus 11.7% speed-up for
plain text). Performance on practised MR items (which were
seen 20 times during training) was faster in session 2 than
in session 1 (P ⬍ 0.001) and did not differ from plain text
in session 2 (P ⫽ 0.16).
For accuracy, there were main effects of session (P ⫽
0.015) and condition (P ⬍ 0.001) and a significant interaction
(P ⬍ 0.001). Planned comparisons showed that accuracy was
greater for plain than for new MR items in both sessions 1
and 2 (Ps ⬍ 0.001). There was no significant difference in
accuracy between new and repeated MR items in either
session 1 or session 2 (Ps ⬎ 0.1). Accuracy on MR items
increased from session 1 to session 2 (P ⫽ 0.003), but there
was no difference in accuracy between sessions for plain text
(P ⫽ 0.69). Accuracy on practised items was greater in
session 2 than session 1 (P ⬍ 0.001), and did not differ from
accuracy on plain text items in session 2 (P ⫽ 0.63).
Mirror Reading II
For response times, there was a significant main effect of
condition only (P ⬍ 0.001); the effect of session (P ⫽ 0.41)
and the interaction (P ⫽ 0.35) were not significant. Responses
to all classes of transformed items were slower than plain
text in both sessions 1 and 2 (Ps ⬍ 0.001). There was no
significant difference between IR and MR items (P ⫽ 0.80)
in session 1, whereas responses to SB items were slower
than MR items (P ⫽ 0.04). In session 2 the difference
between MR and IR (P ⫽ 0.05) and the difference between
MR and SB (P ⫽ 0.04) were both significant. None of the
conditions exhibited significant changes in response time
between sessions (Ps ⬎ 0.18), although inspection of the
results suggests that responses to MR and SB items became
faster with practice, whereas responses to IR items became
slower with practice. The fact that there was no significant
decrease from session 1 to session 2 in MR response times
(whereas such a decrease did occur for the same condition
in Mirror Reading 1) suggests that the inclusion of additional
spatially transformed conditions or the use of the directional
cue may have affected performance on MR items in Mirror
Reading II.
For accuracy, there was a significant effect of session
(P ⬍ 0.001) and a significant interaction (P ⫽ 0.003); the
effect of session was not significant (P ⫽ 0.25). Performance
on all transformed conditions was less accurate than plain
items in both sessions (Ps ⬍ 0.001). Accuracy increased
from session 1 to session 2 for MR (P ⫽ 0.05) and IR
(P ⫽ 0.002), whereas there was no such change for SB
items (P ⫽ 0.21). Accuracy on plain text items decreased
significantly from session 1 to session 2 (P ⫽ 0.04).
Training
Training data for all 16 subjects were analysed separately
for response time (correct responses only) and accuracy using
a four condition (new word, new non-word, repeated word,
repeated non-word), 20 (training block) repeated measures
ANOVA; these data are presented in Fig. 3. For response
times, there were significant main effects of condition and
training block and a significant interaction (all Ps ⬍ 0.001).
Response times decreased with training for all conditions,
with repeated items exhibiting a greater speed-up. For
accuracy, there were significant main effects of condition (P
⬍ 0.001) and training block (P ⬍ 0.001) and a significant
interaction (P ⫽ 0.005). Performance on non-words was near
ceiling, suggesting a speed–accuracy trade-off between words
and non-words. However, the increase in accuracy over
training rules out a speed–accuracy trade-off explanation for
the decreased response times over training.
fMRI results
Results from the fixed-effect analysis are rendered onto a
standard brain in Fig. 4 and are presented on averaged
anatomical slices in Fig. 5. It should be noted that the slice
prescription in some subjects resulted in a truncation of the
image volume at approximately Z ⫽ 45. Thus, data were not
available from the most superior aspects of the parietal and
frontal cortices.
