Cognitive Tasks Augment Gamma EEG Power
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Cognitive tasks augment gamma EEG power
S.P. Fitzgibbona,b, K.J. Popec, L. Mackenziea, C.R. Clarkb, J.O. Willoughbya,*
aCentre for Neuroscience and Department of Medicine (Neurology), Flinders University, P.O. Box 2100 Adelaide, SA, AustraliabCognitive Neuroscience Laboratory, School of Psychology, Flinders University, P.O. Box 2100 Adelaide, SA, Australia
cSchool of Informatics & Engineering, Flinders University, P.O. Box 2100 Adelaide, SA, Australia
Accepted 3 March 2004
Abstract
Objective: Gamma EEG oscillations are low amplitude rhythms in the 30–100 Hz range that correlate with cognitive task execution. They
are usually reported using time-locked averaging of EEG during repetitive tasks. We tested the hypothesis that continuous gamma EEG
would be measurable during mental tasks.
Methods: We investigated sustained human gamma EEG oscillations induced by 8 cognitive tasks (Visual Checkerboard, Expectancy,
Reading, Subtraction, Music, Expectancy, Word learning, Word recall, and a Video Segment) in 20 subjects using standard digital EEG
recording and power spectral analysis.
Results: All of the cognitive tasks augmented gamma power relative to a control condition (eyes open watching a blank computer screen).
This enhancement was statistically significant at more than one scalp site for all tasks except checkerboard. The Expectancy, Learning,
Reading and Subtraction tasks expressed the most impressive gamma response, up to 5 fold above the control condition and there was some
task-related specificity of the distribution of increased gamma power, especially in posterior cortex with visual tasks.
Conclusions: Widespread gamma activation of cortical EEG can easily be demonstrated during mental activity.
Significance: These results establish the feasibility of measuring high frequency EEG rhythms with trans-cranial recordings, demonstrate
that sustained gamma EEG activity correlates with mentation, and provides evidence consistent with the temporal binding model.
q 2004 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Keywords: Spectral analysis; Theta; Alpha; Beta
1. Introduction
Gamma EEG oscillations (low amplitude rhythms in the
30–100 Hz range) became a topic of intense interest in
humans (Aoki et al., 1999; Joliot et al., 1994; Keil et al.,
1999; Revonsuo et al., 1997; Sauve et al., 1998; Tallon-
Baudry et al., 1998) after it was established in animal
models that synchronous recurrent discharge bursts within
the gamma range are involved in perception and cognition
and are correlated with cognitive task execution (Engel and
Singer, 2001).
In several animal studies, gamma EEG derived from
cortex using small electrodes has been closely correlated
with both local multi-unit and single-unit discharges.
Synchronous gamma discharges have been identified in
the visual, auditory, somatosensory, olfactory, motor and
memory modalities in a wide range of animal species (Engel
and Singer, 2001). Within these areas, there were synchro-
nous bursts within groups of neurons in different cortical
columns (Gray et al., 1990), spatially distributed within the
same hemisphere (Engel et al., 1991a; Frien et al., 1994),
between inter-hemispheric sites (Engel et al., 1991b) and in
sub-cortical structures (Alonso et al., 1996). Other animal
experiments have demonstrated the functional significance
of synchronous gamma oscillations by showing that
synchroneity of gamma discharges correlates with cognitive
function (Fries et al., 1997; Murthy and Fetz, 1996;
Roelfsema et al., 1997) and that disrupted synchroneity of
gamma discharges correlates with diminished cognitive
function (Roelfsema et al., 1994; Stopfer et al., 1997).
In humans, trans-cranial EEG integrates measures
summed electrical fields which are volume conducted
from a large population of neurons within an extensive
region around a recording site. Such measurement is
unlikely to detect EEG rhythms derived from small cell
Clinical Neurophysiology 115 (2004) 1802–1809
www.elsevier.com/locate/clinph
1388-2457/$30.00 q 2004 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
doi:10.1016/j.clinph.2004.03.009
* Corresponding author.
E-mail address: [email protected] (J.O. Willoughby).
