Cerebral Cortex March 2006;16:321--327
doi:10.1093/cercor/bhi108
Advance Access publication May 18, 2005
Attentional Modulation of Cortical
Neuromagnetic Gamma Response to
Biological Movement
Processing of biological motion represented solely by a set of lights
on the joints of a human body is traditionally viewed as largely
independent of attention. Here, by manipulating attention-related
task demands, we assess changes in the neuromagnetic cortical
response to a point-light walker. Irrespective of task demands,
biological motion evokes an increase in oscillatory gamma activity
over the left parieto-occipital region at 80 ms post-stimulus. Only an
attended walker, however, yielded further peaks over the right
parietal (120 ms) and temporal (155 ms) cortices. By contrast, the
magnetoencephalographic (MEG) response to an ignored walker is
restricted to the left parieto-occipital region. In addition, peaks in
oscillatory activity occur in response to both attended (canonical
and scrambled) configurations at 180--200 ms from stimulus onset
over the right fronto-temporal regions, most likely reflecting
maintenance of the target configuration in working memory. For
the first time, we demonstrate that the time course and topographic
dynamics of oscillatory gamma activity in response to biological
movement undergoes top-down influences and can be profoundly
modulated by the withdrawal of attention.
Keywords: biological movement, magnetoencephalography, oscillatory
gamma brain activity, point-light walker, task-driven attention, time course,
topography
Introduction
The visual system is exquisitely tuned to biological movement
represented solely by a set of dots attached to the main joints of
an otherwise invisible human body. In both healthy perceivers
and patients, point-light stimuli have proven to be a valuable
tool for exploration of the brain capacity to integrate the local
motion of dots into a cohesive percept (Johansson, 1973;
Pavlova and Sokolov, 2000; Tadin et al., 2002; Fine et al., 2003;
Grossman et al., 2004; Thornton and Vuong, 2004; Vaina and
Gross, 2004; Watson et al., 2004). Early studies proposed that
point-light biological motion attracts attention automatically,
independent of intention or of the current task, but recent
psychophysical work has led to a revision of this idea (Cavanagh
et al., 2001; Thornton et al., 2002; Battelli et al., 2003).
Functional brain imaging indicates the engagement of parietal
cortical regions, the amygdala and the lateral cerebellum in
processing point-light displays (Bonda et al., 1996; Grèzes et al.,
2001; Vaina et al., 2001). These regions are also recruited in
deployment of visual attention (Kastner and Ungerleider, 2000).
Here we ask whether and, if so, how the pattern of cortical
activity in response to point-light biological motion is affected
by the withdrawal of attention. To this end, we analyzed the
time course and topography of the oscillatory neuromagnetic
brain response recorded during performance of attentiondemanding tasks with biological motion displays.
The Author 2005. Published by Oxford University Press. All rights reserved.
