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Changes in neuronal conductance during different components of cortically generated spike-wave seizures
Neuroscience Vol. 96, No. 3, pp. 475–485, 2000 475 Copyright q 2000 IBRO. Published by Elsevier Science Ltd Printed in Great Britain. All rights reserved 0306-4522/00 $20.00+0.00
Neuronal conductance during spike-wave seizures
Pergamon PII: S0306-4522(99)00571-0 www.elsevier.com/locate/neuroscience
CHANGES IN NEURONAL CONDUCTANCE DURING DIFFERENT COMPONENTS OF CORTICALLY GENERATED SPIKE-WAVE SEIZURES D. NECKELMANN, F. AMZICA and M. STERIADE* Laboratoire de Neurophysiologie, Faculte´ de Me´decine, Universite´ Laval, Que´bec, Canada G1K 7P4
Abstract—Neuronal conductance was studied in anesthetized cats during cortically generated spike-wave seizures arising from slow sleep oscillation. Single and dual intracellular recordings from neocortical neurons were used. The changes were similar whether the seizures occurred spontaneously, or were evoked by electrical stimulation or induced by bicuculline. In all seizures, the conductance increased from the very onset of the seizure and returned to control values only at the end of the postictal depression. Simultaneous intracellular recordings from two neurons showed that the neuron leading the other neuron displayed the largest increase in membrane conductance. The changes in neuronal conductance during the two phases of the slow sleep oscillation, i.e. highest during depolarizations and lowest during hyperpolarizations, were similar to those occurring during the “spike” and “wave” components of seizures. (1) Maximal conductance was found during the paroxysmal depolarizing shift corresponding to the electroencephalogram “spike” (median: 252 nS; range: 90 to more than 400 nS). It was highest at the onset of the depolarized plateau and decreased thereafter. (2) During the hyperpolarization corresponding to the electroencephalogram “wave”, the conductance was significantly lower (median: 71 nS; range: 41 to 140 nS). (3) The conductance was elevated during the fast runs (median: 230 nS; range: 92 to 350 nS) which occurred in two-thirds of the seizures. (4) The conductance values during postictal depression were situated between those measured during the seizure hyperpolarizations and during sleep hyperpolarizations. The conductance decreased exponentially back to the values of the slow sleep oscillation over the total duration of the postictal depression. The data suggest that the major mechanism underlying the “wave”-related hyperpolarizing component of spike-wave seizures relies mainly not on active inhibition, but on a mixture of disfacilitation and potassium currents. q 2000 IBRO. Published by Elsevier Science Ltd. Key words: cat, neocortex, intracellular, conductance, spike-wave seizures, slow sleep oscillation.
The spike-wave (SW) pattern is an electroencephalographic (EEG) manifestation of seizures in some epileptic syndromes 17,35 and is also seen in animal models of epilepsy. Recently, cortically generated seizures with SW or polyspike (PSW) complexes (1.5–3 Hz) and fast runs (10–15 Hz) have been described, using extra- and intracellular recordings in behaving and anesthetized cats. 25 Such seizures develop without discontinuity from sleep patterns, 23,25,26 particularly from a slow oscillation generated in neocortex. 28–30 The neocortex is the minimal necessary substrate for the expression of these seizures as they can occur in the absence of the thalamus 27 and in isolated cortical slabs, 33 and they are primarily synchronized through intracortical connections. 16 During the EEG “spike” component cortical neurons are depolarized and fire briskly, whereas neurons are hyperpolarized and silent during the EEG “wave”. 19,22 The depolarization associated with the EEG “spike” is thought to be a giant postsynaptic potential, 12,13 termed paroxysmal depolarizing shift (PDS). It has been suggested that the cellular hyperpolarization associated with the EEG “wave” component is mainly mediated by inhibitory conductances 19 and that the intracellular correlate of the initial 40–80 ms of this component is Cl 2 dependent, presumably mediated by GABAA receptors. 8 A recent model 6 suggested that GABAB-mediated K 1 currents produce SW oscillations. These hypotheses have
in common the idea that the neuronal hyperpolarization is caused by a GABAergic mechanism. The main mechanism underlying the hyperpolarization phase of the slow sleep oscillation is disfacilitation and the apparent input resistance (Rin) is highest during this phase. 3 Thus, since SW seizures develop without discontinuity from the slow sleep oscillation, and the intracellular counterparts of SW complexes are related to field potentials in a similar way as the depolarizing–hyperpolarizing phases of the slow oscillation, 25 we hypothesized that disfacilitation, rather than a highly increased inhibitory conductance, may play a major role in the neuronal hyperpolarizations during SW complexes. To study the evolution of the membrane input conductance, we took intracellular recordings from neurons in anesthetized cats during the slow oscillation and its development to SW seizures, and we also induced such seizures by electrical stimulation or using the GABAA antagonist bicuculline. EXPERIMENTAL PROCEDURES
Fifty-two cats were anesthetized with ketamine and xylazine (10– 15 mg/kg and 2–3 mg/kg, respectively). All tissues to be incised were infiltrated with lidocaine. The depth of anesthesia was monitored by continuous EEG recording. Supplementary doses of ketamine and xylazine (3–4 mg/kg and 0.6–0.8 mg/kg, respectively) were administered at the slightest change towards an activated state expressed by diminished amplitudes and increased frequencies of the EEG. Heart rate (acceptable range 90–110 beats/min) and temperature (36–398C) were monitored. When deep anesthesia was reached and a sleep-like pattern was present in the EEG, a muscle relaxant (gallamine triethiodide) was administered, and the animal was mounted in a stereotactic frame and artificially ventilated under control of end-tidal CO2 (3.5–3.8%). The stability of the recordings was improved by drainage of cisterna magna, hip suspension, bilateral pneumothorax, and by filling the hole made for recordings with a solution of 4% agar.
