Institute for Neurobiology, University of Amsterdam, 1098 SM Amsterdam, The Netherlands
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ABSTRACT |
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Wierenga, Corette J. and Wytse J. Wadman. Miniature Inhibitory Postsynaptic Currents in CA1 Pyramidal Neurons After Kindling Epileptogenesis. J. Neurophysiol. 82: 1352-1362, 1999. Miniature inhibitory postsynaptic currents (mIPSCs) were measured in CA1 pyramidal neurons from long-term kindled rats (>6 weeks after they reached the stage of generalized seizures) and compared with controls. A large reduction in the number of mIPSCs was observed in a special group of large mIPSCs (amplitude >75 pA). The frequency of mIPSCs in this group was reduced from 0.042 Hz in controls to 0.027 Hz in the kindled animals. The reduction in this group resulted in a highly significant difference in the amplitude distributions. A distinction was made between fast mIPSCs (rise time <2.8 ms) and slow mIPSCs. Fast mIPSCs, which could originate from synapses onto the soma and proximal dendrites, had significantly larger amplitudes than slow mIPSCs, which could originate from more distal synapses (35.4 ± 1.1 vs. 26.2 ± 0.4 pA in the kindled group; means ± SE). The difference in the value of the mean of all amplitudes and frequency of fast and slow mIPSCs did not reach significance when the kindled group was compared with controls. The mIPSC kinetics were not different after kindling, from which we conclude that the receptor properties had not changed. Nonstationary noise analysis of the largest mIPSCs suggested that the single-channel conductance and the number of postsynaptic receptors was similar in the kindled and control groups. Our results suggest a 40-50% reduction in a small fraction of (peri-) somatic synapses with large or complex postsynaptic structure after kindling. This functionally relevant reduction may be related to previously observed loss of a specific class of interneurons. Our findings are consistent with a reduction in inhibitory drive in the CA1 area. Such a reduction could underlie the enhanced seizure susceptibility after kindling epileptogenesis.
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INTRODUCTION |
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Alteration of the strength of synapses between
cells is an important mechanism for plasticity in the brain. This
plasticity provides the nervous system with the possibility to store
(new) information, but if not adequately controlled, it also can lead to changes in the dynamics of neuronal networks that underlie pathological states such as epilepsy (Goddard et al.
1969; Racine 1972
). In the kindling model of
epilepsy, daily tetanic stimulations of specific afferents result in an
epileptic focus and the generation of afterdischarges in the neuronal
assemblies in the projection area. Behavioral convulsions appear and
gradually increase in severity and duration. The changes in the network
seem to be persistent: months after the last stimulation was given, a
short tetanus will still induce a generalized convulsion. This altered
state of the network is usually called the kindled state. A
characterization of the kindled state is important for gaining insight
into the pathology of epilepsy.
During epileptogenesis the balance between excitation and inhibition,
which is essential to maintain stability in a neuronal network, shifts
in favor of excitation. Several of the factors that determine
glutamatergic and GABAergic synaptic transmission in the CA1 area are
changed after kindling epileptogenesis. Previous work demonstrated that
the binding of the GABA agonist muscimol is decreased (Titulaer
et al. 1994) and that a specific change in
GABAA receptor subunit mRNA occurs
(Kamphuis et al. 1995
). After kindling epileptogenesis
the effective inhibition in the hippocampal CA1 network as judged from
paired pulse inhibition is reduced (Kamphuis et al.
1988
; Zhao and Leung 1993
) and 50% of the
GABAergic interneurons that do not contain parvalbumin are lost
(Kamphuis et al. 1989
). The precise consequences of
this reorganization are not known, but the functional effect is a
reduced level of inhibition.
The strength of functional inhibition is determined by many factors. In
a central synapse, the receptors opposite each bouton are thought to be
largely saturated by the release of a single vesicle of transmitter, so
that the number of available receptors rather than the amount of
transmitter released determines the quantal amplitude (Edwards
et al. 1990; Jonas et al. 1993
; Nusser et
al. 1997
). The number of active zones per synapse is also
important for determining synaptic strength. The time course of the
inhibitory postsynaptic current (IPSC) is largely determined by the
receptor kinetics and the release process (Borst et al.
1994
; De Koninck and Mody 1994
;
Glavinovic and Rabie 1998
).