Mirror reading versus plain text
Stereotactic locations for activations during reading of novel
MR items compared with plain text in each session are
presented in Table 1. Mirror reading in session 1 (pretraining) was associated with extensive activation along both
the dorsal and ventral visual streams, including the occipital,
parietal and inferior temporal regions. In addition, there was
activation throughout the posterior left prefrontal cortex,
including the premotor and inferior frontal cortices, and less
extensive activation in the right prefrontal cortex. Activation
was also found in the right cerebellum and right basal ganglia
(putamen/globus pallidus). Mirror reading in session 2 (posttraining) engaged a similar set of regions.
Learning-related changes
In order to examine directly changes related to learning,
activation for mirror reading compared with plain text was
compared across the pre-training and post-training scanning
sessions (by testing for a condition ⫻session interaction).
These results are presented in Table 2 and are illustrated in
Neural basis of skill learning and priming
Fig. 4 Rendering of activation maps from fixed-effects analysis for mirror-reading, learning-related changes, short-term priming and
long-term priming.
73
74
R. A. Poldrack et al.
Fig. 5 Projection of activiation maps from fixed-effects analysis for mirror-reading and learning-related changes on averaged anatomical
slices.
Fig. 4. Learning-related increases were found in the right
cerebellum, left inferior frontal/premotor cortex, left inferior
temporal/fusiform regions, anterior cingulate and in the tail
of the caudate nucleus.
Only two regions showed significant decreases in activation
in the fixed-effects analysis related to skill learning in
the mirror-reading task: the left cerebellum and the left
hippocampus. However, the superior parietal region that
exhibited a learning-related decrease in the previous study
(Poldrack et al., 1998) was not fully included in the imaging
window for this analysis (because of missing data for some
subjects due to the slice prescription). An additional fixedeffect group analysis was run on the eight subjects for whom
the slice prescription covered the superior parietal cortex (i.e.
with data extending to at least Z ⫽ 56), in order to determine
whether a decrease occurred for those subjects. However, no
significant decrease was found in the superior parietal region
in this analysis.
Short-term repetition priming
Regions exhibiting significant priming-related reductions in
activation (novel MR ⬎ repeated MR) are presented in Fig. 4
and their stereotactic locations are presented in Table 3. In
session 1 (pre-training), priming-related reductions were
evident bilaterally along the ventral visual pathway, including
the inferior occipital, fusiform and parahippocampal cortices,
with activation extending into the hippocampus proper in the
left hemisphere. Following training, reductions in ventral
path activation were still evident. In addition, extensive
priming-related reductions became evident in the left inferior
frontal and premotor regions.
Long-term repetition priming
Long-term priming (measured as the difference between
novel and practised MR items in session 2) was associated
Neural basis of skill learning and priming
75
Table 1 Activations for new MR items compared with plain text items in Mirror Reading I scans
Location
Session 1 (pre-training)
L intraparietal sulcus/occipital (BA 7/18/19)
L inferior frontal (BA 44/45)
R superior cerebellum
L inferior temporal (BA 37)
R intraparietal/inferior parietal (BA 7/40)
L orbitofrontal cortex
R parahippocampal cortex
R cerebellum
Brainstem
R orbitofrontal cortex
R putamen/GP
R anterior thalamus
R frontal operculum (BA 47)
Session 2 (post-training)
L inferior frontal (BA 44/45) (cluster also included L caudate)
L intraparietal sulcus/occipital/inferior temporal (BA 7/18/19/37)
R inferior occipital/intraparietal sulcus/superior cerebellum (BA 18/19/7)
Brainstem
R inferior frontal (BA 44/45)
L parahippocampal
R hippocampus
x
y
z
Cluster extent
Max. t value
–24
–45
39
–45
36
–12
21
30
3
12
24
12
30
–69
6
–72
–54
–42
60
–30
–51
–27
60
9
0
30
45
24
–21
–18
42
–12
–6
–21
–18
–9
3
3
–3
1113*
695*
494*
65*
40
12
32
41
76*
13
28
11
13
9.43†
7.97†
7.72†
6.26†
5.36†
4.58†
4.45†
4.39
4.38
4.16
3.70
3.67
3.39
–48
–24
42
–6
48
–15
24
0
–63
–78
–27
9
–51
–27
36
45
–15
–21
27
3
–3
3037*
2875*
‡
277*
147*
85
18
12.62†
9.05†
8.87†
6.46†
6.35†
5.27†
4.19
R ⫽ right; L ⫽ left. P ⬍ 0.001 uncorrected, extent of at least 10 voxels. *Significant at cluster-level corrected P ⬍ 0.05; †significant at
voxel-level corrected P ⬍ 0.05. ‡Activation in the left and right occipitoparietal regions comprised one larger cluster; we report the right
hemisphere maximum, although it did not comprise a separate cluster.