*To whom correspondence should be addressed. Abbreviations: AHP, spike after-hyperpolarization; EEG, electroencephalogram; FRB, fast-rhythmic-bursting neuron; IPSP, inhibitory postsynaptic potential; PDS, paroxysmal depolarizing shift; PID, post-ictal depression; PSW, polyspike-wave; Rin, apparent input resistance; SW, spike-wave; Vm, membrane potential. 475
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To compensate for fluid loss, 20–30 ml saline was given intravenously during the experiments, which lasted for 8–12 h. Field potential recordings were made with coaxial electrodes placed with the ring at the cortical surface and the tip at 0.8–1 mm in the cortical depth of suprasylvian areas 5, 7 and 21. Coaxial recording electrodes were also inserted into the thalamic intralaminar central lateral and lateral posterior nuclei. Field potentials were also recorded by tungsten microelectrodes (3–8 MV) inserted at different depths of various cortical areas. Single or dual simultaneous intracellular recordings in suprasylvian areas 5 and 7 were made with glass micropipettes filled with 3 M potassium acetate (d.c. resistance 25–45 MV). A high-impedance dual amplifier with active bridge circuitry was used to record and inject current into the neurons. The bridge was continuously monitored and adjusted when necessary. The signals were band-pass filtered (0– 9 kHz), digitized at 20 kHz and stored on an eight-channel tape recorder for off-line analysis. In addition to spontaneously occurring seizures during sleep-like patterns, we induced paroxysmal activities by electrically stimulating cortical or appropriate thalamic nuclei, or by inserting a Hamilton syringe filled with 10 ml of a 0.2 mM solution of bicuculline in saline in the rostral part of area 5. The syringe content was not injected, but some of the bicuculline diffused slowly into the cortex. 25 Square current pulses (0.5–2 nA; 30–200 ms) were injected into the neurons through the recording pipette at regular intervals during seizures. By measuring the change in Vm, the apparent neuronal input resistance (Rin) could be calculated using Ohm’s law (Rin DVm/I), where I is injected current. Cellular conductance is G 1/Rin. Only representative responses were used in the analysis, to avoid spurious variations (e.g., when spontaneous activity was superimposed over the charging curve; see the 4th pulse in Fig. 2B2, where a paroxysmal depolarization started during a current pulse). However, each pulse was visually examined to see whether or not the result was influenced by prominent spontaneous activity. At the end of the experiments, the cats were given a lethal dose of intravenous pentobarbital sodium followed by 10% formaldehyde. The location of stimulating and recording electrodes was verified on 80-mm sections stained with Thionine. RESULTS
Intracellular recordings with stable resting membrane potential (Vm) more negative than 255 mV and overshooting action potentials were obtained from 221 cortical neurons. In 160 seizures we recorded intracellularly from two neurons simultaneously (48 cell couples). In 98 neurons we recorded conductance tests during both the slow oscillation and seizures. Spontaneously occurring seizures Figure 1 shows a typical seizure developing spontaneously and without discontinuity from the slow sleep-like oscillation. At the EEG level, the slow oscillation consists of long-lasting depth-positive waves followed by prolonged depth-negative waves, repeated at a frequency of < 0.8 Hz. During the depth-positive EEG waves cortical neurons were hyperpolarized, whereas during the depth-negative wave neurons were depolarized. 2 In Fig. 1, the recorded neuron was identified by depolarizing current pulses as a fast-rhythmic-bursting (FRB) neuron 9,31 and it displayed pronounced changes in its activity pattern before a seizure was apparent in the depth-EEG recorded close to the cell (pre-seizure panel in Fig. 1). A leading role of FRB neurons in the generation of SW/PSW seizures has been proposed. 25 The slope as well as the amplitude of the shift in Vm from hyperpolarized to depolarized levels increased. The shift from depolarized to hyperpolarized Vm levels was also steeper. The amplitudes of Vm changes increased because the neuron reached a more hyperpolarized neuronal Vm during the EEG positivity and a more depolarized
Vm during the EEG negativity. At this stage, the shape of the action potentials and the fast after-hyperpolarization (AHP) remained unchanged. During the part of the seizure characterized by SW/PSW complexes, the action potentials were partially inactivated and the AHP disappeared. The fast run period was characterized by EEG “spikes” at 10–20 Hz and, at the neuronal level, a tonically depolarized Vm with smaller depolarizations superimposed. The end of the seizure was associated with a short period of hyperpolarization, followed by a resumption of the slow oscillation. Dynamic evolution of conductance changes during seizures Figure 2 shows a spontaneously occurring seizure recorded in area 7 of the suprasylvian gyrus. The seizure had a duration of around 60 s and developed from the slow oscillation (see extreme left part in the figure). Hyperpolarizing current pulses were injected throughout the period shown. Below the intracellular trace the estimated conductance values are plotted coded according to the type of neuronal activity when the current pulse was injected (see legend). The conductance increased from the onset of the seizure. This pattern was observed in all 221 recorded cortical neurons. However, there was considerable variation in the measured conductance. Some of this variation was due to whether the current pulse was injected during a hyperpolarized or depolarized state of the neuron. In Fig. 2, the left part of panels A and B1 show variation of conductance during the slow oscillation, with increased Rin during the hyperpolarization related to the depth-EEG positive wave and decreased Rin during the depolarization related to the depth-EEG negative wave (see also Ref. 3). As the SW pattern developed (B2), there was a gradual increase in conductance during both the depolarizations (“spikes”) and hyperpolarizations (“waves”). During the period with fast runs (B3), the neuron was depolarized to Vms that caused inactivation of action potentials. During the fast runs, the conductance was increased relative to the hyperpolarized phase of the SW seizure, but did not reach the maximal increase observed during the depolarized phase (see below and Discussion). During the following SW pattern and the postictal depression, the conductance gradually decreased to the control values. Seizures could be evoked by pulse-trains applied to the suprasylvian gyrus. In Fig. 3A, three pulse-trains were applied to area 5 (arrowheads) and the neuron as well as field potentials were recorded in the vicinity. The changes in conductance were similar to the spontaneous seizures, as can be seen in details 1–4 from panel A. Panel B shows a seizure evoked by bicuculline diffusion. The activity pattern consisted of periods of interictal depression alternating with seizures of 40–180 s duration. Below the intracellular trace the estimated conductance values are plotted, coded according to the type of cellular activity (depolarizations and hyperpolarizations during SW complexes, and fast runs, as indicated by symbols). A gradual increase in cellular conductance preceded the start of the seizure (left part) and was most pronounced during the depolarizations. During the seizure the conductance remained high, and then gradually returned to the initial values during the interictal period. Thus, a similar dynamic evolution of the cellular conductance was observed in spontaneously occurring seizures and in seizures evoked by electrical stimulation or bicuculline
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Fig. 1. Spontaneously occurring seizure developing without discontinuity from the slow sleep-like oscillation. Intracellular recording from area 5 fastrhythmic-bursting (FRB) neuron together with depth-EEG from the vicinity in area 5. Seizure is indicated by arrows. Detail 1 shows typical activity during slow oscillation. During 2 there are clear pre-seizure changes in the activity of the cell, whereas the depth-EEG is not significantly altered. Detail 3 shows typical SW complexes at around 2 Hz in the depth-EEG. The cell displayed high-frequency spike-bursts, with an intraburst frequency of 300–600 Hz. The fourth depth-negativity in the EEG had a polyspike-wave pattern, similar to the start of the fast run, depicted in 4; the cell also displayed high-frequency spikebursts during the fast runs and remained tonically depolarized in this period. The Vm is indicated with an arrow.
