Laboratoire de Neurophysiologie, Faculté de Médecine, Université Laval, Quebec G1K 7P4, Canada
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ABSTRACT |
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Amzica, Florin and
Dag Neckelmann.
Membrane Capacitance of Cortical Neurons and Glia During Sleep
Oscillations and Spike-Wave Seizures.
J. Neurophysiol. 82: 2731-2746, 1999.
Dual intracellular
recordings in vivo were used to disclose relationships between cortical
neurons and glia during spontaneous slow (<1 Hz) sleep oscillations
and spike-wave (SW) seizures in cat. Glial cells displayed a slow
membrane potential oscillation (<1 Hz), in close synchrony with
cortical neurons. In glia, each cycle of this oscillation was made of a
round depolarizing potential of 1.5-3 mV. The depolarizing slope
corresponded to a steady depolarization and sustained synaptic activity
in neurons (duration, 0.5-0.8 s). The repolarization of the glial
membrane (duration, 0.5-0.8 s) coincided with neuronal
hyperpolarization, associated with disfacilitation, and suppressed
synaptic activity in cortical networks. SW seizures in glial cells
displayed phasic events, synchronized with neuronal paroxysmal
potentials, superimposed on a plateau of depolarization, that lasted
for the duration of the seizure. Measurements of the neuronal membrane
capacitance during slow oscillating patterns showed small fluctuations
around the resting values in relation to the phases of the slow
oscillation. In contrast, the glial capacitance displayed a
small-amplitude oscillation of 1-2 Hz, independent of phasic sleep and
seizure activity. Additionally, in both cell types, SW seizures were
associated with a modulatory, slower oscillation (0.2 Hz) and a
persistent increase of capacitance, developing in parallel with the
progression of the seizure. These capacitance variations were dependent
on the severity of the seizure and the distance between the presumed seizure focus and the recording site. We suggest that the capacitance variations may reflect changes in the membrane surface area (swelling) and/or of the interglial communication via gap junctions, which may
affect the synchronization and propagation of paroxysmal activities.
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INTRODUCTION |
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The cortical network is made of neuronal and glial
cells. The membrane of each element undergoes the influence of synaptic and/or ionic currents. The ensuing changes are reflected by
corresponding variations of the conductance and/or capacitance of the
membrane. Glial cells initially were considered to accomplish only
connective and trophic functions for neurons. Growing evidence,
however, attributes them with important tasks in the electrical dialog with neurons (Nedergaard 1994; Parpura et al.
1994
). Recent reports bring into attention reciprocal
neurotransmitter-based exchanges between neurons and glia. On one hand,
glial membranes possess receptors for a variety of transmitters
(Nicholson 1995
). On the other hand, glia release
neurotransmitters (Levi and Gallo 1995
). Glial cells
possess receptors for most of the neurotransmitters involved in
behavioral state control, such as glutamate
[non-N-methyl-D-aspartate (non-NMDA)]
(Sontheimer et al. 1988
; Steinhäuser and
Gallo 1996
), GABA (GABAA) (Bormann
and Kettenmann 1988
; MacVicar et al. 1989
; Rosier et al. 1993
), acetylcholine (Tse et al.
1992
), and norepinephrine (McCarthy et al.
1995
). Glutamate, an ubiquitous transmitter in the CNS,
depolarizes glia through receptors similar to the ones of the neurons
(Bowman and Kimelberg 1984
; Kettenmann and
Schachner 1985
) and triggers slow
Ca2+-dependent oscillations in cortical and
hippocampal astrocytes (Pasti et al. 1995
, 1997
).
Calcium waves may travel through gap junctions between astrocytes and
may unidirectionally cross glia-neuron gap junctions (Nedergaard
1994
).
During the state of resting sleep, neurons have been shown to display a
slow (<1 Hz) oscillatory activity generated within the cortex
(Steriade et al. 1993a,b
). This activity consists of periods of neuronal depolarization associated with intense neuronal activity alternating with periods of neuronal hyperpolarization and
cessation of cellular firing. Although this slow oscillation first was
described under various anesthetics, its relevance to sleep has been
demonstrated (Achermann and Borbély 1997
;
Amzica and Steriade 1998
; Steriade et al.
1996
). The behavior of glial cells during the slow oscillatory
sleep pattern is not known.
Sleep enhances the propensity of the brain to generate spike-wave (SW)
seizures (Kellaway 1985; Steriade 1974
).
SW seizures gradually develop from the slow (<1 Hz) sleep oscillation
(Steriade and Amzica 1994
; Steriade et al.
1998
). The neuronal activity during SW seizures is similar to
that observed during slow sleep oscillations, only the synchrony of the
neuronal pool is higher and the depolarizations and hyperpolarizations
are more ample.
In simple preparations, glial cells are reliable potassium detectors
(Kuffler et al. 1966; Nicholls and Kuffler
1964
). Neuronal excitatory activity is associated with the
opening of transmitter- and voltage-gated channels resulting in
Na+ influx and K+ efflux.
The latter may induce increases of the extracellular K+ by several mM (Somjen 1979
),
which in turn will depolarize neighboring glial cells due to their high
K+ conductances. Janigro et al.