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assemblies and it would be even less likely to permit
identification of synchronous rhythms from small cell
assemblies in different cortical areas. However, the presence
of gamma oscillations in trans-cranial EEG indicates
significant synchronicity in large populations of subjacent
neurons and, therefore, that there are relatively large local
cell assemblies exhibiting rhythmic bursting, possibly
synchronous with cell groups elsewhere.
Synchronous gamma activity between widely distributed
cell groups, sometimes referred to as ‘binding’ gamma, is
thought to integrate (bind) information processed in dis-
tributed neurons and/or neural circuits and/or cortical areas
into a coherent cognitive process/percept (Engel and Singer,
2001). Thus synchronous cortical gamma EEG provides a
measure of binding activity and has been observed for short
durations, for example in auditory discrimination (Joliot et al.,
1994), somatosensory discrimination (Sauve et al., 1998),
stereoscopic fusion (Revonsuo et al., 1997), the formation of
percepts (Keil et al., 1999), working memory (Tallon-Baudry
et al., 1998), and sensory-motor processing (Aoki et al.,
1999). In many studies such as these, the involvement of
gamma has been demonstrated using repetitive tasks, time-
locked averaging, and short post-stimulus time windows.
We determined if sustained gamma EEG oscillations,
induced by a variety of complex mental tasks in human
subjects, could be measured trans-cranially and if the strength
and spatial pattern of enhancement would be task-dependant.
2. Method
2.1. Subjects
Twenty adults (8 male and 12 female) free of psychiatric
or neurological disorder participated in the study, approved
by the Flinders Clinical Research Ethics Committee, and all
subjects gave informed and written consent. They were
recruited as age, gender and education-matched controls for
patients as part of a larger clinical study (published
elsewhere (Willoughby et al., 2003)).
2.2. EEG
Sixty-four channel EEG was recorded continuously
(linked-ear reference, 512 samples per second, 16-bit analog
to digital conversion, 107 Hz low-pass filter) using a
commercial EEG acquisition system (Compumedics,
Victoria, Australia). A 64-channel electrode cap with tin
electrodes provided uniform scalp coverage. Electrode
impedances were kept below 5 kV.
2.3. Cognitive tasks
EEG was recorded whilst participants performed the
following 8 tasks, chosen to activate mental activity in a
variety of circumstances, and a Control procedure:
2.3.1. Visual checkerboard
The participant was instructed to fixate for 20 s on a red
dot located in the centre of an alternating, rectangular black-
and-white checkerboard pattern for 20 s (check size
1.5 £ 2 cm, alternation rate 8 Hz).
2.3.2. Story reading
The participants were instructed to read silently for a
period of 28 s from the beginning of page 46 of ’Politically
Correct Bed-Time Stories’ by James Finn Garner (Souvenir
Press, London, 1994). The book contained only text in size
12 point font.
2.3.3. Subtraction task
The participants were instructed to serially subtract 7
from 1000 and, in a practice session, the participants were
intermittently interrupted to check their accuracy and to
ensure compliance with the task. The recorded Subtraction
period was not interrupted. A small number of subjects who
were unable to serially subtract 7 from 1000 were given a
simpler serial Subtraction task.
2.3.4. Music
The participants listened to a segment of Pachelbel’s
Cannon in D for 28 s.
2.3.5. Expectancy
The participant was presented with a series of 11
expectancy trials, each involving stimulus pairs. Each pair
consisted of a visual direction cue presented at eye height in
the centre of the computer screen followed 4 s later by a
lateralised visual target. Each cue consisted of an arrow
pointing equally probably to the left or right. The target was
a cross, located on the side indicated by the preceding
arrow. The period between each direction cue and the
subsequent target was 4 s. Participants were required to
respond by a button press as soon as a target was presented.
The expectancy period recorded was the interval between
each directional cue and the subsequent target.
2.3.6. Learning
The participants were instructed to memorise a set of 10
words that were presented simultaneously on a computer
monitor for 20 s. The words were medium frequency
(Kucera and Francis, 1967) concrete nouns of 4–7 letters
in length. In order to induce intentional learning, partici-
pants were advised that they would be tested on them
subsequently.