Table 2 Regions exhibiting significant learning-related changes in activity
Location
Learning-related increase
R superior cerebellum
L inferior frontal/premotor (BA 44/6)
L inferior temporal (BA 37)
L fusiform (BA 19/37)
L anterior cingulate
R inferior occipital/fusiform (BA 19/37)
R tail of caudate
R anterior cingulate
L cingulate sulcus
R lingual gyrus (BA 19)
Learning-related decrease
L cerebellum
L hippocampus
x
y
z
Cluster extent
Max. t value
24
–42
–54
–24
–9
15
9
15
–18
12
–60
3
–60
–66
18
–78
–15
12
0
–51
–24
39
–15
–9
42
–9
15
42
45
–3
70*
137*
35
17
18
59
48
18
20
30
6.15†
5.33†
4.41†
4.33
4.18
4.12
3.96
3.86
3.77
3.75
–15
–27
–63
–12
–21
–18
35
17
4.94†
4.06
P ⬍ 0.001 uncorrected, extent of at least 10 voxels. *Significant at cluster-level corrected P ⬍ 0.05; †significant at voxel-level corrected
P ⬍ 0.05.
with extensive reductions in activation compared with new
MR items. These regions (shown in Fig. 4 and listed in
Table 3) included bilateral inferior frontal and premotor
cortex, bilateral intraparietal and occipital cortex, bilateral
basal ganglia (caudate/putamen) and the anterior cingulate.
Mirror reading of practised items was compared with
reading of plain text, in order to determine whether differences
in neural processing persisted even when response times and
accuracy did not differ from plain text. This analysis found
regions of activation in the precuneus, orbitofrontal cortex
and right inferior parietal cortex. Thus, the occipital, parietal
and frontal activations apparent during reading of new MR
items were not evident during reading of highly trained MR
items compared with plain text.
