1The Center for Basic Neuroscience and 2Department of Psychiatry, The University of Texas Southwestern Medical Center, Dallas, Texas 75235-9111
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ABSTRACT |
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Joho, Rolf H.,
Chi Shun Ho, and
Gerald A. Marks.
Increased - and Decreased
-Oscillations in a Mouse
Deficient for a Potassium Channel Expressed in Fast-Spiking
Interneurons.
J. Neurophysiol. 82: 1855-1864, 1999.
Kv3.1 is a voltage-gated, fast activating/deactivating potassium
(K+) channel with a high-threshold of activation and a
large unit conductance. Kv3.1 K+ channels are expressed in
fast-spiking, parvalbumin-containing interneurons in cortex,
hippocampus, striatum, the thalamic reticular nucleus (TRN), and in
several nuclei of the brain stem. A high density of Kv3.1 channels
contributes to short-duration action potentials, fast
afterhyperpolarizations, and brief refractory periods enhancing the
capability in these neurons for high-frequency firing. Kv3.1
K+ channel expression in the TRN and cortex also suggests a
role in thalamocortical and cortical function. Here we show that fast gamma and slow delta oscillations recorded from the somatomotor cortex
are altered in the freely behaving Kv3.1 mutant mouse. Electroencephalographic (EEG) recordings from homozygous
Kv3.1
/
mice show a three- to fourfold increase in both
absolute and relative spectral power in the gamma frequency range
(20-60 Hz). In contrast, Kv3.1-deficient mice have a 20-50%
reduction of power in the slow delta range (2-3 Hz). The increase in
gamma power is most prominent during waking in the 40- to 55-Hz range,
whereas the decrease in delta power occurs equally across all states of arousal. Our findings suggest that Kv3.1-expressing neurons are involved in the generation and maintenance of cortical fast gamma and
slow delta oscillations. Hence the Kv3.1-mutant mouse could serve as a
model to study the generation and maintenance of fast gamma and slow
delta rhythms and their involvement in behavior and cognition.
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INTRODUCTION |
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Kv3.1 is a voltage-gated K+
channel involved in the repolarization of the action potential
(Luneau et al. 1991; Yokoyama et al.
1989
). Subunits forming the tetrameric Kv3.1 channel are
expressed in the adult rat and mouse brain in a subset of interneurons
in cerebral cortex, striatum, and hippocampus, in the thalamic
reticular nucleus (TRN), in cerebellar granule cells, and in several
brain stem nuclei involved in auditory signal processing (Drewe
et al. 1992
; Perney et al. 1992
; Rettig
et al. 1992
; Rudy et al. 1992
; Weiser et
al. 1994
, 1995
). Kv3.1-expressing neurons in rat
neocortex, hippocampus, striatum, and the TRN contain the
calcium-binding protein parvalbumin (Du et al. 1996
;
Lenz et al. 1994
; Weiser et al. 1994
,
1995
), a marker for fast-spiking GABAergic interneurons (Kawaguchi 1995
; Kawaguchi and Kubota
1997
, 1998
). Heterologously expressed,
homotetrameric Kv3.1 channels display rapid kinetics of activation and
deactivation, a high-threshold of activation (approximately
10 mV),
and a relatively large unit conductance (~30 pS) (Grissmer et
al. 1994
). Indeed, Kv3.1 channels may contribute to
short-duration action potentials (APs) by rapidly opening during the
peak of depolarization leading to fast repolarization and fast
afterhyperpolarization (fAHP). This, in turn, may shorten the
refractory period following an AP; hence the relative amplitude of such
a current may influence AP duration and high-frequency firing
(Kanemasa et al. 1995
). Inasmuch as the duration of APs is closely related to calcium influx mediating neurotransmitter release, the activity of Kv3.1 channels may also influence the amount
of GABA released from fast-spiking GABAergic interneurons.
The widespread distribution of Kv3.1 in cortical interneurons suggests
a role in cortical function. Fast-spiking interneurons, which may
express Kv3.1 channels, are thought to be involved in generating fast
gamma (~40 Hz) oscillations in the hippocampus as well as the
neocortex (Bragin et al. 1995; Jefferys et al. 1996
; Steriade et al. 1998
; Traub et al.
