Rhythm and Beat Perception in Motor Areas

of the Brain

Jessica A. Grahn and Matthew Brett

Abstract
& When we listen to rhythm, we often move spontaneously rhythm type, which had integer ratio relationships between its
to the beat. This movement may result from processing of the intervals and regular perceptual accents. A subsequent func-
beat by motor areas. Previous studies have shown that several tional magnetic resonance imaging study found that these
motor areas respond when attending to rhythms. Here we rhythms also elicited higher activity in the basal ganglia and
investigate whether specific motor regions respond to beat in SMA. This finding was consistent across different levels of
rhythm. We predicted that the basal ganglia and supplementary musical training, although musicians showed activation in-
motor area (SMA) would respond in the presence of a regular creases unrelated to rhythm type in the premotor cortex,
beat. To establish what rhythm properties induce a beat, we cerebellum, and SMAs (pre-SMA and SMA). We conclude that,
asked subjects to reproduce different types of rhythmic in addition to their role in movement production, the basal
sequences. Improved reproduction was observed for one ganglia and SMAs may mediate beat perception. &

INTRODUCTION
of encoding each individual interval length. In non-
In most Western music, people perceive a regular, under- integer ratio sequences (e.g., 1:2.4:3.6) beats cannot be
lying pulse called the ‘‘beat’’ or ‘‘tactus’’ (Drake, Penel, used, and thus, sequence reproduction is worse. Sub-
& Bigand, 2000). Perception of the beat often causes jects may even ‘‘regularize’’ noninteger ratio sequences,
spontaneous synchronized movement, such as toe tap- reproducing them as integer ratios (Collier & Wright,
ping or head nodding. The presence of a beat also 1995; Essens, 1986).
affects the ability to remember and perform a rhythm. Others propose that integer ratios are insufficient to
For example, when a rhythm is presented with a beat induce a beat and that regularly occurring ‘‘perceptual
(the beat occurring as a series of external metronome accents’’ may also be necessary (Essens & Povel, 1985).
clicks), reproduction accuracy of the rhythm improves Accents cause a particular note to feel more prominent
(Patel, Iversen, Chen, & Repp, 2005; Essens & Povel, than surrounding notes, and previous work shows that
1985). The beat is emphasized in musical contexts by our attention is attracted to accented events (Drake,
nontemporal cues such as pitch, volume, and timbre, Jones, & Baruch, 2000; Jones & Pfordresher, 1997; Jones
yet even rhythms without these cues can induce listen- & Boltz, 1989). One common type of accent occurs in
ers to ‘‘feel’’ a beat internally (Brochard, Abecasis, music, where louder notes are perceived as more prom-
Potter, Ragot, & Drake, 2003). The beat is somehow inent. However, humans perceive a beat in rhythmic
conveyed solely by the temporal properties of the patterns even when no volume changes occur. In this
rhythm itself. It is still unclear, however, exactly what case, any perceptual accents that occur are due to the
temporal properties are critical for beat perception to temporal pattern. This is the type of accent investigated
spontaneously occur. One property that may be impor- in the current experiments: the type of accent that arises
tant for beat perception in rhythm is the presence of solely from the temporal context when all other factors
simple integer ratio relationships between intervals in (such as pitch or volume) are held constant. For exam-
a sequence (Sakai et al., 1999; Essens, 1986). For exam- ple, onsets not closely followed by other onsets in time
ple, a sequence containing intervals of 250, 500, and are perceived as accented (Parncutt, 1994), as is the
1000 msec has a 1:2:4 relationship between its intervals. final onset of two or three onsets in a row (Povel &
By using a beat that is the length of the smallest interval, Okkerman, 1981). The latter type of accent is present
the sequence can be encoded in terms of beats, instead in the Overture to William Tell (da da dum, da da dum,
da da dum dum dum . . .) on the ‘‘dum’’ of each ‘‘da
da dum.’’ If perceptual accents occurring at regular
MRC Cognition and Brain Sciences Unit, Cambridge, UK temporal intervals are necessary to feel the beat, then