ROI analysis of priming effects
In order to examine more directly priming effects in the
context of skill learning, magnetic resonance signal was
examined in each of the ROIs based upon all transformed
conditions compared with plain text; these data were analysed
using a 2 (session)⫻4 (condition: novel MR, repeated MR,
practised MR and plain text) repeated measures ANOVA. A
significant session⫻condition interaction (P ⬍ 0.05) was
76
R. A. Poldrack et al.
Table 3 Regions exhibiting significant priming-related reductions in activity
Location
Short-term priming—pre-training
Orbital frontal*
L hippocampus/parahippocampal cortex/fusiform gyrus
R parahippocampal cortex/fusiform gyrus
L inferior occipital (BA 18/19)
White matter
Short-term priming—post-training
L inferior frontal/premotor (BA 44/6)
L parahippocampal
Orbital frontal*
R inferior occipital
L premotor (BA 6)
R inferior occipital
L cerebellum
L intraparietal sulcus (BA 7)
L lateral occipital (BA 18/19)
L inferior frontal (BA 45/47)
Long-term priming (post-training)
L inferior frontal/premotor (BA 6/44/45/47)/
caudate/putamen
L intraparietal sulcus (BA 7)/occipital (BA 18/19)
Anterior cingulate
R intraparietal sulcus (BA 7)/occipital (BA 18/19)
R frontal operculum (BA 44/47)/caudate/putamen
L inferior frontal/premotor (BA 6/44)
Brainstem
x
y
z
Cluster extent
Max. t value
–21
–39
33
–21
24
36
–42
–42
–78
–48
–9
–9
–6
–9
18
305†
687†
146†
168†
10
6.12‡
4.65‡
4.39
4.05
3.37
–45
–12
3
24
–30
15
–21
–18
–24
–54
3
–48
48
–84
–6
–72
–75
–75
–81
30
24
6
–15
0
45
–9
–18
42
18
18
234†
97†
413†
74†
19
19
20
24
10
11
5.47‡
5.26‡
4.76‡
4.26
4.00
3.73
3.70
3.62
3.49
3.28
–42
3
27
1536†
12.37‡
–24
–6
27
30
48
–3
–63
15
–66
27
9
–27
45
42
42
0
27
–18
1177†
282†
964†
409†
122†
16
9.55‡
7.73‡
7.27‡
5.84‡
5.48‡
3.70
P ⬍ 0.001 uncorrected, extent of at least 10 voxels. *This activation occurred in a region of signal dropout due to magnetic
susceptibility artefact; †significant at cluster-level corrected P ⬍ 0.05; ‡significant at voxel-level corrected P ⬍ 0.05.
found in eight regions. The data from these ROIs are presented
(as percentage signal change compared with plain text)
in Fig. 6.
Long-term priming effects (i.e. less activity for practised
compared with new MR items) occurred in all ROIs. Shortterm priming effects (i.e. reduced signal change for repeated
compared with novel MR stimuli) were not significant in
any of the ROIs prior to training (although trends were
visible in the left occipital cortex), whereas short-term priming
effects were significant following training in the left inferior
frontal, left intraparietal and posterior left inferior occipital
regions, with visible trends toward such priming in the
caudate nucleus and anterior left inferior occipital cortex.
The right frontal operculum exhibited long-term priming but
no evidence of either skill learning or short-term priming in
either session.
Effects of different spatial transformations
The brain regions engaged by different visuospatial transformations (in Mirror Reading II) were examined using contrasts to compare brain activity arising from items with those
transformations. When compared with reading of plain text in
session 1, reading of MR, IR and SB items all engaged a set of
brain regions similar to those engaged by mirror reading in
Mirror Reading I (see Fig. 4). For this reason, we focused on
those regions that exhibited differential response between the
different transformations. These regions are shown in Fig. 4
and their stereotactic locations are listed in Tables 4 and 5.
Compared with MR items, there was little additional
activation for items spelled backwards; in session 1 there
was activation in the right inferior frontal cortex and in
session 2 there was activation in the left cerebellum. There
were a number of regions that exhibited greater activation
for MR compared with SB items. In both sessions, there
was activation in the posterior parahippocampal/lingual gyri
bilaterally. In session 1, there was additional activation in
the right hippocampus, whereas a number of regions were
activated in session 2, including the left dorsolateral prefrontal
cortex, left anterior fusiform gyrus, left cerebellar nuclei,
cingulate cortex and left inferior parietal cortex (additional
regions listed in Table 4).
In the comparison of IR items to MR items, the bilateral
inferior occipital/temporal cortices and right cerebellum were
active in both sessions (stereotactic locations are listed in
Table 5). Additionally, in session 1 there was activation for
IR items in the right frontal operculum, whereas in session
2 there was activation in the intraparietal cortex bilaterally,
right superior parietal cortex and left cerebellum. For MR
compared with IR items, the right lingual/parahippocampal
cortex was active in both sessions; additionally, the left
occipital and left inferior frontal cortex was active in session
1 and the left cerebellar nuclei and precuneus were active in
session 2.
Neural basis of skill learning and priming
77
Fig. 6 ROI analysis of repetition priming effects. Open columns ⫽ session 1; stippled columns ⫽ session 2; inf ⫽ inferior; ant ⫽
anterior; L ⫽ left; R ⫽ right. Error bars reflect within-subject standard error. Asterisks denote significant difference from MR items
(P ⬍ 0.05).
