Ketamine Modulates Theta and Gamma Oscillations
Ketamine, an N-methyl-D-aspartate (NMDA) receptor glutamatergic antagonist, has been studied as a model of schizophrenia when applied in subanesthetic doses. In EEG studies, ketamine affects sensory gating and alters the oscillatory characteristics of neuronal signals in a complex manner. We investigated the effects of ketamine on in vivo recordings from the CA3 region of mouse hippocampus referenced to the ipsilateral frontal sinus using a paired-click auditory gating paradigm. One issue of particular interest was elucidating the effect of ketamine on background network activity, poststimulus evoked and induced activity. We find that ketamine attenuates the theta frequency band in both background activity and in poststimulus evoked activity. Ketamine also disrupts a late, poststimulus theta power reduction seen in control recordings. In the gamma frequency range, ketamine enhances both background and evoked power, but decreases relative induced power. These findings support a role for NMDA receptors in mediating the balance between theta and gamma responses to sensory stimuli, with possible implications for dysfunction in schizophrenia.
University of Pennsylvania
Departmental Papers (BE) Department of Bioengineering
Ketamine Modulates Theta and Gamma
Maciej T. Lazarewicz
University of Pennsylvania
Richard S. Ehrilichman
University of Pennsylvania
Christina R. Maxwell
University of Pennsylvania
Michael J. Gandal
University of Pennsylvania, email@example.com
Leif H. Finkel
University of Pennsylvania
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Lazarewicz, M.T., R.S. Ehrlichman, C.R. Maxwell, M.J. Gandal, L.H. Finkel and S.J. Siegel. (2009). "Ketamine Modulates Theta and Gamma
Oscillations." Journal of Cognitive Neuroscience. Vol. 22(7). pp. 1452-1464.
© 2009 Massachusetts Institute of Technology
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Ketamine Modulates Theta and Gamma Oscillations
Maciej T. Lazarewicz, Richard S. Ehrlichman, Christina R. Maxwell,
Michael J. Gandal, Leif H. Finkel, and Steven J. Siegel
Ketamine, an N-methyl-D-aspartate (NMDA) receptor gluta-
matergic antagonist, has been studied as a model of schizophrenia
when applied in subanesthetic doses. In EEG studies, ketamine
affects sensory gating and alters the oscillatory characteristics of
neuronal signals in a complex manner. We investigated the effects
of ketamine on in vivo recordings from the CA3 region of mouse
hippocampus referenced to the ipsilateral frontal sinus using a
paired-click auditory gating paradigm. One issue of particular in-
terest was elucidating the effect of ketamine on background net-
work activity, poststimulus evoked and induced activity. We find
that ketamine attenuates the theta frequency band in both back-
ground activity and in poststimulus evoked activity. Ketamine also
disrupts a late, poststimulus theta power reduction seen in control
recordings. In the gamma frequency range, ketamine enhances
both background and evoked power, but decreases relative induced
power. These findings support a role for NMDA receptors in mediat-
ing the balance between theta and gamma responses to sensory stim-
uli, with possible implications for dysfunction in schizophrenia.
Two main hypotheses for the pathogenesis of schizo-
phrenia focus on disor ders of dopamine (Abi-Dargham
et al., 2002; Carlsson, Waters, Waters, & Carlsson, 2000; Akil
et al., 1999; Weinberger, Berman, & Illowsky, 1988) and glu-
tamate mechanisms (Coyle, 2006; Tamminga, 1998). Many
of the changes in the glutamatergic dysfunction model are
reported in hippocampus (Reynolds & Harte, 2007). Keta-
mine is a glutamate-receptor blocking agent that can mimic
several symptoms and cognitive deficits associated with
schizophrenia (Lahti, Weiler, Tamara Michaelidis, Parwani,
& Tamminga, 2001). Ketamine models both the hyperdo-
paminergi c and hypoglutamatergic putative mechanisms
of schizophrenia (Gunduz-Bruce, 2009). Acute administra-
tion of ketamine is accepted as a model of psychosis and is
correlated with both positive and negative symptoms of
schizophrenia in both humans (Adler et al., 1999) and ani-
mals (Adams & Moghaddam, 1998). At pharmacologically
relevant concentrations, ketamine acts as a noncompeti-
tive antagonist of the N-methyl-
D-aspartate (NMDA) recep-
tor. This mechanism is considered responsible for the
schizophrenia-like symptoms (Tsai & Coyle, 2002) and is
linked to the disinhibitio n of hippocampal interneurons
(Lewis & Moghaddam, 2006; Greene, 2001). Enhancement
of NMDA receptor action is implicated in reducing some
of the positive symptoms of schizophrenia (Wood, 2005),
suggesting that facilitating NMDAR function may be a useful
Ketamine at subanesthetic doses has been extensively
studied as a model of glutamatergic dysfunction in animal
models of schizophrenia (Bubenikova-Valesova, Horacek,
Vrajova, & Hoschl, 2008; Becker et al., 2003; Moghaddam
& Jackson, 2003; Mansbach & Geyer, 1991). Loss of gluta-
mate receptor function is believed to underlie a range of
cognitive and sensory deficits associated with the disease
(Coyle, 2006). Ketamine has been shown to alter both glu-
tamatergic and dopaminergic neurotransmission, in brain
regions including neocortex, entorhinal cortex, hippocam-
pus, medial septum, thalamus, and brain stem among oth-
ers (Becker et al., 2003). Specifically interesting are the
effect s that ketamine has on gamma oscillations, as they
are thought to be crucial for binding together different fea-
tures o f incoming s ensory information (Gray & Singer,
1989) as well as coordinating the activity of local neuronal
populations (Lee, Williams, Haig, & Gordon, 2003). Gamma
oscillations have also been linked to information process-
ing (Gray & Singer, 1989), consciousness (Engel, Fries, &
Singer, 2001), attention (Vidal, Chaumon, OʼRegan, & Tallon-
Baudry, 2006; Herrmann, Munk, & Engel, 2004; Tiitinen et al.,
1993), and memory (Kaiser & Lutzenberger, 2005; Howard
et al., 2003; Sederberg, Kahana, Howard, Donner, & Madsen,
2003; Tallon-Baudry, Bertrand, Peronnet, & Pernier, 1998).