1996
; Wang and Buzsáki 1996
;
Whittington et al. 1995
, 1997
). Fast
rhythms have been proposed to underlie the dynamic, coherent
synchronization of neuronal populations and to play a role in higher
cortical functions including perception, alertness, and learning
(Llinás and Ribary 1993
; Llinás et
al. 1991
; Ritz and Sejnowski 1997
; Singer
and Gray 1995
; Steriade et al. 1996a
). Inasmuch
as parvalbumin-containing GABAergic interneurons express high levels of
Kv3.1 and may be involved in gamma oscillations, it is possible that
Kv3.1 K+ channels are important for the
generation or maintenance of these fast rhythms.
The TRN consists exclusively of GABAergic neurons capable of firing
short-duration APs at high discharge rates, and these neurons express
relatively high levels of Kv3.1 (Drewe et al. 1992;
Perney et al. 1992
; Rettig et al. 1992
;
Rudy et al. 1992
; Weiser et al. 1994
,
1995
). The TRN occupies a central position in the
interacting neuronal networks within the thalamus and between cortex
and thalamus (McCormick and Bal 1997
; Steriade et
al. 1993
; von Krosigk et al. 1993
). TRN neurons
project to the various relay nuclei of the dorsal thalamus and receive
reciprocal, excitatory projections from thalamocortical collaterals and
from descending corticothalamic collaterals. In many species
investigated, TRN neurons during natural slow-wave sleep discharge in
bursts of spikes, with interspike frequencies >200 Hz (Kim et
al. 1997
). Trains of spike bursts, which occur at 10-14 Hz,
are followed by pauses giving rise to a rhythm in the very
low-frequency range (<1 Hz) (Contreras et al. 1993
;
Marks and Roffwarg 1993
; Steriade et al.
1986
). The interburst intervals at 10-14 Hz are associated with the genesis of sleep-spindles (Steriade et al.
1986
). Evidence is emerging that synchronization of the very
low-frequency rhythms in corticothalamic networks is responsible for a
range of cortical oscillations characteristic of slow-wave sleep
(Contreras and Steriade 1997
; Steriade and Amzica
1998
). The functional position of TRN in thalamocorticothalamic
interactions, the expression of Kv3.1 in TRN neurons, and the
channels' influence on AP duration and firing frequency suggest a
possible role in the generation of these oscillations.
We recently generated a Kv3.1-deficient mouse mutant using homologous
recombination in embryonic stem cells (Ho et al. 1997). Potential changes in AP waveform and duration in the absence of Kv3.1
might lead to altered firing patterns of TRN and cortical interneurons
and could affect thalamocortical and cortical oscillatory activity.
This, in turn, may affect behavior subserved by these rhythmic neuronal
activities. If this is indeed the case, then, the Kv3.1 mutant mouse
could serve as a model to study altered fast and slow rhythms and their
roles in behavior.
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METHODS |
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Breeding of Kv3.1-deficient mice
The generation of the original Kv3.1 mutant mouse on the 129/Sv
background has been described by Ho et al. (1997).
Briefly, embryonic stem cells derived from 129/Sv mice were used to
inactivate the Kv3.1 gene by homologous recombination. Stem cells
carrying a nonfunctional Kv3.1 gene were injected in BALB/c blastocysts to obtain chimeric mice. Male chimeric mice were mated with 129/Sv females, and heterozygous Kv3.1+/
offspring
were used to establish a 129/Sv colony. To generate a C57BL/6 colony,
male Kv3.1+/
129/Sv mice were crossed to female
wild type C57BL/6. Heterozygous Kv3.1+/
F1
males were backcrossed to wild type C57BL/6 females, and heterozygous offspring (N2) were used for further backcrossing to C57BL/6. Mutant
(129/Sv × C57BL/6) F1 hybrids were derived from a cross of
homozygous Kv3.1
/
129/Sv males to
heterozygous Kv3.1+/
C57BL/6 females (N5
generation or higher, i.e., >96.9% C57BL/6). Wild type F1 hybrids
were obtained by crossing wild type or heterozygous 129/Sv males with
C57BL/6 females.
