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Brain networks underlying timing behavior are influenced by prior context


Abstract and Figures

The continuation paradigm is often used to investigate the behavioral and neural mechanisms of timing. Typically, a movement rate is established by pacing with a metronome. Then, the metronome is turned off and the subject continues at the established rate. Performance during continuation is assumed to be based on internal timing mechanisms. Here, we investigated the degree to which the neural activity underlying time representation depends on the initial pacing context, that is, whether pacing was established by moving in-phase (the usual procedure) or anti-phase (syncopation) with an auditory metronome. Functional MRI was measured from 14 subjects during four conditions: synchronized pacing, synchronized continuation, syncopated pacing, and syncopated continuation. In general, movements were timed consistently for all four conditions. However, a much broader network of activation was engaged during syncopation compared with synchronization, including increased activation in supplementary motor area, left premotor area, right thalamus, bilateral inferior frontal gyrus, and cerebellum. No differences were found when comparing continuation with the preceding pacing phase except for decreased activity in auditory-related regions due to the absence of the metronome. These results demonstrate that the cortical and subcortical areas recruited to support a simple motor timing task depend crucially on the method used to establish the temporal reference. Thus, the neural mechanisms underlying time and timing are highly flexible, reflecting the context in which the timing is established.
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Brain networks underlying human timing behavior are
influenced by prior context
Kelly J. Jantzen*, Fred L. Steinberg, and J. A. Scott Kelso
Center for Complex Systems and Brain Sciences, Florida Atlantic University, 777 Glades Road, Boca Raton, FL 33431
Communicated by Ann M. Graybiel, Massachusetts Institute of Technology, Cambridge, MA, February 24, 2004 (received for review September 17, 2003)
The continuation paradigm is often used to investigate the behav-
ioral and neural mechanisms of timing. Typically, a movement rate
is established by pacing with a metronome. Then, the metronome
is turned off and the subject continues at the established rate.
Performance during continuation is assumed to be based on
internal timing mechanisms. Here, we investigated the degree to
which the neural activity underlying time representation depends
on the initial pacing context, that is, whether pacing was estab-
lished by moving in-phase (the usual procedure) or anti-phase
(syncopation) with an auditory metronome. Functional MRI was
measured from 14 subjects during four conditions: synchronized
pacing, synchronized continuation, syncopated pacing, and synco-
pated continuation. In general, movements were timed consis-
tently for all four conditions. However, a much broader network of
activation was engaged during syncopation compared with syn-
chronization, including increased activation in supplementary mo-
tor area, left premotor area, right thalamus, bilateral inferior
frontal gyrus, and cerebellum. No differences were found when
comparing continuation with the preceding pacing phase except
for decreased activity in auditory-related regions due to the ab-
sence of the metronome. These results demonstrate that the
cortical and subcortical areas recruited to support a simple motor
timing task depend crucially on the method used to establish the
temporal reference. Thus, the neural mechanisms underlying time
and timing are highly flexible, reflecting the context in which the
timing is established.
he ability of humans to accurately maintain temporal infor-
mation af ter the removal of external environmental cues is
of ten exploited to investigate the neural basis of internal timing
mechan isms (1). An illustrative approach first used by Stevens
(2) and popularized by Wing and K ristofferson (3) is the
c ontinuation paradigm. The task consists of two stages. In the
first stage (termed pacing), movements are made to coincide
with an external periodic stimulus or metronome. In the sec ond
so-called continuation stage, the metronome is removed and the
subject is required to maintain movement at the rate previously
established during pacing. During c ontinuation it is assumed that
timing is based on internal mechanisms that use a represent ation
of the required interval developed during pacing. When applied
to patient populations, this approach has been central in iden-
tif ying cerebellum and basal ganglia as putative structures
mediating these temporal processes during continuation (46).
More recent functional imaging studies employing this paradigm
have identified broader networks of cortical and subcortical
str uctures underlying timing (7, 8). Although these latter studies
demonstrate that pacing and c ontinuation, in addition to im-
posing similar task demands, activate substantially overlapping
net works, the degree to which the neural areas supporting
c ontinuation are influenced by the network of neural activity
generated during pacing has not been investigated. Here, we
ex plore the relationship between how the time representation is
established during the pacing stage and its later neural expres-
sion when pacing information is removed. We explicitly inquire
into whether changing the way in which a movement rate is
established during pacing modulates the functional network
activated during subsequent continuation.
This question may be crucial because, although synchroniza-
tion is the preferred method of c oordination used during pacing,
it represents only one coordination pattern that can be adopted
to establish rhythmic movements. For instance, both synchron i-
zation and sync opation (moving between beats) are easily per-
for med at low movement rates and can therefore be used
ef fectively to establish pacing. However, within the framework of
c oordination dynamics (9), it is known that synchronization is a
more st able form of c oordination (10–12) that imposes fewer
demands on neural resources than alternative timing relation-
ships such as syncopation (13–15). Even at low movement rates,
sync opation compared with synchronization produces additional
activity across a broad range of cortical and subcortical areas,
including supplement ary motor area (SMA), basal ganglia,
cerebellum, and lateral premotor areas (refs. 14 and 16; see also
ref. 17), structures implicated either directly in the processing of
temporal information (18) or indirectly in nontemporal pro-
cesses, such as attention and working-memory (19), that may
support timing. Although increased or additional activity within
this functional network may reflect an increase in timing de-
mands imposed by the syncopation pattern, it is not clear
whether the network supporting the subsequent continuation
phase (when the metronome is removed and coordination
c onstraints no longer exist) are influenced by this prior context.
To address this question, we used functional MRI to investi-
gate paced finger flexion to an auditory metronome by using a
modified continuation paradigm. During pacing subjects were
directed to c oordinate by using either a synchronized (on the
beat) or syncopated (off the beat) coordination pattern with an
auditory metronome presented at 1.25 Hz. When the metronome
was removed, subjects were instructed to c ontinue moving at the
established rate. Based on existing work (14), we expected
sync opated pacing to result in greater activity within a charac-
teristic c ortical-subcortical network. If the areas supporting
c ontinuation are independent of the method for establishing
pacing (i.e., reflect only the timing demands imposed during
c ontinuation), no differences in activity should be observed
when comparing c ontinuation after synchron ized pacing and
c ontinuation af ter syncopated pacing. An alternative hypothesis
is that the method of pacing influences the activity observed
during continuation. This hypothesis predicts that, during the
c ontinuation phase when no metronome is present, neural
activity reflects not only the task demands of the current
behavior, but also the preceding mode of pacing. As a result,
dif ferences in neural activit y between the two c ontinuation
c onditions should mirror initial differences between synchroni-
zation and sync opation even though behavioral performance
may be, to all intents and purposes, identical.