2.3.7. Recall
Three lists of 10 words were presented sequentially for
10 s each, with an inter-list interval of 2 s. The first list
contained the same words as the Learning list but in
different order. The other two lists contained some of the
words in the first list. Following the presentation of all 3 lists
the participant was asked to identify which list contained
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the words that they had previously learnt. EEG was recorded
during the presentation of the first list.
2.3.8. Strictly ballroom
The participant was required to watch a 28 s segment of
the film ‘Strictly Ballroom’ (with permission of Andrew
Pike, Ronin Films, Canberra, Australia). The segment
selected contained a complex mix of intense colour,
movement, speech, drama and music.
Subjects also completed a Control task requiring them to
relax with eyes open and to look at a blank computer screen.
During the experiment, participants were seated 1.5 m in
front of a computer monitor on which the various task
materials were presented. Participants were instructed on
the requirements of each task immediately beforehand.
Because the subject group were controls for a study of
patients with different forms of epilepsy and the numbers of
patients were not known, it was not feasible in advance to
undertake a Latin square design in administering the tasks.
In addition, there were two tasks that required a fixed order,
namely Learn and Recall. The tasks were therefore
administered in fixed order: Checkerboard, Reading,
Subtraction, Music, Expectancy, Learn, Recall, Strictly
Ballroom, Control and there was a half to 1 min rest
between each task.
2.4. EEG analysis
All uncontaminated EEG for each task (usually around
20 s) was epoched into consecutive 1 s blocks. Each epoch
was transformed from the temporal domain to the frequency
domain using fast-Fourier transform (1 Hz resolution, 512
point block-size, Hanning window, 1–100 Hz). While
artifact due to eye blinks was present, eye blinks frequency
and expression in the power spectra could not be detected
because of their brief duration and infrequent occurrence
(around once every 10 s) even during the Strictly Ballroom
task. Muscle activity, if present, occurred in isolated regions
and did not prevent the use of recordings from other leads.
When muscle activity affected electrodes in a widespread
distribution, all leads were edited from the analysis.
The frequency epochs were averaged within each task for
each subject to yield an averaged power spectrum and then
divided by the power spectrum for the Control task for that
subject. This provided a relative spectral response profile for
each subject for each task. The data was banded into theta
(3–7 Hz), alpha (8–12 Hz), beta (13–29 Hz) and gamma
(30–100 Hz) frequency bands. For visualisation purposes
the relative spectra were averaged across subjects within
each task to provide group mean spectra relative to Control
for each task. To ensure data were not contaminated by
50 Hz mains frequency and 60 Hz computer monitor refresh
rate, power values in the 50 ^ 1, 60 ^ 1, 99 and 100 Hz
values were omitted from analysis.
2.5. Statistical analyses
The Kolmogorov–Smirnov test was used to assess
normality of power estimates, which was achieved when
the power estimates were log-transformed. Significant
differences in spectral power between experimental tasks
and the Control task were calculated for each power band
using a single factorial analysis of variance for each
electrode. Significances were corrected form multiple
comparisons using the Modified Bonferonni procedure.
3. Results
Relative to the Control condition there were widespread
increases in EEG power during all tasks except Checker-
board. We illustrate in Fig. 1 the average relative power-
response to Learning at each electrode as a montage of
power spectra with 1 Hz resolution.
3.1. Gamma power
All of the tasks other than Checkerboard exhibited
significantly increased gamma band power ðP , 0:05Þ
relative to the Control condition (Fig. 2). These increases
were evident in all cases at more than one scalp site and their
spatial distribution was task-specific.
The most striking enhancement of gamma power was
expressed in the Expectancy, Learning, Reading, and
Subtraction tasks. All 4 of these tasks induced widespread
2–5 fold increases in gamma power relative to Control at a
large number of posterior and central scalp sites (Fig. 2).
The Recall, Music and Strictly Ballroom tasks also induced
increases in gamma power, but of lower order and at fewer
electrodes. The spatial distribution of enhanced gamma
power for Recall was similar to that for Expectancy and
Learning.