EEG recordings in freely behaving mice
Mice were anesthetized by injection of ketamine/acepromazine
(80/2.5 mg/kg ip) and placed in a stereotaxic apparatus. To record the
electroencephalogram (EEG), screw electrodes (000) were placed in the
skull based on skull landmarks, one overlying the somatomotor region of
cortex (, L-1.0 mm), and another over the cerebellum and used as a
grounded reference. The electromyogram (EMG) was recorded from two
spring electrodes embedded in the nuchal musculature. Wires were
inserted into a connector cemented to the animal's skull. After 1 wk
recovery, mice were placed in an unrestraining, chronic recording
environment on a 12/12 light-dark schedule. A light-weight cable was
attached to the animal's connector, and a total of 21 days were
allowed before recording commenced. Potentials between the cortical
electrode and the grounded cerebellar electrode, and bipolar potentials
from muscle electrodes were amplified (Grass, P511), filtered between
0.3-100 Hz (EEG) and 10-1,000 Hz (EMG), digitized at 125 Hz, and
stored on optical disk. Only the EEG data were used for off-line
spectral power analysis. Electrical activity was recorded continuously
for one 24-h period.
Scoring states of arousal
Continuous 24-h records were divided into 5,760 15-s epochs, and each polygraphic epoch was scored either as waking, rapid eye movement (REM) sleep, or slow-wave (nonREM) sleep. Standard criteria as applied to rodents were used. Slow-wave sleep epochs were dominated by a slowing of the frequency, an increase in amplitude of the EEG in the presence of moderate to low tone in the EMG, and the absence of any signs of movement. REM sleep was always preceded by a period of slow-wave sleep and was characterized by a higher frequency, lower amplitude EEG with a clear and continuous 5- to 7-Hz theta rhythm. The EMG of REM sleep was of the lowest amplitude attained punctuated with short bursts of activity corresponding to phasic paroxysmal muscle twitches. The EEG of wakefulness was similar in appearance to that of REM sleep except that the theta rhythm was not continuous and, when present, was usually of lower amplitude than REM sleep. The EMG supplied the definitive distinction between REM sleep and wakefulness. Muscle tone was always considerably higher, even during periods of inactivity. Visual selection on a computer monitor was performed by an experienced scorer without knowledge of the genotype and on tracings where activity above 15 Hz was beyond the resolution of the monitor. For each hour, the total number of 15-s epochs scored as waking, slow-wave, and REM sleep was used to calculate the time spent in a particular state.
For subsequent power spectral analysis, 10 15-s epochs, 5 from the 2nd hour after lights on and 5 from the 2nd hour after lights off, were chosen to represent each state of arousal. Epochs were selected from the first five artifact-free 15-s epochs of the hour, consisting of purely a single state. REM epochs did not include the first or last epoch of a REM period. Similarly, slow-wave epochs did not include epochs that were preceded or followed by a state change. Slow-wave sleep epochs were also excluded if transient arousals were present. Brief 1- to 2-s drops in EEG amplitude and increases in frequency, which may or may not be accompanied by increases in EMG, were common in the light slow-wave sleep of the mouse. As a result, slow-wave sleep epochs were predominantly of a deep slow-wave sleep with continuous high-amplitude, slow waves in the EEG. It was rare for mice to sustain wakefulness without some type of movement. Epochs of wake were chosen from the polygraph record without knowledge of the specific behavior expressed by the animal. Inasmuch as frequency of the EEG, such as generation of hippocampal theta, is related to specific behaviors, we attempted to standardize the selection of wake epochs by choosing epochs with movement based on the EMG. The EEG was used only to confirm the absence of slow waves and movement artifacts.
Power spectral analysis
Sets of 10 15-s epochs, each set representing uncontaminated waking, slow-wave, or REM sleep, were used to select 30 nonoverlapping 4-s epochs. Each 4-s epoch was subjected to a fast Fourier transform algorithm (Microcal Origin 4.1; Hamming window) to generate the power spectrum (at 0.25 Hz resolution). The averaged power spectrum for each state corresponds to the mean power spectrum of the 30 individual power spectra. For each animal, the mean absolute power density (in µV2/Hz) for a particular frequency band (delta, theta, etc.) was calculated by taking the mean of the power densities in all 0.25-Hz bins (in µV2/0.25 Hz, averaged from 30 4-s epochs) included in that frequency band divided by 4 (so it can be expressed as µV2/Hz).