Abbreviations: SMA, supplementary motor area; STG, superior temporal gyrus; MFG,
middle frontal gyrus; MTG, middle temporal gyrus; BA, Brodmann’s area; BOLD, blood
oxygen level-dependent; IRI, inter-response interval; SII, secondary somatosensory cortex;
PoG, post central gyrus; DLPMC, dorsolateral premotor cortex.
*To whom correspondence should be addressed. E-mail:
© 2004 by The National Academy of Sciences of the USA
www.pnas.orgcgidoi10.1073pnas.0401300101 PNAS
April 27, 2004
vol. 101
no. 17
Fourteen neurologically nor mal volunteers (12 male, 2 female;
mean age 28.5 yr, ranging from 23 to 37) gave infor med consent
to participate in the study. All subjects reported being strongly
right handed. Procedures were carried out in ac cordance with
the guidelines set out by the Internal Review Board at Florida
Atlantic University and the human subject guidelines of the
National Institutes of Health. During pacing, subjects coordi-
nated finger-thumb opposition movements with a series of tones
presented at a const ant rate of 1.25 Hz (pacing c onditions). The
tones were then discontinued, and subjects were required to
c ontinue moving at the same rate in the absence of pacing
(c ontinuation conditions). During pacing, finger movements
were either synchronized with the stimulus such that the point of
peak flexion c oincided with each tone, or syncopated with the
stimulus such that each movement occurred directly in between
c onsecutive tones. Regardless of the coordination pattern during
pacing, subjects were instructed to maintain the movement rate
as accurately as possible during continuation. A single 1-s tone
was presented at the end of the continuation stage signaling the
subject to rest until the start of the next pacing interval. Auditory
stimuli (1,000 Hz sine tones; 60-ms duration) were presented
binaurally to the subject through headphones. Behavioral re-
sponses were recorded as a change in pressure in a small air-filled
pillow placed bet ween the index finger and thumb of the right
MRI. Changes in neural activit y were characterized as changes in
local blood oxygenation [blood oxygen level-dependent (BOLD)
ef fect] by using echo planar imaging on a 1.5-Tesla GE Signa
Scanner (General Electric). Echo-planar images were acquired
by using a single shot, gradient-echo, echo planar pulse sequence
[echo time (TE)repetition time (TR)flip angle (FA)field of
view (FOV) 60 ms3s90°24 cm, 64 64 matrix). Twenty
axial 5-mm-thick slices spaced 2.5 mm prov ide coverage of the
entire brain. High-resolution anatomical spoiled gradient recall
(SPGR) images (TETRFAFOV in-phase325 ms90°24
cm; 5-mm thick ness, 2.5-mm spacing, number of excitations
(NEX) 2) were c ollected at the same slice locations as the
functional images. These images were used to c oregister the
functional scans onto anatomical 3D SPGR axial images (TE
TRFAFOV 5ms34 ms45°24 or 26 cm; resolution
256 256; thickness 2 mm).
A modified block design was used in which a single block
c omprised a rest period (9 images; 27 s) followed by pacing (7
images; 21 s) and c ontinuation (7 images; 21 s) conditions,
respectively. A total of four blocks were completed for both
sync opation and synchronization. Blocks were grouped such that
all syncopation trials were presented together and all synchro-
n ization trials were presented together. The order of grouped
blocks was randomized such that half the subjects started with
sync opation and the other half with synchronization.
Behavioral Analysis. The time of each behavioral response was
defined as the point of maximum compression of the air pillow
(i.e., peak flexion of the index finger and thumb). The time of
each response was corrected by 30 ms to acc ount for the
temporal delay of the pneumatic device as determined by
multiplying the length of the tube by the speed of sound in air.
Two relative measures of perfor mance were calculated. Inter-
response interval (IRI) was defined as the time between con-
secutive behavioral responses, and relative timing (phase) was
defined as the time bet ween each behavioral response and the
preceding stimulus onset, divided by the stimulus period (20). In
addition to motor timing, simple kinematic analysis was per-
for med by averaging individual response profiles for syncopation
and synchronization conditions, respectively. Finally, according
to the two-process model of Wing and Kristofferson (3), variance
and lag-one autoc ovariance measures were computed on the
response intervals observed during continuation to detect rela-
tive changes in variability within putative central clock and motor
mechan isms.
Neuroimaging Analysis. Unless otherwise stated, all analyses were
perfor med by using
AFN I (21, 22). Preprocessing included mo-
tion detection and c orrection followed by spatial smoothing by
c onvolution with a Gaussian kernel [full-width half-maximum
(FWHM) 4 mm] and temporal filtering below 0.1 Hz. Multiple
regression was used to determine the relative contribution of
pacing and continuation model functions to the observed time
series of each voxel. Model time series consisted of vectors
c omprised of ones when a stimulus was present (pacing or
c ontinuation), and zeros other wise, convolved with a hemody-
namic response function. The resulting fit c oefficient for each
regressor of interest was divided by the average offset of each
voxel to give a measure of percent signal change.
SPM99 was used
to coregister functional images to 3D anatomical images that
were later transformed into the c oordinate space of Talairach
and Tournoux (23) before being subjecting to further statistical
To characterize the BOLD activit y elicited by each experi-
ment al condition, group t tests were per formed comparing the
mean of activity for all subjects to rest (no activation). Voxels
were c onsidered t ask related if they, exceeding a statistical
threshold of P 0.0005, were members of a spatially continuous
cluster across an area of at least 500 mm
(c orrected to P 0.01).
Sign ificant differences between experimental c onditions were
assessed by a 2-way ANOVA with factors of mode (synchron ize,
sync opate) and t ask (pace, c ontinue). The resulting statistical
maps were thresholded at P 0.005 and clustered with a
min imum volume of 632 mm
(c orrected P 0.05). A more
stringent threshold was selected for the more robust comparisons
(activation vs. rest) to provide a focused view of the distinct
c ortical and subcortical regions involved in the performance of
the individual c onditions.
Performance. During pacing, subjects successfully produced both
the synchronized and syncopated patterns. The average relative
phase across subject was 17.7 27.9° (mean SD) for synchro-
n ized pacing and 187.9 50.7° for sync opated pacing. Both
patterns are performed w ith similar st ability as indexed by the
SD of the relative phase. No sign ificant dif ference (P 0.05) was
found in the variability of the relative phase between paced
synchron ization (29.8 4.9°) and syncopation (39.6 17.9°).
During all c onditions, subjects were able to produce an
average interval close to the required 800 ms (Fig. 1A). Syn-
chron ization (filled bars) was performed slightly faster than the
metronome with a mean IRI of 791 8.6 ms and 799 50.3 ms
for the pacing and continuation phases, respectively. During
sync opation (open bars), the average response rate was slightly
slower w ith mean IRIs of 812 40.5 ms for pacing and 844
65.3 ms for continuation. A two-way ANOVA per formed using
factors of mode (synchronize and syncopate) and t ask (pacing
and continuation) showed a main effect for mode (F
P 0.016), but no effect of task. All conditions were performed
with similar stability, as reflected in the mean SD (Fig. 1B). SDs
across c onditions ranged from 54 16.97 ms to 63.5 17.18 ms.
