Increased gamma - and Decreased delta -Oscillations in a Mouse Deficient for a Potassium Channel Expressed in Fast-Spiking Interneurons

Rolf H. Joho,1 Chi Shun Ho,1 and Gerald A. Marks2

 1The Center for Basic Neuroscience and  2Department of Psychiatry, The University of Texas Southwestern Medical Center, Dallas, Texas 75235-9111


    ABSTRACT
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

Joho, Rolf H., Chi Shun Ho, and Gerald A. Marks. Increased gamma - and Decreased delta -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.


    INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

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.


    METHODS
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

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 (beta , 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.


    RESULTS
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

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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Fig. 1. Polygraphic recordings from Kv3.1+/+ and Kv3.1-/- mice in different states of arousal. Representative, 10-s samples from each state are shown for Kv3.1+/+ and Kv3.1-/- 129/Sv mice. The electroencephalogram (EEG) is recorded from the somatomotor cortex (SMcx) and the electromyogram (EMG) from the neck musculature. Bars to the right of the traces represent 200-µV calibrations. The high activity in the EMG of the Kv3.1-/- mouse during slow-wave sleep (SW) and rapid eye movement (REM) sleep is an electrocardiogram (EKG) artifact.



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Fig. 2. Twenty-four-hour distribution of states of arousal in Kv3.1+/+ and Kv3.1-/- mice. The curves connect mean hourly values (in %) for REM sleep and total sleep (slow-wave and REM). REM sleep is indicated in black shading, slow-wave sleep in gray shading, and waking as the unshaded area below the 100% line (n = 3 for each genotype).


                              
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Table 1. Time spent in wakefulness, slow-wave (SW), or REM sleep during a 24-h period

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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Fig. 3. Power spectral analysis for the 2nd hour of the light and dark period. The absolute power values (µV2/Hz) of the somatomotor cortical EEG across different states of arousal are shown for several frequency bands. The results of wild type and Kv3.1-deficient 129/Sv mice are plotted (mean ± SE; n = 4 for each genotype) for the 2nd hour of the light (L) cycle and the 2nd hour of the dark (D) cycle. SW, slow-wave sleep; REM, REM sleep.



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Fig. 4. Power spectral analysis of Kv3.1+/+ and Kv3.1-/- mice. The power values of the somatomotor cortical EEG for the 2nd hour of the light and dark period were combined. A: the absolute power (µV2/Hz) for Kv3.1+/+ and Kv3.1-/- 129/Sv mice is shown for the indicated frequency bands (mean ± SE; n = 4 for each genotype). A 2-factor ANOVA reveals significant differences between genotypes at frequencies >10 Hz (p1 values) and significant differences across states of arousal for frequencies <20 Hz (p2 values). B: absolute power of (129/Sv × C57BL/6) F1 hybrids (mean ± SE; n = 4 for each genotype) is shown. A 2-factor ANOVA shows significant differences between genotypes in frequency bands >20 Hz (p1 values) and among states of arousal (p2 values). There is no interaction between the 2 factors (genotype × state). SW, slow-wave sleep; REM, REM sleep.

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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Fig. 5. Distribution of relative power in 129/Sv and (129/Sv × C57BL/6) F1 mice. Power spectra for the different states of arousal are plotted for Kv3.1+/+ (A and D) and Kv3.1-/- (B and E) 129/Sv and (129/Sv × C57BL/6) F1 mice (n = 4 for each strain and genotype). For each animal, the relative power in each 0.25-Hz bin is the absolute power (in µV2/0.25 Hz) in that frequency bin divided by the mean of the animal's total power (in µV2/0.25 Hz) from 0.7 to 60 Hz. The change of relative power in Kv3.1-deficient mice (C and F) is plotted (relative power of mutant divided by relative power of wild type). The Kv3.1-/- mutant on both genetic backgrounds shows a decrease in relative power at 2-3 Hz and an increase in relative power above ~10 Hz across all states of arousal. There is an additional marked increase that is specific to waking in the 40- to 55-Hz range. (The y-axis in C is from 0.3 to 3.7, in F from 0.3 to 5.0.)

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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Table 2. Peak delta power is reduced in Kv3.1-deficient 129/Sv mice

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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Fig. 6. Differences between Kv3.1+/+ and Kv3.1-/- mice are visible in the somatomotor EEG. Five randomly selected, 2-s EEG epochs from somatomotor cortex representing active waking are shown for a Kv3.1+/+ and a Kv3.1-/- mouse on the (129/Sv × C57BL/6) F1 background (amplitudes are indicated in µV). The corresponding power spectra are shown to the right (maximal power is 1,000 µV2/Hz). The 2 animals have similar total mean power enabling a direct comparison.



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Fig. 7. Filtered EEGs of Kv3.1+/+ and Kv3.1-/- mice during slow-wave sleep. Eight-second EEG epochs during SW sleep are shown for a Kv3.1+/+ and a Kv3.1-/- mouse on the (129/Sv × C57BL/6) F1 background (same animals as Fig. 6). The middle and bottom traces were generated from the top trace by software filters: low pass at 3 Hz and high pass at 20 Hz, respectively. Bars to the left are 200-µV calibrations.


    DISCUSSION
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

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.


    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.


    FOOTNOTES

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.


    REFERENCES
TOP
ABSTRACT
INTRODUCTION
METHODS
RESULTS
DISCUSSION
REFERENCES

0022-3077/99 $5.00 Copyright © 1999 The American Physiological Society