To determine the relative distribution of power across the spectrum, the mean absolute power in each 0.25-Hz bin (the mean of 30 4-s epochs) was divided by the mean of the total power for all 0.25-Hz bins between 0.7 and 60 Hz (again for 30 4-s epochs). The resulting number, relative power, indicates to what degree the power at a particular frequency differs from the mean total power between 0.7 and 60 Hz.
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RESULTS |
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No differences in sleep-wake behavior in the Kv3.1-deficient mouse
We first tested the possibility that the absence of Kv3.1
K+ channels might lead to an altered or even
disturbed sleep-wake pattern in Kv3.1-deficient mice. We recorded the
somatomotor cortex EEG and nuchal EMG of freely moving wild type and
homozygous Kv3.1/
male 129/Sv mice. A
representative sample is shown in Fig. 1. Continuous 24-h records were divided into 15-s epochs and visually scored either as waking, REM sleep, or slow-wave (nonREM) sleep by an
observer unaware of the animal's genotype. The distribution of states
of arousal during a 24-h period for Kv3.1+/+
(n = 3) and Kv3.1
/
(n = 3) 129/Sv mice is shown in Fig.
2. No significant differences were found
between normal and Kv3.1-deficient mice in the times spent in waking,
slow-wave, or REM sleep during the 24-h period. All mice were generally
more active and spent significantly more time awake during the dark
period than the light period. Significant differences were detected
across the light-dark cycle in the expression of all states of arousal
both for wild type and mutant 129/Sv mice (2-factor ANOVA,
P < 0.005). Table 1
summarizes these findings and shows that mice spent more time awake in
the dark (66.1 ± 1.79%, mean ± SE, for
Kv3.1+/+, 61.9 ± 2.33% for Kv3.1
/
)
than in the light (41.5 ± 0.75% for Kv3.1+/+,
41.5 ± 2.32% for Kv3.1
/
). Although statistically
significant, the differences between dark and light are small compared
with differences reported for other mouse strains (Valatx & Bugat 1974
). No significant differences between
Kv3.1+/+ and Kv3.1
/
mice were found in the
times spent in any arousal state neither during the light nor the dark
period (Table 1).
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Altered slow and fast rhythms in the somatomotor EEG of the Kv3.1 mutant mouse
While scoring the polygraph records, it was apparent that some
mice expressed lower amplitude low-frequency activity in the EEG during
slow-wave sleep (see Fig. 1). These animals were all subsequently
identified as Kv3.1 mutants. To quantify differences in cortical
rhythmic activity, we determined the power spectra for EEG traces
representative of the different states of arousal. For all frequency
bands analyzed in any state, the absolute power densities computed for
the second hour of the light and dark period were not significantly
different (Fig. 3) and were therefore
pooled for further analysis. Figure
4A shows that wild type
(n = 4) and Kv3.1/
(n = 4) 129/Sv mice had the highest power values in the
delta band (0.7-4.4 Hz) during slow-wave sleep, and, for frequencies <20 Hz, each genotype similarly showed significant power differences across states of arousal (2-factor ANOVA; 0.7-4.4 Hz,
P < 10
6; 4.4-10.0 Hz,
P < 0.01; 10-20 Hz, P < 10
4). We found no significant differences,
however, between Kv3.1+/+ and
Kv3.1
/
mice in absolute power values in the
delta (0.7-4.4 Hz) or theta bands (4.4-10 Hz). In contrast,
significantly greater absolute power was seen in Kv3.1-deficient mice
starting with the 10- to 20-Hz band and extending through the gamma
band (20-60 Hz; 2-factor ANOVA; 10-20 Hz, P < 0.05;
20-50 Hz, P < 0.01; 50-60 Hz, P < 0.05). This disparity of absolute power in the high-frequency bands
between wild type and mutant increased with increasing frequency,
occurred across all states of arousal, and reached ~300% of the wild
type value between 40 and 50 Hz during wakefulness (Fig.
4A).
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To control for the variation in absolute power among individual mice,
the relative power distribution was determined for each animal in each
state of arousal. The relative power spectra for waking, slow-wave, and
REM sleep of 129/Sv Kv3.1+/+ (n = 4) and Kv3.1/
(n = 4) mice
are shown in Fig. 5, A and
B. The relative power for wild type mice was highest in the
theta band during wakefulness and REM sleep; in contrast, relative
power was highest in the delta band during slow-wave sleep (Fig.