(1997)
have shown that, in hippocampal slices, astrocytic
inwardly rectifying K+ channels play a crucial
role in regulating the extracellular K+
concentration. A major part of the K+ uptake
occurs via passive Donnan-like redistribution of
K+ and Cl
(Ballanyi et al. 1987
; Kettenmann 1987
;
Walz 1989
). The accumulation of K+
in the extracellular space is associated with two phenomena: water
influx in glial cells leading to swelling (Ballanyi et al. 1990
); increased propensity to seizure onset leading to
regenerative events underlying the seizure (Fertziger and Ranck
1970
; McBain et al. 1993
; Zuckermann and
Glaser 1968
). It becomes therefore of particular interest to
understand the cellular mechanisms of neuron-glia interactions as they
evolve from physiological slow sleep oscillations to pathological paroxysms.
Our experimental approach is based on double intracellular recordings in vivo, which enables the recording of simultaneous neuronal and glial activities as they develop in intact cortical networks. This is especially useful in the case of glial ("silent") cells, which lack overt signaling that can be recorded extracellularly.
In this paper we also investigate the membrane conductance and
capacitance of cortical neurons and glia during normal (slow sleep
oscillation) and paroxysmal (SW seizures) electrical patterns. Changes
in the membrane capacitance may betray variations in the somatic
membrane surface, in a similar way exocytosis is detected using
capacitance measurements (Moser and Neher 1997).
Hippocampal slices display activity-dependent swelling (Andrew
and MacVicar 1994
) and transient shrinkage of the extracellular
space occurs during periods of increased extracellular potassium
([K+]o) (Dietzel
et al. 1980
), leaving open the issue of whether neurons or glia
are responsible for this phenomenon. Evidence presented here points to
the glial cells and suggests mechanisms through which they may
influence neuronal behavior. It also will be shown that several types
of capacitance changes occur during normal and paroxysmal oscillations.
This is the first report of such capacitance variations in vivo, i.e.,
under physiological conditions, where the cortical network is preserved totally.
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METHODS |
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Animal preparation and recordings
Twenty adult cats were anesthetized with a mixture of ketamine and xylazine (10-15 and 2-3 mg/kg im, respectively), intubated, paralyzed with gallamine triethiodide, and artificially ventilated (20-30/min). All pressure and incision points were infiltrated with lidocaine. To avoid any pain, the electroencephalogram (EEG) and the heart rate were monitored continuously and supplementary doses of anesthetic were readministered at the slightest activation of the EEG or acceleration of the pulse rate. The end-tidal CO2 concentration was maintained at 3.7% (±0.2). Surgery consisted of craniotomy exposing mainly the suprasylvian gyrus. Cisternal drainage, hip suspension and pneumothorax were performed to improve the mechanical stability of the brain. To further reduce eventual pulsations, after installing the recording electrodes, the hole in the calvarium was filled with a solution of 4% agar.
Intracellular recordings were performed with glass micropipettes (tip
diameter <0.5 µm) filled with potassium acetate (3 M, impedance
30-40 M) and, on some occasions, with neurobiotin (2%, Vector
Laboratories). Staining of cells with neurobiotin was performed by
applying depolarizing pulses (150 ms at 3.3 Hz) of 1-2 nA for 5-15
min. Signals were passed through a high-impedance amplifier with active
bridge circuitry, and recorded on tape (band-pass: DC to 9 kHz). Field
potentials (AC traces in figures) were recorded with tungsten
macroelectrodes (0.5-1 M
impedance), inserted in the depth of the
suprasylvian cortex (
1 mm), amplified and band-pass filtered
(0.3-1,000 Hz). For off-line computer analysis, signals were passed
through an analogue-digital converter at a sampling rate of 20 kHz. SW
seizures occurred spontaneously (22% of the seizures), were triggered
by electric stimulation (15% of the seizures), or were induced by
inserting the needle of a syringe, filled with 10 µl of a 0.2 mM
solution of bicuculline in saline, into the rostral part of the
suprasylvian gyrus (cortical area 5); very small amounts of bicuculline
(0.02-0.05 µl) leaked slowly into the cortex. Intracellular
recordings were performed at some distance (>10 mm) from the
bicuculline focus to avoid the direct action of the drug on the
cellular membrane.
At the end of the experiments where neurobiotin was used, the deeply anesthetized cats were perfused transcardially with saline followed by 10% paraformaldehyde. The brain was removed and stored in formalin with 30% sucrose for 2-3 days, then it was sectioned at 50 µm, and processed with the avidin-biotin standard kit (ABC standard kit, Vector Laboratories): the sections were incubated over night at room temperature in the avidin-biotin-horseradish peroxidase complex solution at a dilution of 1:200 and 0.5% Triton X-100. After rinsing, the sections were reacted with 3,3'-diaminobenzidine tetrahydrochloride (0.05%), H2O2 (0.003%), incubated in a solution of glial fibrillary acidic protein (GFAP) at a dilution of 1:800, mounted on gel-dipped slides and cover-slipped.
At the end of all other experiments, the cats were given a lethal dose of intravenous pentobarbital sodium.