For permissions, please e-mail: [email protected]
Marina Pavlova1,2, Niels Birbaumer1,3 and Alexander Sokolov4
1
Institute of Medical Psychology and Behavioral Neurobiology,
MEG-Center, University of Tübingen, Germany,
2
Developmental Cognitive and Social Neuroscience Unit,
Department of Paediatric Neurology and Child Development,
Children’s Hospital, University of Tübingen, Germany, 3Center
for Cognitive Neuroscience, University of Trento, Italy and
4
Center for Neuroscience and Learning, Department of
Psychiatry, University Hospital of Ulm, Germany
Binding of widely spread cell assemblies by synchronizing
their high-frequency oscillatory activity (20--80 Hz) is thought
to underlie cohesive stimulus representation in the human
brain. In accord with this assumption, changes in gamma
electroencephalographic (EEG) and magnetoencephalographic
(MEG) activity have been considered as indicators of processing
Gestalt-like patterns (e.g. Keil et al., 1999; Rodriguez et al.,
1999; Bertrand and Tallon-Baudry, 2000; Herrmann and
Mecklinger, 2000). In recent years, however, evidence has
accumulated to suggest that both evoked (phase-locked to
stimulus onset) and induced (non-phase locked) gamma response may be profoundly affected by task-driven attention
(e.g. Tiitinen et al., 1993; Gruber et al., 1999; Sokolov et al.,
1999; Haenschel et al., 2000; Engel et al., 2001; Yordanova et al.,
2002; Debener et al., 2003; Müller and Keil, 2004; Sokolov
et al., 2004; Tallon-Baudry et al., 2005). Active visual search for
a camouflaged target, for example, leads to an increase in the
gamma response (Tallon-Baudry et al., 1997). Previously, we
showed that when a task requires attention to both a point-light
biological motion and a similar moving noise, only a point-light
walker elicits a specific pattern of enhancements in the evoked
gamma MEG response (Pavlova et al., 2004). For a better
understanding of the relationship between feature integration
and task-driven influences in modulation of oscillatory gamma
activity, in the present work we manipulated both stimulus
coherence and attention-related task demands. Healthy volunteers were presented with a canonical point-light walker and
a scrambled configuration for which spatial positions of dots
were randomly rearranged on the screen so that the display
lacked the implicit spatial structure of a canonical figure. In two
separate runs, we had participants respond to the third identical, either canonical or scrambled, point-light configuration in
a randomized set of both types of stimuli while ignoring the
stimuli of the other type (for details, see Experimental Design).
Material and Methods
Participants
Fourteen (seven females) paid right-handed volunteers, aged between
20 and 32 years, with normal or corrected-to-normal vision participated
in the study. None had a history of neurological or psychiatric disorders.
Informed written consent was obtained in accordance with the requirements of the Ethical Committee of the Faculty of Medicine at the
University of Tübingen.
Stimuli
Two types of computer-generated point-light configurations were used.
A canonical point-light walker consisted of 11 dots attached to the head
and main joints (ankles, shoulder, etc.) of an otherwise invisible human
body moving as if on a treadmill (with no net translation), in a sagittal
view, facing right (Fig. 1b). A gait cycle was completed in 40 frames with
Figure 1. Static representation of biological motion stimuli. (a) An outline of the
walking figure with the locations of 11 dots on its head and main joints (shoulders,
knees, wrists, etc.). (b) A frame from a walking cycle of a canonical point-light figure.
A walker moved as if on a treadmill, facing right, with a walking speed of ~48 complete
gait cycles per minute. Vectors illustrate the motion of each dot of a point-light walker.
(c) A scrambled configuration includes the same number of moving dots as the
canonical figure. The spatial positions of dots are randomly rearranged on the screen
so that the display lacks the implicit coherent structure of a canonical walker.
frame duration of 31 ms that produced a walking speed of ~48 complete
cycles per minute. The scrambled configuration contained the same
number of dots moving as if attached to the joints of the canonical
figure. The spatial locations of dots on the screen were randomized in
such a way that the resulting display lacked the implicit coherent
structure of a canonical figure (Fig. 1c). The motion of each point of the
scrambled configuration matched the motion of one of the points
defining the canonical figure. The size, luminance, velocity and phase
relations of the moving dots also remained unchanged. The figures were
created by Cutting’s algorithm (Cutting, 1978). Both configurations
subtended a visual angle of 9 in height and 6 in width.
Experimental Design
In two separate sessions, participants were presented with a randomized
set of 200 stimuli with an equal number of stimuli of both types (100
canonical and 100 scrambled). They were asked to lift their right
forefinger after the offset of the third identical either canonical (in one
run) or scrambled (in the other run) configuration while ignoring
stimuli of the other type. This movement triggered a light barrier signal
in a response box. For example, in a string of stimuli W (walker) and S
(scrambled) (WWSW*SWSWW*SSWSWSSW*S), asterisks designate the
requested points of the responses to the canonical walker. Participants
had no explicit identification task. Instead, they were asked about their
visual impressions only after the recording session was completed. The
order of runs was counterbalanced across subjects. Participants visually
fixated a gray cross in the middle of the screen that was seen during the
entire run. The stimulus appeared for 650 ms on a blank screen with an
inter-stimulus interval that varied randomly between 2.5 and 3 s. For
each participant we calculated the miss rate as the ratio of the number
of failures to respond to the third stimulus to the total number of
required responses (~33 per participant and per run). Similarly, for the
false alarm rate, the number of false alarms was divided by the total
number of trials in which this type of error might occur.