5A). In the gamma range (>30 Hz), the relative power was
similar between wakefulness and REM sleep and higher than during
slow-wave sleep, in agreement with reports showing that gamma
oscillations are increased in the aroused brain (Franken et al.
1994
; Maloney et al. 1997
; Steriade et
al. 1996a
,b
). The relative power spectra of
Kv3.1
/
mice displayed several clear
differences to the ones of Kv3.1+/+ mice (Fig.
5B). At peak power levels (~2-3 Hz) of delta
oscillations, homozygous Kv3.1
/
mutants
showed a decrease in relative power compared with wild type across all
states of arousal; in contrast to this reduction of relative power in
the delta band, there was an abrupt power increase of ~50% near 10 Hz (Fig. 5C). At higher frequencies (>30 Hz), there were
additional increases of relative power for
Kv3.1
/
mice compared with wild type mice
(corresponding to the significant increase of absolute power shown in
Fig. 4A). Up to ~40 Hz, the absence of Kv3.1 channels
affected the increase of relative power similarly across all states of
arousal; in the 40- to 50-Hz range, there appeared an additionally
enhanced increase of relative power that was specific to wakefulness
(Fig. 5C). This increase was also evident for absolute power
(Fig. 4A).
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Although we could not detect a statistically significant decrease in
absolute delta power in the 0.7- to 4.4-Hz band (Fig. 4A),
we saw a consistent reduction of relative power at ~2-3 Hz across
all arousal states (Fig. 5, B and C). To
ascertain its significance, we calculated the absolute and relative
power values in this narrow delta band of 2-3 Hz (Table
2). The absolute peak power in this
narrowband in Kv3.1/
mice was reduced by
15.5, 19.3, and 22.1% in waking, slow-wave, and REM sleep,
respectively. Although the mutant values were consistently smaller, the
differences between wild type and mutant were not statistically
significant (2-factor ANOVA, P = 0.14). When we calculated the relative power, the corresponding values were reduced by
32.9, 24.8, and 32.0% in Kv3.1
/
mice and
were significantly different between wild type and mutant (2-factor
ANOVA, P < 0.05).
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Altered slow and fast rhythms are present in two different genetic backgrounds
We initially used 129/Sv mice for our studies because the Kv3.1
mutation had been introduced on this background (Ho et al. 1997). However, wild type mice of this strain are difficult to breed, perform poorly in several behavioral tests, and, potentially important for the present study, can display a defective or absent corpus callosum (Livy and Wahlsten 1991
; Wahlsten
1982
). To rule out that the decrease in delta and increase in
gamma power observed in 129/Sv mice was artifactual and restricted to
this strain, we extended our analysis to wild type and
Kv3.1
/
mice on the (129/Sv × C57BL/6)
F1 hybrid background. Both wild type and mutant F1 hybrids express a
normal corpus callosum (Livy and Wahlsten 1991
;
Wahlsten 1982
) and perform better in several behavioral
and physiological tests (Joho et al. 1998
). When we compared absolute and relative power between wild type and
Kv3.1
/
F1 mice, the differences were even
greater on the F1 background than the ones observed on the 129/Sv
background (Fig. 4B). The absolute power in the delta band
was significantly reduced in Kv3.1
/
F1 mice
(2-factor ANOVA; P < 0.01). This is in contrast to
129/Sv mice in which only relative not absolute power was significantly reduced (Table 2). As with 129/Sv mice, the absolute power values in
frequency bands >20 Hz were significantly increased (2-factor ANOVA;
20-30 Hz, P < 0.01; 30-60 Hz, P
0.001). Figure 5, D-F, summarizes the changes in relative
power. Kv3.1
/
F1 mice display a ~30-60%
decrease of relative power in the narrow delta band (2-3 Hz) and
increased gamma power with a peak at ~400-450% of wild type values
between 40 and 50 Hz (Fig. 5F).