D 2007 Massachusetts Institute of Technology Journal of Cognitive Neuroscience 19:5, pp. 893–906
sequences with this property should be reproduced if certain brain areas responded to perception of a beat
more accurately (Essens, 1995). (induced by the temporal structure of the rhythms).
Perceptual accents have not always been considered Beat perception may require a temporal representa-
in previous research (Sakai et al., 1999). Thus, enhance- tion or level of processing that is more complex than
ment in integer ratio sequence performance may be due that required for the more basic timing of individual
to some sequences in that condition that also had intervals. Given that the basal ganglia and SMA are not
regular perceptual accents. The role of perceptual ac- only involved in attention to time (Coull et al., 2004),
cents and integer ratios in rhythm reproduction is but are critical to temporal sequencing (Shima & Tanji,
examined in our first experiment. Subjects listened to 2000; Brotchie, Iansek, & Horne, 1991) and predict-
and then reproduced rhythms that contained either able, internally generated movements (Cunnington,
integer ratios or noninteger ratios and regular or ir- Windischberger, Deecke, & Moser, 2002; Freeman, Cody,
regular perceptual accents. A follow-up functional mag- & Schady, 1993), we hypothesize that they are the most
netic resonance imaging (fMRI) study used the same likely candidate areas for the detection or generation of
rhythms to investigate neural activity during rhythm an internal beat.
perception. Perception and production are likely to rely
on similar neural mechanisms, as previous behavioral
work demonstrates comparable difference thresholds METHODS
between timing during perception and production tasks Reproduction Experiment
(Ivry & Hazeltine, 1995). This behavioral similarity is
supported by neuroimaging experiments. Timing, dura- Subjects and Stimuli
tion perception, and rhythm perception and production Twenty subjects (9 men, 11 women) took part in the
tasks consistently activate the same brain areas, in- reproduction experiment. Subjects ranged in age from
cluding the premotor and supplementary motor areas 24 to 40 years, with an average age of 30 years. For each
(SMAs), cerebellum, and basal ganglia (Coull, Vidal, condition, 30 rhythmic sequences were constructed
Nazarian, & Macar, 2004; Lewis, Wing, Pope, Praamstra, from sets of five, six, or seven intervals. The intervals
& Miall, 2004; Pastor, Day, Macaluso, Friston, & in the metric rhythms were related by ratios of 1:2:3:4,
Frackowiak, 2004; Dhamala et al., 2003; Ferrandez et al., and the intervals in the nonmetric rhythms were related
2003; Nenadic et al., 2003; Ramnani & Passingham, 2001; by ratios of 1:1.4:3.5:4.5. The metric rhythms were of
Rao, Mayer, & Harrington, 2001; Schubotz & von Cramon, two types: simple and complex.
2001; Penhune, Zatorre, & Evans, 1998). Damage to these In the metric simple condition the intervals were
areas also impairs timing abilities (Molinari, Leggio, De arranged to induce a perceptual accent at the beginning
Martin, Cerasa, & Thaut, 2003; Mangels, Ivry, & Shimizu, of each group of four units (see Figure 1). Nothing was
1998; Halsband, Ito, Tanji, & Freund, 1993; Artieda, added to the sequence to produce the perceptual
Pastor, Lacruz, & Obeso, 1992). It is thus reasonably clear accents: they arise spontaneously from the temporal
that the timing processes that underlie both perception
and production involve these areas.
However, these brain regions are unlikely to subserve
identical timing functions. It has been suggested that
one distinction between commonly activated neural
structures may be their respective roles in ‘‘automatic’’
timing, defined as ‘‘the continuous measurement of
predictable subsecond intervals defined by movement,’’
and ‘‘cognitively controlled’’ timing, defined as the
‘‘measurement of suprasecond intervals not defined by
movement and occurring as discrete epochs’’ (Lewis &
Miall, 2003). Beat perception has characteristics of both
automatic and cognitively controlled timing, as the
length of the beat humans perceive can span from ap-
proximately 200 to 2000 msec (Parncutt, 1994; Warren,
1993), and the beat may or may not be marked by
movement. Accordingly, a different distinction may be
that certain motor areas are involved in extracting a
regular beat from incoming temporal stimuli. The role Figure 1. Schematic of sample stimuli. Vertical bars indicate interval
for motor areas in beat processing is supported by onset; ‘‘>’’ indicates where perceptual accents should be heard
(Povel & Okkerman, 1981). Perceptual accents can occur on final
findings of a direct link between movement and beat interval onsets of consecutive runs of two or three short intervals
perception in infants (Phillips-Silver & Trainor, 2005). and on onsets either preceded or followed by a relatively long period
Thus, the current studies were conducted to determine of no onsets (such as the first and last onsets of a sequence).

894 Journal of Cognitive Neuroscience Volume 19, Number 5

context, in accordance with the model of Povel and Experimental Design
Essens (Essens & Povel, 1985). The perceptual accents
Rhythms were presented diotically over headphones.
were there to induce subjects to hear a regular beat
On each trial a rhythm was presented three times, with
coinciding with the onset of each group of four units.
1100 msec between presentations. After the third pre-
Other work in our laboratory suggests that participants’
sentation, subjects tapped the rhythm from memory on
representation of the beat agree with the model’s accent
one key of a computer keyboard. Subjects had 4.5 sec to
predictions. Pilot data reveal that when participants are
tap the rhythm before the next one was presented.
asked to listen to rhythmic sequences and decide if a
Subjects practiced four trials, then completed three
beat is present, a beat is felt 90% of the time for metric
blocks of 30 trials each. There were 30 trials of each
simple sequences. Increased finger tap velocity or force
rhythm type (metric simple, metric complex, nonmetric)
on particular taps during reproduction can also indicate
presented in random order.
where participants feel the beat. When tap velocity was
measured during a reproduction task similar to the one
outlined here, the velocity was significantly higher for Data Analysis
taps coinciding with the perceptual accents at the onset
Performance was evaluated based on the keypresses the
of each group of four units than for the other taps in
subjects reproduced. Trials with the incorrect number
each sequence (Grahn & Brett, 2005, 2006).
of keypresses or incorrect order of intervals were con-
In the metric complex condition, the intervals were
sidered errors. Incorrect ordering was defined as any
identical to those in the metric simple condition, but
reproduced interval exceeding the length of another
rearranged so as not to be regularly grouped, and
reproduced interval that was supposed to be shorter
therefore had irregular perceptual accents. The nonmet-
(e.g., a 2 interval exceeding the length of a 3 interval)
ric rhythms had the same interval arrangements as the
and vice versa (e.g., a 4 interval shorter than a 1 in-
metric complex rhythms but used the noninteger ratio
terval). More stringent criteria (e.g., rejecting any se-
interval lengths: 1.4 replaced 2, 3.5 replaced 3, and 4.5
quence with a reproduced interval that deviated by
replaced 4. For a complete list of sequences, see Table 1.
more than 10% or 20% of the specified interval length)
The length of the ‘‘1’’ interval was chosen randomly
were also used, but led to the same pattern of results
from 220 to 270 msec (in 10-msec steps) on each trial to
between conditions and thus are not presented here.
prevent subjects from using a beat perceived in the
On correct trials, the reproduced ratios were calculated
previous trial. The rest of the intervals in each sequence
from the mean duration of each reproduced interval
were multiples of the 1 interval. For example, with a 1
length on each trial. Perfect reproduction results in
interval of 250 msec, the sequence 321411 has intervals
ratios of 2, 3, and 4 for both metric conditions, and
of length 750 500 250 1000 250 250 (msec). Sine tones
1.4, 3.5, and 4.5 for the nonmetric condition. In order to
(rise/fall times of 8 msec) sounded for the duration of
compare accuracy between conditions, each reproduced
each interval, ending 40 msec before the specified
ratio was divided by its ideal ratio (the ratio actually
interval length to create a silent gap that demarcated
presented in the stimulus), so reproduction across the
the intervals. The sequences used filled intervals, as
different ratios was normalized to 1 (perfect reproduc-
piloting indicated performance was similar for empty
tion). The absolute value of the deviation from 1 was
and filled interval sequences, and filled intervals provide
then tested to see if accuracy differed across ratios and
the benefit of attenuation of environmental noise (e.g.,
conditions.
that experienced during MRI). In addition, differences in
the average psychophysical discrimination threshold
between empty and filled auditory intervals are a few Functional Imaging Experiment
milliseconds and thus unlikely to affect perception of
sequences composed of the interval lengths used here Subjects
(Grondin, 1993). One of six pitches (varying from 294 to Twenty-seven right-handed subjects participated (19
587 Hz) was picked at random for each trial and held men, 8 women). Fourteen had musical training (over
constant for that trial. The pitch differences between 5 years of formal musical training and current regular
trials helped cue subjects to each new trial. musical activity) and 13 had no musical training (re-
In the first experiment, the task was to reproduce the ported no formal musical training or musical activities).
sequence as accurately as possible. During reproduction, They ranged in age from 19 to 38 years, and the average
the onset of each reproduced interval is indicated by the age was 24.5 years. The fMRI participants had not taken
subject’s tap, and the reproduced lengths of each inter- part in the previous reproduction experiment.
val were measured by the intertap time. We therefore
added an additional tone, the length of the 1 interval, to
Experimental Design
the end of each sequence. Otherwise, without this final
onset for subjects to tap, the last reproduced interval’s Rhythms were presented diotically over electrostatic head-
length would not have been measured. phones (Palmer, Bullock, & Chambers, 1998) inserted into