The change in network excitability induced by the kindling protocol is persistent and leads to the kindled state. We used long-term kindled rats (the last stimulation that resulted in a generalized seizure was given >6 weeks before the slice experiments) to prevent interference with phenomena that are a direct result from the seizures. We investigated in this study the long-term change in inhibition at the synapse level by measuring miniature IPSCs (mIPSCs) in CA1 pyramidal neurons in hippocampal slices. The mIPSCs are small currents that occur due to the spontaneous release (without a presynaptic action potential) of one (or more) GABA containing transmitter vesicle(s) by presynaptic terminals.
The mIPSCs reflect properties of the underlying GABAergic synapses
(Faber et al. 1998). Edwards presented a model of
plasticity of central synaptic transmission in which an altered synapse
morphology leads to a change in miniature amplitude distribution
(Edwards 1995
). Changes in the number of postsynaptic
receptors after kindling should show up in mIPSC amplitude, whereas
changes in receptor kinetics (for example due to a change in subunit
composition) will be reflected in mIPSC kinetics. A change in the
number of spontaneous active synapses should be reflected in the mIPSC frequency.
We used the in situ patch-clamp technique to record mIPSCs in CA1 pyramidal neurons in slices from kindled and control rats and analyzed their amplitudes, kinetics and frequency to study possible long-term changes in the inhibitory synapses after kindling epileptogenesis.
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METHODS |
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Kindling
Under electrophysiological control and pentobarbital anesthesia
(65 mg/kg) electrodes were implanted in the dorsal hippocampus of adult
male Wistar rats (200-300 g), as described previously in detail
(Kamphuis et al. 1988). In total 19 rats were used for this study of which 11 were implanted. Of these animals, eight received
twice daily a tetanic stimulation (200-300 µA at 50 Hz for 2 s)
onto the Schaffer collaterals to induce epileptogenesis. Evoked
potentials were monitored and electroenchephalographic (EEG) recordings
were made to follow the gradual increase in length and severity of the
afterdischarges. Behavioral seizures of class V (Racine
1972
) were obtained after 27 ± 2 (SE) kindling tetani. The animals were decapitated without anesthesia 6-8 wk after they had
reached the fully kindled state (5-6 class V seizures). The control
group consisted of eight age-matched and three implanted rats, which
had not received tetanic stimulations. Significant differences between
the implanted and nonimplanted controls were not observed, therefore
they will be pooled and referred to as controls. All animals (control
and kindled) were handled similarly during the time of the experiments.
Slice preparation
After decapitation the brain was removed rapidly and the hippocampus was dissected. With a tissue chopper 300-µm-thick transverse slices were cut, which were incubated at 32°C in artificial cerebrospinal fluid (ACSF) for 1 h. The ACSF contained (in mM): 125 NaCl, 2.4 KCl, 1 MgCl2, 2 CaCl2, 1.1 NaH2PO4, 26 NaHCO3, and 25 D-glucose and was gassed continuously with 95% O2-5% CO2 to set the pH at 7.3. During experiments slices were perfused with ACSF which contained 7 mM KCl and 120.4 mM NaCl to increase mIPSC frequency. All chemicals were obtained from Sigma (St. Louis, MO). To block action potentials 1 µM tetrodotoxin (TTX; obtained from Latoxan Rosans, France) was added and glutamatergic transmission was blocked by 10 µM 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX) and 5 µM 7-chlorothiokynurenic acid (both chemicals from Tocris Bristol, UK).
Recordings
An upright microscope with a ×40 water immersion objective and
a CCD camera with a high-pass 700-nm filter were used to locate CA1
pyramidal neurons in the hippocampal slice. The overlying tissue first
was cleared gently by a large pipette, after which the cells could be
patched. Whole cell voltage-clamp recordings were made at room
temperature at a membrane potential of 70 mV. Series resistance and
whole cell capacitance were monitored during the experiments. Series
resistance compensation was not used because it introduced unnecessary
noise to the signal and currents were too small to produce significant
voltage errors over the pipette resistance (4-6 M
). The pipettes
were filled with intracellular solution containing (in mM): 140 CsCl,
10 EGTA, 5 HEPES, 2 CaCl2, and 2 MgATP (pH
adjusted with CsOH to 7.3; 280-290 mOsm). Recordings were made using
an Axopatch 200 amplifier (Axon Instruments) and started 5-10 min
after a stable whole cell access was obtained. Recordings were low-pass
filtered at 2 kHz with an eight-pole Bessel filter and sampled at 4 kHz
on an ATARI TT030 computer using custom-made interface and software.