ROI analysis of spatial transformation effects
In order to determine the degree to which learning-related
effects were specific to the MR font, magnetic resonance
signal for each condition in Mirror Reading II was examined
in each of the regions independently identified in the analysis
of learning-related effects (listed in Table 2). These data
were analysed using a 2 (session)⫻4 (condition: MR, IR,
SB and plain text) repeated measures ANOVA. Two regions
in this analysis exhibited significant condition⫻session
interactions (P ⬍ 0.05): the right inferior occipital/fusiform
cortex (which exhibited a learning-related increase) and the
left hippocampus (which showed a learning-related decrease).
Signal from these regions is displayed in Fig. 7. The left
fusiform cortex was also included because of a priori interest
based upon a previous study (Poldrack et al., 1998), although
the session⫻condition was only marginally significant in
this region (P ⫽ 0.13). In each of these regions, learning
resulted in similar increases in activity for each of the spatial
transformations. There was no evidence of changes that were
specific to MR text.
Discussion
We examined neural changes related to skill learning and
repetition priming in a mirror-reading task using fMRI. The
results indicated that learning was associated with increased
activation in left inferior temporal, left inferior prefrontal,
striatal and right cerebellar regions and with decreased
activity in the left hippocampus and left cerebellum. These
results partially replicate the findings of our previous study
78
R. A. Poldrack et al.
Table 4 Regions exhibiting significant activity for SB compared with MR stimuli
Location
Session 1: SB ⬎ MR
R inferior frontal (BA 45/47)
Session 2: SB ⬎ MR
L cerebellum
Session 1: MR ⬎ SB
R lingual/parahippocampal cortex
L lingual/parahippocampal cortex
White matter
R hippocampus
Session 2: MR ⬎ SB
L dorsolateral prefrontal cortex (BA 9/46)
L fusiform
L cerebellar nuclei
Anterior cingulate
L inferior parietal (BA 39/40)
R lingual/parahippocampal cortex
Posterior cingulate
L orbitofrontal‡
R inferior parietal (BA 39/40)
R orbitofrontal
R fusiform
L lingual/parahippocampal cortex
x
y
z
Cluster extent
Max. t value
48
27
–3
29
4.79*
–6
–81
–18
17
4.29
9
–9
3
27
–48
–45
21
–24
–6
–6
9
–3
13
29
18
19
3.76
3.69
3.63
3.51
–21
–42
–12
–15
–45
12
–12
–30
45
12
33
–12
27
–30
–48
45
–24
–45
–39
36
–30
48
–54
–51
42
–21
–27
6
45
0
45
–9
24
0
–18
3
45†
29
68†
72†
60†
119†
218†
16
13
11
15
14
4.59
4.30
4.27
4.23
4.22
4.18
4.10
3.72
3.70
3.69
3.56
3.39
P ⬍ 0.001 uncorrected, extent of at least 10 voxels. *Significant at voxel-level corrected P ⬍ 0.05; †significant at cluster-level corrected
P ⬍ 0.05. ‡This activation occurred in the region of signal dropout due to magnetic susceptibility artefact.