Grahn and Brett 895

Table 1. Rhythmic Sequences for Each Condition
Interval Set Metric Simple Metric Complex Nonmetric
5 Intervals 11334 31413 11343 1 1 3.5 4.5 3.5
41331 33141 3.5 3.5 1 4.5 1
43113 41133 4.5 1 1 3.5 3.5
12234 22413 13242 1 3.5 1.4 4.5 1.4
31422 21324 1.4 1 3.5 1.4 4.5
43122 41232 4.5 1 1.4 3.5 1.4
6 Intervals 111234 112314 124113 1 1.4 4.5 1 1 3.5
211134 214311 1.4 1 4.5 3.5 1 1
211413 321411 3.5 1.4 1 4.5 1 1
411231 421311 4.5 1.4 1 3.5 1 1
112224 112422 122142 1 1.4 1.4 1 4.5 1.4
211224 214221 1.4 1 4.5 1.4 1.4 1
222114 221241 1.4 1.4 1 1.4 4.5 1
422112 412212 4.5 1 1.4 1.4 1 1.4
112233 221331 121233 1 1.4 1 1.4 3.5 3.5
223113 132321 1 3.5 1.4 3.5 1.4 1
311322 231123 1.4 3.5 1 1 1.4 3.5
312213 323211 3.5 1.4 3.5 1.4 1 1
7 Intervals 1111134 1111431 1314111 1 3.5 1 4.5 1 1 1
3141111 1411311 1 4.5 1 1 3.5 1 1
4111131 3114111 3.5 1 1 4.5 1 1 1
1111224 1122114 1112412 1 1 1 1.4 4.5 1 1.4
2211114 2141211 1.4 1 4.5 1 1.4 1 1
4221111 4111221 4.5 1 1 1 1.4 1.4 1
1111233 1123113 1132131 1 1 3.5 1.4 1 3.5 1
2113113 2331111 1.4 3.5 3.5 1 1 1 1
3121113 3113121 3.5 1 1 3.5 1 1.4 1
1112223 1123122 1132212 1 1 3.5 1.4 1.4 1 1.4
2112231 2123211 1.4 1 1.4 3.5 1.4 1 1
3122112 3221112 3.5 1.4 1.4 1 1 1 1.4

1 = 220–270 msec (in steps of 10 msec), chosen at random for each trial. All other intervals in that sequence are multiplied by length chosen for
the 1 interval.

sound-attenuating ear defenders. Further attenuation of presentations of a rhythm, to which they compared a
scanner noise was achieved with insert earplugs rated to subsequent third presentation. The third presentation
attenuate by
30 dB (3M 1100 earplugs, 3M United could be the same rhythm or a different rhythm. To
Kingdom PLC, Bracknell, UK). When wearing earplugs indicate whether the third rhythm was same or different,
and ear defenders, participants reported no difficulty in participants pressed one of two buttons with either the
hearing the rhythms or focusing on the task. The discrim- right index or middle finger. On 39% of trials the third
ination task used the same sequences as the reproduction presentation was different. Each rhythm presentation was
task but required participants to listen to two identical separated by 1100 msec. The deviant sequences contained