A two-way ANOVA showed no significant dif ference between
c onditions.
A paired, two-tailed t test comparing the mean clock variance
(SD, Fig. 1C) during c ontinuation after synchronization (2,782
, left side) and continuation after sync opation (2,333 ms
, left
side) conditions revealed no statistical differences (P 0.12).
Similarly, no differences were observed when comparing the
www.pnas.orgcgidoi10.1073pnas.0401300101 Jantzen et al.
motor variance during c ontinuation (synchronization, 70 ms
sync opation, 68 ms
; P 0.99). These data indicate that,
ac cording to the hierarchical timing model proposed by Wing
and Kristofferson (3), the use of alternative c oordination pat-
terns during pacing does not affect variability in the underlying
timing process, or in the independent motor delay.
Fig. 1D shows the normalized movement profiles averaged
within an 800-ms window centered on the point of peak flexion.
Movement trajectories and amplitude are virtually identical for
synchron ized (solid lines) and sync opated (dotted lines) re-
sponses. Only a slight nonsignificant increase in amplitude is
observed for sync opation, indicating that subjects performed
very similar movement trajectories for both coordination con-
ditions. Taken together, these behavioral results support two
c onclusions. First, subjects were able to perform equally well in
both pacing c onditions, whether synchronizing or syncopating.
Sec ond, regardless of the coordination pattern used during
pacing, reproduction of the required interval during continua-
tion was perfor med basically similar on all behavioral measures.
Neuroimaging. Fig. 2 shows the average parametric maps from
each of the four conditions overlaid on selected slices of an
average anatomical scan. As ex pected, syncopated pacing (c ol-
umn 3) activates a broader network of areas than synchronized
pacing (column 1). These differences carry over into continua-
tion (columns 2 and 4) such that the two continuation conditions
activate substantially different neural net works.
Synchronized Pacing. Regions of significant activation for synchro-
n ized pacing (Fig. 2, column 1) were identified in contralateral
precentral gyr us (PcG), c orresponding to primary sensori-motor
c ortex (M1S1) and extending anteriorly into the ventrolateral
premotor region of the middle front al gyrus (MFG). In addition,
a single activation within the medial wall of the MFG was
identified (corresponding to SMA). Bilateral activity occurred in
more inferior temporal regions, with clusters centered in the
precentral gy rus (PcG) extending from the inferior aspects of the
PcG [corresponding to secondary somatosensory cortex (SII)] to
the superior temporal gyrus (STG). Subcortical activity was
observed in the contralateral putamen and in the lateral declive
of the ipsilateral cerebellum.
Synchronized Continuation. Synchronized c ontinuation showed a
very similar activit y pattern to synchronized pacing, with clusters
located within contralateral M1, SMA, and ventrolateral pre-
motor region (column 2). In addition, a small cluster was present
in the inferior lateral portion of the post central gyrus (PoG), a
region in the vicinity of SII. A final cluster of activity was
observed within the ipsilateral declive. Neither the putamen nor
the STG was active, the latter likely related to the absence of the
auditory stimulus.
Syncopated Pacing. Syncopated pacing resulted in a broader
net work of activity than synchronized pacing. In addition to
those regions active during synchronization, syncopated pacing
(Fig. 2, column 3) resulted in activity bilaterally in dorsolateral
premotor cortex (DLPMC). In addition, MFG activation ex-
tended bilaterally into both the lef t and right SM A and inferiorly
into the cingulate. Activations centered in bilateral PoG ex-
Fig. 1. Means (A) and SDs (B) of the IRIs for both synchronization (filled) and syncopation (open) conditions. The dashed line in A marks the required response
interval. (C) Covariance analysis separating the response variability into a clock component (shaded) and a motor component (filled). (D) Mean movement profile
averaged across synchronization (solid lines) and syncopation (dotted lines) conditions shown together with the SD. For A, B, and C, error bars are at 1 SD.
Jantzen et al. PNAS
April 27, 2004
vol. 101
no. 17
tended into STG, the planum temporale, and the insula, encom-
passing large portions of both primary auditory cortex (A1) and
SII. In addition to subcortical activity in the left put amen,
thalamus, and right declive, significant BOLD activity was also
observed more inferiorly in bilateral caudate.
Syncopated Continuation. The activations observed during sync o-
pated continuation (Fig. 2, column 4) paralleled those described
for syncopated pacing. Moreover, the number and extent of
active regions was much greater for syncopated than synchro-
n ized c ontinuation. Activation was found in bilateral DLPMC,
SM A, cingulate, and also in the inferior pariet al lobe [Brod-
mann’s area (BA) 40]. A single large contralateral cluster
centered on the left post central gyrus BA3 encompassed M1, S1,
and also extended inferolaterally to include the SII region of the
PoG but did not extend beyond the lateral fissure into auditory
regions. A similar smaller cluster extended laterally and inferi-
orly into the SII region on the ipsilateral side. Bilateral middle
temporal gyrus (MTG, BA22), superior frontal gyrus, and insula
were also significantly activated during syncopated continuation.
Subc ortical activity occurred in bilateral caudate and put amen,
lef t thalamus, and bilaterally in the cerebellum.
Statistical Comparisons. Main ef fects from the t wo-way ANOVA
are displayed in Fig. 3. Areas demonstrating a sign ificant main
ef fect for task (Fig. 3A, pacing continuation) were identified
exclusively in bilateral superior temporal g yrus (for det ails, see
t able 1). These effects resulted from greater activity during
pacing than during continuation and reflect a decrease in activity
in primary auditory cortex in the absence of the metronome.
Areas demonstrating a main effect of mode (syncopation
synchron ization) are shown in Fig. 3B. Significant cortical ac-
tivity (Table 1) was found in the medial (SMA) and right lateral
(DLPMC and left prefrontal c ortex, BA10) portions of the
MFG, left superior parietal lobe, and the right MTG. Subcortical
clusters were identified in the right caudate extending into the
thalamus, the lef t ventral posterior lateral nucleus of the thal-
amus, as well as bilaterally in the culmen of the cerebellum.
There were no voxels showing a significant mode task
interaction, indicating that the observed differences between
synchron ization and syncopation occurred during both pacing
and continuation.
A possible explanation of greater BOLD activity during
c ontinuation after syncopation is that of ‘‘carry-over’’ of the
hemodynamic response generated during the preceding pacing
phase. To evaluate this methodological issue, we investigated the
hemodynamic response to the dif ferent t ask conditions within
Fig. 2. Average parametric maps from the four experimental conditions
overlaid on selected slices of an average anatomical scan. Data from each
condition are organized into columns. M1S1, primary sensorimotor cortex;
thal, thalamus; put, putamen.