Analysis
Conductance and capacitance of the cellular membrane were
derived from the charging curve of hyperpolarizing pulses applied intracellularly. Constant care was taken to keep the bridge balanced throughout the period with hyperpolarizing current pulses, regardless of the ongoing spontaneous synaptic activity. Only recordings with a
balanced bridge were considered for analysis. Time constants were
estimated with a double-exponential fit using the Levenberg-Marquardt algorithm (IGOR software, WaveMetrics). In the case of neurons, the
double-exponential fit is required by the nonisopotential intracellular
voltage distribution (Rall 1959). Isopotentiality also
may be compromised in glial cells due to their coupling through gap
junctions. Indeed, synaptic neuronal activity may modulate interglial
communication (Marrero and Orkand 1996
), and a recent model (McKhann et al. 1997
) points toward transient
changes of the coupling ratio between glia. Thus the charging curve was
fitted with a function of the type:
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The duration of the injected current (I) was 60% longer
than 10 times the expected main time constant
(10
1), to obtain a reliable plateau to be used
as Vm(
). Thus single glial
impalements required pulses of
10 ms, whereas double-glia-neuron
recordings or single-neuron impalements were imposed with pulses of
50 ms. In each cell, we applied a series of depolarizing and
hyperpolarizing pulses (Fig. 1B) to find the current limit
at which active conductances were still not triggered. In some cases,
depolarizing pulses were associated with rectifying components (not
shown). Hence we decided to use hyperpolarizing pulses. As shown in
Fig. 1B, hyperpolarizing pulses of up to
2 nA were devoid
of overt active responses. In the sequences of pulses depicted in Fig.
1B, we also estimated the dependence of the time constants
on the intensity of the injected current. The main time constant
(
1) was extremely stable (variation <3%),
whereas the second time constant (
2) presented
larger variations (<25%), but these were unrelated with the intensity
of the pulse. Thus for the testing of the dynamic evolution of the
capacitance and conductance, we generally applied current pulses of 1 nA.
Pulses were delivered at a frequency of 5-10 Hz, and in some cases
they were delivered with variable frequencies to verify whether some of
the oscillations reported here could have been artifacts of the
stimulation rate. Several parameters were extracted from each pulse
(Fig. 1A). The average membrane potential before the onset
of the hyperpolarizing pulse (Vdep)
was calculated over a period tdep
representing five main time constants
(tdep = 51). Similarly, Vm(
), or
Vhyp, is the average of the membrane
potential toward the end of the hyperpolarization calculated over an
identical time span (thyp = 5
1). The input conductance of the cell
(YN) is
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In some of the figures, the hyperpolarizing pulses were removed artificially from the intracellular trace to reconstruct the membrane potential. This was achieved by displacing the charging curve from the bottom of the hyperpolarizing pulse toward the level of the resting membrane potential and by canceling the eventual transients. These traces were used only for descriptive, graphic purposes, never for calculating time constants.
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RESULTS |
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Database and cellular identification
From the total of intracellularly recorded cells, we retained for
analysis only the best recordings, i.e., 58 neurons and 53 glia, of
which 29 were double intracellular impalements. The criteria for this
choice were, in the case of neurons: stable resting membrane potentials
more negative than 60 mV (
71 ± 2.8 mV; mean ± SD) for
15 min and overshooting action potentials. Although a wide range of
glial resting membrane potentials has been described recently
(McKhann et al. 1997
), we retained for analysis only
glial recordings starting with a sudden drop of membrane potential from
0 mV to resting membrane potentials more negative than
70 mV
(
85 ± 3.4 mV; see Fig. 4). Membrane potentials had to remain
stable for
15 min and never needed the application of steady
hyperpolarizing currents. In no circumstance were action potentials
triggered spontaneously after impalement or by depolarizing pulses. At
the end of the glial recording, the micropipette was withdrawn from the
cell and field potentials were recorded. These displayed a reversed
polarity for the main components recorded intracellularly. During SW
seizures, glial recordings displayed intracellularly steady
depolarizations of 10-30 mV, and extracellularly corresponding
negative shifts of 3-6 mV (see Fig. 4). These values were in
accordance with previous in vivo intraglial recordings (Grossman
and Hampton 1968
; Sypert and Ward 1971
).
Moreover, values of the resting time constants calculated in this paper
are in agreement with those of previous studies (e.g.,
Trachtenberg and Pollen 1970
).
All glial and neuronal elements were recorded within the cortex, at
<1.5 mm from the surface, as read from the stepping device carrying
the microelectrode (the precision of this estimate was better than 85%
when compared with the precise location of stained cells). Cellular
staining with neurobiotin and reactivity to GFAP (Fig.
2B) show that most of the
glial cells (88%) were protoplasmatic astrocytes (Fig. 2, C
and D), whereas neurons were generally pyramidal shaped
(Fig. 2A). Only a few dye-coupled cells (4 couples) were disclosed. Of these, only two couples contained glial cells, but they
failed to react to GFAP immunocytochemistry and are therefore not
shown. However, the low level of dye-coupling observed here may be
explained by fact that the use of neurobiotin generally leads to false
negative estimation of the dye-coupling (Moser 1998). In
the case of neurons, dye-coupling diminishes dramatically with age
(Connors et al. 1983
).