Induced gamma oscillations are implicated in object repre-
sentation (Rodriguez et al., 1999; Tallon-Baudry, Kreiter, &
Bertrand, 1999) and activation of associative memories
(Miltner, Braun, Arnold, Witte, & Taub, 1999; Pulvermuller,
Lutzenberger, & Preissl, 1999). Stimulus evoked gamma-
band responses have been suggested to reflect synchro-
nously active neural assemblies and the precise temporal
relationship of concurrently incoming stimuli (Tallon-Baudry
et al., 1999). Recently, it was shown that the power of gamma
oscillations correlates with wor king memory dur ing the
n-back task in humans (Sederberg et al., 2006; Howard
University of Pennsylvania, Philadelphia
© 2009 Massachusetts Institute of Technology Journal of Cognitive Neuroscience 22:7, pp. 1452–1464
et al., 2003). In patients with schizophrenia, this correla-
tion is disturbed (Cho, Konecky, & Carter, 2006). A recent
clinical paper has shown that increasing gamma oscilla-
tions with a novel GABA type A agonist correlates with in-
creased cognitive perfo rmance in schizophrenic patients
(Lewis et al., 2008). Several studies have demonstrated in-
creased gamma power after ketamine administration in hip-
pocampus in vivo (Hinman, Sabolek, & Chrobak, 2007; Ma
& Leung, 2007). Because ketamine acts through blocking
glutamatergic rec eptors and has an inhibit ory effect on
cells, it is perhaps unexpected to see an increase of gamma
power. However, in hippocampus, NMDA receptors are
located not only on pyramidal cells but also on several
classes of interneurons such as oriens lacunosum-moleculare
(O-LM) cells (Nyiri, Stephenson, Freund, & Somogyi, 2003;
Hajos, Freund, & Mody, 2002) or bistratified and basket cells
(Buhl, Szilagyi, Halasy, & Somogyi, 1996; Koh, Geiger, Jonas,
& Sakmann, 1995; McBain & Dingledine, 1993), suggesting
that ketamine may be acting to increase gamma power via
Theta oscillations have been implicated in sensorimotor
integration (Bland & Oddie, 2001; OʼKeefe & Recce, 1993),
emotion (Gray, 1982), and formation and recall of episodic
and declarative memory ( Jacobs, Hwang, Curran, & Kahana,
2006; Vertes, 2005), as well as working and long-term mem-
ory encoding (Klimesch, Freun berger, Sauseng, & Gruber,
2008). It was suggested that restoring theta-range rhythmic-
ity restores hippocampal function (McNaughton, Ruan, &
Woodnorth, 2006). The theta rhythm may also play a role
in information processing using an attentional double-gating
mechanism, “filtering-in” signals for effective registration and
encoding of selected information and additionally “filtering-
out” interfering inputs (Vinogradova, 1995). A relationship
between gamma and theta oscillations has been well estab-
lished in hippocampus (Canolty et al., 2006; Bragin et al.,
In this article, we analyze data acquired in an auditory
paired-click gating paradigm. This experimental design
has been extensively investigated in normal cognitive and
schizophrenic studies (Brockhaus-Dumke, Mueller, Faigle,
& Klosterkoetter, 2008). In this auditory gating paradigm in
healthy subjects and animals, the ratio of EEG responses of
the second click to the first click is significantly less than
one, what is called “sensory gating.” In patients diagnosed
with schizophrenia, this sensory gating phenomenon is re-
duced or abolished (the ratio is close to one). Several stud-
ies suggest that gating ratio abnormalities in schizophrenia
are actually mediat ed by reductions i n the first click re-
sponse in unmedicated patients, rather than increased am-
plitude of the second (Clementz & Blumenfeld, 2001; Jin
et al., 1997; Jin & Potkin, 1996; Adler, Rose, & Freedman,
1986; Freedman, Adler, Waldo, Pachtman, & Franks, 1983).