diffusion. There were no systematic differences in the observed magnitude of the conductance changes. In the following, we will report the results for all seizures together, without considering how they were evoked. Membrane conductance during the slow oscillation compared with spike-wave seizures Figure 4 shows the variations in conductance during the two main (depolarizing and hyperpolarizing) components of the slow oscillation and during the two (“spike”-related depolarization and “wave”-related hyperpolarization) components of a SW seizure. Square hyperpolarizing pulses of 60 ms and 0.5 nA were injected every 100 ms (A). During the slow oscillation three distinct phases in the
EEG could be discerned: the depth-positive EEG wave (1), the depth-negative EEG wave (2), and a phase of varying duration (marked by asterisk in panel B), with low amplitude fast frequency activity, preceding the next depthpositive EEG wave. The responses to 20 hyperpolarizing pulses delivered during each of these three phases were averaged (C). Similarly to the results from a previous study, 3 we found the conductance to be smallest during the depth-positive wave (in this neuron: 36 nS; observed range in recorded neurons: 19–74 nS), maximal during the depth-negative wave (in this neuron: 54 nS; observed range: 36–120 nS), and intermediate during the period preceding the depth-positive wave (in this neuron: 42 nS). At the level of 98 neurons, the conductance decreased by 36% during the depth-positive phase with respect to the
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Fig. 2. Conductance changes during spontaneously occurring seizure. (A) Intracellular recording from area 7 neuron together with depth-EEG from the vicinity in area 7. During this period, square current pulses of 1 nA amplitude and 50 ms duration were injected through the recording pipette every 200 ms. The estimated conductance is plotted below at the corresponding time-point (Conductance). The values are coded according to the type of cellular activity at the time of the pulse. Conductance values from pulses that were delivered during the depolarized phase of the slow oscillation or the depolarized phase of the paroxysmal activity are plotted as crosses ( 1 ). Values from pulses that were delivered during the hyperpolarized phase of the slow oscillation or hyperpolarized phase of the paroxysmal activity are plotted as dots (.). Values from pulses during the fast runs (where the duration of the hyperpolarized and depolarized phase are too short to allow for a separate estimation of the two) are plotted as open triangles. For the method used to estimate apparent cellular input resistance during fast runs, see Fig. 6. (B1–B3) show details from slow oscillation, SW seizure, and fast run. The detail below shows a superimposition of a pulse from slow oscillation and a pulse from the SW seizure. In A, the Vm is indicated with an arrow.
intermediate epoch, while it increased by 20% during the depth-negative phase. The SW seizure depicted in the right column of Fig. 4 occurred spontaneously in the same neuron, 6 min later. We averaged the responses to 20 pulses from the depth-positive EEG phase corresponding to the “wave” (1) and from the depth-negative EEG wave corresponding to the “spike” (2). The conductance was increased relative to the respective phase of the slow oscillation. During the depth-positive “wave” component the conductance was 45 nS (observed range 41–140 nS; median: 71 nS), while it increased to 144 nS during the depth-negative “spike” (observed range: 90– .400 nS; median 252 nS). Within the depth-negative “spike” component, there was a considerable variation in the observed conductance over a short period of time, the conductance depending on the interval from the onset of the cellular depolarization to the start of the hyperpolarizing
pulse (Fig. 5). Shorter intervals were associated with larger conductance values. Indeed, when the intervals were very short, no precise estimates could be made of the conductance, because the voltage deflection was too small relative to the spontaneous variation in Vm. We measured the conductance during SW seizures in a sample of 98 neurons. During the “wave” component, the mean conductance was 78.4 nS (S.D. 28.8), while during the “spike” component, the mean conductance was 245.7 (S.D. 75.6). Cellular conductance during fast runs During the fast runs, the continuously fluctuating Vm made it difficult to directly measure a voltage deflection; also, we could not estimate conductance for the hyperpolarized and depolarized phases of fast runs separately. Figure 6 shows
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Fig. 3. Seizures induced by electrical stimulation (A) and bicuculline diffusion (B) show similar patterns of changes in membrane conductance. Both panels show intracellular recording from a neuron in area 5b together with depth-EEG from the vicinity. Panel A illustrates a seizure evoked by three trains of 200 pulses at 100 Hz to cortical area 5a. Square current pulses of 1 nA amplitude and 30 ms duration were injected through the recording pipette every 100 ms. A1 shows a detail from the preceding slow oscillation. A2 shows the cellular monosynaptic response to the cortical stimuli at 100 Hz. A3 shows a detail from the SW part of the evoked seizure. A4 shows a detail from the fast runs. Vm of 270 mV is indicated in all panels. Panel B shows a seizure resulting from the insertion of a syringe with 10 ml 0.2 mM bicuculline in area 5a. The neuron and field potentials were recorded in area 5b. Several hours after the insertion of the syringe, the activity pattern of the brain consisted of paroxysms separated by periods of interictal depression. Square current pulses of 1 nA amplitude and 50 ms duration were injected though the recording pipette every 200 ms. The calculated conductance values are plotted below at the corresponding time-point (Conductance). They are coded according to the type of cellular activity at the time of the pulse as explained in the legend of Fig. 2. The Vm is indicated with an arrow.
the cellular response to square current pulses (1 nA, 100 ms) injected through the recording pipette every 200 ms during a fast run. In A, the responses to 10 pulses that had an onset during the first half of an oscillation cycle after a nadir were aligned at the time of the pulse (see current monitor below). To estimate the mean conductance during the fast runs we realigned these responses at the time and the Vm of the nadir preceding the pulse (B, arrows). Since the mean Vms of the preceding and following nadir were equal, we may assume that the observed shift in mean Vm in the intervening nadir was caused by the current pulses. There was no consistent relationship between the time since the onset of the current
pulse and the observed Vm of the intervening nadir; hence, the time-constant was short enough to allow the average apparent Rin to be estimated in this way (5.9 MV, corresponding to a cellular conductance of 169 nS; observed range in recorded neurons: 92–350 nS). The bottom panel in Fig. 6 shows a comparison of the averaged responses (n 20) in this cell during the hyperpolarized phase of the slow oscillation (1), and during the “wave” (2) and “spike” (3) components of a SW seizure. Apparent cellular conductances were 62, 104 and 222 nS, respectively. We measured the mean conductance during the fast runs of SW seizures in a sample of 40 neurons (out of those 98 that
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Fig. 4. Neuronal conductance increases during the SW seizure, compared with the slow sleep-like oscillation. Intracellular recording from an area 5 neuron together with depth-EEG from the vicinity in area 5. (A) Square current pulses of 0.5 nA amplitude and 60 ms duration were injected through the recording pipette every 100 ms during slow oscillation (left) and during a spontaneous SW seizure, 6 min later (right). (B) Superimposition of averaged fragments of the EEG, extracted around the times when the pulses were applied during slow oscillation (left), and SW seizure (right). The fragments were positioned to create averaged oscillation cycles. (C) Left column: 20 pulses were averaged from each of the three phases of the slow oscillation (1: the EEG depth-positive phase associated with the cell’s hyperpolarization; 2: the EEG depth-negative phase associated with cellular depolarization; and *: the relatively stable period, intermediate level, that separated each positive–negative cycle). C, Right column: 20 pulses were averaged (1: the “wave” associated with cellular hyperpolarization; and 2: the “spike” associated with cellular depolarization during the SW seizure). The conductance was increased during SW seizures compared with the slow oscillation. This was true both for the hyperpolarized (1) and depolarized (2) phases.