Table 5 Regions exhibiting significant activity for IR compared with MR stimuli
Location
Session 1: IR ⬎ MR
R inferior occipital/temporal (BA 37/19)
R frontal operculum (BA 45/47)
R cerebellum
L inferior occipital/temporal (BA 37/19)
Session 2: IR ⬎ MR
R inferior occipital/temporal (BA 37/19)
R intraparietal/inferior parietal
L inferior temporal (BA 37)
R superior parietal (BA 7)
L cerebellum
R cerebellum
Brainstem
L intraparietal cortex
Session 1: MR ⬎ IR
R lingual/parahippocampal
L occipital (BA 17/18)
L inferior frontal (BA 44/45)
Session 2: MR ⬎ IR
Orbitofrontal cortex‡
R lingual/parahippocampal
L cerebellar nuclei
Precuneus
x
y
z
Cluster extent
Max. t value
42
48
30
–33
–66
24
–45
–72
–21
0
–21
–18
106*
60*
13
53*
5.63†
4.26
3.93
3.90
42
39
–39
24
–9
18
0
–15
–66
–36
–57
–78
–81
–78
–21
–78
–21
42
–21
42
–21
–21
–15
42
101*
87*
190*
84*
25
15
16
10
5.52†
5.14†
4.97†
4.95†
4.34
4.30
3.86
3.80
9
–12
–51
–45
–90
24
–9
–3
24
28
13
26
3.93
3.67
3.57
–6
9
–15
0
48
–45
–48
–57
–12
–3
–27
33
37
16
26
57*
4.05
4.00
3.99
3.84
P ⬍ 0.001 uncorrected, extent of at least 10 voxels. *Significant at cluster-level corrected P ⬍ 0.05; †significant at voxel-level corrected
P ⬍ 0.05. ‡This activation occurred in the region of signal dropout due to magnetic susceptibility artefact.
(Poldrack et al., 1998), and extend those results by
demonstrating the involvement of striatofrontal circuits in
skill learning on this task. Short-term repetition priming was
associated with reduced activity in many of the regions active
during mirror reading and extensive item-specific practice
resulted in a virtual elimination of activity in those regions.
Neural basis of skill learning and priming
79
Fig. 7 ROI analysis of spatial transformation effects. Open columns ⫽ session 1; stippled columns ⫽ session 2; inf ⫽ inferior. Error
bars reflect within-subject standard error.
Nearly all of the regions exhibiting significant learning-related
changes also exhibited increased priming-related reductions,
suggesting common neural substrates for priming and skill
learning in this task. Comparison of MR items with other
transformed typographies showed that the learning-related
changes associated with skill learning are not specific to the
MR typeface, extending equally to IR and SB items.
Neural mechanisms of skill learning
Learning in the mirror-reading task was associated with
increased activation in a number of regions. Increasing
activity in the left prefrontal and right cerebellar regions may
reflect increased engagement of lexical search and/or retrieval
systems necessary to perform the lexical decision task. It is
unlikely that these changes reflect duty cycle or total timeon-task (Poldrack, 2000) because response time decreased
from session 1 to session 2. Rather, the increase in the frontalcerebellar system may reflect increased lexical processing that
is a consequence of increasingly accurate decoding of the
transformed stimuli. Early in training, most of the time on
task is spent on visually decoding the transformed stimuli
(because the amount of time available to perform the task is
limited), whereas later in training a greater proportion of that
time on task can be spent on lexical processing.
The left inferior temporal and fusiform cortex also
exhibited increased activation with training on the mirrorreading task. These increases were previously attributed to
the development of novel representations of the MR letters
(Poldrack et al., 1998). However, in the present study there
was a similar learning-related increase in activation for MR,
IR and SB stimuli (Fig. 7), which suggests that learning
is specific neither to individual letters nor to particular
typographies. This finding is consistent with several
behavioural studies, which have found (contrary to Masson,
1986) that learning in the mirror-reading task is not specific
to the particular typography encountered during training
(Horton, 1985; Tardif and Craik, 1989; Horton and McKenzie,
1995). These studies have suggested instead that facilitation
on the mirror-reading task is based upon lexical and/or
semantic representations instead of orthographic (letter form)
representations. Based upon these results and other relevant
findings, we hypothesize that the learning-related increase in
left inferior temporal and fusiform regions found in the
present study and in that of Poldrack and colleagues (Poldrack
et al., 1998) may reflect increased engagement of lexical/
phonological processes as learning progresses. There is
evidence that the inferior temporal region is engaged in
service of phonological processing in reading, particularly
for unfamiliar word-like stimuli; e.g. comparisons of visual
presentation of pseudowords compared with letterstrings have
demonstrated activation in this area (e.g. Frith et al., 1995;
Price et al., 1996). In addition, this region is activated
during the performance of phonological monitoring tasks
with auditory stimuli (Demonet et al., 1992, 1994; Zatorre
et al., 1996), suggesting that the region is involved in
phonological processing more generally. The increase in
inferior temporal activation in the present study may reflect
increased access to phonological representations by spatially
transformed stimuli. It is not, however, currently clear how
such increased access could generalize across the different
stimulus types. Alternatively, increased activation in this
region may reflect increased neural synchronization of lexical/
phonological processing with spatial transformation
processing occurring in the parietal cortex. Similar changes in
effective connectivity have been observed during associative
object-spatial learning (Buchel et al., 1999). Further work
is necessary to determine which of these interpretations
is correct.