Previous studies from our group and others demonstrate
a high degree of similarity between human and mouse EEG
and ERPs for morphology, as well as physiological and phar-
macological response properties using this configuration
(Ehrlichman, Maxwell, Majumdar, & Siegel, 2008; Halene
& Siegel, 2008; Rabin et al., 2008; Metzger, Maxwell, Liang,
& Siegel, 2007; Phillips, Ehrlichman, & Siegel, 2007; Maxwell,
Ehrlichman, Liang, Gettes, et al., 2006; Maxwell, Ehrlichman,
Liang, Trief, et al., 2006; Maxwell, Liang, et al., 2006; Siegel
et al., 2003, 2005; Connolly et al., 2003, 2004; Maxwell, Kanes,
Abel, & Siegel, 2004; Maxwell, Liang, et al., 2004; Umbricht
et al., 2004; Umbricht, Latanov, Vissotksi, Nitsch, & Lipp,
2002; Ste vens, Kem, & Fre edman, 1999; Stevens, Kem,
Mahnir, & Freedman, 1998; Stevens & Wear, 1997; Stevens
et al., 1996; Stevens, Meltzer, & Rose, 1995). In animals,
acute injection of ketamine similarly affects this ratio, as
well as the magnitude and latency of the ERP components
(Ehrlichman et al., 2008; Maxwell, Ehrlichman, Liang,
Tri e f , et a l ., 2 0 0 6; Connolly et al., 2003, 2004). As such,
ketamine may represent a model of alter ed circuitry in
schizophrenia. We use the auditory paired-click paradigm
to elucidate the contributions of background, evoked, and
induced power changes whose interaction obscure the
role of altered glutamatergic responses following ketamine
(using 5 vs. 20 mg/kg) application.
C57BL/6Hsd (B6) male mice (n = 20) were obtained at
8 weeks of age from Harlan (Indianapolis, IN). All proto-
cols were performed in accordance with University Labo-
ratory Animal Resources guidelines and we re approved
by the Institutional Animal Care and Use Committee.
Testing was conducted between 10 and 13 weeks of age.
Mice were housed three to four per cage in a light- and
temperature-controlled Association for Assessment a nd
Accreditation of Laboratory Animal Care-accredited animal
facility. All efforts were made to minimize animal number
and suffering. Water and standard rodent chow were avail-
able ad lib. Experiments were conducted during the light
phase between the hours of 0900 and 1300. Mice were ac-
climated to the housing facility for at least 1 week prior to
Treatment groups consisted of acute ketamine (5 and 20 mg/
kg ip). In the ketamine condition, 20 mg/kg ip was used, un-
less otherwise stated. Although the ketamine doses used in
this study represent 5% and 20% of the minimum anesthetic
dose, we assessed their effects on locomotor activity to con-
trol for possible motor effects on EEG. Mice (n = 6/group,
total = 18) were tested in the same home cage environment
for the same duration as recording of ERPs according to pre-
viously published methods (Halene & Siegel, 2008). Animals
were transferred from their housing facility to the locomotor
activity testing room in their home cages for a habituation
period of 15 min prior to testing. Animals were placed in
automated locomotor activity frames that creates a grid of
infrared light beams throughout the transparent home cages
(31 cm length, 19 cm width, 16 cm height) (Med Associates,
Lazarewicz et al. 1453
St. Albans, VT, USA). Data were collected over a total period
of 30 min using a personal computer.
Animals underwent stereotaxic implantation of electrode
assemblies (PlasticsOne, Roanoke, VA) for nonanesthe-
tized recording of auditory ERPs as previously reported
(Maxwell, Ehrlichman, Liang, Trief, et al., 2006; Connolly
et al., 2003, 2004; Maxwell, Kanes, et al., 2004; Siegel et al.,
2003). Animals were anesthetized with isoflurane, and uni-
polar recording electrodes were placed in the CA3 hippo-
campal region (positive polarity) (1.4 mm posterior, 2.65 mm
lateral, and 2.75 mm deep relative to bregma) and referenced
to the ipsilateral frontal sinus (negative polarity) to reflect
whole-brain electrical activity. Electrode localization in CA3
was histologically verified using the Perlʼsironmethodaspre-
viously described (Figure 1A; Connolly et al., 2003; LaBossiere
& Glickstein, 1976). ERPs recorded from this electrode con-
figuration are characteristically similar to human recordings
from the Cz scalp location as illustrated in the third figure
from a prior publication (Siegel et al., 2003). The electrode
pedestal was secured to the skull using dental cement and
cyanoacrylate glue. EEGs were recorded 2 weeks after elec-
trode surgery, as described below.