The large increase in gamma power seen in the averaged power spectra
could be detected in the raw EEG traces of
Kv3.1/
mice. The EEG of a wild type and a
mutant F1 mouse (with nearly identical total power suitable for direct
comparison) was used to select randomly five 2-s epochs representing
wakefulness. The somatomotor EEG traces showed an increased amplitude
in the high-frequency waves that ride on and between the high-amplitude
slower waves (Fig. 6). The corresponding
power spectra for each 2-s epoch of the Kv3.1-deficient mouse clearly
showed multiple peaks representing components of increased power at
high frequencies. The frequency of these peaks varied between epochs,
explaining why the increase of relative gamma power showed a relatively
broad peak between 30 and 50 Hz (Fig. 5F). Application of a
high-pass software filter made differences between genotypes even more
obvious and revealed, in all states of arousal, an increased amplitude
of waves above 20 Hz. The appearance of high-frequency waves was
discontinuous without any apparent fixed periodicity. No clear time
relationship could be discerned among the occurrence of high- and
low-frequency waves (see Fig. 7 for
samples of EEG recordings in slow-wave sleep with both high and
low-pass filters).
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DISCUSSION |
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Possible role of Kv3.1 K+ channels in neuronal excitability
The voltage-gated K+ channel Kv3.1 is
expressed in a subset of interneurons, the parvalbumin-containing,
fast-spiking GABAergic cells. Fast-spiking GABAergic interneurons have
been implicated in neocortex and hippocampus to be involved in the
generation of fast rhythms in the gamma (>30 Hz) frequency range
(Bragin et al. 1995; Jefferys et al.
1996
; Steriade et al. 1998
; Traub et al.
1996
; Wang and Buzsáki 1996
;
Whittington et al. 1995
, 1997
). In the
Kv3.1 mutant, the absence of a rapidly repolarizing outward current may
prolong the AP waveform, reduce the fAHP, and slow the firing pattern
of these normally fast-spiking interneurons. Several recent reports
indicate that Kv3.1 K+ channels are indeed
involved in high-frequency firing (Brew and Forsythe
1995
; Kanemasa et al. 1995
; Massengill et
al. 1997
; Wang et al. 1998
).
We reported earlier that homozygous Kv3.1/
mice had impaired motor skills, a behavioral phenotype attributed to
the altered contractile properties of their skeletal muscles and to the
smaller forces generated on muscle contraction (Ho et al.
1997
). Initially, we did not detect an obvious neuronal
phenotype in spite of the high density of Kv3.1 in several brain
regions. Using continuous 24-h EEG recordings from the somatomotor
cortex of freely behaving mice, we now report alterations in slow and,
particularly, fast oscillatory, cortical activity in the
Kv3.1-deficient mouse.
The lack of difference between wild type and Kv3.1-deficient mice in time spent in the states of arousal indicates that Kv3.1 K+ channels are not involved in the mechanisms generating and maintaining the sleep-wake cycle (Fig. 2 and Table 1). All the characteristics of state-related alterations in cortical EEG activity are present in Kv3.1-deficient mice. For both genotypes, the EEGs of wakefulness and REM sleep contain higher relative power in the theta and gamma frequencies compared with slow-wave sleep, which shows the highest power in the delta band. During waking and REM sleep, 129/Sv mice show a distinct peak in the theta band that is less prominent during waking in wild type (129/Sv × C57BL/6) F1 mice. We currently cannot explain the relatively low contribution of theta power in wild type F1 hybrids.
Both, Kv3.1+/+ and
Kv3.1/
129/Sv mice fail to demonstrate the
dynamic, state-related regulation of EEG power shown in other species to accompany the circadian cycle. Delta power is not increased at the
beginning (2nd hour) of the light cycle compared with the beginning
(2nd hour) of the dark cycle (Fig. 3). This may relate to the poor
polarization in the diurnal rhythm of the sleep of 129/Sv mice as is
known for some other mouse strains (Valatx & Bugat
1974
). The study of the Kv3.1 mutant on genetic backgrounds showing more polarized sleep-wake distributions will be needed to
determine whether Kv3.1 channels may be involved in the circadian regulation of activities determining the EEG power spectra.