896 Journal of Cognitive Neuroscience Volume 19, Number 5

two temporal changes (as piloting indicated that the motion) with respect to the first image in the series by
presence of two deviants allowed behavioral performance using trilinear interpolation. Magnetic field maps were
between conditions to be equal, but not at ceiling or floor). used to undistort the EPI images (Cusack & Papadakis,
One interval in the sequence was divided into two in- 2002). The SPGR image was skull-stripped by using the
tervals, and two separate intervals were combined into Brain Extraction Tool (BET) (Smith, 2002), then normal-
one (e.g., 211314 becomes 223113, 11 ! 2, and 4 ! 13). ized (using affine and smoothly nonlinear transforma-
Thus, the number of intervals and overall sequence length tions) to a brain template in Montreal Neurological
was identical between standard and deviant sequences. Institute (MNI) space. The resulting normalization pa-
Before scanning, participants completed eight practice rameters were then applied to the EPIs and all normal-
trials. During scanning, participants completed four con- ized EPI images were spatially smoothed with an 8-mm
secutive sessions of 38 trials each, approximately 40 min full width half maximum Gaussian kernel.
in total. Trials were equally distributed between four For each participant, each session, and each condition
types: rest (no sound presented), metric simple, metric (metric simple, metric complex, and nonmetric) the
complex, or nonmetric rhythms, presented in a pseudo- following event types were modeled separately: first
random order. Participants were instructed not to move presentation; second presentation; third presentation
any part of their body during the scan (other than to for same trials; third presentation for different trials;
respond). button press response. Each event was modeled by
using a regressor made from an on–off boxcar convolved
with a canonical hemodynamic response function. Six es-
Image Acquisition timated parameters of movement between scans (trans-
lation and rotation along x, y, and z axes) were entered
Participants were scanned on a Bruker MEDSPEC 3-T
as covariates of no interest. Before running the model,
scanner at the Wolfson Brain Imaging Centre in Cam-
the time course of the average brain signal was screened
bridge, using a head coil gradient set. Echo-planar
for spikes of high variance. Short periods of high
imaging (EPI) data were collected with the following
variance are usually associated with brief subject move-
parameters: 21 slices, matrix size of 64  64, TE =
ments as shown in the spatial realignment parameters.
37.5 msec, TR = 1.1 sec, FOV = 20  20 cm, flip angle =
The high-variance scans were removed from the model
65.58. The resulting EPIs had a slice thickness of 4 mm,
by using a modified version of the SPM99 modeling
interslice distance of 1 mm, and in-plane resolution of
routines (www.mrc-cbu.cam.ac.uk/Imaging/Common/
3.125  3.125 mm. The EPI acquisition was continuous
missing_time.shtml). Low-frequency noise was removed
to prevent periodic silent gaps between TRs from dis-
with a standard high-pass filter of 120 sec. The results
rupting participants’ encoding of the rhythms. Although
estimated from single subject models were entered into
some studies of auditory cortex have used ‘‘sparse’’
second-level random effects analyses for standard SPM
imaging in order to reduce the effects of scanner noise
group inference (Penny & Holmes, 2003). All reported
on detecting subtle differences in auditory activity, we
peaks passed a whole-brain false detection rate (FDR)
chose to use standard continuous imaging, as this of-
threshold (Genovese, Lazar, & Nichols, 2002; Benjamini
fered considerably greater power (number of scans) and
& Hochberg, 1995) of p < .05.
the stimuli were easily heard over the scanner noise. In
A region-of-interest (ROI) analysis was conducted to
addition, motor areas, not auditory areas, were of pri-
test the prediction that the basal ganglia and SMA are
mary interest. A map of the magnetic field was ac-
more active to rhythms that induce a beat, and to
quired to correct for distortion to the EPIs resulting
elucidate the pattern of activation between conditions
from inhomogeneities in the field. High-resolution
in other ROIs. For the basal ganglia, where structure is
three-dimensional spoiled gradient recalled (SPGR) at
easily defined by anatomy and relatively invariant across
steady-state anatomical images were collected for ana-
individuals, structural ROIs were used for the pallidum,
tomic localization and coregistration.
putamen, and caudate (Tzourio-Mazoyer et al., 2002).
For the SMA, dorsal premotor areas (PMds), superior
temporal gyri, and cerebellum, functional ROIs were
Image Processing and Statistical Analysis
defined from the all rhythms–rest contrast. The SMA
SPM2 was used for preprocessing of the fMRI data and activation was predominantly anterior to the anterior
SPM99 for statistical analysis (SPM99, SPM2; Wellcome commissure, so the SMA ROI should be considered to be
Department of Cognitive Neurology, London, UK). largely pre-SMA with some component of SMA proper
SPM99 was used to take advantage of previously adapted (Picard & Strick, 1996; Rizzolatti, Luppino, & Matelli,
routines to remove time series artifacts from the data 1996). The ROI analysis was conducted with the software
(www.mrc-cbu.cam.ac.uk/Imaging/Common/missing_ package MarsBar (marsbar.sourceforge.net). For each
time.shtml). Images were slice-timing corrected, with ROI, a t test was carried out to compare the mean voxel
the first slice in each scan used as a reference. They value during trials of each rhythm type, and between
were then realigned spatially (to correct for subject each group.