EEGs were recorded during the presentation of a paired-
click auditory task. All raw EEG was inline band-pass filtered
between 1 and 500 Hz during collection. Stimuli were gen-
erated by Micro1401 hardware and Spike 5 software (Cam-
bridge Electronic Design, Cambridge, UK) and were delivered
through speakers attached to the cage top. All recordings
were performed in a home cage environment that was placed
in a Faraday cage 15 min before stimulus onset. A series of
50 pairs of white noise clicks (10 msec in duration each)
with a 500-msec interstimulus interval were presented
with a 9-sec intertrial interval at 85 dB compared with back-
ground of 70 dB. T esting commenced 5 min after intra-
peritoneal injection for each treatment group.
Data analysis was performed using MatLab (MathWorks,
Natick, MA) and JMP (SAS, Cary, NC) software. Four mice
were rejected from the study because of severe recording
artifacts. Two groups of eight mice were each analyzed un-
der two conditions: after saline and after ketamine injec-
tion using a within-subjects experimental design. The first
group was injected with 5 mg/kg ketamine and the second
with 20 mg/kg ketamine. Single-trial epochs between −2.5
and 2.5 sec relative to the first click were extracted from
the continuous data. Individual sweeps were rejected for
movement artifact on the basis of a criterion of two times
the root-mean-squared amplitude per mouse. The mean
number of trials in each condition was not significantly
different. ERPs for the first and the second clicks were
obtained by averaging epochs centered at Time 0 and
500 msec to 0 μ V, respectively. For each epoch, power
was calculated by the EEGLAB MatLab toolbox (Delorme
& Makeig , 2004) using Morle t wavelet s in 91 logarithmi-
cally spaced frequency bins between 2.4 and 150 Hz, with
wavelet cycle numbers ranging from 3 to 12. Time intervals
of 685 msec were dropped from both sides of the epoch.
The remaining 3630 msec were divided into 600 time bins.
All measures of power were expressed in decibels (dB) as a
logarithm of the power amplitude multiplied by 10. Evoked
power was calculated by averaging the raw data across trials,
and taking the power of that averaged data. For induced ac-
tivity, the power of individual trials was taken and averaged,
and then the part attributable to evoked activity was sub-
tracted. In order to compute the power spectral density,
the mean of total power between −1100 and −100 msec
was averaged. Event-related spectral perturbations (ERSP)
were calculated by averaging power relative to the mean
Figure 1. Demonstration of electrode placement in hippocampus.
(A) Positive electrode tips are marked using Perlʼs iron reaction. Four
examples are shown with the characteristic staining for iron adjacent to
CA3. (B) Gamma power is modulated by theta oscillation phase. The
gray line represents a grand average of gamma power (30–50 Hz) aligned
to the peak of the theta power (3–12 Hz). The black line shows gamma
activity that is not aligned to the theta oscillations. The peak of the
gamma is shifted 10 msec from the peak of the theta with secondary
peak locations compatible with 7–8 Hz oscillations.
1454 Journal of Cognitive Neuroscience Volume 22, Number 7
baseline between −1100 and −100 msec. To confirm our
results, we estimated the envelope of the amplitude of
band-pass filtered signal using analytical amplitude as pre-
viously performed by Freeman (2004). Briefly, the raw sig-
nal was band-pass filtered using a two-way least-squares
FIR filter in three frequency ranges: low theta (3–5Hz),
high theta (6–12 Hz), and gamma (30–80 Hz). Subsequently,
the signal envelope was extracted by calculating the module
of the Hilbert transform. Statistical analysis was performed
using the permutation method (Westfall & Young, 1993)
with 10,000 iterations. Nonpaired and paired t tests were
used for the saline/ketamine factor, and the after-event/
baseline factor, respectively. This method keeps the family-
wise error type II at the desired level for multiple compar-
isons in the time or frequency domain. We do not report
statistically significant changes shorter then 10 msec. For
evoked power analysis, the ANOVA repeated measure of
averaged squared analytical amplitude was calculated
using JMP in time intervals 0–60 and 515–575 msec. The
power of statistical test was stronger in the case of the
power spectral density than analytical amplitude because
the former contains data accumulated over relatively long
There was no effect of ketamine on locomotor activity at
these subanesthetic doses [F(2, 15) = 1 .67, p =.22;
mean ± SEM: saline 2721 ± 333.7, 5 mg/kg ketamine
2270 ± 341.9, 20 mg/kg ketamine 3324 ± 524.5]. The
qualitative pattern of ERPs is demonstrated in Figure 2.
The authors have previously published the effects of ke-
tamine on the amplitude and latency of time-locked aver-
aged activity in the time domain (Maxwell, Ehrlichman,
Liang, Trief, et al., 2006; Connolly et al., 2004; Siegel et al.,
2003). The current work focuses on the time–frequency do-
main to extend previous findings. Examples of single-trial
recordings are shown in Figure 3. A clear change of rhythm
due to the auditory clicks is evident in the saline condition.
In the ketamine condition, a change in rhythm is almost
nonexistent. Figure 1B demonstrates the pattern of theta-
modulated gamma activity present in these recordings, in-
dicating a large contribution of hippocampal activity to the
To investigate the effect of ketamine on background activ-
ity unrelated to the stimulus, the average power was calcu-
lated before th e fir st click in the time window −1100 to
−100 msec (Figure 4).