Evoked IPSCs
In four slices (from 1 control and 3 kindled animals) also IPSCs
evoked by electrical stimulation were recorded. In these experiments a
second pipette (3-4 M) was placed onto the surface of a pyramidal
cell close to the cell of which recordings were made. A short current
pulse (200 µs of 200-500 µA) was injected through the second
pipette. With this pipette we searched to stimulate an interneuron that
evoked an IPSC in the recorded pyramidal cell. Extracellular medium
used in these latter experiments contained no TTX, only CNQX and
7-chlorothiokynurenic acid. In two of the four cells (both kindled), we
succeeded in washing in the TTX-containing medium after the evoked
experiment and also recorded mIPSCs from the same cells.
Detection of mIPSCs
Custom-made software was used to detect events off-line by comparing their waveform with that of a template. The template was constructed by averaging 100 large mIPSCs that were selected by eye. After removing the DC level just before the event, the precise timing of the events was determined by calculating the least-square error of the fit of the scaled template to the signal for each successive time point. Within a time window in which the error was below a threshold and the amplitude >13 pA, the local minimum of this error was taken as the moment of occurrence. In this way, detection of events with different amplitudes was objective, automatic, and comparable. The same template could be used in all cells, because templates constructed from different cells resulted in the same set of detected events. This detection method based on the combination of amplitude and mIPSC waveform rather than on amplitude alone proved to be less dependent of the noise level and quite robust. Hardly any improvement was seen after using additional filtering.
In both the kindled and the control group <1% of the total number of events were overlapping (time between 2 succeeding events <15 ms). Because the properties of these events will be distorted by the overlap, we only selected the event that had the best match with the template, the other was disregarded.
Analysis of mIPSCs
In the template matching described in the preceding text, we purposely used a low detection level. In the second phase of the analysis, an additional set of criteria was used to select those events that could reasonably be called mIPSCs. In this phase ~50% of the initially detected events were rejected, most of which had very low amplitudes.
The amplitude, rise time, and decay time constants were calculated for all events that matched the template. The sampling of the signal at 4 kHz and the noise level made it difficult to calculate fast rise times (<1 ms) with high accuracy. The rise time was defined as the time interval between the last data point with a value <20% and the first that was >80% of the peak value. The (20-80%) rise time determined in this way was overestimated by 0.5 ms at most.
The decay phase of each event was fitted with an exponential function characterized by a single time constant. Events were only considered to be mIPSCs and accepted for further analysis if the fitted decay time constant was between 5 and 250 ms and if the coefficient of determination (r2) of the least squares fit was >0.33. Fitting the decay of the current with a biexponential function hardly improved the fit, indicating that these mIPSCs have a mono-exponential decay.
For the largest mIPSCs (>75 pA), we also used nonstationary noise
analysis. We scaled the mIPSCs to the mean mIPSC of the same cell and
then plotted the variance 2 of the
current against the mean current I, both calculated in bins
of 2 ms. The relation between
2 and
I could be fitted with the following equation (De
Koninck and Mody 1994
; Sigworth 1980
)
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Statistics
Differences in the mean values of mIPSC properties between the kindled and control groups were tested statistically using the Student's t-test and the nonparametric Mann-Whitney test. Differences in variance were tested using the F test. All data were tested per rat (n = 8 and n = 11 for kindled and control group) as well as per cell (n = 22 for both kindled and controls). Differences were accepted if both approaches lead to a similar conclusion and P < 0.05 was used to indicate a significant difference.
Distributions were compared between groups with Kolmogorov-Smirnov statistics. Possible correlations were tested with the Spearman rank-order test and with Pearson's correlation coefficient. The first gave a good estimation of the significance of the correlation, whereas the latter gave an estimation of the strength of the correlation.
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RESULTS |
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Kindling
During the kindling procedure field potentials in the stratum
radiatum of the CA1 area were recorded in each rat. Paired-pulse stimuli were given at the same stimulation electrodes on the Schaffer collaterals through which the kindling tetani were applied. The response was quantified as the mean ratio between the minimum amplitude
of the first and the second negative field potential recorded in
stratum radiatum (Fig. 1). The
paired-pulse ratio gradually increased from 0.9 ± 0.1 (inhibition; n = 8) before kindling to a value of
1.2 ± 0.1 (facilitation) after the rats had received 22 tetani.
Also the shape of the field potential changed: over the same period the
amplitude measured at 17 ms after the first stimulus changed from a
positive overshoot (0.14 ± 0.08 mV) to a negative amplitude
(0.4 ± 0.1 mV; see Fig. 1). This reduction in paired pulse
inhibition and broadening of the field potential after kindling
epileptogenesis confirmed previous observations and has been
interpreted as a reduced inhibitory drive (Kamphuis et al.