Grahn and Brett 897

RESULTS tended to shorten the longest intervals in a sequence.
Reproduction Results To determine if the timing accuracy significantly dif-
fered between conditions, the absolute value of the
After hearing a rhythm three times, participants tapped deviation of these ratios from perfect performance was
the rhythm back on one key of a computer keyboard. As tested. Differences between conditions were confirmed
shown in Figure 2, participants correctly performed by a significant interaction between Rhythm type and
metric simple rhythms significantly more often than Ratio on timing accuracy: F(4,76) = 4.41, p = .003.
the metric complex and nonmetric rhythms (metric Further analyses revealed that accuracy of the longest
simple, 74% correct; metric complex, 53% correct; non- ratios (the 4 ratio in the metric conditions and the
metric, 58% correct). Metric complex and nonmetric 4.5 ratio in the nonmetric condition) did significantly
rhythms were not significantly different in percent cor- differ between conditions. The accuracy of the longest
rect performance, as confirmed by a one-way analysis of ratio in the metric simple condition was significantly
variance (ANOVA) with Rhythm type (metric simple, better than in the metric complex and nonmetric con-
metric complex, nonmetric): F(2,38) = 20.67, p < .001, ditions, which did not significantly differ: metric simple
with Bonferroni-corrected post hoc tests: metric sim- versus metric complex, t(1,19) = 6.52, p < .001; metric
ple versus metric complex: t(1,19) = 5.47, p < .001; simple versus nonmetric, t(1,19) = 5.00, p < .001; metric
metric simple versus nonmetric: t(1,19) = 5.24, p < .001; complex versus nonmetric, t(1,19) = 1.42, p = .17
metric complex versus nonmetric: t(1,19) = 1.38, p = .19. (Bonferroni-corrected post hoc tests). In addition, the
The error types varied widely and could be due to the 3 ratio was significantly more accurate in the metric
taxing nature of the reproduction task on working simple than the nonmetric condition: metric simple
memory. Usually just part of the sequence was repro- versus nonmetric t(1,19) = 2.88, p = .029 (Bonferroni-
duced incorrectly. For example, in sequences with sev- corrected post hoc tests). No other significant differ-
eral short intervals in a row, participants sometimes ences in ratio accuracy were found. Examination of
reproduced the wrong number of short intervals, but histograms and rasters of the reproduced ratios for each
the rest of the intervals were correct. Sometimes just the participant in each condition showed no evidence that
beginning or the end of a sequence was reproduced participants were ‘‘regularizing’’ the nonmetric rhythms,
incorrectly. Other time intervals were transposed. Occa- that is, reproducing them using integer ratios instead of
sionally participants only reproduced the beginning or noninteger ratios.
the end of a sequence without attempting the rest of the Overall, in the metric simple condition, participants
sequence. did not truncate the longer ratios as much as they did in
Analyses of how accurately participants reproduced the other conditions. Thus, the metric simple condition
the timing of the intervals were conducted on sequences had not only the greatest number of correctly repro-
where the overall order of the intervals was correct duced sequences, but also more accurate timing of the
(see Methods for details). Perfect reproduction would longest intervals within those sequences.
result in ratios of 2:3:4 for the metric conditions, and
1.4:3.5:4.5 for the nonmetric condition. The ratios repro-
duced by the participants were, in the metric simple Discrimination Results
condition, 2.08:3.01:3.83 (SE = .04, .06, .10); in the Based on extensive pilot testing, a discrimination task
metric complex condition, 2.05:2.84:3.34 (SE = .04, .08, that equalized behavioral performance was created (see
.11); and in the nonmetric condition, 1.41:2.95:3.51 Methods), thus removing confounds of difficulty be-
(SE = .04, .09, .12). Overall, in all conditions, participants tween conditions. In fMRI, difficulty confounds might
have led to activation differences between rhythm con-
ditions that were unrelated to beat processing. Behav-
ioral performance across groups and conditions was
similar. Mean d0 and percent correct scores for each
condition were as follows: metric simple, d0 = 2.5,
percent correct = 87%; metric complex, d0 = 2.2,
percent correct = 84%; nonmetric, d0 = 2.4, percent
correct = 84%. For each group, musicians: d0 = 2.6,
percent correct = 87%; nonmusicians: d0 = 2.2, percent
correct = 82%. There were no main effects or inter-
actions between conditions or groups on percent cor-
rect or d0 scores, as shown by a 3  2 repeated measures
ANOVA with Rhythm type as the within-subjects factor
Figure 2. Reproduction results. Graph demonstrating the percentage
and Musical training (musician, nonmusician) as the
of sequences performed correctly for each of the rhythm conditions. between-subjects factor: Rhythm type: d0: F(2,50) =
**p < .001. 1.44, p = .25, percent correct: F(2,50) = 1.86, p = .17;

898 Journal of Cognitive Neuroscience Volume 19, Number 5

 Table 2. Stereotaxic Locations of Peak Voxels in All
Rhythms–Rest Contrast

Brain Region Z Score p x y z

L pre-SMA/SMA 5.03 <.001 9 6 60
R pre-SMA/SMA 4.97 <.001 3 6 66
L putamen 5.67 <.001 24 6 9

Figure 3. Behavioral data collected during fMRI experiment. The R putamen 5.08 <.001 21 6 6
graph demonstrates the percentage of trials discriminated correctly L premotor 5.3 <.001 54 0 51
by musicians (mus) and nonmusicians (non) for each of the rhythm
conditions. There are no significant differences between groups R premotor 5.24 <.001 54 0 45
or conditions.
R cerebellum 4.68 <.001 30 66 27
L cerebellum 4.41 <.001 30 66 24
0
Musical training: d : F(1,25) = 2.41, p = .13, percent R superior temporal gyrus 6.02 <.001 60 33 6
correct: F(1,25) = 1.85, p = .19. Figure 3 shows the L superior temporal gyrus 5.8 <.001 57 15 9
percent correct scores for musicians and nonmusicians
across the different rhythm conditions. Reaction times L superior temporal pole 4.68 <.001 57 6 3
were not analyzed because participants were not asked R inferior frontal 4.52 <.001 27 30 15
to make a speeded response. Although behavioral per-
This table shows the brain region, p and Z values, and stereotaxic
formance was equal across conditions, the data indicate coordinates (in millimeters) of peak voxels in MNI space. Thresholded
this is not due to floor or ceiling effects. at p < .001, whole-brain corrected (FDR). R = right; L = left; SMA =
supplementary motor area.

Functional Imaging Results

rhythm. Figure 4 shows the results of the random effects
All analyses presented here were conducted on the first
analysis of all rhythms–rest, collapsed across group and
two presentations of the rhythms to exclude activation
condition. Activation was observed in the pre-SMA/SMA,
due to deviant detection, decision making, and response
PMd, basal ganglia, cerebellum, superior temporal gyrus
preparation during the third rhythm presentation, and
(STG), and ventrolateral prefrontal cortex/insula, all
motor activation during the subsequent response. The
bilaterally (see Table 2 for Z scores of local maxima).
activity therefore likely reflects listening to and main-
For these experiments, we created one set of se-
taining in memory two identical presentations of a
quences (the metric simple condition) that were pre-
dicted to induce a beat through the presence of regular
perceptual accents (Essens, 1995; Essens & Povel, 1985;
Povel & Essens, 1985). These sequences were repro-
duced more accurately than sequences composed of
identical intervals, but ordered in such a way as to not
induce a beat. Because the sequences were so closely
matched, we provisionally concluded that the differ-
ences in performance were due to the predicted differ-
ences in beat induction. As the behavioral data showed

Figure 4. Brain activation during all rhythm conditions–rest. The

cortical and cerebellar activations from this contrast defined functional
ROIs for further analysis. Z score of 3.3 = p < .01, whole-brain
corrected (FDR). PMd = dorsal premotor area; SMA = supplementary Figure 5. Brain regions more active for metric simple than metric
motor area; STG = superior temporal gyrus; VI = cerebellar crus VI. complex or nonmetric rhythms. Z score of 3.43 = p < .05, whole-brain
x, y, and z refer to axes in stereotaxic space. corrected (FDR).