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Slow sleep and paroxysmal activities in neuron-glia networks
During natural sleep and under anesthesia, corticothalamic
neuronal networks oscillate at a frequency <1 Hz (Steriade et
al. 1993a). The membrane of cortical neurons displayed a
continuous variation between depolarized and hyperpolarized values
(Fig. 3). The depolarization is made of
synaptic potentials (excitatory and inhibitory) and is associated with
negative depth field potentials. The hyperpolarization is marked by the
abolition of synaptic potentials and is associated in depth field
recordings with positive waves. All glial cells reflected this slow
oscillation (Fig. 3). Their membrane underwent periodic
depolarizing-repolarizing sequences in close temporal relationship with
activities recorded in simultaneously impaled neurons nearby. The onset
of the depolarizing phase of the slow oscillation induced a round-like
depolarization of glial cells. Toward the end of the depolarizing phase
and with the onset of the hyperpolarizing phase, the glial membrane
began to repolarize with a decaying slope to reach more or less the
initial potential. The amplitude of the glial depolarization ranged
between 1.5 and 3 mV and was proportional to the neuronal
depolarization during an oscillatory cycle.
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Figure 4 depicts the general pattern of
cortical SW seizures as recorded with dual impalements and field
potentials. The latter shows the evolution of seizures from a slowly
oscillating sleep-like pattern to a few rhythmic EEG spikes. The rhythm
accelerated (1-2 Hz), produced a short epoch of fast runs (10 Hz),
and continued with recurrent polyspike waves at
1.3 Hz. A first
seizure was recorded with a pipette inside a neuron and with another
pipette in the extracellular space (Fig. 4A). A few seconds
later and only few micrometers below, the second pipette impaled a
glial cell (see the brisk drop of potential), and a new seizure
occurred (Fig. 4B). This glia corresponds to the one
depicted in Fig. 2C.
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The neuronal rhythmic (1-2 Hz) depolarizing potentials evolved from
the depolarizing sequences of the slow oscillation that turned into
paroxysmal depolarizing shifts (PDSs; Fig. 4B1), accelerated their rhythm from <1 to 1-2 Hz and generated the SW pattern. Seizures often displayed periods of continuous fast runs (10 Hz; Fig. 4B2) or bursts of fast runs tailing the recurrent PDSs (Fig.
4B3), thus contributing to the polyspike shape of the EEG.
All these neuronal phasic events were reflected in glial potentials.
The glial PDS grew ampler than any cycle of the slow oscillation. As
the seizure reached its most paroxysmal expression, fast neuronal depolarizing events were reflected partially reversed by the glial cell
(neuronal fast excitatory events were associated with sharp negativities in glia). This is not a voltage-dependent phenomenon because it does not happen at the same membrane potential at the beginning of the seizure. Rather it might be caused by the glial swelling (see following text) that brings neuronal and glial membranes closer. Thus some intraglial potentials may reflect direct
extraneuronal transients. However, slower depolarizing neuronal
potentials continued to be associated with depolarizing glial waves.
Therefore the glial potential during SW seizures reflects the
superimposition of intraglial currents and extraglial field potentials.
The macroscopic glial membrane potential was characterized by a steady depolarization for the whole duration of the seizure (Fig. 4B). When recorded with DC electrodes, the extracellular expression of the sustained excitation appeared as a persistent negative shift (Fig. 4A).
Capacitance variations during slow (<1 Hz) sleep activities
Previously most of the studies monitoring the cellular capacitance
were conducted to disclose secretory mechanisms, where modified
capacitance values are connected to exocytotic or endocytotic processes
(Moser and Neher 1997; Neher and Marty
1982
). Our study extrapolates the principle of the capacitance
technique to in vivo cortical neuronal and glial somatic recordings.
The membrane may be viewed as a battery of capacitors (Holmes et
al. 1992
; Rall 1959
). Three intrinsic membrane
factors may affect the capacitance: the composition of the membrane
lipid bilayer (dielectric constant), the surface, and the thickness of
the membrane. The first two parameters induce proportional effects
while the third has a reciprocal relationship with the capacitance.
Although it appears as a limitation, we consider that the dielectric
constant is invariable over the time scale of our experiments. It is
reasonable to believe that the chemical and physical structure of the
cellular membrane is not modified during seizures lasting for no more
than a few minutes, especially because the electrical behavior returns
to its preseizure values at the end of the seizure. This assumption,
however, may be questioned over longer time spans.
The average time constants of neurons (1 and
2) calculated during slowly oscillating
activities, were respectively 4.02 ± 0.23 ms and 1.06 ± 0.78 ms (all results are provided as means ± SD). The first
exponential coefficient (k1) was
122.6 ± 24.3 and the second exponential coefficient
(k2) was 47.8 ± 15.6. The errors
of the time constants due to the fitting procedure were 33.4 ± 12.1% and 175.3 ± 2%, respectively. All these values were calculated for 30 neurons for an average period of 60 s/cell. The
errors were quite high due to the superimposition of synaptic activities over the charging curves. This is why capacitance
measurements were considered reliable only in fewer neurons
(n = 5), in which errors for at least the main time
constants were below 10% and could not affect the oscillatory
evolution of their values (Fig. 5). The
detail in Fig. 5B depicts a few hyperpolarizing pulses delivered during a cycle of the slow oscillation together with the
fitting curves, the two time constants and the standard deviation errors of the fits. It is shown that the main time constant
(
1) was diminished during the depolarizing
phase of the slow oscillation and increased during the
hyperpolarization. The second time constant (
2) displayed irregular variations that could
not be related to any activity in the network. The behavior of the
first time constant (
1) produced a capacitance
oscillating in a reciprocal manner to oscillations of the membrane
potential of the neuron (Fig. 5C). The neuronal trace in
this panel was reconstructed from the original trace (see
METHODS) and is depicted to outline the inverse relation of
the capacitance with the neuronal activity. The average neuronal
capacitance was 170 pF (range from 100 to 800 pF). The amplitude of the
capacitance variation during slow oscillations was proportional to the
amplitude of the slow oscillation and ranged from 50 to 150 pF.