MEG Recording and Data Analysis
A participant was seated in an electromagnetically shielded chamber
(Vakuum-Schmelze, Hanau, Germany). The cortical responses were
recorded with the whole head MEG system (CTF Systems, Inc.;
Vancouver) consisting of 151 hardware first-order magnetic gradiometers distributed with an average distance of 3 cm between the sensors.
The signals were sampled at a rate of 312.5 Hz in the frequency range of
0--100 Hz. A baseline was recorded during a pre-stimulus duration of
300 ms. Participants were instructed to blink only during inter-trial
intervals. Vertical eye movements were monitored by EEG/electroolfactogram recording from the left eye (impedance was kept below
5 kX). Both at the beginning and at the end of each recording session,
the participant’s head position was determined with three localization
coils fixed at the nasion and the periauricular sites. Sessions with head
movements exceeding 0.5 cm were discarded. Each MEG recording
322 Attention and MEG Response to Biological Motion
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Pavlova et al.
session lasted 10--12 min. The entire experimental session including the
preparatory period, instructions, familiarization, and recording took
~1.5 h per participant.
All epochs of MEG activity were first automatically and then manually
inspected for artifacts. Epochs containing blinks or eye movements
( > ±100 lV) were rejected. The only trials analyzed were those for
which a motor response was not required by the task. This procedure
eliminates the influence of motor activity on recorded MEG traces
(Kristeva-Feige et al., 1993). If a participant failed to respond to the third
identical attended stimulus, all trials from the last correct response were
discarded. We also discarded trials between the second and third
attended stimuli. The reasons for this were twofold. First, it avoids
a possible influence of readiness in responding that could potentially
affect gamma-range activity in unattended trials. It has been shown that
holding an object representation in visual working memory can
facilitate posterior and frontal gamma activity (Tallon-Baudry et al.,
1997, 1998, 1999; Bertrand and Tallon-Baudry, 2000; Howard et al.,
2003). Second, this procedure ensures that an equal number of trials
enter the averages for all types of displays. On average, therefore, a total
of 61.8 ± 1.0 artifact-free trials were analyzed for each type of stimulus
and each participant. For instance, for attended stimuli and for each
participant, 100 trials (in each run) minus 33 trials (with motor
responses) minus incorrect responses (misses and false alarms) and
discarded artifacts (trials confounded with eye movements) gives the
above number of artifact-free trials. The evoked oscillatory response was
analyzed primarily because it makes the findings comparable with those
from our earlier MEG study with biological motion (Pavlova et al., 2004).