The dosage of 5 mg/kg ketamine yields a statistically sig-
nificant increase in power in frequency range 33–93 Hz
( p < .001) including the gamma range (30–80 Hz).
At 20 mg/kg, the increase in power additionally includes
the frequency range 26.5–143 Hz ( p < .001) including the
gamma range. We note a statistically significant decrease
in power within the frequency range 2.5–21 Hz ( p <
.001), which includes parts of the delta, theta, alpha, and
beta frequency bands. The two curves cross near 23.5 Hz.
ERSP (Figure 5) and analytic amplitude (Figure 6) for evoked
power did not show a statistically significant effect between
saline and 5 mg/kg ketamine ( p >.05).
For 20 mg/kg ketamine, there was a decrease in low theta
(3–5Hz)[F(1, 7) = 14.5, p < .01] and high theta (6–12 Hz)
power [F(1, 7) = 6.2, p < .05] in the time range 0–60 msec,
[F(1, 7) = 12.7, p < .01] and 515–575 msec [F(1, 7) = 29.9,
p < .001].
Using induced ERSPs, two main effects ( p < .001) are vis-
ible in the saline condition (Figure 7). There is an early burst
of power near 20–40 msec in the 15– 150 Hz frequency
range, and a strong depression starting near 160 msec
and lasting over 1 sec is pronounced in the 3–20 Hz fre-
quency range. This depression has three visible peaks, the
first two of which are near 300 msec at 4 Hz and 10 Hz
Figure 2. ERPs during the auditory paired-click task after saline (black
lines) and ketamine (gray lines) injections with (A) 5 mg/ kg and (B)
20 mg/kg. Left panel responses are shifted to 0 μV at the time of the
first click (at 0 sec), and right panel responses are shifted to 0 μV at the
time of the second click (at 0.5 sec). Inset shows zoom at 0–50 msec in
each panel. ERPs were calculated averaged over 50 trials and across
Lazarewicz et al. 1455
and the latter near 700–800 msec at 10 Hz. In the ketamine
condition, the power burst in the early 20–40 msec interval
is less pronounced, and in the 20-mg/kg ketamine condi-
tion, the late theta depression is lost.
To further quantify these changes, we calculated square
analytic amplitude (Freeman, 2004) in three frequency
bands: low theta (3–5Hz),hightheta(6–12 Hz), and gamma
(30–80 Hz) (Figure 8). The family-wise error was set to a level
of 0.01. At 5 mg/kg ketamine, excepting three short intervals
in the gamma frequency range (135–155, 335–350, and
595–605 msec), there is no significant difference between
the ketamine and saline conditions. In the saline condition
for low theta, a significant attenuation of analytic amplitude
from baseline is apparent in the time interval 155–400 msec.
In the ketamine condition for low theta, the depression
is slightly longer and localized in the time interval 125–
730 msec. In the saline condition for high theta, the deviation
from baseline is localized in the intervals 115–500, 600–920,
and 990–1025 msec. In the ketamine condition for high theta,
the power is depressed in the time interval 155–705 msec.
The induced gamma frequency band shows an early increase
from the baseline in the saline condition during 6–45 msec
and in the ketamine condition during 10–36 msec.
In contrast to 5 mg/kg, signal power at 20 mg/kg in the
low theta saline and ketamine conditions are statistically dif-
ferent for all calculated time intervals. Low thetaʼs depres-
sion from baseline in the saline condition is pronounced in
the time interval 200–755 msec, but there is no statistically
significant deviation from the baseline in the ketamine con-
dition. For high theta, the two conditions are different ex-
cept for two time intervals: 185–850 and 970–1360 msec. In
the saline condition, power is depressed during the long
time interval 115–1220 msec and, in the ketamine condition,
power is depressed only briefly at 660–740 msec. For the
gamma frequency range, the two conditions are statistically
different except for the short time interval after the first click
(14–52 msec) within which both the saline and ketamine
conditions are attenuated during 10–47 and 13–29 msec,
respectively. In the saline condition, for the gamma range
during the time interval 100–1100 msec, power has inter-
mittent depression from baseline that is not present in the
ketamine condition, nor in the 5-mg/kg dataset.
Our results suggest the following findings.
• Ketamine produces a marked decrease in background
theta (3–7 Hz, 8–12 Hz), and an increase in background
gamma power (30–80 Hz).
• Evoked responses follow the background trend: 0–100 msec
poststimulus theta evoked power is decreased, and gamma
evoked power is increased.
• Induced responses in the gamma range have similar
characteristics to background gamma power and evoked
Figure 4. Power spectral densities calculated for intervals between
−1100 and −100 msec before the first click (background data). Saline
(black lines) and ketamine (gray lines) injection with (A) 5 mg/kg and
(B) 20 mg/kg. Horizontal lines with star above represent frequency
ranges with statistically significant differences between saline and
ketamine conditions with p < .001. At (A) horizontal bar spreads from
33 to 95 Hz. At (B) the curve intersection is located about 23.5 Hz.
Figure 3. Example of five
consecutive raw single-trial
recordings (A) after saline and
(B) ketamine injection.