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The glial capacitance, measured as in the case of neurons, during
periods with slow oscillations, expressed a periodic variation of
~1-2 Hz (n = 53; Fig.
6). The main time constant
(1) was 0.148 ± 0.02 ms and had a
coefficient k1 = 134.81 ± 25.57 (fitting error 3.67 ± 0.6%). The second time constant
(
2) was 2.14 ± 0.24 ms with
k2 = 25.12 ± 3.57 and the
fitting error of 13.57 ± 3.2%. Both time constants oscillated at
roughly the same frequency (see autocorrelograms in Fig.
6D). The average of the glial capacitance during slow
oscillations was 13.45 pF (range 10-25 pF) and its variation
(amplitude of 0.5-3 pF) was independent of synaptic activities and the
slow (<1 Hz) oscillation of the network (Fig. 6A). Figure
6C also presents a comparison between the capacitance evolution derived from fitting the charging curves with a double exponential (top) and a single exponential
(bottom). Although both traces show basically the same
oscillation, as proven by their cross-correlation (CROSS in Fig.
6D), some differences were evident: the average conductance
value was higher (~30%) with single than with double-exponential fit
and the oscillatory variations were less pronounced and regular with
the simple exponential. Adding to this the fact that the fitting error
was higher with single exponentials (19 ± 3.4%,
n = 23), we decided to use only the double-exponential
fit.
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We propose to call the capacitance oscillation displayed by glia the pulsatory capacitance variation (PCV). The term "pulsatory" is suggested by the stereotyped pattern of the capacitance trace. The PCV had an average frequency of 1.52 ± 0.4 Hz (in 53 cells) as derived from the maximum peak of the power spectrum of the capacitance curves. These microswellings were not induced by eventual heart pulsations (the heart rate was monitored during experiments). They were not time-related to the oscillatory activity of the network (see also following text). On the contrary, none of the tested neurons displayed PCV, their only capacitance changes being related to the ongoing network activity (slow oscillation).
Glial capacitance variations during SW seizures
SW seizures in glial cells were associated with increased membrane conductance and capacitance. These variations were dependent on the distance between the presumed seizure focus (site of bicuculline infusion or of electrical stimulation) and the location of the impaled cell. They also depended on the severity of the seizure.
In the case of epileptic foci induced in cortical area 5 and glial
cells recorded 10-15 mm away from the focus in area 7, the onset of
the seizure was marked by a progressive build-up of the persistent
glial depolarization, in contrast with the relative fast onset showed
by the focal DC field potential in area 5 (Fig. 7A). In spite of this, the
glial cell responded with depolarizing waves from the first PDS,
suggesting that the propagation of the seizure was quite fast (>2
m/s). This estimated propagation velocity resulted from a time lag of
<5 ms between the onset of corresponding PDSs in area 5 (close to the
focus) and area 7 and knowing that the distance between the two
electrodes was of ~10 mm. Here too, as was often the case for
epileptic foci induced by intracortical infusion of bicuculline,
recurrent SW seizures occurred every minute or so, separated by silent
periods with postictal depression (PID). The membrane conductance
followed a similar time-course (Fig. 7B) but was even more
delayed from the onset of the seizure (25 s). Once the conductance
began to increase, it followed an accelerated course to finally mark a
27% increase. Out of 53 glial cells, 27 were situated at some distance
(>5 mm) from the presumed epileptic focus, and all of them had
increased conductances during the seizure with an average of 32 ± 7.5%.
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The membrane capacitances of distantly located glial cells followed a
similar time-course as the conductance and started to increase ~25 s
after the onset of the seizure (Fig. 7C). Several components
could be distinguished: 1) the PCV was still very obvious throughout the recording (thin line in Fig. 7C; see also
narrow peak at 0.88 Hz in the power spectrum of Fig. 7D).
The PCV was not affected by the various membrane potential activities
displayed during the seizure (1.5 Hz of the SW seizure, 10 Hz of the
fast runs, and PID after the end of the seizure). It was not seen in the 2 curve (not shown). 2) A slow
modulation of ~0.2 Hz, hereafter called modulatory capacitance
variation (MCV), appeared with the development of the seizure (e.g.,
the few higher peaks marked with open arrowheads in Fig. 7C,
and the corresponding peak in the power spectrum of Fig.
7D). The MCV appeared only during seizures, independently of
the distance from the focus, in 48 of the 53 tested glial cells (90%).
The amplitude of the MCV reached a maximum during the most paroxysmal
segment of the seizure. The average capacitance increase due to the MCV
compared with the control value was of 92 ± 11%. Peak values
from various seizures ranged between 66 and 400%. And finally,
3) there was a slow trend reflecting a progressive
capacitance increase of the glial cells with the progression of the
seizure (thick line in Fig. 7C). This glial capacitance
component was obtained as a polynomial fit of fourth order of the
original curve.