1988
; Zhao and Leung 1993
).
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mIPSCs
All currents were recorded at room temperature from CA1 pyramidal
cells, which were clamped at a membrane potential of 70 mV. During
experiments, slices were perfused with ACSF that contained 7 mM KCl to
increase mIPSC frequency. The input resistance of the cells of kindled
and control rats were not different and in the range of 70-100 M
.
Recordings were accepted for analysis if they were stable, that is, if
the amplitude and frequency of the mIPSCs did not significantly differ
during the first and the second half of the recording period. In total
recordings of 22 cells from 8 kindled rats and of 22 cells from 11 control rats were performed during a time period of ~20 min per cell
and contained in each group in total >20,000 mIPSCs. In Fig.
2A, part of a typical recording is shown. The events accepted as mIPSCs for further analysis
are marked (*).
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The mIPSCs disappeared when 10 µM bicuculline was added to the
extracellular medium and reversed at a membrane potential around 0 mV
(data not shown), indicating that they were GABAA
receptor mediated Cl currents.
Fast and slow mIPSCs
The most important condition that the detected events had to meet before being accepted as mIPSCs was that the decay phase was well fitted by an exponential function with a time constant between 5 and 250 ms. No additional restrictions on the rise time were necessary because the template matching already emphasized on realistic rise times. Nevertheless there was a considerable variance in the rise times of mIPSCs. The rise time distribution of each cell showed a large peak at fast rise times and a broad tail of slower rising mIPSCs (Fig. 2B). On the basis of this rise time distribution, we distinguished two groups of mIPSCs with rise times smaller and larger than 2.8 ms, which in the following we will refer to as fast and slow mIPSCs. The precise threshold of 2.8 ms for the distinction is not critical for the analysis to follow. It was an optimal separation based on a fit of the distribution with two Gaussians. Fast mIPSCs had significantly larger amplitudes than slow mIPSCs of the same cell. The decay time constants of slow rising mIPSCs tended to be somewhat larger than that of fast mIPSCs, but this difference did not reach significance (details are given in the following text).
In Fig. 2C, the means constructed by averaging 300 fast and 300 slow mIPSCs of the cell in Fig. 2B are shown. The mIPSCs were aligned (during the detection procedure) at the time point halfway the rising phase. Of all analyzed mIPSCs ~70% were fast and 30% were slow mIPSCs. The mean rise time of slow mIPSCs was in agreement with the rise time of the mean of the same slow mIPSCs, indicating that the slow kinetics are not due to a large jitter in the detection of the mIPSCs. This was confirmed by the fact that the mean amplitude also came close to the amplitude of the mean, implying that the shapes of the mean currents as given in Fig. 2C are good representations of the types of mIPSCs. The mean decay time constant of the mIPSCs (both fast and slow) was larger than the decay time constant of the mean mIPSC. This was because mIPSCs were not normalized to the peak amplitude before averaging and small mIPSCs tended to have a slower decay than larger mIPSCs.
Amplitudes, rise times, and decay time constants of mIPSCs
All mIPSCs were characterized by their amplitude, (20-80%) rise time, and their decay time constant. A summary of the parameters for both fast and slow mIPSCs in kindled and control cells is listed in Table 1. None of the differences between the kindled and control groups reached significance irrespective of whether they were determined per cell or per animal. Many of the distributions are not Gaussian, but for ease of comparison, the data are quoted as means ± SE determined by averaging over all cells. The significance of the shape of the distributions and the changes in those distributions, which are not evident in the calculated means, are discussed later.
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From Table 1 it is clear that slow mIPSCs had significantly
smaller amplitudes than fast mIPSCs. Fast mIPSCs had a significantly larger variance in amplitude and a smaller variance in rise time compared with slow mIPSCs. These variances were not different in the
control and kindled groups (F test). Decay time constants were similar for both mIPSC types in kindled and controls and showed a
large variance in all groups. The fraction of fast and slow mIPSCs per
cell was not different in the kindled and control groups: from the
total number of mIPSCs, 27 ± 2% (kindled) or 32 ± 3%
(control) were slow. The amplitude and kinetics of the mIPSCs in this
study are in good agreement with previous reports (Hájos
and Mody 1997; Jarolimek and Misgeld 1997
;
Katchman et al. 1994
; Lupica 1995
).