For determining the frequency bands that exhibit significant changes
in stimulus-related neuromagnetic activity relative to baseline, we first
conducted a broad-band spectral power analysis of the averaged artifactfree MEG traces for each type of stimulus in the attended and
unattended conditions. This analysis was done using 200 ms epochs
ranging from 300 to 100 ms (pre-stimulus) at baseline and from 0 to 200
ms post-stimulus onset. After the frequency bands with significant
changes in MEG activity were detected, a narrow-band analysis was
conducted for these specific frequency bands. Because the broad-band
analysis revealed the mostly significant increase in spectral amplitude at
frequencies of ~25 Hz, an acausal Gaussian shaped Gabor filter with
a center frequency of 25 ± 5 Hz was applied separately over the entire
epochs of 300 ms pre- and 650 ms post-stimulus onset. To assess the
time course of the narrow-band MEG activity, we performed amplitude
demodulation of the filtered MEG records using a Hilbert transformation. For elimination of baseline distortions caused by these procedures,
the baseline epoch was restricted to 200 ms (from –200 to 0 ms) prestimulus onset. The significance of the observed spectral power values
for each frequency bin and MEG sensor was tested using a statistical
probability mapping approach based on permutation tests that include
corrections both for multiple comparisons and for possible correlations
between data either from neighboring frequency bins (for spectral
analysis) or time points (for time course analysis). This procedure is
described in detail elsewhere (Lutzenberger et al., 2002). For assessment of the cortical topography of significant changes in spectral
amplitude, we used a common coil system. For each participant, the
sensor positions were assigned to common spatial sensor coordinates of
one representative subject, and the spatial locations of changes in
spectral amplitude were determined on the 2-D brain model derived
from this participant’s structural magnetic resonance imaging (MRI)
scan. Applicability of the common coil system for the purposes of the
present study, in which the exact source localization was beyond the
focus of interest, has been established earlier (for detailed description,
see Kaiser et al., 2002; Lutzenberger et al., 2002). The localization errors
introduced by employing the common coil system, as opposed to the
individual sensor locations, were within the range of spatial resolution
determined by the spacing of sensors in the MEG system.
Results
Performance and Stimulus Recognition
Participants performed the task with great accuracy: they
responded to the third stimulus of each type (either canonical
Figure 2. Temporal and topographic dynamics of the evoked gamma (25 Hz) response to a point-light walker. Blue highlighted regions correspond to increases in the gamma
response as revealed by the statistical probability mapping. (a) The oscillatory gamma response to an unattended walker (UAW) was topographically restricted to the left parietotemporal area. (b) Consecutive enhancements in gamma activity were found at latencies of 80 ms (left parieto-occipital), 120 ms (bilateral parietal) and 155 ms (right temporal
cortices) for an attended walker (AW).
or scrambled display) almost without error. When they had to
count scrambled configurations, they often reported the task as
more difficult. However, the performance level was equally high
in both runs. The miss rate (failure to respond to the third
stimulus) was on average 0.013 ± 0.016 (mean ± SEM) in
responding to the canonical and 0.009 ± 0.025 to the scrambled
configuration. The rate of false alarms was 0.007 ± 0.01 and
0.012 ± 0.01 in responding to the canonical and scrambled
configurations, respectively. Pairwise comparisons performed
on individual error rates did not reveal any significant differences between the distinct stimuli. Response time (the interval
from the stimulus offset to response) to the canonical walker
was on average 460 ± 33 ms, and to the scrambled configuration
478 ± 31 ms. Pairwise comparison (Student’s t-test, one-tailed)
did not reveal any differences in response time to these displays.
Following each run, subjects briefly described what they saw
and indicated any stimulus interpretations they might have had.
Even during the familiarization session, all subjects spontaneously reported seeing the canonical walker. In accord with
earlier findings (Grossman and Blake, 2002; Pavlova et al., 2004),
scrambled configurations were typically described as a meaningless disorganized cloud of moving dots.
onset) cortical areas (t > tcrit = 4.77). For the ignored walker an
enhancement in evoked oscillatory response was topographically restricted to the left temporo-occipito-parietal junction
(t > tcrit = 4.74), and attenuated by 180 ms. Figure 3 shows the
evoked magnetic fields in response to attended and unattended
scrambled configurations. The topography and magnitude of
the neuromagnetic response did not substantially differ between these displays. Most important, in the range from 80 to
180 ms we did not find any increases in the gamma oscillatory
activity in response to the scrambled displays.
For both attended scrambled and canonical configurations,
the peaks in gamma activity occurred in the latency range from
190 to 200 ms over the right fronto-temporal region (Fig. 4a,b).