Grahn and Brett 899

Table 3. Stereotaxic Locations of Peak Voxels in Metric Table 4. t Values for Metric Simple–Metric Complex, and
Simple–Metric Complex and Nonmetric Contrast Metric Simple–Nonmetric Contrasts, for Each ROI

Brain Region Z Score p x y z t Value

L superior temporal gyrus 4.60 .039 51 3 3 Metric Metric
Simple–Metric Simple–
3.87 .040 51 9 3
ROI Complex Nonmetric
R superior temporal 3.78 .045 42 36 18
gyrus/insula L superior temporal gyrus 4.13*** 2.08*

R insula 3.92 .040 45 6 6 R superior temporal gyrus 3.91*** 1.72*

3.87 .040 30 21 12 Pre-SMA/SMA 2.36* 2.12*

L putamen 4.47 .039 27 0 9 L caudate 1.83* 1.1 (ns)

4.19 .039 27 0 0 R caudate 2.06* 1.19*

3.77 .045 27 12 6 L pallidum 2.66** 1.74**

R putamen 4.31 .039 24 0 9 R pallidum 3.45*** 2.78***

4.31 .039 24 12 6 L putamen 4.05*** 3.4***

4.24 .039 24 3 9 R putamen 3.65*** 2.97***

L inferior frontal gyrus 4.03 .040 51 33 6 R premotor cortex 1.25 (ns) 0.46 (ns)

L superior frontal gyrus 4.01 .040 12 69 18 L premotor cortex 1.49 (ns) 0.58 (ns)

R amygdala 3.88 .040 21 9 15 R cerebellum 0.48 (ns) 0.22 (ns)

L cerebellum 0.71 (ns) 0.22 (ns)
This table shows the brain region, p and Z values, and stereotaxic
coordinates (in mm) of peak voxels in MNI space. Thresholded at p <
ns = not significant; R = right; L = left; SMA = supplementary motor
.05, whole-brain corrected (FDR). R = Right, L = Left.
area.
*p < .05.
that the metric simple condition was performed signifi- **p < .01.
cantly better than the other two conditions, we com- ***p < .001.
pared activation in the metric simple condition to that in
the metric complex and nonmetric conditions. We sug-
gest that this comparison is between beat-inducing and plex condition significantly activated the pallidum, puta-
non-beat-inducing rhythms. Increased activation for men, caudate, pre-SMA/SMA, and STG bilaterally. The
metric simple rhythms was observed bilaterally in the same pattern was observed when the metric simple
putamen and superior temporal gyri, as well as left condition was compared to the nonmetric condition,
inferior frontal gyrus, shown in Figure 5. See Table 3 although the caudate no longer reached significance
for Z scores of local maxima. (t values for both contrasts shown in Table 4). No
The ROI analysis (shown in Figure 6) found that the significant differences in activation were seen between
metric simple condition compared to the metric com- the metric complex and nonmetric rhythms. In addition,

Figure 6. Graph of activation

during each rhythm condition–
rest in each ROI. Metric
complex and nonmetric
activations in all areas were
not significantly different from
each other. *p < .05 for both
metric simple versus metric
complex and metric simple
versus nonmetric (except in
the caudate, where only the
metric simple versus metric
complex difference reaches
significance). R = right;
L = left; SMA = supplementary
motor area.

900 Journal of Cognitive Neuroscience Volume 19, Number 5

none of the areas were activated significantly more by Table 5. t Values for Activation Differences between
the metric complex or nonmetric rhythms than the Musicians and Nonmusicians in Selected ROIs
metric simple rhythms. This finding confirms that re-
ROI t Value
moval of difficulty confounds was successful: If the
metric complex and nonmetric conditions were more Pre-SMA/SMA 1.99*
difficult or required greater attentional or working R premotor cortex 2.99**
memory demands, increased, not decreased, activity
would be expected in the dorsolateral prefrontal and L premotor cortex 0.75 (ns)
anterior cingulate cortices (Duncan & Owen, 2000). To R cerebellum 2.77**
verify this had not occurred, a whole-brain, random
L cerebellum 2.91**
effects analysis was conducted, contrasting metric com-
plex and nonmetric rhythms to metric simple rhythms L superior temporal gyrus 0.30 (ns)
(i.e., all non-beat-inducing–beat-inducing rhythms). R superior temporal gyrus 1.1 (ns)
Even at a much reduced statistical threshold ( p < .5,
L caudate 0.32 (ns)
FDR corrected), no significant activation was observed.
The ROI analysis found that musicians showed several R caudate 0.98 (ns)
areas of greater activation compared to nonmusicians L pallidum 1.26 (ns)
(see Figure 7). Musicians activated the pre-SMA/SMA,
bilateral cerebellum, and right PMd significantly more R pallidum 0.47 (ns)
than did nonmusicians in all rhythm conditions com- L putamen 0.76 (ns)
pared to rest (see Table 5 for t values). Further analysis
R putamen 0.21 (ns)
showed no significant interactions between group and
rhythm type. In addition, a correlation analysis was ns = p > .05. R = right; L = left; SMA = supplementary motor area.
performed to determine if a relationship between acti- *p < .05.
vation in any of the ROIs correlated with behavioral **p < .01.
discrimination performance. No significant results were
found, probably due to the low variability in behavioral
performance. beat (as predicted by the Povel and Essens model
[Essens, 1995; Essens & Povel, 1985]), then metric
simple rhythms should be more accurately reproduced.
This is indeed what we found. Significantly more met-
DISCUSSION
ric simple rhythms were reproduced accurately. In
Previous work indicates that rhythms encoded in rela- addition, shortening of the longest intervals was ob-
tionship to a beat are reproduced more accurately than served during reproduction in all rhythm types, but
rhythms that are not (Patel et al., 2005; Essens & Povel, this shortening was significantly less in the metric sim-
1985). In this experiment, we compared the perform- ple condition. Given that the metric simple and metric
ance of metric simple rhythms (which had regular per- complex conditions were identical apart from whether
ceptual accents) to that of metric complex rhythms the arrangement of the intervals produced regular or
(which did not). If regular perceptual accents induce a irregular perceptual accents, we feel that the most
plausible explanation for these effects is that, as pre-
dicted, a regular beat was induced in the metric simple
condition.
The reproduction results suggest that integer ratios
and regular perceptual accents are required for beat
induction. However, as we did not succeed in creating a
condition with regular perceptual accents and nonin-
teger ratios, it is possible that regular perceptual accents
alone could induce a beat. This remains an interesting
avenue for future research. In contrast to previous re-
search (Sakai et al., 1999), we find that integer ratios
alone appear to be insufficient for beat induction, as
the number of correctly reproduced metric complex (in-
teger ratios) and nonmetric (noninteger ratios) rhythms
was not significantly different in this experiment. The
Figure 7. Activation during all rhythms–rest for musicians and
nonmusicians. Graph of activation collapsed across conditions, for difference between previous work and the current ex-
pre-SMA/SMA, right and left cerebellum, and right premotor area. periments likely arises because the previous study did
*p < .05. mus = musician; non = nonmusicians. not assess accent structure. Therefore, the integer ratios