Fig. 3. Results from a two-way ANOVA. (A) A main effect for task (pacing vs.
continuation) was observed in bilateral STG. (B) A main effect for mode
(syncopate vs. synchronize) occurred in several regions, including SMA, left
superior parietal lobe (SPL), left DLPMC, left MFG, right MTG, bilateral thal-
amus, right caudate, and bilateral culmen.
Table 1. Brain regions showing significant effects
Side xyzVol, cm
BA Region
Pacing continuation
L 47 21 11 6.99 41 STG
R5220 15 5.05 40 STG
Synchronization syncopation
B 0 3 46 5.67 32 SMA
L 24 3 53 3.28 6 MFG
L 12 55 61 7.74 7 SPL
L 28 40 23 5.85 10 MFG
R6222 6 2.19 21 MTG
R163 20 2.26 - Caudate
L 19 19 7 2.16 - VPL
L 14 37 17 2.24 - Culmen
R2843 28 1.88 - Culmen
L 30 50 33 2.08 - Tonsil
L, left; R, right; B, bilateral; SPL, superior parietal lobe; VPL, ventro posterior
lateral thalamus.
www.pnas.orgcgidoi10.1073pnas.0401300101 Jantzen et al.
key brain regions. Representative mean functional time series
averaged across voxels and presentation blocks within three
functionally defined regions of interest (ROI) are illustrated in
Fig. 4. Also plotted are t wo model functions (dashed lines)
derived by convolv ing a hemodynamic response function with
boxcars representing the pacing phase alone (early return to
baseline) and the pacing and c ontinuation phases together (later
return to baseline). As expected, BOLD signal increases in
c ontralateral primary motor area (M1) remain elevated across
pacing (filled bars) and c ontinuation (shaded bars) blocks for
both the syncopation (open circles) and synchronization (Xs)
c onditions. This sustained activity reflects the continuous nature
of the movement. Within primary auditory cortex (A1), a
decrease in BOLD amplitude is associated with the end of the
pacing phase for both syncopation and synchronization. The
mean time series corresponds well to the function that explicitly
models BOLD increases only during pacing and is consistent
with the ANOVA result showing sign ificant difference in BOLD
signal amplitude between continuation and pacing within STG.
The final time series is f rom the SMA where, according to the
st atistical analysis, BOLD signal amplitude was unaffected by
the transition from pacing to continuation but was sensitive to
the coordination pattern (differences between syncopation and
synchron ization). It is clear from this trace that activity during
c ontinuation is not a result of a slow return to baseline after
pacing (see A1) but signifies persistent activation that does not
begin to decline until the end of the continuation phase.
This research provides insight into the neural basis of coordi-
nation and timing by exploiting two well established paradigms,
the syncopation-synchronization paradigm of coordination dy-
namics and the continuation paradigm of classical motor pro-
gram theory. Results demonstrate how neural areas recruited in
the perfor mance of a simple timing behavior not only reflect the
temporal and motor demands of the task at hand, but also seem
to be strongly influenced by the way in which the required
temporal interval is established. During continuation, the pat-
tern of hemodynamic activity generated in the production of
paced finger flexion was considerably different when the pacing
was established by using the syncopated pattern compared with
the synchronized one. On the other hand, when comparing the
t wo c ontinuation c onditions with their respective pacing coun-
terparts, the only common difference was a relative decrease in
activity within auditory processing areas. This finding leads to
the interesting consequence that two related but different timing
net works were invoked to support a simple self-paced motor
t ask.
The general pattern of activity supporting continuation after
synchron ization reported here bears similarity to the results of
Ja¨ncke et al. (8), who also observed no statistical difference
bet ween auditory synchron ization and continuation. Several
dif ferences are noted, however, when comparing the current
results with those of Rao et al. (7). During synchron ized pacing,
in addition to those areas of activation reported by Rao et al. (7),
we observed additional activity in SMA, put amen, and insula
whereas the STG activity reported by Rao et al. (7) was modest
in c omparison with that reported here. Furthermore, whereas we
show no significant dif ference bet ween synchron ization and
c ontinuation, Rao et al. (7) indicate that continuation results in
additional activity in SMA, thalamus, putamen, and inferior
f rontal gyrus. However, care must be taken in interpreting the
Rao et al. (7) results because a statistical comparison between
pacing and continuation conditions was not performed. Al-
though the source of dif ferences between the current results and
those of Rao et al. (7) is not immediately clear, differences in
analysis and ex perimental parameters (such as movement rate)
may certainly contribute.
The location of regions showing significantly greater activit y
during syncopated pacing compared with synchronized pacing
are in agreement with those reported recently by Mayv ille et al.
(14). Increased activity within subsystems associated with timing
(basal ganglia and cerebellum) (46, 18) motor planning and
preparation (SMA and dorsal-premotor) (24), and working
memory and attention (prefrontal c ortex, superior pariet al lobe,
and MTG) (19) have been postulated to reflect increases in
c ognitive demand for performance of the off-the-beat c oordi-
nation pattern. What is most interesting, however, is that these
dif ferences in neural activit y are still observed during continu-
ation when no metronome is present and the specific cognitive
c onstraints ex pressed during pacing no longer exist.
Dif ferentiation in BOLD activity between syncopation and
synchron ization and the subsequent differences between con-
tinuation conditions cannot be explained by the presence of
dif ferences in behavioral parameters. Although there is evidence
that the BOLD signal may be modulated by movement param-
eters such as rate (25) and force (26), the similarity of the
movement profiles for the two coordination modes indicates that
movement parameters did not significantly influence the present
results. Similarly, differences in BOLD amplitude were not
related to overall performance of the task, as indicated by the
mean and standard deviation of the IRI. These per formance
dat a further suggest that both syncopation and synchron ization
Fig. 4. BOLD time series from a representative subject are averaged across
presentation blocks and voxels within three regions of interest (ROI). Func-
tionally defined ROI were identified in contralateral precentral gyrus (M1),
STG (A1), and in the medial aspect of the MFG (SMA). Dashed lines show
theoretical bold responses to the pacing phase alone (filled bar) or pacing and
continuation together (shaded bar). Mean signals are shown for both synco-
pation (open circles) and synchronization (X). BOLD amplitude is shown on the
vertical axis and time in terms of scan repetitions [repetition time (TR) 3s]
relative to the onset of the rest period is shown on the horizontal axis.
Jantzen et al. PNAS
April 27, 2004
vol. 101
no. 17
were adequate in generating a representation of the required
movement interval.