The peak in the oscillatory response to the attended walker
occurred at 40 Hz, whereas the response to the scrambled
configuration peaked in the lower gamma range at 25 Hz. These
peaks of activation were absent in response to both ignored
configurations. Analysis of the low frequency ( <20 Hz) oscillatory activity and the slow neuromagnetic responses indicated
that the effects pertain to the gamma frequency range.
Discussion
Oscillatory Gamma-range Activity
Inspections of the statistical probability maps (Fig. 2a,b) show
that both attended and ignored canonical walkers evoke
a significantly increased lower gamma-band (25--30 Hz)
MEG activity over the left parieto-occipito-temporal junction
(t > tcrit = 4.74). For both attended and ignored canonical
walkers, these peaks in oscillatory response were observed as
early as 80 ms after stimulus onset. The ignored and attended
scrambled configurations did not evoke any early increases in
oscillatory gamma activity over the modality-specific brain
regions.
Attended and ignored canonical walking figures yield different topographic and temporal dynamics of gamma-range
activity (Fig. 2a,b). For the attended walker only, two further
consecutive increases in gamma activity occurred over the
parietal (at 120 ms) and right temporal (at 155 ms from stimulus
By manipulating attention-related task demands, we assessed
changes in the evoked oscillatory MEG activity in response to
a point-light walker and a similar scrambled configuration that
lacked an implicit coherent structure of a canonical figure. The
data indicate that both attended and ignored point-light walkers
evoke early enhancements in the oscillatory cortical response in
the lower gamma-band range (25 Hz) peaking at 80 ms poststimulus onset. Irrespective of task demands, therefore, a canonical point-light figure yields an early increase in gamma
activity. Both attended and ignored scrambled configurations do
not elicit any changes in early oscillatory gamma activity over
the occipito-parietal regions. These findings correspond to
previous data (Pavlova et al., 2004) inasmuch as the early
evoked gamma response (80--100 ms) exhibits sensitivity to
spatial coherence revealed through biological motion. In this
earlier work, the peaks in gamma activity were found in
Cerebral Cortex March 2006, V 16 N 3 323
Figure 3. Evoked magnetic fields in response to (a) an unattended, UAN, and (b) an attended, AN, scrambled (noise) configuration at latencies of 100, 120 and 155 ms. In the
latency range from 80 to 180 ms there were no significant changes in the oscillatory gamma activity in response to unattended and attended scrambled displays. The x-axis shows
the time course of a trial with stimulus onset at 0 s and the y-axis represents the magnitude of the neuromagnetic response in fT.
response to both upright and inverted 180 in the image plane
point-light walkers, but not to the scrambled configurations.
Notably, in that study both upright and inverted point-light
figures were attended. The present data show that even when
the task requires the participant to ignore the canonical walker,
an early posterior peak in oscillatory cortical response accompanies processing of point-light biological motion. This finding
suggests that, although both theoretically and experimentally it
appears obvious that attentional resources are required in order
to join features or elements into a cohesive percept (Corbetta
et al., 1995; Treisman and Kanwisher, 1998; Robertson, 2003),
integration of elements may occur despite the task demands to
ignore a moving point-light configuration.
Only an attended walker, however, evokes two further
consecutive peaks in the gamma response (25 Hz) over the
right parietal (120 ms) and temporal (155 ms) cortices. The
remarkable similarity in the time course and topography of
the pattern of evoked gamma activity in response to the attended
point-light walker with our earlier data (Pavlova et al., 2004)
324 Attention and MEG Response to Biological Motion
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Pavlova et al.
obtained with a different (one-back repetition) task and an
independent group of participants confirm the robustness of the
present findings. These findings agree with, and further illuminate, single cell data indicating that neurons in the macaque
superior temporal polysensory area (STPa) rapidly (within 100
ms from stimulus onset) respond to biological motion (for
reviews, see Puce and Perrett, 2003; Jellema et al., 2004).