Altered fast and slow rhythms in the cortical EEG of Kv3.1-deficient mice
Using spectral power analysis, we find that homozygous
Kv3.1/
mice show altered fast and slow
oscillations in the EEG of somatomotor cortex (Figs. 4-6). The main
findings are as follows: 1) Kv3.1
/
mice show a two- to fourfold increase of relative and absolute power in
the gamma frequency range (20-60 Hz); 2) homozygous
Kv3.1
/
mice have a 20-50% reduction of
delta power (at 2-3 Hz), in agreement with our results using period
amplitude analysis (Joho et al. 1997
); and 3)
these changes in fast and slow rhythms are present in Kv3.1-deficient
mice on two distinct genetic backgrounds.
Although absolute gamma power increases two- to fourfold in the Kv3.1 mutant mouse, the actual values above 20 Hz are small and contribute a small fraction to the total power between 0.7 and 60 Hz. Hence the decrease in relative delta power at 2-3 Hz in 129/Sv mice cannot be solely explained by the increase of gamma power above 20 Hz; moreover, this decrease would have to be uniform in the lower frequency range and not show a peak decrease at ~2-3 Hz. In summary, we find dramatically altered fast and slow cortical rhythms in Kv3.1-deficient mice on two different genetic backgrounds. These findings argue for a role of Kv3.1 K+ channels in fast and slow cortical oscillatory activity.
The constant configuration of electrode placement across all animals
ensures that the basis of spectral differences in the EEG is related to
the Kv3.1 genotype. The locations of the neural generators of the
different frequency components in the cortical EEG are less certainly
determined. This is especially so in the mouse with its small brain and
thin cortical mantle. Through volume conduction, noncortical structures
could contribute to the EEG recorded from neocortex. This is
illustrated by the high spectral power detected in the theta band of
the cortical EEG that is known to be generated in the hippocampus. Many
structures containing Kv3.1-expressing neurons are potentially capable
of contributing to the EEG differences currently observed. This may
partially account for our inability to observe temporal correlations in the occurrence of slow and fast waves as has been reported for the
cortical, focal potentials in the cat (Amzica and Steriade 1998; Contreras and Steriade 1997
). The use of
an array of surface and depth electrodes recording focal potentials may
resolve this issue.
Fast-spiking interneurons have been implicated in fast oscillations
Kv3.1 channels are expressed in fast-spiking interneurons, and
fast-spiking interneurons have been implicated in entraining gamma
oscillations in hippocampus and cortex (Bragin et al.
1995; Jefferys et al. 1996
; Steriade et
al. 1998
; Traub et al. 1996
; Wang and
Buzsáki 1996
; Whittington et al. 1995
,
1997
). In the hippocampus, the frequency of these
oscillations depends on the decay time constant of the inhibitory
postsynaptic currents triggered in pyramidal cells by GABAergic
interneurons. The fact that we find altered fast and slow rhythms in
Kv3.1-deficient mice supports the idea that Kv3.1-expressing cells
participate in the neuronal networks generating these rhythmic
oscillations. The shift in spectral power toward high-frequency rhythms
is found in all states of arousal, but it is particularly enhanced in
the 40- to 50-Hz range during wakefulness. Inasmuch as gamma power in
the mutant is the least enhanced during REM sleep, a state of
generalized cortical activation, it appears that cortical activation
per se is not the sole determining factor for the phenotypic
differences we observe. Because we find these changes of fast and slow
rhythms in two distinct strains of mice, it reinforces the notion that increased gamma and reduced delta oscillations are robust phenotypes of
the Kv3.1-deficient mutant mouse.
What are the possible mechanisms underlying altered cortical
oscillations? It has been shown that Kv3.1 is involved in maintaining narrow APs and fAHPs necessary for the rapid firing of certain neurons
in cortex, hippocampus, and the medial nucleus of the trapezoid body
(Brew and Forsythe 1995; Du et al. 1996
;
Kanemasa et al. 1995
; Massengill et al.
1997
; Wang et al. 1998
), and initial studies
indicate that TRN neurons of Kv3.1
/
mice
display AP broadening and reduced fAHP (Huguenard et al. 1997
). Also, it has recently been shown that pharmacological
blockade of a K+ channel (probably Kv3.1) in
cerebellar granule cells, which express high levels of Kv3.1, leads to
wider APs, increased axonal Ca2+
influx, and a two- to threefold increase in excitatory postsynaptic currents in Purkinje cells, presumably through the mechanism of increased presynaptic neurotransmitter release (Sabatini and
Regehr 1997
). If these changes are caused by block of Kv3.1
(other K+ channels expressed in granule cells
cannot be ruled out) and if the findings for the excitatory granule
cell/Purkinje cell synapses apply also to GABAergic synapses formed by
Kv3.1-expressing interneurons, we would expect a substantial
strengthening of the GABAergic synapses in thalamus and neocortex.