ANOVA of the animal data showed that within the kindled and control groups the variance between and within the data per animal was not different for all parameters of Table 1. This indicates that the observed variance in mIPSC parameters originates from cellular processes and cannot be explained as the influence of specific animals.
mIPSC frequency
In all cells, the time intervals between succeeding mIPSCs (fast
and slow separately) were determined. For every 250 mIPSCs a histogram
(binwidth 200 ms) of these time intervals was made. The interval
distribution could be well fitted by a single exponential function
A0 exp(rt) with
r the mean frequency at which the mIPSCs occurred (Fig.
3). This is the expected distribution for
independently occurring events generated by a Poisson process. The mean
frequency of mIPSCs in a cell was determined as the mean of all
frequencies determined per 250 mIPSCs from that cell.
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We also calculated the mIPSC frequency by determining the number of mIPSCs observed during every 100 s of recording. Both methods gave similar results. The mean mIPSC frequency (determined by the 1st method) in the kindled and control groups were (means ± SE from averaging over all cells): 0.65 ± 0.10 versus 0.63 ± 0.07 Hz for fast and 0.35 ± 0.04 versus 0.37 ± 0.04 Hz for slow mIPSCs, respectively (Table 1). Differences between kindled and control did not reach significance. The probability of occurrence of a fast or a slow mIPSCs did not depend on the type of mIPSC preceding it, indicating that fast and slow mIPSCs occurred independently.
The mean frequency varied much between individual cells of the same group. The coefficients of variation (100% * SD/mean) were 67 and 49% in the kindled group and 51 and 48% in the control group for fast and slow mIPSC frequency. ANOVA of mIPSC frequencies showed that this variance originated from differences between cells rather than from the variance of the individual cells.
Distributions of amplitude, rise time, and decay time constant
As mentioned in the preceding text, equal mean values for
variables describing the mIPSC for the kindled and control groups do
not exclude different distributions of the individual values. The types
of morphological changes of the underlying synapses that have been
suggested (Edwards 1995) indeed predict only subtle effects on such distributions. They even could be masked partially if
not all interneurons and their synapses are affected. Such changes
could nevertheless have important consequences for the efficacy of the
inhibitory input. Therefore distributions of the individual mIPSC
amplitudes, of the rise times, and of the decay time constants were
constructed for each cell.
In Fig. 4 typical examples of the
amplitude distribution of fast and slow mIPSCs of a kindled and a
control cell are shown. All distributions show a peak at a value
smaller than the mean amplitude and are skewed toward larger values as
was reported previously (Edwards 1995; Edwards et
al. 1990
). Notice the broader amplitude distribution of the
fast mIPSCs compared with that of the slow mIPSCs. Also the
distributions of the rise time (Fig. 2B) and of the decay
time constant (data not shown) were skewed toward the right.
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It was possible to fit the amplitude distributions with functions
previously derived by Jonas (Jonas et al. 1993) and
Bekkers (Bekkers et al. 1990
). However, the quality of
the fit was not very high and the functions did not add sufficient
explanatory power to justify further evaluation.
Large mIPSCs
The cumulative amplitude distribution gives the fraction of mIPSCs with amplitudes below a certain value. In Fig. 6A, the cumulative amplitude distributions for the kindled and control mIPSCs (pooled from all cells) are shown. The cumulative amplitude distributions show a small but highly significant difference between the kindled and the control group (Kolmogorov-Smirnov test, P < 0.0001). Notice the crossing of the two curves in Fig. 6A at ~40 pA. In the kindled group, only 3% of all mIPSC have amplitudes >75 pA, which is a significantly smaller fraction than in the control group (5%). For every given amplitude, the number of mIPSCs in both experimental groups that have larger amplitudes can be calculated. The ratio of these numbers is plotted as a function of amplitude in Fig. 6B. This graph shows that the reduction in the kindled group is systematic for all mIPSCs with amplitudes > ~60 pA. The reduction in large amplitude mIPSCs also can be expressed in the frequency of occurrence. For example, mIPSCs with amplitudes >75 pA occurred with a frequency of 0.042 Hz in the control group, whereas this was only 0.027 Hz in the kindled group. The frequencies were calculated by dividing the total number of observed large mIPSCs (1,094 for the controls and 727 for the kindled) by the total recording time for both groups. The tails of the amplitude distributions are shown in detail in Fig. 6C. The high significance of the difference in amplitude distribution did not depend on the part of the distribution in the small amplitude range, which was the part most affected by our detection method. Hence, the precise separation between small and large mIPSCs did not influence this conclusion.