Increases in clock variance (and in some cases motor variance)
have been demonstrated to occur in patient populations suffering
from cerebellar lesions (6), frontal lobe lesions (27), and Parkin-
son’s disease (4, 5), and in normal participants when simultaneously
performing a secondary task (28). However, although BOLD
increases within basal ganglia, cerebellum, and frontal areas, as
seen during syncopated continuation, may be considered as repre-
senting greater demand within similar subsystems as those affected
in patient populations, no concomitant increase in clock variance
was observed. Such a result suggests that recruitment of a broader
cortical-subcortical network during syncopated continuation com-
pensates for increased temporal demand, allowing for stable per-
formance of interval production.
Dif ferential expression of neural activity during synchroniza-
tion and syncopation may reflect the functioning of distinct
processing networks such as those postulated recently by Lewis
and Miall (29) for automatic and c ognitively controlled timing.
A ll ex perimental conditions in the present study activated a
net work c ompatible with the automatic, motor-related timing
net work (M1, SMA, basal ganglia, and cerebellum). However,
the additional activity during syncopation tasks in prefrontal,
dorsolateral premotor, and parietal areas is compatible with
increased participation of memory and attention processes,
presumably reflecting increased cognitive control (29). More-
over, this interpretation is consistent with behavioral findings
showing that anti-phase relationships impose greater cognitive
and attentional demands than in-phase patterns (17, 30). Within
the current context, this finding not only suggests that different
timing networks are required for the performance of the differ-
ent pacing patterns, but that once established, the same timing
net works c ontinue to operate during continuation.
Our results show that a more restricted timing network than
the one used after syncopation can clearly meet the motor and
temporal demands of continuation. This finding leads to the
question of why the more extended network recruited for
sync opation persists during continuation. A lthough other me-
diating factors may contribute, one distinct possibility is that
these BOLD patterns reflect differential representation of tem-
poral information during the two pacing phases. Most popular
process models of interval timing propose the existence of
specific mechanisms for representing and storing temporal in-
tervals (31–33). However, there has been little consideration of
the specific neural form this memory might take. Based on the
present results, we propose that the pattern of activity within and
across the various subsystems involved in pacing may c omprise
specific sensory-motor and timing infor mation required for
ac curate performance during continuation. The global pattern
of neural activity that underlies temporal information and
processing may thus be defined not only by activity within
functionally specific timing regions, but also by the connectivity
or c ommunication between regions. Thus, the same timing
net work recruited to meet the constraints of the syncopated
c oordination pattern must also be used during subsequent
c ontinuation, or as long as the temporal information continues
to be referenced. The overriding consequence of this proposed
mechan ism is that substantially dif ferent networks bec ome
recr uited for processing of the same temporal task.
A primary goal of studies employing the continuation para-
digm is to add to our understanding of the neural structures and
processes underlying timing (1). Imperative to this understand-
ing is an appreciation for the deg ree to which the networks
revealed by using this paradigm are dependent on the experi-
ment al context. Although it is recognized that pacing and
c ontinuation involve partially overlapping task demands and
engage similar neural systems (7, 8), the specific role that the
pacing plays in determining brain mechanisms mediating con-
tinuation has not previously been considered. Results presented
here strongly suggest that neural activity underlying continuation
does not generalize across all timing c ontexts but is strongly
influenced by the prior pacing context. It seems that, with respect
to the distributed neural networks engaged, both time (in the
for m of time interval infor mation) and timing (in the form of a
sensorimotor relationship) play an integral role in the venerable
c ontinuation paradigm.
We are g rateful to a reviewer for proposing the carry-over hypothesis and
encouraging us to test it. This work was supported by National Institute
of Mental Health Grants MH42900 and MH01386.
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www.pnas.orgcgidoi10.1073pnas.0401300101 Jantzen et al.
... Finger-tapping studies assess how participants use their mental timing system in a manner that is independent of other motor behavior or feedback mechanisms [4][5][6] . Two leading derivatives of the sensorimotor synchronization approach are synchronization-continuation and syncopation-continuation tasks (tapping on the beat, or off the beat respectively) 7,8 . In these approaches, participants are initially entrained to an external stimulus, such as an auditory tone. ...
... Our results provide insight into the influence of the broader experimental context on timing behavior and the underlying neural activity that supports it, an interpretation consistent with several previous findings 7,8,36 . Thus, representation of timing information is formed in a context-dependent manner, with the introduction of different cognitive states or expectations, as well as difficulty levels, impacting behavioral performance and the corresponding neural engagement supporting it. ...
Full-text available
Procedures used to elicit both behavioral and neurophysiological data to address a particular cognitive question can impact the nature of the data collected. We used functional near-infrared spectroscopy (fNIRS) to assess performance of a modified finger tapping task in which participants performed synchronized or syncopated tapping relative to a metronomic tone. Both versions of the tapping task included a pacing phase (tapping with the tone) followed by a continuation phase (tapping without the tone). Both behavioral and brain-based findings revealed two distinct timing mechanisms underlying the two forms of tapping. Here we investigate the impact of an additional—and extremely subtle—manipulation of the study’s experimental design. We measured responses in 23 healthy adults as they performed the two versions of the finger-tapping tasks either blocked by tapping type or alternating from one to the other type during the course of the experiment. As in our previous study, behavioral tapping indices and cortical hemodynamics were monitored, allowing us to compare results across the two study designs. Consistent with previous findings, results reflected distinct, context-dependent parameters of the tapping. Moreover, our results demonstrated a significant impact of study design on rhythmic entrainment in the presence/absence of auditory stimuli. Tapping accuracy and hemodynamic responsivity collectively indicate that the block design context is preferable for studying action-based timing behavior.
... Overall, the network of brain regions involved in processing complex rhythms is more extensive than both the a) deactivations found for this same analysis and b) the Beat-based (audio-motor control baseline) analysis. Our results align well with findings from Jantzen et al. (2004) who found a much broader network of activity for syncopated tapping compared to synchronization (i.e., isochronous rhythmic pacing) (Jantzen et al., 2004), which may be considered analogous to our more vs. less complex stimulus categorization. ...
... Overall, the network of brain regions involved in processing complex rhythms is more extensive than both the a) deactivations found for this same analysis and b) the Beat-based (audio-motor control baseline) analysis. Our results align well with findings from Jantzen et al. (2004) who found a much broader network of activity for syncopated tapping compared to synchronization (i.e., isochronous rhythmic pacing) (Jantzen et al., 2004), which may be considered analogous to our more vs. less complex stimulus categorization. ...
We conducted a systematic review and meta-analysis of 30 functional magnetic resonance imaging studies investigating processing of musical rhythms in neurotypical adults. First, we identified a general network for musical rhythm, encompassing all relevant sensory and motor processes (Beat-based, rest baseline, 12 contrasts) which revealed a large network involving auditory and motor regions. This network included the bilateral superior temporal cortices, supplementary motor area (SMA), putamen, and cerebellum. Second, we identified more precise loci for beat-based musical rhythms (Beat-based, audio-motor control, 8 contrasts) in the bilateral putamen. Third, we identified regions modulated by beat based rhythmic complexity (Complexity, 16 contrasts) which included the bilateral SMA-proper/pre-SMA, cerebellum, inferior parietal regions, and right temporal areas. This meta-analysis suggests that musical rhythm is largely represented in a bilateral cortico-subcortical network. Our findings align with existing theoretical frameworks about auditory-motor coupling to a musical beat and provide a foundation for studying how the neural bases of musical rhythm may overlap with other cognitive domains.