By contrast, the response to the ignored walker is topographically restricted to the left parieto-occipital area. Thus, attended
and ignored canonical walkers elicit topographically and
temporally distinct patterns of evoked oscillatory gamma MEG
activity. One of the important outcomes of the present work,
therefore, is that it provides the first direct evidence for the
role of visual attention in cortical processing of point-light
biological movement.
Although perception of point-light stimuli is traditionally
thought to be a kind of ‘pop-out’ phenomenon which is
considered the hallmark of pre-attentive processing, recent
psychophysical data suggest that the integration of moving dots
Figure 4. Frontal peaks in the gamma MEG response to an attended canonical walker
and an attended scrambled configuration. (a) The oscillatory response to the
scrambled configuration occurs in the lower gamma range (25 Hz) at a latency of
190 ms over the right frontal cortex. (b) The peak in the oscillatory response at 40 Hz
and a latency of 200 ms to an attended walking figure occurs over the right frontotemporal region. The peaks of activation were absent in response to both an ignored
canonical walker and a scrambled configuration. The x-axis shows the time course of
a trial with stimulus onset at 0 s and the y-axis represents the spectral power
enhancements (Z-values) in the respective gamma ranges assessed within stimulus
presentation relative to the 200 ms pre-stimulus baseline.
into the overall kinetic form of a point-light figure might require
attentional resources (Cavanagh et al., 2001; Thornton et al.,
2002; Battelli et al., 2003). Earlier brain imaging data indirectly
favor the conjecture that attention is involved in biological
motion processing, and indicate the engagement of parietal
cortical regions (anterior portion of the intraparietal sulci, the
inferior and superior parietal lobule — Brodmann areas 39 and
7), the amygdala and cerebellum in the neural circuits subserving processing of point-light displays (Bonda et al., 1996;
Grossman et al., 2000; Grèzes et al., 2001; Vaina et al., 2001;
Ptito et al., 2003; Pavlova et al., 2004). These regions have also
been implicated in attentional processes.
Patients with bilateral damage to the superior parietal cortex
(Brodmann areas 7 and 40), which is a part of the posterior
attentional system (Posner and Dehaene, 1994), and to the
underlying white matter are unable to identify moving pointlight walkers embedded in an array of static or dynamic
distracters, although they have no difficulties in perceiving
point-light figures per se (Schenk and Zihl, 1997). The motionblind patient LM with bilateral lesions affecting the lateral
parieto-temporo-occipital cortex (primarily, area V5) and the
underlying white matter demonstrates an intact ability to
recognize point-light figures presented against static noise
(McLeod et al., 1996). Patients with unilateral parietal lesions
have difficulties in recognition of point-light displays, and
especially in a visual search for a point-light walker camouflaged
by similar moving distracters (Battelli et al., 2003). Attentiondemanding processing of point-light biological motion stimuli is
compromised in patients suffering congenital bilateral damage
to the parieto-occipital periventricular regions, and the degree
of this impairment positively correlates with the severity of
lesions (Pavlova et al., 2003; 2005).
The brain areas involved in biological motion processing are
currently being intensively explored by neuroimaging techniques such as positron emission tomography (Bonda et al., 1996;
Ptito et al., 2003) and, especially, functional magnetic resonance
imaging (fMRI; Grossman et al., 2000, 2004; Vaina et al., 2001;
Grossman and Blake, 2002; Servos et al., 2002; Beauchamp et al.,
2003; Pelphrey et al., 2003). The right superior temporal sulcus,
the intraparietal cortex, and the lateral occipital complex
(primarily the regions corresponding to the kinetic occipital
area) are often reported to be activated during viewing of pointlight biological movement (for reviews, see Giese and Poggio,
2003; Puce and Perrett, 2003). However, other brain regions,
such as the amygdala, the lateral and medial cerebellum, the
lingual gyrus at the cuneus border, the occipital and fusiform
face areas, and the frontal regions, also exhibit an increased
gradient of activation in response to biological motion displays.