Horizontal scale line represents
500 msec and vertical line
represents 250 μV. Two vertical
lines represent the first and the
second auditory clicks.
1456 Journal of Cognitive Neuroscience Volume 22, Number 7
Figure 5. Evoked ERSPs.
Colors represent average
deviation in decibels (dB) from
the mean baseline before the
first click. (A) After saline
(pre 5 mg ketamine), (B) after
5 mg/kg ketamine injection,
(C) after saline (pre 20 mg
ketamine), and (D) after
20 mg/kg ketamine injection.
Figure 6. Evoked analytic
amplitude calculated for three
frequency bands: low theta
(3–5 Hz), high theta (6–12 Hz),
and gamma (30–80 Hz) after
saline (green lines) and
ketamine (red lines) injections
with (A) 5 mg/kg and (B)
20 mg/kg. Width of the line
indicates standard error of
measurement (SEM ). Stars
mean statistically significant
difference between saline and
ketamine conditions (*p < .05,
**p < .01, ***p < .001).
Lazarewicz et al. 1457
Figure 7. Induced ERSPs.
Colors represent average
deviation in decibels (dB) from
the mean baseline before the
first click. (A) After saline
(pre 5 mg ketamine), (B)
5 mg/kg ketamine injection,
(C) saline (pre 5 mg ketamine),
(D) 20 mg/kg ketamine
injection. Only statistically
significant results are shown
( p < .05). Black contour
indicates statistical significance
at the level of ( p < .001).
Figure 8. Induced analytic
amplitude calculated for three
frequency bands: low theta
(3–5 Hz), high theta (6–12 Hz),
and gamma (30–80 Hz) after
saline (green lines) and
ketamine (red lines) injections
with (A) 5 mg/kg and (B)
20 mg/kg. Horizontal bars
represent time ranges with
differences between saline and
ketamine conditions (black
line), saline condition and saline
mean baseline (green line), and
ketamine condition and
ketamine mean baseline (red
line) with p < .01. Width of the
line indicates standard error of
measurement (SEM ).
1458 Journal of Cognitive Neuroscience Volume 22, Number 7
responses. However changes relative to the background
are reduced by ketamine.
• There is a clear suppression of induced theta power that
pers ists for roughly 1000 msec in control animals, but
this suppression is lost following ketamine.
Theta and Gamma Oscillations
We investigated the effect of ketamine during the auditory
paired-click paradigm using two doses (5 and 20 mg/kg).
We analyzed the relationship between background, evoked,
and induced power before and after the auditory stimulus
and their alteration in the presence of ketamine. We have
specifically focused on the theta and gamma frequency
ranges. Our results demonstrate that ketamine, in subanes-
thetic doses, produces complex changes in the network os-
cillatory activity of neurons, specifically in theta and gamma
frequency ranges. These perturbations affected ongoing,
background activity as well as event-related activities. Addi-
tionally, power values in the theta and gamma bands tended
to move in opposite directions, which may be explained by
the fact that oscillations in hippocampus in these frequency
ranges may be interrelated (Chrobak & Buzsaki, 1998; Bragin
et al., 1995; Llinas & Ribary, 1993; Soltesz & Deschenes,
1993; Woolley & Timiras, 1965). Of special note, ketamine
attenuates the depression in late induced theta power, leav-
ing only a short depressed activity after the second click lo-
cated in the high theta frequency range. This may correlate
with recent human EEG data showing a decrease in the
8–12 Hz total power during a P300 task in the control healthy
group and an attenuation of this decrease in patients with
schizophrenia (Ford, Roach, Hoffman, & Mathalon, 2008).
Because ketamine is thought to exert its effects via block-
ing NMDA receptors, these data support their role in medi-
ating the balance between theta and gamma responses to
sensory stimuli with implications for dysfunction in schizo-
phrenia. We also observed that ketamine produced changes
in the prestimulus power content, indicating that the state
of the animal brain changed independent of the auditory
stimuli used in the experiment. This makes the analysis of
the event-related changes more complex, as changes in
power relative to the background may depend upon their
absolute values. We found an increase in power in the gamma
frequency range (30–80 Hz) and a decrease in power in lower
frequencies, including the theta range (low: 3–5 Hz; high:
6–12 Hz). The transition point between decrease and in-
crease in power was located around 23.5 Hz. For the lower,
subanesthetic concentration of 5 mg/kg ketamine, the
only statistically significant change was the gamma power
amplification. The increase of in vivo gamma power after
ketamine administration in hippoc ampus was previously
reported (Hinman et al., 2007; Ma & Leung, 2007). Magneto-
encephalography studies suggested a positive correlation
between theta power in the temporal lobe and positive symp-
toms such as hallucinations (Sperling, Bleich, Maihofner, &
Reulbach, 2009; Ince, Goksu, Pellizzer, Tewfik, & Stephane,
2008; Fehr et al., 2001, 2003; Ishii et al., 2000; Sperling, Vieth,
Martus, Demling, & Barocka, 1999; Canive et al., 1998). These
studies suggest an opposite change in theta power than that
reported here. It is not possible to evaluate the effects of
ketamine on constructs such as hallucinations in our ani-
mals, complicating the ability to correlate our findings with
symptomatic exacerbations in huma ns. Consistent with
our results, Chrobak, Hinman, and Sabolek ( 2008) also
demonstrated ketamine-induced changes in theta and
gamma power, including a decoupling of the theta/gamma
phase relationship in hippocampus.