... Several studies showed that depending on the task and timescale, many areas had been implicated in different temporal contexts [39][40][41][42][43][44][45][46] . The results of these previous studies suggest that Previous studies reported that the basal ganglia are activated in timing tasks with different effectors 42 , sensorimotor domains 47,48 , and duration scales 49 . ...
Full-text available
An accurate sense of time is crucial in flexible sensorimotor control and other cognitive functions. However, it remains unknown how multiple timing computations in different contexts interact to shape our behavior. We asked humans to perform timing tasks that differed in the sensorimotor domain (sensory timing vs. motor timing) and effector (hand vs. saccadic eye movement). To understand how these different behavioral contexts contribute to timing behavior, we applied a three-stage Bayesian model to behavioral data. We found that these behavioral contexts affect different stages of computations about time. Moreover, our results indicated that the mode of response also affects computations related to measuring and sensing time. These findings suggest that both context-specific and context-invariant computations contribute to shaping our timing behavior.
... Although the ribbon is a physical connection, the coordination observed in MCR is clearly informational and presumably relies on an intact nervous system. In this regard, although we know quite a lot about the neural circuitry (DeLuca et al. 2010;Jantzen et al. 2004) and dynamics Mayville et al. 2002) involved in simple synchronization and syncopation tasks, developmental research using fMRI is at a very early stage (Mullally and Maguire 2014). Combining MCR with modern brain imaging methods is thus highly desirable. ...
The question of agency and directedness in living systems has puzzled philosophers and scientists for centuries. What principles and mechanisms underlie the emergence of agency? Analysis and dynamical modeling of experiments on human infants suggest that the birth of agency is due to a eureka-like, pattern-forming phase transition in which the infant suddenly realizes it can make things happen in the world. The main mechanism involves positive feedback: when the baby's initially spontaneous movements cause the world to change, their perceived consequences have a sudden and sustained amplifying effect on the baby's further actions. The baby discovers itself as a causal agent. Some implications of this theory are discussed. What Is this 'I'? We humans tend to believe that we are agents, masters and mistresses of our fate, that our deeds and desires are our destiny. Yet, despite a sizeable literature on 'the sense of agency' and its behavioral and neuroimaging correlates (see [1,2] for recent reviews), the scientific basis of causal agency and how we come to experience ourselves as agents is lacking. Agency means action towards an end. When it comes to the behavior of living things, our inability to understand end-directedness forces us to posit (often implicitly) an intelligent agent residing somewhere inside the system that is responsible for the end-directed behavior we observe. The self as a causal agent remains a ghost in the machine awaiting exorcism, perhaps by new insights from the brain and cognitive sciences. Charles Darwin, in On the Origin of Species, touched only briefly on the topic of agency, although he noted how 'admirably adapted' was the woodpecker to catch insects under the bark of trees and how mistletoe 'absolutely' required the agency of certain insects to bring pollen from one flower to another ([3] p.12). His later work on the habits of worms notwithstanding [4], Darwin admitted 'I must promise that I have nothing to do with the origin of the primary mental powers, any more than I have with life itself' ([3] p.189). In the introduction to his remarkable history of physiological psychology, Franklin Fearing [5] noted that 'Even before man speculated about the nature and source of his own experiences, he was probably curious about the agencies by which animal motion was effected' ([5] p.1). Life and motion, Fearing remarks, are almost synonymous terms. In his famous book What Is Life?, Erwin Schrödinger [6], one of the chief architects of quantum mechanics and the author of the famous equation that bears his name, proposed an 'order from order' principle as the physical basis of life. Schrödinger speculated that this new kind of order took the form of an aperiodic crystal, later exposed as the beautiful double helical structure of the DNA molecule [7]. Not much more was said about Schrödinger's order from order principle or his call for 'new laws to be expected in the organism' (but see [8,9]). Still less truck was given to the question raised by Schrödinger in the final chapter of his small book. Each of us, says Schrödinger, has the indisputable impression that the sum total of our own experience and Trends Over the past 30 years, higher-order principles of self-organizing dynamical systems have influenced our understanding of brain, cognition, and behavior. They might also offer insights into age-old puzzles about the origins of agency and directedness in living things. Experiments and observations of human infants combined with theoretical modeling suggest that the birth of agency corresponds to a eureka-like phase transition in a coupled dynamical system whose key variables span the interaction between the baby and its environment. Analysis shows that the main mechanism underlying the emergence of agency is autocatalytic and involves positive feedback. When the baby's initially spontaneous movements cause the world to change, their perceived consequences have a sudden and sustained amplifying effect on the baby's further actions. The prelinguistic baby realizes it can make things happen!
... The former type of task is expected to engage the motor circuitry associated with timing tasks, such as motor cortical areas, cerebellum, and basal ganglia, with some studies suggesting even stronger involvement of the premotor cortex and cerebellum with such externally paced movement than when a tempo is internally maintained (Del Olmo et al., 2007;Kornysheva and Schubotz, 2011), like in the continuation phase of synchronization-continuation tasks. While a few studies suggest the same areas to be involved in continuation as in synchronization (Jäncke et al., 2000;Jantzen et al., 2004), continuation tapping after an external stimulus has faded might elicit additional activation in primary sensory and motor cortices (Gerloff et al., 1998), premotor cortex, SMA (Serrien, 2008), thalamus, and basal ganglia (specifically, putamen; Lewis et al., 2004). One study also demonstrated that a prefrontal-parietal-temporal network, containing the dorsal and ventral prefrontal cortex, middle temporal gyrus, and parietal lobes, may be especially activated during continuation tapping (Jantzen et al., 2007). ...
Full-text available
Sensorimotor synchronization (SMS), the coordination of physical actions in time with a rhythmic sequence, is a skill that is necessary not only for keeping the beat when making music, but in a wide variety of interpersonal contexts. Being able to attend to temporal regularities in the environment is a prerequisite for event prediction, which lies at the heart of many cognitive and social operations. It is therefore of value to assess and potentially stimulate SMS abilities, particularly in aging and neurocognitive disorders (NCDs), to understand intra-individual communication in the later stages of life, and to devise effective music-based interventions. While a bulk of research exists about SMS and movement-based interventions in Parkinson’s disease, a lot less is known about other types of neurodegenerative disorders, such as Alzheimer’s disease, vascular dementia, or frontotemporal dementia. In this review, we outline the brain and cognitive mechanisms involved in SMS with auditory stimuli, and how they might be subject to change in healthy and pathological aging. Globally, SMS with isochronous sounds is a relatively well-preserved skill in old adulthood and in patients with NCDs. At the same time, natural tapping speed decreases with age. Furthermore, especially when synchronizing to sequences at slow tempi, regularity and precision might be lower in older adults, and even more so in people with NCDs, presumably due to the fact that this process relies on attention and working memory resources that depend on the prefrontal cortex and parietal areas. Finally, we point out that the effect of the severity and etiology of NCDs on sensorimotor abilities is still unclear: More research is needed with moderate and severe NCD, comparing different etiologies, and using complex auditory signals, such as music.