served for conductance measure during the “spike” and “wave” components; see above) and found it to be 226.5 nS (S.D. 69.2). Cellular conductance during postictal and interictal depression Figure 7 shows how cellular conductance decreased from the last part of a seizure through the interictal depression. In A responses from the hyperpolarized phase of the seizure (1) and the early phase of the interictal depression (2–4) illustrate that the membrane conductance during the interictal depression is lower than the observed values during the hyperpolarizing phases of the preceding SW complexes. In B the measured conductance in four different neurons during
postictal depression is plotted normalized in time (expressed as per cent duration of the postictal depression) and conductance (expressed as per cent of the observed conductance during the hyperpolarizing phase of the slow oscillation). The magnitude and evolution are similar to those observed during interictal depression. The solid line represents an exponential model, which provided the best fit in the majority of neurons. Dynamic changes of cellular conductance in simultaneously recorded neurons The time relations between simultaneously recorded neurons can vary during a seizure. 16 Figure 8A depicts a dual simultaneous intracellular recording from areas 5 and
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Fig. 5. The apparent cellular conductance during a paroxysmal depolarization depended on the time since the onset of the depolarization. Intracellular recording from a regular-spiking area 5 neuron. Square current pulses of 1 nA amplitude and 30 ms duration were injected through the recording pipette every 100 ms Left: five pulses delivered at different times since the onset of a paroxsysmal depolarizing shift (PDS). They are aligned at the time of the pulse. Right: a plot of calculated cellular conductance versus time since the onset of PDS ( 1 ) and the exponential fit (dotted line).
7. The neuron recorded in area 5 generated spikes tonically during most of the interictal depression which was apparent in the depth-EEG. The neuron in area 7 depolarized the most during the seizure, and its action potentials were inactivated during the fast run. The time relation between the two cells is illustrated below, throughout the seizure. The neuron in area 5 preceded the neuron in area 7 early in the seizure (see 1, lines upwards). Later (2–3), the area 7 neuron preceded the area 5
neuron (lines downwards). The time lags displayed here were calculated between the onset of corresponding depolarizations (PDSs) in the two neurons, as explained in the legend. Expanded details of responses to hyperpolarizing pulses during the three epochs (1–3) are provided in panel B. To compare the dynamic changes of time-relations to the changes in conductance, square current pulses (50 ms, 1 nA, every 200 ms) were injected simultaneously in both neurons.
Fig. 6. Estimation of apparent cellular conductance during fast runs. Intracellular recording from an area 5 neuron. Square current pulses of 1 nA amplitude and 100 ms duration were injected through the recording pipette every 200 ms. The fast runs ( < 10–15 Hz) showed a continuously fluctuating Vm which made it difficult to directly measure apparent input resistance. This is seen in (A), where 10 traces that had a current pulse onset during the first half of an oscillation cycle after a nadir are aligned on the time of the pulse (see current monitor below). To overcome this problem, the traces were realigned (B) at the time and Vm of the nadir preceding the pulse (arrows). Since the mean Vms of the preceding and following nadir are equal, it can be assumed that the observed shift in mean Vm in the intervening nadir was caused by the current pulses. Since there was no consistent relationship between time since onset of pulse and the observed Vm of the intervening nadir, we can assume that the time constant was short enough to allow the average apparent cellular input resistance to be estimated in this way (5.9 MV, thus apparent cellular conductance was 169 nS). In the detail below, there is a superimposition of the averaged cellular responses (n 20) in this cell during the hyperpolarized phase of slow oscillation (1), and during the hyperpolarized (2) and the depolarized (3) phase of a SW seizure. Apparent cellular conductances were 62, 104 and 222 nS, respectively.
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Fig. 7. Membrane conductance decreased during the postictal depression (PID). Intracellular recording from area 5 neuron together with depth-EEG from the vicinity in area 5. The activity pattern was evoked by bicuculline diffusion, and consisted of paroxysms separated by periods of interictal depression. Square current pulses of 1 nA amplitude and 50 ms duration were injected through the recording pipette every 200 ms. The Vm is indicated with an arrow. (A) Pulse 1 is from the SW part of the seizure and pulses 2, 3 and 4 are from the PID, as indicated in the upper panel. It was an exponential decrease in apparent cellular conductance from the high levels observed during the last hyperpolarized phases of the SW seizure during the entire PID. To compare this decrease across several different cells, we have plotted the normalized conductance values from four cells in panel B. The conductance values are expressed as per cent of the observed conductance during the hyperpolarized phase of the slow oscillation in each cell. Since the duration of the PID varied both across and within animals, we used per cent duration of the PID as ordinate, rather than seconds. The line shows an exponential fit.
The ratio between the measured conductances of the two neurons was calculated for each pulse and plotted at the corresponding time (see Conductance ratio in panel A). In this analysis, we only included the pulses that were injected during the hyperpolarized component of the SW seizure and during the fast runs. The dotted line represents the ratio between the two neurons at the endpoint of the postictal depression (PID) following the seizure. There was a parallel evolution in the time-relation and conductance ratio. Initially, when the neuron in area 5 preceded (1), this neuron showed the largest increase in conductance. Later, as the neuron in area 7 started to preceed (2), its conductance increased. A detail from two pulses during the period where the area 5 neuron preceded is shown in B1 (taken from the period marked 1 in panel A). Later, the neuron in area 7 preceded (B2). The conductance in the area 7 neuron increased, while it was not changed in the area 5 neuron. During the fast run (B3) the area 7 neuron also preceded, and while the single responses to the current pulses were difficult to assess, the averages of realigned pulses (according to the method explained in Fig. 6) showed that the area 7 neuron had a larger conductance than the area 5 neuron (see C3). Averages of eight representative responses from each period (1–3) are shown in panel C. These aspects have also been found in other 37 dual intracellular recordings.
DISCUSSION
The intracellular and field potentials during the complex SW/PSW seizures described herein bear a striking resemblance to EEG records in some epileptic patients and we therefore postulate that the electrophysiological mechanisms of these cortically generated paroxysms are similar to those occurring in humans. The major findings from the present experiments are as follows. (1) The conductance increased at the onset of the seizure, and returned to control values only at the end of the postictal depression. (2) The fluctuation in conductance during the slow sleep oscillation, with minimal conductance during the hyperpolarization corresponding to the depth-positive EEG wave and maximal conductance during the depolarization corresponding to the depth-negative EEG wave, continued during the “spike” and “wave” components of SW complexes of seizures. During the depolarizing plateau corresponding to the EEG “spike”, the conductance was maximal close to the onset of the depolarization, and decayed thereafter. (3) The conductance was also highly elevated during the fast runs. (4) During the postictal depression, the conductance slowly returned to control values at the time when normal activity in the neuron and network resumed. (5) With dual simultaneous intracellular recordings which displayed time-lags, the neuron that preceded during the seizure also showed the largest increase in conductance.