Role of the striatum in non-declarative memory
Learning in the mirror-reading task was associated with
increased activation in the caudate nucleus. This finding
extends previous findings of basal ganglia activity associated
with motor skill learning (Seitz et al., 1990; Grafton et al.,
1995) and cognitive skill learning (Poldrack et al., 1999a).
These results are consistent with neuropsychological findings
in Huntington’s disease and Parkinson’s disease,
demonstrating impaired learning of motor skills (Heindel
et al., 1988, 1989), perceptual skills (Martone et al., 1984)
and cognitive skills (Saint-Cyr et al., 1988; Knowlton et al.,
80
R. A. Poldrack et al.
1996a). Together these findings suggest that the striatum is
a critical structure for skill learning, but its particular role
remains to be fully specified. A number of authors (Mishkin
et al., 1984; Knowlton et al., 1996a) have suggested that the
striatum may be involved in the formation of stimulus–
response associations (also called habit learning), whereas
we have previously suggested (Poldrack et al., 1999a) that
the striatum may play a critical role in mediating dynamic
shifts in the involvement of different processing systems as
learning progresses. The results of the present study, although
not conclusive, are more consistent with the process-switching
account than the habit-learning account. Learning-related
changes in the striatum were not specific to the MR
typography, as would be expected if striatal activation
reflected specific stimulus–response associations. However,
further studies are necessary to determine conclusively the
particular role of the striatum.
The role of the striatum may be segregated further on the
basis of its cortical connectivity. Cognitive skill learning has
been associated with activation in the head of the caudate
(Poldrack et al., 1999a), which is strongly connected to the
dorsolateral prefrontal regions that are also active during
cognitive skill learning (e.g. Yeterian and Pandya, 1991). In
the present study, perceptual skill learning was associated
with activation in the tail of the caudate nucleus, which is
reciprocally connected to visual processing regions including
the inferior temporal cortex (Saint-Cyr et al., 1990). Motor
skill learning has been primarily associated with activation
in the putamen (Seitz et al., 1990; Grafton et al., 1995),
which is extensively connected with the motor cortex. Thus,
the different territories of the striatum may support different
classes of skill learning, either through their different
corticostriatal inputs or their different outputs to frontal
cortex.
Relationship between skill learning and
repetition priming
The results of the present study provide neural evidence in
favour of the proposal that skill learning and repetition
priming may rely upon common cognitive and neural
processes within a particular task (Logan, 1990; Poldrack
et al., 1999b; Gupta and Cohen, 2001). All of the regions
identified in our ROI analysis as exhibiting skill-related
changes in activation also exhibited long-term repetition
priming effects, and a number of them also exhibited shortterm priming effects as well (with all but one region exhibiting
at least a trend for short-term priming). These data are plainly
inconsistent with the notion that skill learning and repetition
priming are independent.
This study represents, to our knowledge, the first finding
of significant repetition priming effects in the striatum. On
the face of it, this finding is inconsistent with previous
neuropsychological results, which had demonstrated normal
repetition priming effects in Huntington’s disease patients on
a mirror-reading task (Martone et al., 1984). However, the
design of that study may have encouraged subjects to use
declarative memory (which is relatively spared in early
Huntington’s disease). Mirror-reversed words were presented
in triplets and the order of the words was not varied when
the triplets were repeated. Thus, upon decoding the first word
the subject could explicitly remember the other two words
in the triplet, rather than decoding all three words. This
design feature also explains the impairment of repetition
priming in amnesic patients found by Cohen and Squire
(1980), who used the same triplet procedure. Further work
is necessary, however, to confirm this hypothesis and the
lexical decision procedure developed in the present task may
be a useful tool for studying mirror reading in a single-word
paradigm.