These studies are restricted to localization of areas that show an
increased blood-oxygenation-level-dependent activation, and
fail to uncover the fine changes in brain activity unfolding
over time. Moreover, it is remarkable that the fMRI findings on
point-light biological motion are not congruent, and the areas
of activation do not entirely overlap (e.g. Servos et al., 2002).
It appears that the topographic pattern of activation is strongly
affected by attention-related task demands. Even in the same
subjects, both the magnitude and the topographic pattern of
fMRI activation in response to a point-light walker are colored
by the attention-related task requirements (Vaina et al., 2001).
The present work is the first showing that the withdrawal of
attention can profoundly modulate the time course and dynamic topography of oscillatory neuromagnetic cortical activity
in response to biological movement.
The other important finding is that, when attended, both
canonical and scrambled configurations elicit enhancements in
gamma activity over the right fronto-temporal regions in the
latency range between 180 and 200 ms post-stimulus onset. The
peak in oscillatory response to a meaningful point-light walking
figure was found at 40 Hz, whereas the scrambled configuration
was accompanied by an enhancement in the oscillatory response in the lower gamma range (25 Hz). These increases in
gamma activity were absent in response to both unattended
canonical and scrambled configurations, and therefore most
likely reflect task-dependent rehearsal of the events in working
memory. The present findings dovetail with the data obtained
by other research groups. Involvement of prefrontal and frontal
regions has been repeatedly reported in short-term memory
processes in monkeys and in humans (Goldman-Rakic, 1996;
Ungerleider et al., 1998; Munk et al., 2002; Baeg et al., 2003;
Compte et al., 2003; Curtis and D’Esposito, 2003). Furthermore,
recent EEG and MEG data point to specific frontal increases in
gamma-range oscillatory activity that are related to visual
(Tallon-Baudry et al., 1997, 1998, 1999; Howard et al., 2003)
and auditory (Lutzenberger et al., 2002; Kaiser et al., 2003)
working memory load. For example, by using contour figures in
a delayed-matching-to-sample task, a boosted gamma activity
was found to correspond to the rehearsal of stimulus representation in working memory (Tallon-Baudry et al., 1998). Here, we
showed that enhancements in gamma activity in response to
both visual events (canonical and scrambled biological motion)
occur only when the task requires a response to this particular
event with a time delay, and there is therefore a need to
maintain for some time the memory trace across trials. Although
the task-driven enhancements of oscillatory gamma activity
Cerebral Cortex March 2006, V 16 N 3 325
over the frontal areas are observed for both a point-light walker
and a scrambled configuration, the peak of activity in response
to a meaningless scrambled configuration occurs at a lower
frequency than for biological motion, and therefore these peaks
appear to be stimulus-specific. This assumption agrees well with
macaque single-cell results demonstrating that activity of prefrontal neurons reflects processing of the sensory attributes of
a remembered stimulus that allows for flexibility in the outcome
of a mnemonic process (Constantinidis et al., 2001).
Taken together, the findings suggest that, irrespective of taskdriven shifts of attention, early evoked gamma activity reflects
stimulus coherence resulting from biological motion. The time
course and topography of subsequent gamma responses to
point-light biological motion undergo top-down influences, and
can be profoundly modulated by task-driven attention. Furthermore, the memory-related peaks of gamma-range activity found
over the fronto-temporal regions appear to exhibit stimulus
specificity.
Notes
This work is supported by the Human Frontier Science Program
Organization (M.P.) and by the German Research Foundation (Deutsche Forschungsgemeinschaft, KR 1316/5-P9 and SFB 550). MP greatly
appreciates the encouraging support of Patricia Goldman-Rakic. We
thank Werner Lutzenberger for helping with data analysis and Jürgen
Dax, along with the team of the MEG-Center at the University Hospital
of Tübingen, for technical support.
Address correspondence to Marina Pavlova, Institute of Medical
Psychology and Behavioral Neurobiology, MEG-Center, University of
Tübingen, Gartenstr. 29, 72074 Tübingen, Germany. Email: marina.
[email protected].
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