3.2. Theta, alpha and beta power
There were no significant increases in alpha band power
relative to the Control condition for any of the experimental
tasks.
The distribution of beta band power for each experimen-
tal task relative to the Control condition was similar to the
gamma power distribution, however, the relative enhance-
ment was weaker than for gamma and tended to occur at
frequencies close to the gamma frequency band. Increased
beta power therefore very likely reflects an increase in
power of an equivalent phenomenon to gamma activity. The
only significant increases in apparent beta power were
observed during the Reading and Subtraction tasks ðP ,
0:05Þ and these were localised to a small subset of the scalp
sites that were significant for the gamma band.
There were 2–5 fold increases in theta power at
bilateral and midline frontal scalp sites for all tasks except
S.P. Fitzgibbon et al. / Clinical Neurophysiology 115 (2004) 1802–18091804
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Fig. 1. Montage display of individual (a) and mean (with SEM) of 20 subjects (b) EEG power increases during Reading relative to the Control state (ordinate
scale: from 1 to 5 fold) between 0 and 100 Hz (abscissa) recorded over the scalp. Decreases relative to the Control state (values below 1) are not shown.
S.P. Fitzgibbon et al. / Clinical Neurophysiology 115 (2004) 1802–1809 1805
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Checkerboard. The Subtraction task produced the most
striking augmentation of theta power with a large number
of central, temporal and frontal sites reaching significance
relative to the Control condition (Fig. 3). In addition,
there were 1–3 fold increases in theta power in the Read,
Recall, Strictly Ballroom and Subtraction tasks at bilateral
and midline occipital sites.
4. Discussion
The key finding is that mental activity can easily be
demonstrated to augment gamma activity using trans-
cranial recordings. We recorded ongoing EEG during
continued mental activity without time-locked averaging
of repeated tasks, revealing increased gamma during all
Fig. 2. Topographic maps of group mean gamma power for each Experimental task relative to the Control condition. The maps were scaled from 1 (black) to 5
fold (white) increases in gamma power relative to the Control condition. Each greyscale increment represents a 0.125 fold increase. A relative power of 1
indicates no difference to the Control condition. The transparent red overlay marks scalp sites at which the increase in gamma power relative to Control was
significant (P , 0.05).
Fig. 3. Topographic maps of mean theta power for each Experimental task relative to the Control condition. The maps were scaled from 1 (black) to 5 fold
(white) increases in theta power relative to the Control condition. Each greyscale increment represents a 0.125 fold increase. A relative power of 1 indicates no
difference to the Control condition. The transparent red overlay indicates scalp sites at which the increase in theta power relative to Control was significant
ðP , 0:05Þ:
S.P. Fitzgibbon et al. / Clinical Neurophysiology 115 (2004) 1802–18091806
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tasks other than Checkerboard. Increases were widespread
but quite variable from individual to individual, as indicated
by the maximal mean increases not always reaching
statistical significance. Increases were most striking for
tasks of Expectancy, Learning, Reading, and Subtraction in
which significant, 2–5 fold increases in gamma power were
obtained at widespread posterior and central scalp sites. In
addition, the distributions of augmented gamma EEG
demonstrated some specificity for individual tasks. The
tasks constitute very complex stimuli but we used a ‘blunt’
approach to inducing gamma activity that many would have
hypothesised we would not find. Clearly, given our findings,
the methodology is open to be used in almost unlimited
kinds of studies that will address the detail of ‘how and
where gamma correlates with thinking’, both in health and in
disease. We have interpreted the findings generally and with
an eye to avoiding over-interpretation.
The Expectancy task was similar to tasks used to elicit
the contingent negative variation (CNV). The CNV is a
steady slow negative shift in the EEG observed in the period
prior to the presentation of an expected stimulus. Therefore
the CNV is thought to reflect a state of anticipation by the
brain for the expected stimulus (Walter, 1968). It is this state
of anticipation that is likely to be inducing the enhanced
gamma power response observed in the Expectancy task.
The Expectancy task is a visual and motor paradigm so that
visual and motor areas are obvious candidates for
contributing to the anticipatory state. The distribution of
the gamma power response at posterior and central sites is
consistent with the implied role of the visual and motor
systems.