The medial temporal lobe and skill learning
The independence of skill learning from the medial temporal
lobe (hippocampus and related cortices) is well established
on the basis of neuropsychological studies of amnesic patients
(Cohen and Eichenbaum, 1993). Although activation was
observed in the right hippocampus and bilateral parahippocampal cortices during mirror reading, it is unlikely
that these regions were crucially involved in acquisition of
the mirror-reading skill. Instead, they may reflect responses
to the novelty of the spatially transformed stimuli (Stern
et al., 1996; Gabrieli et al., 1997). Consistent with this is the
finding that right hippocampal and bilateral parahippocampal
activation were greater for MR compared with spelledbackward stimuli, which have novel word forms but familiar
letter forms. These responses would probably support later
explicit remembering of the stimuli (Brewer et al., 1998;
Wagner et al., 1998), but are unlikely to support acquisition
of the mirror-reading skill.
There is some evidence from lesion studies in animals that
the medial temporal lobe and striatum may act competitively
during learning. For example, Packard and colleagues found
that rats with fornix lesions (which disconnect the
hippocampus) were better than control rats at acquiring a
win–stay maze skill, whereas animals with caudate lesions
were impaired at acquiring this skill (Packard et al., 1989).
These data and others (e.g. Eichenbaum et al., 1988) suggest
that the medial temporal lobe and striatum may compete for
control of behaviour during learning. There is also evidence
for such competition in humans as they learned to perform
a probabilistic classification task during fMRI scanning
(Poldrack et al., 1999a). The caudate nucleus was active
throughout learning, consistent with the deficient learning
observed on the task in patients with Huntington’s disease
(Knowlton et al., 1996b). The hippocampus was initially
deactivated compared with the baseline task, and that
deactivation increased during early learning but then
decreased later in learning (consistent with the timecourse of
learning on the task in amnesic patients; Knowlton et al.,
1994). This finding suggested that activity in the hippocampal
Neural basis of skill learning and priming
system was suppressed during skill learning, perhaps via
striatal or ventral tegmental projections to the hippocampus
(e.g. Gasbarri et al., 1994).
In the present study we found a similar learning-related
increase in deactivation of the left hippocampus, which was
similar for each of the stimulus transformations (Fig. 7).
Because performance was only imaged at two points in time,
we are unable to outline the complete timecourse of this
deactivation, but the finding converges with the results of
Poldrack and colleagues to suggest that the hippocampus
may be generally deactivated as a skill is acquired (Poldrack
et al., 1999a). This deactivation may reflect a dynamic
relationship between the declarative and non-declarative
memory systems, in which the two systems compete with
each other to control behaviour. In both the present study and
that of Poldrack et al. (1999a), the hippocampal deactivation
occurred in the anterior hippocampus, suggesting that the
deactivation may reflect a specific suppression of memory
retrieval processes (Gabrieli et al., 1997), whereas the
posterior parahippocampal regions involved in memory
encoding remain active. Thus, the acquisition of memory
traces may continue (explaining the ability of normal subjects
to explicitly remember the stimuli) while the retrieval of
these traces is suppressed during performanace. Further
work is necessary to confirm the generality of hippocampal
suppression during skill learning and to characterize its
functional importance.
Acknowledgements
We wish to thank Joseph Hsieh and Jennifer Burrows for
assistance in data collection and Skip Stebbins for helpful
comments on a draft of this paper. This research was
supported by the McDonnell-Pew Program in Cognitive
Neuroscience and by the National Institutes of Health
(P50NS26985 and AG12995).
81
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Received May 8, 2000. Revised July 27, 2000.
Accepted August 23, 2000