Grahn and Brett 901

condition in that study contained sequences with vary- presentations, is systematically manipulated and the ef-
ing levels of regularity in the accent structure; the fects on reproduction performance are assessed.
sequences with greater accent regularity may be respon- Moving on to the fMRI data collected in the second
sible for the better performance. In the current study, experiment, we find that a bilateral network of motor
accent structure was manipulated to be regular or areas is activated when rhythms are perceived, even
irregular, allowing us to assess the role of accents when no movement is made. When listening to all the
separately from that of integer ratios. When accent rhythms compared to rest, bilateral activation was ob-
structure is accounted for, then the presence of integer served in the pre-SMA/SMA, PMd, basal ganglia, cerebel-
ratios is not enough to improve behavioral rhythm lum, superior temporal gyri, and ventrolateral prefrontal
performance. cortex/anterior insula. The lack of activation in primary
Another interesting phenomenon reported in tempo- motor cortex suggests that participants complied with
ral reproduction studies is that some participants ‘‘regu- instructions not to move any part of their body during
larize’’ noninteger ratio sequences during performance, presentation of the rhythms, and thus the activation
such that the noninteger ratios are distorted into integer observed is likely due only to perception of rhythm.
ratios. We find no evidence of regularization in our study, These findings are consistent with other studies (Lewis
although this is likely due to the stimuli we used. In et al., 2004; Schubotz, Friederici, & von Cramon, 2000;
most previous studies that find regularization (Collier & Penhune et al., 1998) confirming that a bilateral network
Wright, 1995; Essens, 1986; Essens & Povel, 1985) only of motor areas mediate perception of rhythm in addition
one ratio (e.g., 1:2.5 or 1:3.3) is present in any given to rhythm production. These data may also suggest that
sequence or block of stimuli. Therefore, the perception of rhythm perception may lie more within the ‘‘automatic’’
the unit level (1) and the level that is the noninteger timing system proposed by Lewis and Miall (2003), as
multiple of that unit (2.5 or 3.3), and the resulting rela- this system is composed mainly of motor areas and is
tionship between the levels is quite easy to discern. The most involved in timing of subsecond intervals. How-
perception of this relationship may then allow partici- ever, the automatic system is thought to operate mainly
pants to stretch or shrink the noninteger ratio in order for predictable or overlearned stimuli, and without
to make it into an integer multiple of the unit level. This ‘‘attentional modulation.’’ The stimuli here were not
regularization presumably decreases the timing difficulty learned and in many cases were unpredictable. It also
of the task. Other work (Sakai et al., 1999) has used more seems unlikely that perception of such complicated
than one noninteger ratio (1:2.5:3.5), but in this case, rhythms would occur without attention, therefore it
only three (of 6) participants showed regularization, and may be that the automatic system is responsible for
only for some sequences. Another contributing factor to perception of the individual intervals that compose the
whether regularization occurs may be the use of block sequences, but does not mediate cohesive perception of
presentations of the noninteger ratio sequences (Sakai the rhythm as a whole.
et al., 1999) or high numbers of sequence repetitions The fMRI data provide additional confirmation of the
(Collier & Wright, 1995; Essens, 1986; Essens & Povel, importance of regular perceptual accents in rhythm per-
1985), giving participants a greater number of exposures ception. Listening to metric simple rhythms significantly
to perceive the relationships between the intervals. Again, increased activity bilaterally in the basal ganglia, anterior
this perception of the relationship may lead subjects superior temporal gyri, left inferior frontal gyrus, and the
to regularize in order to simplify the task. When many pre-SMA/SMA (although the latter activation only
ratios are present, such as 1:1.4:3.5:4.5 in the current reached significance in the ROI analysis), compared to
study, it is presumably less clear what the relationships the metric complex and nonmetric conditions. A role for
between the unit level (1) and the other levels (1.4, 3.5, the basal ganglia and SMAs in beat induction is con-
and 4.5) are. The relationships are further clouded by the sistent with their involvement in motor prediction (the
presence of other ratios between intervals in the se- spontaneous response to hearing a beat is often to
quence (1.4:3.5, 1.4:4.5, and 3.5:4.5). These sequences move at the time when the next beat is predicted).
may be too complex for participants to determine how to The anatomy supports their mutual contribution, as
go about regularizing them, especially in the current the basal ganglia and pre-SMA/SMA are richly connected
study, where there are only a small number of presenta- through striato–thalamo–cortical loops (Inase & Tanji,
tions of each rhythm and no blocked presentation of the 1994; Alexander, DeLong, & Crutcher, 1992) and are
rhythm types. Finally, other work has used noninteger involved in timing (Macar, Anton, Bonnet, & Vidal,
ratios rhythms and does not report regularization, al- 2004; Ferrandez et al., 2003), including timing of fu-
though perhaps this specific issue was not assessed in ture movements (Sardo, Ravel, Legallet, & Apicella,
detail (Lewis et al., 2004; Ullén, Forssberg, & Ehrsson, 2000; Rao et al., 1997). Patients with lesions in SMAs
2003). It should be noted that our account for lack of are impaired at reproducing temporal sequences from
regularization, is speculative and requires evidence from memory (Halsband et al., 1993). However, further re-
further investigations in which the number of noninteger search is needed to clarify whether increased activity
ratios present in a sequence, or the number of sequence in basal ganglia and pre-SMA/SMA underlies the spon-