Capacitance variations of glial cells during SW seizures depended
on the severity of the seizures. The severity was considered as a
function of the duration of the seizure, the presence of fast runs
(10 Hz), and the amount of depolarization displayed by intracellular
recordings. In the same intraglial recording, two seizures of different
severity induced different modifications at the level of the membrane
conductance and capacitance (Fig. 8A). The first seizure was the
most severe one. The conductance increased almost twofold and the
capacitance increase was ~50% higher compared with the second
seizure. The overall dependence of glial capacitance on two parameters
defining the severity of SW seizures is presented in Fig.
8B.
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SW seizures also were elicited with electrical stimulation of the cortex (Fig. 9). Here again, more severe seizures (Fig. 9, 2) induced increased capacitance modifications. During the first seizure (Fig. 9, 1), the capacitance displayed small-amplitude PCVs and MCVs, especially during the seizure. If a more severe seizure was triggered (Fig. 9, 2), capacitances were drastically increased and followed the time course of the seizure. A sustained swelling can be inferred from the persistent increase in capacitance. The onset of this increase was delayed from the onset of the seizure and coincided with the reaching of a depolarizing plateau in the intraglial recording. This could explain why, in the case of the seizure depicted in the left panel without such a depolarizing plateau, the capacitance modifications were not so dramatic.
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Neuronal capacitance variations during SW seizures
During SW seizures, neurons displayed increased conductances of their membrane. This could contribute to the inactivation of somatic sodium spikes during the steady depolarization (Fig. 10). In contrast to glia, changes in neuronal capacitance during seizures rarely were seen (only in 3 of 58 neurons, i.e., 5%, Fig. 10). In none of the cases could we find PCVs. This does not mean that they do not exist but that synaptic activity and slower time constants often make the extraction of precise values for capacitance more difficult. In these cases interpolations between neighboring pulses free of synaptic interferences were considered. However, the absence of PCV during periods free of synaptic activity, such as the hyperpolarizing phase of the slow oscillation or the PID, suggests that neurons do not possess this kind of capacitance variations.
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The two cells illustrated in Fig. 10 were recorded at very short distance (<0.5 mm) and presumably belonged to a network homogeneously affected by the SW seizure. The neuronal capacitance displayed irregular variations in the range of the MCV (0.3-0.4 Hz) and a very discrete steady increase during the seizure (see - - - in the neuron's graph).
It is clear from the fitting curve of the capacitance values that the
surface area of the neuron and of the glia had different overall
evolutions. The first increase appeared in the neuron and was
paralleled by a corresponding decrease in the glia. Glial capacitance
increase coincided with the middle of the seizure. The correlative
analysis of time constants from the recording presented in Fig. 10 is
depicted in Fig. 11. The two time
constants of the neuron (top left) followed similar
evolutions regardless of whether individual values (gray
curve) or overall tendencies (black curve) were
considered. Even better correlations were disclosed between the two
time constants of the glia (top left). Cross-correlations between neuronal and glial time constants (bottom panels in
Fig. 11) show mostly negative central peaks suggestive of a
complementary interaction between the volume variations of the neurons
and glia (see black traces from the curves that depict the
general tendency during the seizure in Fig. 10). The positive
superimposed peak present in the cross-correlation of the first time
constant (1, bottom left, gray
curve in Fig. 11) is probably due to the epoch where both neuronal
and glial time constants increase simultaneously during the middle of
the seizure.
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DISCUSSION |
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This paper describes patterns of slow (<1 Hz) sleep oscillations
in cortical neuron-glia networks and their development into paroxysmal
patterns of SW type. Three types of capacitance variations, which are
proposed to reflect volume and interglial communication modifications,
accompany these activities in glial cells. These may impose regulatory
processes on the ionic currents flowing through the cellular membranes
and the extracellular space. Neurons display only small-amplitude
capacitance variations time-locked with synaptic activities. All
cortical cells increased their conductance during SW seizures, in
accordance with previous reports (Hablitz 1987;
Oakley et al. 1972
).
Patterns of neuro-glial interactions
Although the role of glial cells in uptaking
[K+]o released by neurons
has been known for a long time (Kuffler et al. 1966; Nicholls and Kuffler 1964
), the neuron-glia interaction
always has been studied through indirect methods. To our knowledge,
Figs. 3 and 4 are the first to show the simultaneous behavior of
neuronal and glial membrane potentials in vivo. Such dual neuron-glia
impalements are particularly useful because SW seizures preferentially
take place during sleep (Kellaway 1985
; Steriade
1974
) and extracellular K+ accumulation
is a major factor in triggering SW seizures (Fertziger and Ranck
1970
; Janigro et al. 1997
; Zuckermann and
Glaser 1968
). Figure 3 suggests a tight relationship between
neuronal and glial activities during physiological sleep oscillation.
The resting concentration of
[K+]o is ~3 mM
(Futamachi et al. 1974
). Although the variations of [K+]o were not measured
in our experiments, we may extrapolate them from other studies
(Janigro et al. 1997
). We made the assumption that, for
the voltage range recorded in this study, the relationship between the
glial membrane potential and the
[K+]o is linear
(Walz et al. 1984
). The
[K+]o elevation during SW
seizures of the type we report here was 9-10 mM (Moody et al.