... The variation of rate of stimuli using plateaus showed that difference across a range of rate. This original and unexpected results calls for new modelling (See promising perspectives in Ermentrout, 1991, and in the same vein Savinov et al., 2021), and neuroimaging studies (Jantzen et al., 2004;Nozaradan et al., 2016). ...
Full-text available
The present study examines to what extent cultural background determines sensorimotor synchronization in humans. The direct comparison of Indian and French students, without particular experience in music or dance, or sport, was motivated by the hypothesis that musical exposure to different musical styles causes a variation in basic synchronization to sound function. At first rate limits of this capacity was sought, using a parametric design increasing the sound periodic frequency up to synchronization breakdown. No robust effect was found in that respect. However, another unpredicted change of the so-called negative mean asynchrony was found. Negative mean asynchrony is defined as the anticipation of movement with respect to sound, of about 40ms. The negative mean asynchrony simply disappears in Indians' participants. This result is very intriguing as negative mean asynchrony was considered ubiquitous for decades, and an invariant hallmark of human timing function. Revision of theoretical modelling of sensorimotor synchronization may be required to account to the found variation. Previous modelling attempts in terms of so-called anticipatory or delayed processes are likely to be revised. A larger adaptation to rate of events, like the one proposed by Bard Ermentrout (1991) to account for reduced phase shift in firefly Pteroptyx malaccae, offers some modelling avenues.
... The Jantzen et al. [153] paper shows that different patterns of behavior are realized by the same cortical circuitry (multifunctionality). Earlier, it was shown that the same overt patterns of behavior [155] and cognitive performance [156] can be produced by different cortical circuitry (degeneracy). Together with the Meyer-Lindenberg et al. study, the Jantzen et al. [153] work demonstrates that dynamic stability and instability are major determinants of the recruitment and dissolution of brain networks, providing flexibility in response to control parameter changes (see also [157]). ...
... The actual experiment consisted of a so-called continuation paradigm (see [104] for the neural underpinnings of this paradigm) in which multiple human subjects (N = 8 per group) arranged in an octagon tapped together rhythmically on a set of touch pads [103]. This is called the continuation paradigm because each person in the group is first paced by a (here visual) metronome at a certain frequency for 10 s, after which the metronome is switched off and the task is to continue tapping for another 50 s. ...
Full-text available
Coordination is a ubiquitous feature of all living things. It occurs by virtue of informational coupling among component parts and processes and can be quite specific (as when cells in the brain resonate to signals in the environment) or nonspecific (as when simple diffusion creates a source–sink dynamic for gene networks). Existing theoretical models of coordination—from bacteria to brains to social groups—typically focus on systems with very large numbers of elements (N→∞) or systems with only a few elements coupled together (typically N = 2). Though sharing a common inspiration in Nature’s propensity to generate dynamic patterns, both approaches have proceeded largely independent of each other. Ideally, one would like a theory that applies to phenomena observed on all scales. Recent experimental research by Mengsen Zhang and colleagues on intermediate-sized ensembles (in between the few and the many) proves to be the key to uniting large- and small-scale theories of coordination. Disorder–order transitions, multistability, order–order phase transitions, and especially metastability are shown to figure prominently on multiple levels of description, suggestive of a basic Coordination Dynamics that operates on all scales. This unified coordination dynamics turns out to be a marriage of two well-known models of large- and small-scale coordination: the former based on statistical mechanics (Kuramoto) and the latter based on the concepts of Synergetics and nonlinear dynamics (extended Haken–Kelso–Bunz or HKB). We show that models of the many and the few, previously quite unconnected, are thereby unified in a single formulation. The research has led to novel topological methods to handle the higher-dimensional dynamics of coordination in complex systems and has implications not only for understanding coordination but also for the design of (biorhythm inspired) computers.
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Background Several psychiatric diseases impair temporal processing. Temporal processing is thought to be based on two domains: supra-second intervals and sub-second intervals. Studies show that temporal processing in sub-second intervals is mainly an automated process. However, the brain functions involved in temporal processing at each time scale remain unclear. We hypothesized that temporal processing in supra-second intervals requires several brain areas, such as the ventrolateral prefrontal cortex, intraparietal sulcus (IPS), and inferior parietal lobe, corresponding to various cognitions in a time scale-dependent manner. We focused on a dual-task paradigm (DTP) involving simultaneous performance of cognitive and motor tasks, which is an effective method for screening psychomotor functions; we then designed a DTP comprising finger tapping at various tempi as the temporal processing task and two cognitive tasks (mental arithmetic and reading) that might affect temporal processing. We hoped to determine whether task-dependent interferences on temporal processing in supra-second intervals differed depending on the cognitive tasks involved. Methods The study included 30 participants with no history of neuromuscular disorders. Participants were asked to perform a DTP involving right index finger tapping at varying tempi (0.33, 0.5, 1, 2, 3, and 4 s inter-tapping intervals). Cognitive tasks comprised mental arithmetic (MA) involving three-digit addition, mental reading (MR) of three- to four-digit numbers, and a control (CTL) task without any cognitive loading. For comparison between tasks, we calculated the SDs of the inter-tapping intervals. Participants’ MA abilities in the three-digit addition task were evaluated. Results The MA and MR tasks significantly increased the SDs of the inter-tapping intervals compared to those of the CTL task in 2–3 s and 3–4 s for the MA and MR tasks, respectively. Furthermore, SD peaks in the finger-tapping tasks involving MA were normalized by those in the CTL task, which were moderately correlated with the participants’ MA ability ( r = 0.462, P = 0.010). Discussion Our results established that DTP involving the temporal coordination of finger-tapping and cognitive tasks increased temporal variability in a task- and tempo-dependent manner. Based on the behavioral aspects, we believe that these modulations of temporal variability might result from the interaction between finger function, arithmetic processing, and temporal processing, especially during the “pre-semantic period”. Our findings may help in understanding the temporal processing deficits in various disorders such as dementia, Parkinson’s disease, and autism.