Networks of inhibitory interneurons connected by synapses using
GABAA receptors can induce "40-Hz"
oscillations in hippocampal and cortical slices, and in modeling these
neuronal networks, the kinetics of inhibitory postsynaptic potentials
appear to be a major determining factor of the frequency of oscillation
(Bragin et al. 1995
; Jefferys et al.
1996
; Traub et al. 1996
; Wang and
Buzsáki 1996
; Whittington et al. 1995
, 1997
).
Two mechanisms could underlie the phenotypic alterations observed in
the Kv3.1-deficient mouse: 1) a reduction in discharge rate
of normally fast-spiking GABAergic neurons due to reduced fAHP and
prolonged refractory period and 2) an increase in the synaptic efficacy of critical GABAergic neurons attendant to increased AP duration and transmitter release. The hypothesized role of cortical
interneurons in the generation of high-frequency gamma oscillations
would favor an increase in synaptic efficacy in the GABAergic
transmission of these neurons in Kv3.1-deficient mice as the mechanism
underlying the increase in gamma oscillations. The possible mechanism
underlying the trend toward reduced slow oscillations is less clear. A
reduced discharge rate during high-frequency spike bursts of TRN
neurons could lead to fewer spikes per burst and diminish the ability
of the TRN to synchronize thalamic relay cells. The reduction in power
in the narrow delta band (2-3 Hz), however, occurs in all arousal
states (Fig. 5 and Table 2). Inasmuch as TRN neurons do not fire in
high-rate bursts of spikes during wakefulness (Marks and
Roffwarg 1993; Steriade et al. 1986
), it is
unlikely that this mechanism underlies the generalized reduction in
slow, cortical oscillations. It has been shown in the cat that slow and
fast activity in the EEG are not independent events (Contreras and Steriade 1997
). Both the increase in gamma and decrease in delta oscillations observed in the Kv3.1 mutant EEG may be dependent on
the same alterations in cortical interneurons. The current findings
inform us of the involvement of Kv3.1 channels in the generation of
fast and slow oscillatory activity, but additional methods will have to
be applied to identify the specific mechanisms.
Cortical oscillations in the 40-Hz range have been implicated in a
variety of cognitive functions (Ritz and Sejnowski 1997; Singer and Gray 1995
). Hence a significant increase in
gamma power could have concomitant behavioral consequences. When we
subjected wild type and Kv3.1
/
(129/Sv × C57BL/6) F1 mice to an active avoidance task (a simple test for
learning and memory), Kv3.1
/
mice avoided the
foot shock twice as often as Kv3.1+/+ mice on the
first day of training (~50 vs. ~25% avoidance events) (Joho
et al. 1998
). The better performance in a learning task is
consistent with altered cognitive ability accompanying the increase in
fast gamma oscillations in the neocortex. This enhanced performance may
be dependent on an increased level of alertness or an improved ability
to make associations in the mutant mice, although it is currently
unknown how alterations of synchronized cortical gamma activity leads
to this phenotype. The Kv3.1 mutant mouse could serve as a model to
study the generation and maintenance of slow and fast cortical rhythms
and their role in behavior and cognition.
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ACKNOWLEDGMENTS |
---|
The authors thank Dr. Daniel Barth for insightful comments and a critical reading of the manuscript, and C. G. Birabil for expert technical assistance.
This work was supported in part by National Institutes of Health Grants NS-28407 to R. H. Joho and MH-49364 to G. A. Marks, and grants from the Muscular Dystrophy Association of America and the Kent Waldrep National Paralysis Foundation to R. H. Joho.
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FOOTNOTES |
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Address for reprint requests: R. H. Joho, The Center for Basic Neuroscience, The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX 75235-9111.
The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Received 30 December 1998; accepted in final form 21 June 1999.
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REFERENCES |
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