1974
; Sypert and Ward 1974
). This would correspond to an average sustained depolarization of glial cells of 20 mV (range 10-30 mV, as a function of distance from the presumed focus), seen in the present study. Equally, the 1.5- to 3-mV rhythmic depolarizing potentials recorded in glia during the slow oscillation would bring the concentration of the
[K+]o somewhere between
3.75 and 4.5 mM. This is within the range where, as shown in the
cerebellum, neurons increase their excitability but close to the limit
(5 mM) where their excitability starts to diminish (Kocsis et
al. 1983
). This reasoning suggests that the pacing of the slow
(<1 Hz) sleep oscillation may result from the critical balance between
periods with enhanced neuronal excitability (depolarized phase) and
with diminished excitability (hyperpolarized phase). Glial cells could
play an important role by setting the [K+]o concentration.
Impaired uptake of K+ could result in
regenerative processes underlying SW seizure (Fertziger and
Ranck 1970; Janigro et al. 1997
). During these
periods, as suggested by reduced time lags between corresponding phasic
events, the synchrony between cortical neurons (Steriade and
Amzica 1994
) and between neurons and glia (present data) is increased.
Three types of capacitance variations
The capacitance variations reported in this study (Figs. 5-10)
were measured by means of hyperpolarizing pulses. The underlying principle already has served to detect exocytosis in chromaffin cells
(Moser and Neher 1997). Here it was used only after
ensuring that the hyperpolarizing pulses did not trigger any visible
active conductances susceptible to affect the charging curve (Fig.
1B). Some differences in the behavior of glia between in
vivo and in vitro preparations are discussed elsewhere (Somjen
1995
).
These capacitance variations tend to point toward swelling and, in the
case of glial cells, to modulation of their coupling through gap
junctions. The ability of glial cells to swell has been acknowledged
repeatedly in cultures and in slice preparations (for a review, see
Kimelberg 1995). However, the actual evolution of glial
volume in situ during slow sleep oscillations and during seizures, in
close time relation to electrical patterns, has not been shown before.
Increases of capacitance may be due to an increased surface area of the
cellular membrane or to its thinning. However, the capacitance
increases cannot be exclusively accounted for by surface enlargement.
Knowing that a surface increase with a factor of k would be
translated into a volume increase of about
k2/3, it would suggest that for a
sustained mean capacitance increase of 55% during SW seizures (values
from Fig. 8B, corresponding to cells located at 2-5 mm from
the focus), the glial volume would increase by 94%. It is known that
the extracellular space has a limited volume representing ±20% of the
total brain volume (Nicholson 1995). Increases of the
glial volume beyond that limit, although possible during severe edema,
would induce displacement of the cells and loss of the impalements.
Because this was not the case, it appears that an enlarged surface has
to be accompanied by thinning of the membrane and possibly by other
phenomena (see following text). Thinning of the membrane also could be
a consequence of increased surface if this were provoked by increased
tension and not by added substance, as is the case during exocytosis.
Limiting the volume increase to the whole available 20% of
extracellular space, by an inverse reasoning, would correspond to a
maximum surface enlargement of 13%. Thus to attain the same 55%
capacitance increase, a thinning of the membrane by 73% would be required.
Our set of cortical glial cells display a basic oscillatory capacitance variation (PCV) of the membrane during physiological sleep oscillations (Fig. 6), suggesting a continuous volume regulation at a frequency of 1-2 Hz. These pulsatile movements are independent of heart rate or respiration. They are not affected by the electrical activity of the network, and they survive during most of the SW seizure and the PID following the seizure. Only during severe paroxysms, was the PCV abolished (see Fig. 9, right). This effect may be due to the fact that the local extracellular space has reached a critical shrinkage, where cellular membranes begin to press against each other and prevent PCV.
During SW seizures, the membrane capacitance displayed a slower variation of ~0.2 Hz (Figs. 7-10). The amplitude of the MCV increased with the development of the seizure (Fig. 7) and could outlast the arrest of the seizure. In the cases of recurrent seizures where the seizure-free periods were short enough (<20 s), the MCV was present throughout the recording, with a small-amplitude reduction before the onset of a new ictal episode (Fig. 9). It may be suggested that the MCV corresponds to a supplementary protection of the extracellular space against accumulation of K+ via at least two possible mechanisms.
First, a series of swelling-dependent conductances have been found in
glial cells. Astrocytes and other cell types counteract volume
increases by an efflux of Cl and other anions
(Crépel et al. 1998
; Pasantes-Morales et
al. 1994
). Besides the receptor- and voltage-gated currents,
which are active during paroxysmal activities,
stretch-activated-currents may play an important role in equilibrating
the membrane potential of the glial cells. If the MCV corresponds to
variations of the cellular surface, it would result that the
stretch-activated channels are periodically opened to allow ion efflux
accompanied by water expulsion. This also could explain why the
membrane potential during seizures saturates at a given level,
regardless of the severity of the seizure (Moody et al.
1974
).
Second, the periodic (every 5 s) swellings of glia would produce
equivalent periodic squeezing pressure on the intracellular ionic
content and would help to evacuate the excess to more distant locations
through the network of gap junctions. This process may be assisted by
the fact that the steady depolarization observed during SW seizures
(Figs. 4 and 7-10) would induce intracellular alkalinization, which
results in increased permeability of gap junctions (see Ransom
1995
). It appears that the phasic potentials superimposed on
the steady depolarization are not related to the MCV, probably because
they are not ample enough to produce an observable modulation of the
gap junction opening.