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Fig. 8. Time-relation and conductance ratio between two simultaneously recorded neurons covaried during seizures. Seizure evoked by insertion of a syringe with 10 ml 0.2 mM bicuculline in area 5. (A) For each cell and each depolarizing complex we selected the time-point of the steepest slope of the Vm (highest dVm/dt). We subtracted the time-point of the area 5 cell from the corresponding time-point of the area 7 cell, and plotted the resulting time lag along the ordinate as a line starting from 0 (see calibration bar from 0 to 20 ms at the extreme right). The lines are plotted at the time point of the area 7 neuron. Throughout the seizure square current pulses of 1 nA amplitude and 50 ms duration were injected through the recording pipettes every 200 ms in both neurons. The Conductance ratio between the two neurons (conductance of area 5 neuron divided by the conductance of area 7 neuron) during the cellular hyperpolarizations were plotted ( 1 ). In B, details from two pulses during the period where the neuron in area 5 preceded is shown in 1 (taken from the period marked 1 in A). Only the first pulse (during the hyperpolarization) was included in the analysis displayed in A. Later, the neuron in area 7 preceded (2). Whereas the conductance in the area 7 neuron increased, conductance remained unchanged in the area 5 neuron. During the fast runs, the individual pulses are difficult to assess, but the averages of realigned pulses (according to the method explained in Fig. 6) show that the conductance of the area 7 neuron was larger. (C) Averages of eight representative responses from each period (1–3).
Transition from sleep patterns to seizure: increased conductance during the seizure The high incidence of seizures under the experimental condition was reported and explained in a previous paper. 25 In brief, it is due to the hypersynchronization of corticothalamic activity during the sleep-like patterns produced by ketamine–xylazine anesthesia. The present data derived from only those cats that displayed paroxysms.
The cortically generated seizures arise without discontinuity from the slow sleep oscillation. 16,23,25,26 The relations between intracellular and field potentials activities are practically identical during sleep patterns and seizures, with the difference that the amplitude of the depth-EEG sharp negativity (the K-complex) during the slow sleep oscillation is increased to become a paroxysmal “spike” and the oscillatory frequency increases from less than 1 Hz during the slow oscillation to 2–4 Hz during SW/PSW seizures. 25 The variable
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duration of the “spike” (from < 70 ms to as long as 200– 250 ms) is accounted for by the history of the network. Indeed, the relative refractoriness of the “spike” explains why, when preceded by spontaneously occurring paroxysmal depolarizations, the duration of the “spike” is dramatically reduced (see Fig. 5 in Ref. 24). The conductance increased gradually in the period immediately preceding the onset of a seizure. There was no clear discontinuity in the conductance values during the transition from the slow oscillation to seizure. This stands in contrast to the idea 18 that there is a critical threshold conductance value for seizure development. The preceding increase in conductance was most pronounced during the depolarizations (see Fig. 3B). In the transition period from the slow oscillation to seizures, the amplitude of the depolarizing component of the slow oscillation increased, as did the number of action potentials per depolarization. The slope and amplitude of the shift in Vm from hyperpolarized to depolarized levels increased, and the neuron reached a more depolarized Vm during the depthnegative EEG “spike”. 25 Such changes in cellular activity patterns in a population are associated with increased postsynaptic potentials, both excitatory and inhibitory, and a series of voltage-gated as well as Na 1- and Ca 21-dependent currents is likely to be activated by the hypersynchronous input. As to the mechanisms underlying the increased conductance during the “wave”-related hyperpolarization, two possible factors, that have repeatedly been invoked, should first be considered. (1) The GABAA-mediated inhibitory postsynaptic potential (IPSP) has a short duration in neocortical neurons. 1 In our experiments, recordings with KClfilled pipettes did not significantly affect the “wave”-related hyperpolarized phase of SW seizures. 32 The GABABmediated IPSP has a longer duration and, in this respect, would be a better candidate. However, including QX-314 (60 mM) in the recording pipette to block the G-proteincoupled GABAB-evoked K 1 current 5,11 did not significantly affect the hyperpolarization (data not shown). Together, these data suggest that GABA-mediated currents are not important for the hyperpolarization during these cortically generated seizures. (2) The other factor relates to different K 1 currents. 10,20,21 Recordings with Cs 1-filled pipettes to nonselectively block K 1 currents showed that, during the “wave” component of SW seizures, pyramidal neurons displayed depolarizing potentials. 32 Thus, at least some role is played by K 1 currents, most probably IK(Ca) because in recordings with pipettes filled with BAPTA (100 mM) the “wave”-related hyperpolarizations were reduced and the Rin increased (I. Timofeev, F. Grenier and M. Steriade, unpublished data). A third factor, disfacilitation, that may be responsible for the “wave”-related hyperpolarization is discussed below. The conductance changes observed during the two major components of the slow sleep oscillation 3 continued during the respective (depolarizing and hyperpolarizing) components of SW seizures (Figs 2–4). Furthermore, we observed that the conductance during the depolarization depended on the interval from the onset of the cellular depolarization (Fig. 5). Shorter intervals were associated with larger conductance values. We did not observe any increase in conductance towards the end of cellular depolarization, as expected if a shunting inhibitory conductance was central to ending
the depolarization and initiating the hyperpolarization. Corroborating the results from the analysis of the slow oscillation and evoked hyperpolarizations, 3 disfacilitation similarly seems to be the most important mechanism underlying the hyperpolarization during cortically generated SW seizures. Hyperpolarization due to disfacilitation has been described in spinal cord 15 and corticostriatal 4 neurons. The fact that the Rin decreased during the “wave”-related hyperpolarization of SW seizures, compared with the Rin during the hyperpolarizing phase of the slow sleep oscillation (see trace 1 in Fig. 4C), indicates that the hyperpolarizations during SW seizure are due to the combined effect of disfacilitation, which would increase the Rin, and some K 1 current, mainly IK(Ca), which would decrease the Rin. Conductance during fast runs During fast runs, which are observed in a variety of experimental conditions, 34 most neurons showed maximal depolarized Vm, sometimes to levels that caused inactivation of action potentials (Figs 2 and 8). Despite this, the conductance rarely reached the levels observed during the early part of the “spike”-related depolarization during SW complexes. This might be caused, at least in part, by a methodological problem. Since there were no periods with a stable Vm long enough to estimate the apparent Rin during the depolarized and repolarized phases of the fast runs, we used the method described in Fig. 6. Whereas the Rin probably varies during the cycle similarly to that observed during a depolarization (Fig. 5), the estimate given represents a mean value for a complete (approximately 100 ms) cycle. A second cause could be the reduction in postsynaptic potentials because some neurons were inactivated, and probably did not release neurotransmitters. Conductance during the postictal depression The EEG postictal depression was associated with a hyperpolarization in all recorded neurons and most of them did not generate action potentials in this period (Figs 1, 3), but some did (area 5 neuron in Fig. 8A). We have reported great reductions in excitatory responses to depolarizing current pulses during the postictal depression (see Fig. 13 in Ref. 25). Still, the decreased conductance relative to the seizure from the very onset of the postictal depression (Fig. 7) contradicts earlier ideas that the corresponding hyperpolarization is the result of an active inhibition that shunts all excitation. 7,14 Relation between preceding site and neuronal conductance In a previous paper, we have reported that various components of cortically generated seizures may be paced from different sites. 16 When two neurons were recorded simultaneously during a seizure, they often took turns preceding. This occurred even when the seizures were evoked by a local intervention such as the diffusion of bicuculline. In this paper, we show that the leading neuron had the largest increase in conductance (Fig. 8). This may be expected if the preceding neuron is the target of a more synchronous neuronal population generating more action potentials with synaptic transmitter release. The evolution of the amplitude of the depth-EEG suggests that whereas the neuronal population generating the paroxysmal activity in area 5 was maximally synchronized from the onset, the neuronal population in area
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7 was progressively synchronized (as judged by the gradual increase in depth-EEG amplitude). These results would support the idea that there is no fixed anatomical focus in these seizures, but that there is a continuous variation of the localization of the site that paces the activity, a kind of equivalent to the clinical Jacksonian march.