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The distributions of mIPSC rise times in the kindled and control group showed a small significant difference in the slow rise time region (rise time >5 ms; Fig. 5C). The distributions of the decay time constants were not different in the kindled and control groups (Fig. 5, A and B). The slow mIPSCs showed a higher percentage of large decay time constants compared with the fast mIPSCs.
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Relations between amplitude, rise time, and decay time constants
The different properties of the mIPSCs within one cell are to some extent related (Fig. 7). No significant correlations were found between amplitudes, rise times and decay time constants of individual mIPSCs, neither in kindled nor in control cells. However, the graphs clearly illustrate that the mIPSCs are not drawn from a homogeneous group with normally distributed parameter values. The mIPSCs with the largest amplitude (>75 pA) form a group with significantly faster rise and decay times than the mean. The very slow mIPSCs (rise time >5 ms) have significantly smaller amplitudes. The mIPSCs with the fastest rise times most likely originate from sites with the least effect of dendritic filtering. In this group of mIPSCs, however, a large variation in amplitude (Fig. 7A) and decay time constant (Fig. 7B) was observed even within the same recording. This indicates that the variation is intrinsic.
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Noise analysis
We applied nonstationary noise analysis to the group of the
largest mIPSCs (amplitude >75 pA) to estimate the single channel conductance and the number of postsynaptic GABAA
receptors that contributed to the event (Fig.
8). There were 727 large mIPSCs from
kindled and 1,094 from controls. The mean single-channel conductance
was 30 ± 9 pS in the kindled and 29 ± 5 pS in the control
group, which is in good agreement with other reports about the
GABA-mediated chloride channels (De Koninck and Mody
1994; Edwards et al. 1990
; Grudt and
Henderson 1998
; Puopolo and Belluzzi 1998
). The
estimated mean number of postsynaptic receptors was 87 ± 8 and
99 ± 14 for kindled and controls, respectively. None of these
differences reached significance.
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Evoked IPSCs
In four cells, we recorded IPSCs that were evoked by a current injection from a large-tip glass electrode, filled with ACSF and positioned on the surface of a nearby pyramidal neuron. The stimulation most likely activated axons from inhibitory neurons that project to the recorded cell (no extracellular TTX). Stimulus intensity varied between 200 and 500 µA. The evoked IPSCs show a small delay after the stimulus (Fig. 9). Failures were observed at all stimulus intensities, but as expected most occurred at low intensity. The amplitudes, rise time, and decay time constants were determined of all evoked IPSCs in the same way as was done for the mIPSCs. Mean rise time and decay time constant were 1.7 ± 0.1 and 16.4 ± 1.0 ms (n = 104). The small number of successful evoked IPSC recordings did not allow a conclusive comparison between kindled and controls. Recordings of evoked and miniature IPSCs obtained from the same cell were, however, useful to indicate the good agreement between the kinetics of the evoked IPSCs and the scaled mean of the fast mIPSCs (Fig. 9B). The mean amplitude of evoked IPSCs was larger than that of the mIPSCs: 57 ± 2 pA at a low stimulus intensity of 200 µA (n = 19, excluding failures).
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DISCUSSION |
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The enhanced excitability characteristic for epilepsy is
brought about by a shift in balance from inhibitory to excitatory drive. A multitude of mechanisms can be involved starting from a direct
enhancement of excitatory transmission (Köhr et al. 1993; Kraus et al. 1994
) or reduction in
inhibition (Kamphuis et al. 1988
; Zhao and Leung
1993
) up to quite specific changes in the excitability of
specific cells (Faas et al. 1996
; Vreugdenhil and
Wadman 1992
; Vreugdenhil et al. 1998
) or the
functional loss of strategically important cell classes
(Kamphuis et al. 1989
; Sloviter 1991
).
Previous field potential recordings (confirmed in the present study)
showed a gradual reduction in functional inhibition in the CA1 network
during kindling epileptogenesis (Kamphuis et al. 1988
).
This effect is maximal immediately after the kindling stimulations, but
partial recovery has been observed in the long-term animals
(Zhao and Leung 1993
).
A special group of large mIPSCs was distinguished in the total population of mIPSCs recorded in CA1 pyramidal cells. This group was distinct in amplitude, and it showed significantly faster kinetics than the mean population event. In long-term kindled animals a 40-50% reduction in the number of mIPSCs in this group was found. Although these large mIPSCs were only a small fraction of the total number of mIPSCs, the specific reduction seen in this group was responsible for a highly significant difference in the amplitude distribution of mIPSCs after kindling.