In parallel with the development of the MCV, there was also a sustained increase in the membrane capacitance of glial cells (Figs. 7-10), which generally followed the course of the SW seizure. The intensity of this phenomenon decreased with the distance from the presumed seizure focus, suggesting its implication in the evacuation of K+ and eventually of other ions (Fig. 8B).
It should be equally noted that the increased capacitance also might
result from modified gap junction properties. It is well established
that glial cells, especially astrocytes, extensively communicate
through gap junctions (Binmöller and Müller
1992; Gutnick et al. 1981
; for review, see
Dermietzel and Spray 1993
). It is possible that the
modification of intraglial voltages or ionic concentrations during
certain activities (especially during seizures) affect gap junction
communication, for example, to increase the global capacitance recorded
by the somatic electrode, thus creating the illusion of a swollen
membrane. This hypothesis is supported by the fact that dye coupling of
astroglia is significantly upregulated by membrane depolarization, both
by increases in the extracellular K+ concentration and directly by
ionophores (Enkvist and McCarthy 1994
). The increased
values for the second time constant reported here during SW seizures
(e.g., Fig. 11) may suggest a modulation of remote glial membranes,
possibly by the opening of gap junctions and creating the illusion of
increased membrane surface area. At this time, however, our
experimental approach is not able to discern between the contribution
of surface, thickness, and gap junction communication to the reported
capacitance variations.
With minor exceptions (<5%), cortical neurons involved in slow (<1
Hz) sleep oscillations or in SW seizures were less inclined to swell.
This finding does not imply that neurons are deprived of volume
regulatory mechanisms of the PCV type. In fact, the ability of
molluscan neurons to swell has been reported as a result of
hypo-osmotic insult (Herring et al. 1998; Wan et
al. 1995
). Additionally, exocytotic processes are certainly
accompanied by increased membrane surface, as demonstrated in a series
of preparations with secretory cells (Moser and Neher
1997
; Zimmerberg and Whitaker 1985
). It
is feasible that such processes also may take place in the cortical
neurons of the cat, but because they occur at remote sites from the
soma, they would not be detected by the technique used in this study.
It is also true that synaptic activities might interfere with the
somatic estimation of the capacitance in neurons. Indeed, when
recording the response of the somatic membrane to the hyperpolarized
pulse, the electrode equally picks up the synaptic potentials generated
in and conducted through the dendritic arbor. Thus the charging curve
undergoes the superimposition of synaptic potentials.
However, besides the small-amplitude capacitance variations related to
the slow (<1 Hz) sleep oscillation (Fig. 5), sustained swelling rarely
was detected in neurons during SW seizures (see, however, Fig. 10).
Several mutually nonexclusive explanations may be envisaged: the ionic
channels work efficiently and do not produce intracellular electrolytic
accumulations; the glial swelling generates a pressure on neurons and
keeps their volume unchanged; the incidence of gap junctions between
neurons diminishes dramatically with age (Connors et al.
1983); and the SW seizures we induced were neither strong
enough nor sufficiently generalized to induce more serious swelling
effects in neurons. As such we are brought to suggest that glial cells
have a specific role in assuming the initial volume regulatory function
in the cortex. This also would protect the neuronal membrane from
mechanic tension and would better preserve the fine tuning of the
channel-mediated ionic exchange.
Functional implications of glial swelling
SW seizures are associated with substantial increases in synchrony
but, at the same time, with impaired ability to generate action
potentials evoked by intrasomatic depolarizing pulses (Steriade et al. 1998). Several lines of evidence have suggested that
signal transmission and synchronization may be achieved through
extrasynaptic mechanisms, of which ephaptic interactions are of
particular interest for the present discussion (Dudek et al.
1986
; Hochman et al. 1995
; Rosen and
Andrew 1990
; Taylor and Dudek 1982
; Yim
et al. 1986
). Transmembrane potential measurements have shown
that during paroxysmal events, the signal reaches amplitudes in the
order of 10 mV (see Fig. 11 in Dudek et al. 1986
). It is
therefore possible that during SW seizures, when the extracellular
space shrinks (Dietzel et al. 1980
), the glial swelling
(present data) would draw near the cellular membranes, thus
facilitating the intercellular ephaptic transmission. Further spreading
of the signal also may occur through the gap junctions of the glial
syncytium. This process also may be amplified by the swelling-induced
release of amino acids by astrocytes (Kimelberg et al.
1990
), as well as direct glia-to-neuron signaling
(Parpura et al. 1994
).
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ACKNOWLEDGMENTS |
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We thank M. Steriade for support and for helpful remarks on the manuscript. We also thank P. Giguère and D. Drolet for technical assistance.
This work was supported by grants to F. Amzica from the Medical Research Council of Canada and to M. Steriade from the Human Frontier Science Program. F. Amzica is a scholar of Fonds de la recherche en santé de Québec and D. Neckelmann is a postdoctoral fellow supported by the Norwegian Research Council.
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FOOTNOTES |
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Address reprint requests to F. Amzica.
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 28 April 1999; accepted in final form 2 June 1999.
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REFERENCES |
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