Ketamine Mode of Action on Local Circuits
The nature of our electrode configuration allows for record-
ing of activity throughout the entire brain. However, hippo-
campus is the main generator of theta rhythms (Buzsaki,
2002) and some investigators have argued that hippocam-
pus contributes strongly to gating (Adler, Hoffer, Wiser, &
Freedman, 1993). It has also been reported that the power
of gamma oscillations is significantly higher in hippocam-
pus than in the rest of the brain (Bartos, Vida, & Jonas,
2007). We propose that hippocampus contributes heavily
to the activity in our recordings. Therefore, understanding
the effect of ketamine on local hippocampal circuits may
help interpret the observed changes in gamma and theta
oscillatory power. We speculate that dysfunction of the
glutamatergic system in schizophrenia affects theta/gamma
oscillations on the level of this local circuit. In particular, we
speculate that a disruption in the interaction between dif-
ferent subtypes of interneurons and pyramidal cells may
mediate our observed oscillatory findings. This circuit
has been shown to be disrupted in schizophrenia (Lewis,
Hashimoto, & Volk, 2005) and it has also been shown to be
a key generator of oscillatory activity in neuronal popula-
tions in vivo (Bartos et al., 2007). Ketamine likely targets
NMDA rece ptors lo cated at hippocampal interneurons
(Greene, 2001), with an emphasis on O-LM cells (Tort,
Rotstein, Dugladze, Gloveli, & Kopell, 2007) that contain
an abundance of NMDA receptors (Nyiri et al., 2003; Hajos
et al., 2002). These interneurons are 10-fold more sensitive
to NMDA-receptor antagonists than pyramidal cells at low
doses (Grunze et al., 1996).
We report significant changes in background gamma (in-
creased) and background theta (decreased) activity with
ketamine administration. In interpreting these results, it is
interesting to note that at the level of hippocampus mod-
ulation of gamma and theta oscillatio ns has been shown
to be coupled. Data from in vitro preparations indicate that
theta oscillations may be masked or inhibited by the pres-
ence of gamma oscillations (Gillies et al., 2002). An implica-
tion of this finding is that disruption of the hippocampal
theta generator would have a secondary effect of unmask-
ing background gamma activity (Gillies et al., 2002), increas-
ing power in this frequency band. Although the precise
mechanism of theta generation is unknown, hippocampal
Lazarewicz et al. 1459
O-LM cells are thought to be integrally involved (Traub,
Bibbig, LeBeau, Buhl, & Whittington, 2004). O-LM cells
are also known to contain an abundance of NMDA recep-
tors (Tort et al., 2007), and thus, would likely be affected by
ketamine or states of altered glutamatergic neurotransmis-
sion. The failure of the theta generator as a mechanism for
the observed changes associated with ketamine is in agree-
ment with the hypothesis that event-related theta oscilla-
tio ns have a double function in information pr ocessing:
“filtering in” the first click, and “filtering out” the second
click (Vinogradova, 1995). Although this is a plausible mech-
anistic explanation of our findings, further experimental
work and computational modeling will be required to so-
lidify these connections.
Absolute vs. Relative Power
There is some variability in the literature regarding abnor-
malities in firing patterns observed in schizophrenia and in
animal models of the disorder. In human EEG studies,
there are reports of a gamma power decrease in schizo-
phrenia patients (Ferrarelli et al., 2008; Gallinat, Winterer,
Herrmann, & Senkowski, 2004), simultaneous decreases
in the left he misphere and frontal sites and an increase
in right hemisphere and parieto-occipital sites (Haig et al.,
2000), a decrease in gamma power associated with negative
symptoms, and an increase in gamma power associated
with positive symptoms (Herrmann & Demiralp, 2005;
Lee et al., 2003).
Taking into account that, in an animal model of the dis-
order after acute injection of ketamine, a complex spec-
trum of changes is observed, we explored possible causes
for the complexities regarding increases and decreases in
signal power in the theta and gamma frequency ranges.
Several measured or calculated values can be confused if
not fully qualified: total power, evoked power, induced
power, absolute power, and power relative to the back-
ground. First, using “relative to the background” versus
“absolute change in power” may intr oduce divergent re-
sults, especially in tasks where the first factor is an external
stimulus and the second factor is saline versus drug condi-
tion. In our data, the induced gamma power is a good ex-
ample of this situation (Figure 8B). Short increases in the
induced gamma power just after the first click reach statis-
tically the same absolute value in the saline and ketamine
condition, but the relative changes ar e different because
they start from different prestimulus baselines. The total
power in that case behaves identically (data not shown).