The Learning task is an intentional episodic memory-
encoding task. Cabeza and Nyberg (2000) conducted a large-
scale review of the many functional neuro-imaging studies
that have investigated intentional episodic memory encod-
ing. They concluded that the key cortical areas associated
with episodic memory encoding are the prefrontal, cerebellar
and medial-temporal brain regions. We did not record from
medial temporal cortex nor from cerebellum. While there
was some pre-frontal gamma augmentation, this was not a
consistent finding and did not reach statistical significance.
However the comparisons made in most encoding studies
contrast a condition involving encoding with a very similar
condition involving less encoding. In this study, we
contrasted a visual language-encoding task with a non-
language visual control condition, and as such the observed
responses may be language related gamma power enhance-
ment at posterior sites related to reading as opposed to
episodic encoding. This task, like others we used, is very
complex and we think it would be difficult to reach consensus
on what might be an appropriate control task. This
experiment also emphasises an obvious limitation of surface
EEG recordings: they do not provide information about brain
regions remote from the scalp.
The distribution of gamma power in the reading task
relative to the Control condition is consistent with
neuro-imaging studies that have consistently demonstrated
temporal, parietal and occipital involvement in written
word recognition and comprehension (Cabeza and Nyberg,
2000). Language studies using event-related potentials
(ERP) have demonstrated that early ERP components first
appear at occipital sites followed closely by the expression
of the subsequent components at occipital-temporal sites
(Vitacco et al., 2002). We report gamma power for Word
Reading relative to Control that is sustained for the
duration of the task and as such we cannot delineate the
timing at which various cortical regions are recruited,
however our distribution of gamma power is supportive of
their involvement.
The Subtraction task exhibited the greatest increase in
gamma power relative to the Control condition and it was
significant at more scalp sites than any of the other
conditions. This may be related to the inherent difficulty
of the task as task complexity correlates with gamma EEG
power (Simos et al., 2002). It is also the only task to exhibit
extensive frontal augmentation of theta power, a correlate of
the augmented attention requisite for this task. It would be
useful in future work to obtain measures of difficulty from
the subjects for each of the tasks. The distribution of the
significant gamma power response at occipital scalp sites is
curious given that subtraction was not a visual task. As the
primary visual cortex has been reported to be involved in
visual imagery (Cabeza and Nyberg, 2000), occipital
gamma enhancement may point to the use of visual imagery
during serial subtraction.
Mental tasks led to augmented theta activity in central
frontal leads and, in addition to frontal sites, Subtraction
was associated with a marked increase in theta power in
temporal sites. In this study, Subtraction was the most
powerful in enhancing gamma power and, intuitively, it
would be expected to be the most mentally challenging of
our tasks. Frontal theta correlates with mental tasks
requiring attention as originally demonstrated with arith-
metic and reasoning (Ishihara and Yoshii, 1972). Recently,
the probable source of this activity has been demonstrated
by magneto-encephalography to be medial prefrontal cortex
(Ishii et al., 1999). Theta activity is generally associated
with cognition and memory (Klimesch, 1999). Further,
intensified theta activity has previously been reported in
humans during recall and other tasks, with some correlation
with task effort (Gundel and Wilson, 1992; Grunwald et al.,
2001; Schober et al., 1995). Theta activation is generated in
hippocampus and related structures in response to alerting
stimuli in rabbit, rat and other species (Blessing, 1997).
Thus enhanced theta activity may be reflective of mental
arousal, analogous to the findings in the hippocampus in
animals. Its temporal prominence may also be partially
supportive of a hippocampal to temporal process, consistent
with the possibility of arousal-induced hippocampal theta
generation in humans. There was a small, but significant,
augmentation of theta power during Reading, Recall and
Strictly Ballroom, an observation that is difficult to account
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for in terms of occipital cortical involvement in mental
processing given the absence of this finding in the Learn
task, which was a visual task.