902 Journal of Cognitive Neuroscience Volume 19, Number 5

taneous movement that often spontaneously occurs to suggests that the beat in the metric simple condition may
the beat. be providing a regular structure (sometimes called a
The bilateral anterior superior temporal gyri were also ‘‘temporal grid’’; Povel, 1984) that aids working memory
more active during metric simple rhythms compared performance for the rhythms.
with metric complex and nonmetric rhythms. The peak We also found that activation to the metric complex
of this activation is
3 cm anterior to the peak of the and nonmetric conditions did not significantly differ.
auditory cortex activation observed in the all rhythms Thus, the fMRI results are in contrast to a previous study
minus rest contrast, placing it in the anterior secondary (Sakai et al., 1999), which reported different patterns of
auditory cortex. Activity here has been observed for activation for sequences with integer- and noninteger
auditory imagery (Zatorre, Halpern, Perry, Meyer, & ratio intervals (although the two conditions were not
Evans, 1996). Accordingly, our participants may have statistically compared, so it is unclear if the differences
been able to form a better auditory image of the beat- are reliable). However, as mentioned before, the integer
based rhythms, consistent with the better performance ratio sequences in that study likely contained varying
of these rhythms in the reproduction experiment. Alter- levels of regularity in the accent structure, as the authors
natively, the anterior auditory areas may be important did not consider perceptual accents in their stimuli;
for perceiving the beat in the first place. This is con- thus, any differences may not be due to the presence
sistent with neuropsychological work (Liegeois-Chauvel, of integer ratios versus noninteger ratios per se.
Peretz, Babai, Laguitton, & Chauvel, 1998) that shows These data may illuminate a controversy about the
that the anterior STG is necessary for normal musical existence of a ‘‘beat-based’’ (or entrainment) timer
meter perception (determining if beat groupings are in a (Pashler, 2001). A beat-based timer is hypothesized to
‘‘waltz’’ or ‘‘march’’ meter). Beat perception itself was encode intervals in reference to an underlying isochro-
not directly tested in the patients, but musical meter nous beat (using a beat to measure if an interval is one
perception depends fundamentally on perceiving the beat long, two beats long, etc.). Several studies have
underlying beat (London, 2001). Intriguingly, resection examined whether a beat-based timer exists, and if so,
in either hemisphere produced impairment, consistent whether it can improve timing. Generally, these studies
with the bilateral nature of the activation in the current test how accurately humans time a single time interval,
study. A visual rhythm condition in future experiments under conditions that are or are not conducive to using
may help determine whether the auditory cortex makes beat-based timing. The results are conflicting (McAuley
a supramodal contribution to rhythm processing, or if its & Jones, 2003; McAuley & Kidd, 1998; Vos, van Assen,
role is restricted to the auditory modality. & Franek, 1997; Schulze, 1978; cf. Pashler, 2001; Ivry &
Difficulty can be a major confound in fMRI experiments. Hazeltine, 1995; Keele, Nicoletti, Ivry, & Pokorny, 1989)
Increased difficulty in a wide range of paradigms cause perhaps because timing of a single interval is most
greater activation in the dorsolateral prefrontal and ante- frequently tested. The reproduction data here, ac-
rior cingulate cortices, suggesting a specific network for quired on a more complicated temporal rhythm task,
effortful processing across domains (Duncan & Owen, show a substantial performance benefit for rhythms
2000). To avoid difficulty confounds in the fMRI experi- that are designed to induce a beat. These data suggest
ment, we used a task that had similar levels of performance that a beat-based mechanism does exist, and improves
across conditions. Reassuringly, although the metric com- timing performance when more difficult temporal tasks
plex and nonmetric conditions were the most difficult are tested. In addition, a specific network of areas was
in the reproduction task, they produced less, not more more active during perception of beat-inducing rhythms
activity in the fMRI study. In addition, the timing require- compared with other rhythms, even when no signifi-
ments of the individual intervals across the conditions cant behavioral performance differences were observed.
were very well matched. Taken together, these findings This suggests that the beat-based system can be active
indicate that it is unlikely that the increased activation in even when no behavioral performance benefit is ob-
the metric simple condition can be explained by difficulty. served. Thus, the fact that some previous work does
Nevertheless, it was initially surprising that no brain not find a behavioral beat-based timing benefit does
areas were significantly more active in the metric complex not necessarily mean that such a mechanism was not
or nonmetric conditions than in the metric simple condi- active or used.
tion, given that the reproduction study indicates the metric Interestingly, the observed cerebellum and premotor
complex and nonmetric conditions are more difficult. cortex activations were not significantly different across
Working memory studies, however, indicate that pre- the three rhythm types. Many other studies show involve-
frontal areas can show increased activity when encoding ment of these areas in temporal processing (Penhune &
easier stimuli compared with harder stimuli if the easier Doyon, 2002; Ramnani & Passingham, 2001), but they
stimuli contain structure (Bor, Cumming, Scott, & Owen, appear not to have a specific role in beat-based timing.
2004; Bor, Duncan, Wiseman, & Owen, 2003). The pre- Musically trained participants recruit these areas more
frontal area activated in those studies is very near the left than untrained participants do, although behavioral
inferior frontal gyrus activation found in this study. This discrimination performance is the same between these

Grahn and Brett 903

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