Purpose: Visuospatial disorders (VSDs) are common in Parkinson's disease (PD). VSDs may involve cerebellar vermis, but evidence from functional connectivity (FC) studies is lacking. Here we compared FC between cerebellar vermis and the entire brain between PD patients with or without VSD, and between patients and healthy controls. Methods: Resting-state 3.0-T functional magnetic resonance imaging was performed on 19 controls, 31 PD patients with VSD and 12 PD patients without VSD. Correlations in brain network were calculated between eight regions of interest in the cerebellar vermis (I-VIII) and other voxels in the brain, and voxel-based FC was analyzed. Patients were assessed in terms of cognitive function as well as motor and non-motor symptoms. Results: In both types of patients, cerebellar vermis VIII, IX and X showed positive FC with the default-mode network (DMN), executive control network and sensorimotor network. Cerebellar vermis I and II showed positive FC with the visual network and DMN in controls, but negative FC in PD patients without VSD. Cerebellar vermis X showed negative FC with lobules VIII and IX of the left cerebellar hemisphere in controls, but positive FC in PD patients with VSD. Conclusion: Positive FC connecting the cerebellar vermis VIII and X with associated brain networks in PD patients with VSD may be compensatory activation. PD may involve disruption of functional coupling between the cerebellar vermis and cerebral cortex.
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A model for the timing of repetitive discrete motor responses is proposed, and a prediction of negative dependency between successive interresponse intervals is confirmed by data from a Morse key tapping task. A method that makes use of the first-order serial correlation between interresponse intervals is used to distinguish between variance due to a timekeeping process and variance in motor response delays subsequent to the timekeeper. These two quantities are examined as a function of mean interresponse interval.
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That animals and humans can accomplish the same goal using different effectors and different goals using the same effectors attests to the remarkable flexibility of the central nervous system. This phenomenon has been termed 'motor equivalence', an example being the writing of a name with a pencil held between the toes or teeth. The idea of motor equivalence has reappeared because single-cell studies in monkeys have shown that parameters of voluntary movement (such as direction) may be specified in the brain, relegating muscle activation to spinal interneuronal systems. Using a novel experimental paradigms and a full-head SQUID (for superconducting quantum interference device) array to record magnetic fields corresponding to ongoing brain activity, we demonstrate: (1), a robust relationship between time-dependent activity in sensorimotor cortex and movement velocity, independent of explicit task requirements; and (2) neural activations that are specific to task demands alone. It appears, therefore, that signatures of motor equivalence in humans may be found in dynamic patterns of cortical activity.
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Learning a bimanual coordination task (synchronization to a visually specified phasing relation) was studied as a dynamical process over 5 days of practicing a required phasing pattern. Systematic probes of the attractor layout of the 5 Ss' coordination dynamics (expressed through a collective variable, relative phase) were conducted before, during, and after practice. Depending on the relationship between the initial coordination dynamics (so-called intrinsic dynamics) and the pattern to be learned (termed behavioral information, which acts as an attractor of the coordination dynamics toward the required phasing), qualitative changes in the phase diagram occurred with learning, accompanied by quantitative evidence for loss of stability (phase transitions). Such effects persisted beyond 1 week. The nature of change due to learning (e.g., abrupt vs. gradual) is shown to arise from the cooperative or competitive interplay between behavioral information and the intrinsic dynamics.
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Temporal discrimination was investigated by the methods of production, reproduction, constant stimuli, single stimuli, and estimation. The Weber function was found to give a good fit to the relation between ΔT and T; evidence was obtained that a dip in the Weber function at a short interval is not an essential feature of time estimation but may be due to the development of rhythmic modes of response or other factors. Productions or reproductions of intervals tend to lengthen during the course of a session at a rate proportionately greater for short intervals; but estimates tend to shorten. A model for the "internal clock" is described, based on a pacemaker, counter, store, and comparator with functional relations tending to reduce error, and it is shown to provide explanations for the Weber function, the indifference interval, overestimation of short and underestimation of long intervals, the features of "lengthening," assimilation, and other findings.
Coordination represents one of the most striking, most taken for granted, but least understood features of living things. Recently a new foundation for understanding coordination has emerged called Coordination Dynamics. This book brings together scientists from all over the world who have defined and developed the field of Coordination Dynamics. Grounded in the concepts of self-organization and the tools of nonlinear dynamics, appropriately extended to handle informational aspects of living things, Coordination Dynamics aims to understand the coordinated functioning of a variety of different systems at multiple levels of description. The book addresses the themes of Coordination Dynamics and Dynamic Patterns in the context of the following topics: Coordination of Brain and Behavior, Perception-Action Coupling, Control, Posture, Learning, Intention, Attention, and Cognition.
This study investigated the effects of different types of neurological deficits on timing functions. The performance of Parkinson, cerebellar, cortical, and peripheral neuropathy patients was compared to age-matched control subjects on two separate measures of timing functions. The first task involved the production of timed intervals in which the subjects attempted to maintain a simple rhythm. The second task measured the subjects' perceptual ability to discriminate between small differences in the duration of two intervals. The primacy of the cerebellum in timing functions was demonstrated by the finding that these were the only patients who showed a deficit in both the production and perception of timing tasks. The cerebellar group was found to have increased variability in performing rhythmic tapping and they were less accurate than the other groups in making perceptual discriminations regarding small differences in duration. Critically, this perceptual deficit appears to be specific to the perception of time since the cerebellar patients were unaffected in a control task measuring the perception of loudness. It is argued that the operation of a timing mechanism can be conceptualized as an isolable component of the motor control system. Furthermore, the results suggest that the domain of the cerebellar timing process is not limited to the motor system, but is employed by other perceptual and cognitive systems when temporally predictive computations are needed.
Using a circular 37-SQUID (superconducting quantum interference device) sensor array, we observe spontaneous transitions in neuromagnetic field patterns in the human brain which occur at a critical value of a systematically varied behavioral parameter. Coherent states of both brain and behavior are captured by the spatiotemporal pattern of phase relations among participating components. Such observations support the thesis that the brain is a pattern forming system that can switch flexibly from one coherent state to another.
A series of experiments measured human ability to discriminate between durations of auditory signals presented in a noise background. Independent variables were the signal voltage, the “base” duration T, and the increment duration ΔT. Separate experiments assessed the effect of each of these on discrimination. A decision‐theoretical model is presented, based on a “counting mechanism,” which operates on impulses generated over the relevant durations. The source of these impulses is assumed to be random. Limitations on performance come from uncertainty regarding the end points of the time interval and from limited memory. The decision processes underlying the model are presented as a general theory of duration discrimination.
The academic achievement and extracurricular achievements in science, art, writing, dramatics, music, and leadership during the 1st year in college of a large national sample of high aptitude students were predicted from an assessment of their aptitudes, originality, self-ratings, aspirations, personality, interests, home backgrounds, and the child rearing attitudes of their parents. The 0-order and multiple correlations between predictors and criteria were presented and discussed. The findings revealed a number of nonintellective predictors of the college achievement criteria.