The Recall, Music and Strictly Ballroom tasks expressed
significant increases in gamma power relative to Control in
only a small number of sites, whilst Checkerboard expressed
no significant gamma power enhancement relative to
Control. These results may be related to lack of complexity
in the task. With the exception of Recall, these tasks were
passive, as they did not require the subject to actively
engage in the task. This is in contrast to the Expectancy,
Learning, Reading and Subtraction tasks all of which
required active involvement by the participant and there-
fore, we propose, induced far more impressive gamma
power responses. While the Recall task was not passive, it
was still simple as the participants were presented with lists
from which they had to select the list they had previously
learnt. They were not required to spontaneously recall the
learnt words un-cued. Although gamma enhancement with
Music was left-sided, a subset of subjects undertook a
similar task, viz listening to Mozart, in which the gamma
augmentation was bi-temporal (unpublished). We are
therefore reluctant to interpret the apparent lateralization
with Pachelbel as a robust finding at this stage.
There were different distributions between the areas of
augmented gamma EEG determined by significance versus
areas determined by maximal amplitude. Maximal mean
power was sometimes markedly influenced by powerful
gamma responses in a few subjects with little or no
enhancement at the same area in others. This observation
points to striking individual variability in the brain areas
recruited into mental activity, possibly correlating with the
widely differing strategies individuals use in solving mental
problems. The areas most consistently activated were
parietal and central, an observation that fits with the
known general involvement of fronto-parietal networks
during working memory processes in humans (Cabeza and
Nyberg, 2000).
How do the findings from this study relate to the
temporal binding model of cortical processing? The
model proposes that increased gamma power, as
presented here, reflects large-scale integration of many
coactive cell assemblies synchronously discharging in
recurrent bursts at different periodicities within the
gamma band. The discharges would serve the purpose
of binding assemblies, both local and distant, so that the
information processed in both could be integrated into a
coherent whole. While we have not attempted to define
different regions with synchronous (same-phase) gamma
oscillations, enhanced synchroneity of neuronal bursting
locally is a prerequisite for enhancement of gamma EEG
activity, and we observed 2–5 fold increases in mean
gamma power, strongly supportive of gamma involve-
ment in cerebral processing and consistent with the
temporal binding model. In the Reading task, for
example, the gamma response reflects binding in
the various visual perception and language comprehen-
sion assemblies across the occipital, parietal and temporal
areas to form the story. In the temporal binding model,
task complexity demands utilisation of more cognitive
resources. This requires more binding and subsequently
results in increased gamma power. From this viewpoint,
Subtraction and Reading would be the most complex of
the tasks we administered, intuitively something that
seems likely.
Using spectral analysis to examine EEG correlates of
mental processing permits measurement of oscillatory
phenomena only. While evidence that oscillatory activity
is an important aspect of cortical processing and reflects
synchrony and binding, it is not established that oscillatory
activity is essential for all mental processing nor for
mediating all synchronous (bound) neuronal activity. For
example, Newsome et al. (1990) demonstrate that firing
rates of neurons correlate with the perception of motion
(control condition 10–45 spikes per 2 s versus activated
condition 45–90 spikes per 2 s). Konig et al. (1995) have
also observed that synchronous neural discharges may be
achieved over distances less than 2 mm with or without
oscillating firing patterns. Our methodology does not permit
measurement of any aspect of such non-rhythmic activity if
it occurs during the mental tasks we used.
In conclusion, all of the cognitive tasks we administered
clearly increased gamma power relative to a Control
condition. This enhancement was significant at more than
one scalp site for all tasks with the exception of Checker-
board. The Expectancy, Learning, Reading and Subtraction
tasks were the most complex tasks and expressed the most
impressive gamma power response. Finally, different tasks
led to different distributions of gamma EEG power increase.
These results establish the easy feasibility of examining
sustained high frequency EEG activity without time-locked
averaging and demonstrate some of the EEG correlates of
mentation. It provides evidence of the involvement of
gamma EEG rhythms in these processes and demonstrates
some specificity in the distribution of gamma EEG
activation. The findings are consistent with the temporal
binding model. This method also offers a simple means of
defining the distribution of gamma over the cerebral
convexity correlating with thought processes in individuals,
as well as in health and in disease.
Acknowledgements
Funded by National Health and Medical Research
Council.
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