Additionally, four combinations of experimental condi-
tions exist: before auditory stimulus when saline is in-
jected, after auditory stimulus when saline is injected,
before auditory stimulus when ketamine is injected, after
auditory stimulus when ketamine is injected. In all of these
four conditions, total/induced power of the field poten-
tial may differ. If A and B are two of these conditions and
the background/induced power is larger in Condition B
(F igure 9D, red color) than in Condition A (Figure 9D,
green color ), and relative-to-the-background change in
power is larger in Condition A, it still may not be large
enough to make the absolute power after the stimulus larger
in the Condition A, than in the Condition B. Therefore, a
comparison of relative changes of power needs to be evalu-
ated in the context of changes of the background power.
This complication does not apply to evoked power because
the background evoked power comes close to zero.
In an animal model of schizophrenia, it is possible to
perform a within-subjects experiment in which measure-
ments of power are taken in all four conditions for each
mouse. Human data in schizophrenia research come from
a comparison of the control and patient groups before and
after stimulus in a between-subjects experiment. It is not
possible to make within-subject comparisons between
control and schizophrenia conditions. Therefore, it is pos-
sible that, in the human experiments, the relative and ab-
solute changes of power may be confounded, taking into
account the large variability of spontaneous (background)
power levels within a control and patient group. Data re-
garding the effects of schizophrenia on gamma oscillations
are mixed. Some studies suggest reductions in gamma ac-
tivity using a gamma frequency stimulus to evaluate en-
trainment. Others show reductions in evoked power,
albeit a fter removal of baseline activity (Spencer et al.,
2003, 2004; Kwon et al., 1999). Our group has found in-
creased gamma power in schizophrenia, which is due to
the increase in baseline (Turetsky & Siegel, 2007; Turetsky,
McGue, Ramsey, Siegel, & Gur, 2006). Indeed, the variabil-
ity in findings is largely a function of how each group han-
dles background activity as its removal yields a reduction,
but its inclusion yields the opposite finding.
It may be that the local increase in gamma power (recorded
by intracranial electrode) is associated with the global de-
crease in the gamma power (recorded by a scalp electrode)
by breaking down the long-range synchronization in this
frequency range (Yeragani, Cashmere, Miewald, Tancer,
& Keshavan, 2006). It is conceivable that local changes in
oscillations, such as an increase in gamma, may break down
Figure 9. Summary of the absolute and relative changes in power
before and after an event in the saline (green) and ketamine (red)
conditions. (A) Theta evoked power, (B) gamma evoked power,
(C) theta induced power, (D) gamma induced power.
1460 Journal of Cognitive Neuroscience Volume 22, Number 7
the mechanisms for long-range synchronization, or in-
versely, the loss of long-range synchronization may cause
a local , comp ensatory increase in gamma power. T his
may explain the decrease in gamma power in EEG record-
ings in pa tients with schizophreni a and the increase in
power in potentials recorded in the animal models of schizo-
phrenia. Another explanation may be that the effect of ke-
tamine depends upon brain area and cortical layer (Roopun
et al., 2008). An increase in gamma power after ketamine
administration has also been found in neocortex (Pinault,
2008). In contrast, decreases in gamma power are seen
in vitro in medial-temporal structures (Cunningham et al.,
2006; Uhlhaas et al., 2006). Functional variability along the
longitudinal axis of hippocampus has also been described
(Kjelstrup et al., 2008); therefore, further investigation of
ketamine action in these regions may confirm some of
The use of a bipolar configuration spanning a negative pole
adjacent to frontal cortex and a positive pole in hippocam-
pus has both advantages and disadvantages. This configura-
tion allows for a better translation to human EEG, which is
subject to signals from multiple sources. However, our con-
figuration does not allow for isolation of signals to a single,
unitary source. As such, we are not suggesting that the ob-
served EEG spectral analysis reflects only hippocampal ac-
tivity. Rather, it reflects the gestalt of EEG signals that
coalesce to yield the pattern of abnormalities in schizophre-
nia from these two perspectives. Of note, this configuration
is most sensitive to the structures closest to the electrode
tips, and therefore, does include activity from both hippo-
campus and frontal cortex. Because our goal is to examine
the extent to which ketamine recapitulates the changes in
gamma and theta oscillations in schizophrenia, this method
is able to address the primary question posed in this study.
Future studies could examine the regional source contribu-
tions of these abnormalities.
In summary, we found that after injection of ketamine, theta/
gamma frequency oscillations display opposing effects that
suggest possible fundamental alterations in information
processing in schizophrenia.
Supported by NIH Conte Center MH-0640450640 45 and R01
DA023210-01. We thank Marieke van Vugt for fruitful discussion
about permutation methods, and Mark Lippmann for helpful
discussions and comments on the manuscript.
Reprint requests should be sent to Maciej T. Lazarewicz, Neuro-
engineering Laboratory, Department of Bioengineering, Univer-
sity of Pennsylvania, Room 240 Skirkanich Hall, 210 S. 33rd Street,
Philadelphia, PA 19104, or via e-mail: email@example.com.
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