The mean mIPSC amplitude and frequency and the total number of fast and slow mIPSCs were not different in the kindled and the control group. The characteristic properties of the individual mIPSCs (kinetics for all mIPSCs, single-channel conductance and number of postsynaptic channels for only mIPSCs with amplitudes >75 pA) reflect the properties of the GABAA receptors involved. These were not different in the two experimental groups.
Fast and slow mIPSCs
We found fast and slow mIPSCs in the CA1 pyramidal neurons. The
fast mIPSCs could represent currents originating from synapses on the
soma and proximal dendrites, whereas the slow mIPSCs could be generated
in synapses located more distally on the dendrites. Linear correlations
between kinetics and amplitudes of mIPSCs might be obscured by the
large intrinsic variance in amplitude and decay time constants.
Different interneuron classes could evoke IPSCs with specific kinetics
(Ouardouz and Lacaille 1997) and differences in
pharmacological properties between fast and slow mIPSCs cannot be ruled
out (Banks et al. 1998
; Pearce 1993
). The
properties of fast and slow mIPSCs overlap, but the precise threshold
level used for qualification hardly affected the conclusions drawn
here. Several factors could underestimate the ratio between slow and
fast mIPSCs. Small mIPSCs from dendritic synapses are filtered and may
not be detected in the soma. The noise level will also bias against the
small amplitude mIPSCs. As a consequence, the observed ratio should not
be quantitatively translated to the distribution of synapses over the
cell surface.
Postsynaptic GABAA receptors
Kindling epileptogenesis in CA1 is associated with a decrease in
binding density of the GABA agonist muscimol (Titulaer et al.
1994). This decrease could reflect a change in receptor
affinity, it could indicate a reduction in GABA receptor density per
synapse or a reduction in the absolute number of GABAergic synapses.
The latter two possibilities should lead to differences in mIPSC
amplitude and frequency after kindling, none of which were found. If
GABA receptors operate in a saturated mode (Edwards et al.
1990
; Faber et al. 1992
; Jonas et al.
1993
), changes in receptor affinity will not be reflected in
mIPSC properties. However, reduced affinity should decrease the
amplitude of mIPSCs that are mediated by unsaturated receptors as has
been suggested for the large amplitude mIPSCs (Nusser et al.
1997
).
The noise in the decay of a mIPSC reflects gating of the postsynaptic
GABAA receptors (Borst et al.
1994; De Koninck and Mody 1994
; Sigworth
1980
). The number of receptors and their single-channel conductance can be estimated if channel noise dominates. For the largest mIPSCs, we obtained numbers in agreement with previously reported values for GABAA receptors (De
Koninck and Mody 1994
; Edwards et al. 1990
;
Grudt and Henderson 1998
; Puopolo and Belluzzi 1998
). We found no indications for a change at the molecular
level in GABAA receptors after kindling.
Synapse morphology
A hypothesis proposed by Edwards predicted that plasticity of
synapses induces morphological changes reflected in the skewness of the
amplitude distribution (Edwards 1995). Large-amplitude miniature postsynaptic currents can either originate from synapses with
a large number of receptors or they reflect the synchronous release of
vesicles from several active zones (Edwards 1995
). Consequently, the reduction in large-amplitude mIPSCs in kindled animals should show up morphologically as a reduction in the number of
synapses with a large postsynaptic grid or multiple active zones.
GABAergic synapses with several separate active zones within one
synapse have been reported (Nusser et al. 1997
;
Peters et al. 1990
). An increase in the number of
perforated synapses and an increase in synaptic area of GABAergic
synapses were shown previously in dentate gyrus after kindling
epileptogenesis (Geinisman et al. 1990
; Nusser et
al. 1998
).
Network function
The consequences of kindling induced changes at the synapse level
also have to be considered at the network level. The relation between
the mIPSCs caused by spontaneous release of vesicles and functional
inhibitory synapses in the intact network is not evident (Faber
et al. 1998). In the cells in which we were able to record both
miniature and evoked IPSCs, we observed a striking similarity between
their kinetics. This at least suggests that the evoked IPSCs consisted
of the synchronous activation of synapses from the same type that
produced the mIPSCs.
If linked to functional synapses, the reduction in mIPSCs reflects a
loss of inhibitory innervation. The group of mIPSCs with high
amplitudes and fast kinetics most likely originates from the soma.