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Acknowledgements—We thank P. Gigue`re and D. Drolet for technical assistance. This work was supported by the Medical Research Council (Grant MT-3689) and the Human Frontier Science Program (Grant RG-81/96). D. Neckelmann and F. Amzica have been postdoctoral fellows partly supported by the Norwegian Research Council (D. Neckelmann) and the Fonds de recherche en sante´ du Que´bec (F. Amzica).
REFERENCES
1. Connors B. W., Malenka R. C. and Silva L. R. (1988) Two inhibitory postsynaptic potentials, and GABAA and GABAB receptor-mediated responses in neocortex of rat and cat. J. Physiol., Lond. 406, 443–468. 2. Contreras D. and Steriade M. (1995) Cellular basis of EEG slow rhythms: a study of dynamic corticothalamic relationships. J. Neurosci. 15, 604–622. 3. Contreras D., Timofeev I. and Steriade M. (1996) Mechanisms of long-lasting hyperpolarizations underlying slow sleep oscillations in cat corticothalamic networks. J. Physiol., Lond. 494, 251–264. 4. Cowan R. L. and Wilson C. J. (1994) Spontaneous firing patterns and axonal projections of single corticostriatal neurons in the rat medial agranular cortex. J. Neurophysiol. 71, 17–32. 5. Deisz R. A., Billard J. M. and Zieglga¨nsberger W. (1997) Presynaptic and postsynaptic GABAB receptors of neocortical neurons of the rat in vitro: differences in pharmacology and ionic mechanisms. Synapse 25, 62–72. 6. Destexhe A. (1998) Spike-and-wave oscillations based on the properties of GABAB receptors. J. Neurosci. 18, 9099–9111. 7. Efron R. (1961) Post-epileptic paralysis: theoretical critique and report of a case. Brain 84, 381–394. 8. Giaretta D., Avoli M. and Gloor P. (1987) Intracellular recordings in pericruciate neurons during spike and wave discharges of feline generalized penicillin epilepsy. Brain Res. 405, 68–79. 9. Gray C. M. and McCormick D. A. (1996) Chattering cells: superficial pyramidal neurons contributing to the generation of synchronous oscillations in the visual cortex. Science 274, 109–113. 10. Halliwell J. V. (1986) M-current in human neocortical neurones. Neurosci. Lett. 67, 1–6. 11. Jensen M. S., Cherubini E. and Yaari Y. (1993) Opponent effects of potassium on GABAA-mediated postsynaptic inhibition in the rat hippocampus. J. Neurophysiol. 69, 764–771. 12. Johnston D. and Brown T. H. (1981) Giant synaptic potential hypothesis for epileptiform activity. Science 211, 294–297. 13. Johnston D. and Brown T. H. (1984) The synaptic nature of the paroxysmal depolarizing shift in hippocampal neurons. Ann. Neurol. 16, Suppl., S65–S75. 14. Levy R. and O’Leary R. L. (1965) Arrest of seizure activity. Epilepsia 6, 116–121. 15. Llina´s R. R. (1964) Mechanisms of supraspinal action upon spinal cord activities. Differences between reticular and cerebellar inhibitory action upon alpha extensor motorneurones. J. Neurophysiol. 27, 1117–1126. 16. Neckelmann D., Amzica F. and Steriade M. (1998) Spike-wave complexes and fast components of cortically generated seizures. III. Synchronizing mechanisms. J. Neurophysiol. 80, 1480–1494. 17. Niedermeyer, E. (1998) Abnormal EEG patterns: epileptic and paroxysmal. In Electroencephalography: Basic Principles, Clinical Applications, and Related Fields (eds Niedermeyer E. and Lopes da Silva F.), pp. 235–260. Williams and Wilkins, Baltimore. 18. Oakley J. C., Sypert G. W. and Ward A. A. J. (1972) Conductance changes in neocortical propagated seizure: seizure initiation. Expl Neurol 37, 287–299. 19. Pollen D. A. (1964) Intracellular studies of cortical neurons during thalamic induced wave and spike. Electroenceph. clin. Neurophysiol. 17, 398–404. 20. Schwindt P. C., Spain W. J. and Crill W. E. (1989) Long-lasting reduction of excitability by a sodium-dependent potassium current in cat neocortical neurons. J. Neurophysiol. 61, 233–244. 21. Schwindt P. C., Spain W. J., Foehring R. C., Stafstrom C. E., Chubb M. C. and Crill W. E. (1988) Multiple potassium conductances and their functions in neurons from cat sensorimotor cortex in vitro. J. Neurophysiol. 59, 424–449. 22. Steriade M. (1974) Interneuronal epileptic discharges related to spike-and-wave cortical seizures in behaving monkeys. Electroenceph. clin. Neurophysiol. 37, 247–263. 23. Steriade M. and Amzica F. (1994) Dynamic coupling among neocortical neurons during evoked and spontaneous spike-wave seizure activity. J. Neurophysiol. 72, 2051–2069. 24. Steriade M. and Amzica F. (1999) Intracellular study of excitability in the seizure-prone neocortex in vivo. J. Neurophysiol. 82, 3108–3122. 25. Steriade M., Amzica F., Neckelmann D. and Timofeev I. (1998) Spike-wave complexes and fast components of cortically generated seizures. II. Extraand intracellular patterns. J. Neurophysiol. 80, 1456–1479. 26. Steriade M. and Contreras D. (1995) Relations between cortical and thalamic cellular events during transition from sleep patterns to paroxysmal activity. J. Neurosci. 15, 623–642. 27. Steriade M. and Contreras D. (1998) Spike-wave complexes and fast components of cortically generated seizures. I. Role of neocortex and thalamus. J. Neurophysiol. 80, 1439–1455. 28. Steriade M., Contreras D., Curro´ Dossi R. and Nun˜ez A. (1993) The slow (,1 Hz) oscillation in reticular thalamic and thalamocortical neurons: scenario of sleep rhythm generation in interacting thalamic and neocortical networks. J. Neurosci. 13, 3284–3299. 29. Steriade M., Nun˜ez A. and Amzica F. (1993) A novel slow (,1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components. J. Neurosci. 13, 3252–3265. 30. Steriade M., Nunez A. and Amzica F. (1993) Intracellular analysis of relations between the slow (,1 Hz) neocortical oscillation and other sleep rhythms of the electroencephalogram. J. Neurosci. 13, 3266–3283. 31. Steriade M., Timofeev I., Du¨rmu¨ller N. and Grenier F. (1998) Dynamic properties of corticothalamic neurons and local cortical interneurons generating fast rhythmic (30–40 Hz) spike bursts. J. Neurophysiol. 79, 483–490. 32. Steriade M., Timofeev I. and Grenier F. (1998) Inhibitory components of cortical spike-wave seizures in vivo. Soc. Neurosci. Abstr. 24, 2143. 33. Timofeev I., Grenier F. and Steriade M. (1998) Spike-wave complexes and fast components of cortically generated seizures. IV. Paroxysmal fast runs in cortical and thalamic neurons. J. Neurophysiol. 80, 1495–1513. 34. Traub R. D., Borck C., Colling S. B. and Jefferys J. G. R. (1996) On the structure of ictal events in vitro. Epilepsia 37, 879–891. 35. Weir B. (1965) The morphology of the spike-wave complex. Electroenceph. clin. Neurophysiol. 19, 284–290. (Accepted 29 November 1999)
Neuronal conductance during spike-wave seizures
Pergamon PII: S0306-4522(99)00571-0 www.elsevier.com/locate/neuroscience
CHANGES IN NEURONAL CONDUCTANCE DURING DIFFERENT COMPONENTS OF CORTICALLY GENERATED SPIKE-WAVE SEIZURES D. NECKELMANN, F. AMZICA and M. STERIADE* Laboratoire de Neurophysiologie, Faculte´ de Me´decine, Universite´ Laval, Que´bec, Canada G1K 7P4
Abstract—Neuronal conductance was studied in anesthetized cats during cortically generated spike-wave seizures arising from slow sleep oscillation. Single and dual intracellular recordings from neocortical neurons were used. The changes were similar whether the seizures occurred spontaneously, or were evoked by electrical stimulation or induced by bicuculline. In all seizures, the conductance increased from the very onset of the seizure and returned to control values only at the end of the postictal depression. Simultaneous intracellular recordings from two neurons showed that the neuron leading the other neuron displayed the largest increase in membrane conductance. The changes in neuronal conductance during the two phases of the slow sleep oscillation, i.e. highest during depolarizations and lowest during hyperpolarizations, were similar to those occurring during the “spike” and “wave” components of seizures. (1) Maximal conductance was found during the paroxysmal depolarizing shift corresponding to the electroencephalogram “spike” (median: 252 nS; range: 90 to more than 400 nS). It was highest at the onset of the depolarized plateau and decreased thereafter. (2) During the hyperpolarization corresponding to the electroencephalogram “wave”, the conductance was significantly lower (median: 71 nS; range: 41 to 140 nS). (3) The conductance was elevated during the fast runs (median: 230 nS; range: 92 to 350 nS) which occurred in two-thirds of the seizures. (4) The conductance values during postictal depression were situated between those measured during the seizure hyperpolarizations and during sleep hyperpolarizations. The conductance decreased exponentially back to the values of the slow sleep oscillation over the total duration of the postictal depression. The data suggest that the major mechanism underlying the “wave”-related hyperpolarizing component of spike-wave seizures relies mainly not on active inhibition, but on a mixture of disfacilitation and potassium currents. q 2000 IBRO. Published by Elsevier Science Ltd. Key words: cat, neocortex, intracellular, conductance, spike-wave seizures, slow sleep oscillation.
The spike-wave (SW) pattern is an electroencephalographic (EEG) manifestation of seizures in some epileptic syndromes 17,35 and is also seen in animal models of epilepsy. Recently, cortically generated seizures with SW or polyspike (PSW) complexes (1.5–3 Hz) and fast runs (10–15 Hz) have been described, using extra- and intracellular recordings in behaving and anesthetized cats. 25 Such seizures develop without discontinuity from sleep patterns, 23,25,26 particularly from a slow oscillation generated in neocortex. 28–30 The neocortex is the minimal necessary substrate for the expression of these seizures as they can occur in the absence of the thalamus 27 and in isolated cortical slabs, 33 and they are primarily synchronized through intracortical connections. 16 During the EEG “spike” component cortical neurons are depolarized and fire briskly, whereas neurons are hyperpolarized and silent during the EEG “wave”. 19,22 The depolarization associated with the EEG “spike” is thought to be a giant postsynaptic potential, 12,13 termed paroxysmal depolarizing shift (PDS). It has been suggested that the cellular hyperpolarization associated with the EEG “wave” component is mainly mediated by inhibitory conductances 19 and that the intracellular correlate of the initial 40–80 ms of this component is Cl 2 dependent, presumably mediated by GABAA receptors. 8 A recent model 6 suggested that GABAB-mediated K 1 currents produce SW oscillations. These hypotheses have
in common the idea that the neuronal hyperpolarization is caused by a GABAergic mechanism. The main mechanism underlying the hyperpolarization phase of the slow sleep oscillation is disfacilitation and the apparent input resistance (Rin) is highest during this phase. 3 Thus, since SW seizures develop without discontinuity from the slow sleep oscillation, and the intracellular counterparts of SW complexes are related to field potentials in a similar way as the depolarizing–hyperpolarizing phases of the slow oscillation, 25 we hypothesized that disfacilitation, rather than a highly increased inhibitory conductance, may play a major role in the neuronal hyperpolarizations during SW complexes. To study the evolution of the membrane input conductance, we took intracellular recordings from neurons in anesthetized cats during the slow oscillation and its development to SW seizures, and we also induced such seizures by electrical stimulation or using the GABAA antagonist bicuculline. EXPERIMENTAL PROCEDURES
Fifty-two cats were anesthetized with ketamine and xylazine (10– 15 mg/kg and 2–3 mg/kg, respectively). All tissues to be incised were infiltrated with lidocaine. The depth of anesthesia was monitored by continuous EEG recording. Supplementary doses of ketamine and xylazine (3–4 mg/kg and 0.6–0.8 mg/kg, respectively) were administered at the slightest change towards an activated state expressed by diminished amplitudes and increased frequencies of the EEG. Heart rate (acceptable range 90–110 beats/min) and temperature (36–398C) were monitored. When deep anesthesia was reached and a sleep-like pattern was present in the EEG, a muscle relaxant (gallamine triethiodide) was administered, and the animal was mounted in a stereotactic frame and artificially ventilated under control of end-tidal CO2 (3.5–3.8%). The stability of the recordings was improved by drainage of cisterna magna, hip suspension, bilateral pneumothorax, and by filling the hole made for recordings with a solution of 4% agar.