Because the somatic inhibitory synapses are the most effective, even a
relative small reduction in their number could lead to a noticeable
impairment of inhibition. The fact that also the fraction of very slow
mIPSCs (rise time >5 ms) is smaller after kindling could indicate that
the loss of synapses is not restricted to the soma. Previous
immunocytochemical work (Kamphuis et al. 1989) has shown
that 50% of the GABAergic interneurons that do not contain parvalbumin
have disappeared after kindling epileptogenesis. Whether the synapses
of these interneurons are responsible for the large amplitude mIPSCs
needs to be determined.
Functional rewiring of the local circuit with a change in function of
specific neurons has been observed after epileptogenesis and other
challenging conditions. Bragin reported a reduced activity of the
interneurons in the CA1 area during an epileptic seizure, indicative of
specific participation of different classes of neurons in epileptic
activity (Bragin et al. 1997). Long-term stimulation that induces epilepsy leads to the loss of hilar neurons in the dentate
gyrus and so removes the excitatory input from interneurons which then
become dormant (Sloviter 1991
). This phenomenon was not
observed in the self-sustained limbic status epilepticus model (Rempe et al. 1997
), but after anoxia functionally
disconnected interneurons also have been reported (Khazipov et
al. 1995
). Denervated interneurons result in normal GABAergic
innervation of the principal neurons, which due to the lack of
excitatory input on the interneurons will never function. But the
opposite situation also exists. Unchanged GABAergic innervation of
principal neurons will be more effective if the interneurons that drive
it are innervated more effectively or highly synchronized. Sprouting
that occurs heavily in the dentate gyrus (Cavazos et al.
1994
) could compensate for the loss of cells and reduction in
connectivity, but such compensation would most likely result in a
higher degree of synchronization. In the CA1 area sprouting is more
disputed (Perez et al. 1996
), but also much harder to detect.
Comparison with dentate gyrus
The observations in the dentate gyrus after kindling
epileptogenesis are almost opposite to the ones that we report for the CA1 area. In the dentate gyrus, the mean mIPSC amplitude was increased (Otis et al. 1994), and this change recently was found
to be linked to an increase in the number of postsynaptic
GABAA receptors (Nusser et al.
1998
). These findings are consistent with an overall
enhancement of the GABAergic inhibition in the dentate gyrus as has
been reported (Kamphuis et al. 1992
; Oliver and
Miller 1985
). They are, however, hard to link causally to the
emergence of epileptic activity (but see Buhl et al.
1996
). In the CA1 area, the changes in mIPSCs and field
potential inhibition are also consistent, but in the opposite
direction. Here they could underlie the emergence of epilepsy. These
findings indicate that different brain areas can react differently on
the establishment of an epileptic focus.
A reduction in inhibitory drive in the CA1 network after kindling
epileptogenesis will involve changes in cell properties and in their
functional connectivity. Because the epileptic network is properly
functioning most of the time, the changes observed after kindling are
expected to be subtle. At the cell membrane level, many changes in
properties or abundance of calcium and sodium channels have been
reported (Vreugdenhil and Wadman 1992; Vreugdenhil et al. 1998
), but these changes need not be
the same in all cells of the network. The transfer of a local network
can be changed in even more ways because it comprises the changes in
all cells and their connectivity. Synapses can adapt their strength
depending on the activity in pre- and postsynaptic cells (Davis
and Goodman 1998
; Turrigiano et al. 1998
).
In the CA1 region, kindling epileptogenesis induces a shift in the balance between inhibition and excitation. In pyramidal cells, membrane excitability is enhanced, whereas in the network, inhibition is reduced. Our new data suggest that the loss of specific somatic synapses or of the projecting interneurons could be an important factor. The net result of all mechanisms is a lower threshold for seizure activity. In particular in the kindling model, the network is stable for most of the time; this suggests that the changes are at least partly compensated. The most intriguing mechanism, the one that defines the long-term balance between excitation and inhibition, still needs to be determined.
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ACKNOWLEDGMENTS |
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The authors thank H. van Hooft, G. Advokaat, and E. Hendriksen for implanting the rats, F. Edwards for advice and hospitality, and F. Lopes da Silva and M. Joëls for critical reading of the manuscript.
This work was supported by Grant 805-25-243 of the Dutch Organization for Scientific Research (NWO).
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FOOTNOTES |
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Address for reprint requests: C. J. Wierenga, Institute for Neurobiology, Kruislaan 320, 1098 SM Amsterdam, The Netherlands.
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 22 January 1999; accepted in final form 17 May 1999.
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REFERENCES |
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