*To whom correspondence should be addressed. Abbreviations: AHP, spike after-hyperpolarization; EEG, electroencephalogram; FRB, fast-rhythmic-bursting neuron; IPSP, inhibitory postsynaptic potential; PDS, paroxysmal depolarizing shift; PID, post-ictal depression; PSW, polyspike-wave; Rin, apparent input resistance; SW, spike-wave; Vm, membrane potential. 475
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To compensate for fluid loss, 20–30 ml saline was given intravenously during the experiments, which lasted for 8–12 h. Field potential recordings were made with coaxial electrodes placed with the ring at the cortical surface and the tip at 0.8–1 mm in the cortical depth of suprasylvian areas 5, 7 and 21. Coaxial recording electrodes were also inserted into the thalamic intralaminar central lateral and lateral posterior nuclei. Field potentials were also recorded by tungsten microelectrodes (3–8 MV) inserted at different depths of various cortical areas. Single or dual simultaneous intracellular recordings in suprasylvian areas 5 and 7 were made with glass micropipettes filled with 3 M potassium acetate (d.c. resistance 25–45 MV). A high-impedance dual amplifier with active bridge circuitry was used to record and inject current into the neurons. The bridge was continuously monitored and adjusted when necessary. The signals were band-pass filtered (0– 9 kHz), digitized at 20 kHz and stored on an eight-channel tape recorder for off-line analysis. In addition to spontaneously occurring seizures during sleep-like patterns, we induced paroxysmal activities by electrically stimulating cortical or appropriate thalamic nuclei, or by inserting a Hamilton syringe filled with 10 ml of a 0.2 mM solution of bicuculline in saline in the rostral part of area 5. The syringe content was not injected, but some of the bicuculline diffused slowly into the cortex. 25 Square current pulses (0.5–2 nA; 30–200 ms) were injected into the neurons through the recording pipette at regular intervals during seizures. By measuring the change in Vm, the apparent neuronal input resistance (Rin) could be calculated using Ohm’s law (Rin DVm/I), where I is injected current. Cellular conductance is G 1/Rin. Only representative responses were used in the analysis, to avoid spurious variations (e.g., when spontaneous activity was superimposed over the charging curve; see the 4th pulse in Fig. 2B2, where a paroxysmal depolarization started during a current pulse). However, each pulse was visually examined to see whether or not the result was influenced by prominent spontaneous activity. At the end of the experiments, the cats were given a lethal dose of intravenous pentobarbital sodium followed by 10% formaldehyde. The location of stimulating and recording electrodes was verified on 80-mm sections stained with Thionine. RESULTS
Intracellular recordings with stable resting membrane potential (Vm) more negative than 255 mV and overshooting action potentials were obtained from 221 cortical neurons. In 160 seizures we recorded intracellularly from two neurons simultaneously (48 cell couples). In 98 neurons we recorded conductance tests during both the slow oscillation and seizures. Spontaneously occurring seizures Figure 1 shows a typical seizure developing spontaneously and without discontinuity from the slow sleep-like oscillation. At the EEG level, the slow oscillation consists of long-lasting depth-positive waves followed by prolonged depth-negative waves, repeated at a frequency of < 0.8 Hz. During the depth-positive EEG waves cortical neurons were hyperpolarized, whereas during the depth-negative wave neurons were depolarized. 2 In Fig. 1, the recorded neuron was identified by depolarizing current pulses as a fast-rhythmic-bursting (FRB) neuron 9,31 and it displayed pronounced changes in its activity pattern before a seizure was apparent in the depth-EEG recorded close to the cell (pre-seizure panel in Fig. 1). A leading role of FRB neurons in the generation of SW/PSW seizures has been proposed. 25 The slope as well as the amplitude of the shift in Vm from hyperpolarized to depolarized levels increased. The shift from depolarized to hyperpolarized Vm levels was also steeper. The amplitudes of Vm changes increased because the neuron reached a more hyperpolarized neuronal Vm during the EEG positivity and a more depolarized
Vm during the EEG negativity. At this stage, the shape of the action potentials and the fast after-hyperpolarization (AHP) remained unchanged. During the part of the seizure characterized by SW/PSW complexes, the action potentials were partially inactivated and the AHP disappeared. The fast run period was characterized by EEG “spikes” at 10–20 Hz and, at the neuronal level, a tonically depolarized Vm with smaller depolarizations superimposed. The end of the seizure was associated with a short period of hyperpolarization, followed by a resumption of the slow oscillation. Dynamic evolution of conductance changes during seizures Figure 2 shows a spontaneously occurring seizure recorded in area 7 of the suprasylvian gyrus. The seizure had a duration of around 60 s and developed from the slow oscillation (see extreme left part in the figure). Hyperpolarizing current pulses were injected throughout the period shown. Below the intracellular trace the estimated conductance values are plotted coded according to the type of neuronal activity when the current pulse was injected (see legend). The conductance increased from the onset of the seizure. This pattern was observed in all 221 recorded cortical neurons. However, there was considerable variation in the measured conductance. Some of this variation was due to whether the current pulse was injected during a hyperpolarized or depolarized state of the neuron. In Fig. 2, the left part of panels A and B1 show variation of conductance during the slow oscillation, with increased Rin during the hyperpolarization related to the depth-EEG positive wave and decreased Rin during the depolarization related to the depth-EEG negative wave (see also Ref. 3). As the SW pattern developed (B2), there was a gradual increase in conductance during both the depolarizations (“spikes”) and hyperpolarizations (“waves”). During the period with fast runs (B3), the neuron was depolarized to Vms that caused inactivation of action potentials. During the fast runs, the conductance was increased relative to the hyperpolarized phase of the SW seizure, but did not reach the maximal increase observed during the depolarized phase (see below and Discussion). During the following SW pattern and the postictal depression, the conductance gradually decreased to the control values. Seizures could be evoked by pulse-trains applied to the suprasylvian gyrus. In Fig. 3A, three pulse-trains were applied to area 5 (arrowheads) and the neuron as well as field potentials were recorded in the vicinity. The changes in conductance were similar to the spontaneous seizures, as can be seen in details 1–4 from panel A. Panel B shows a seizure evoked by bicuculline diffusion. The activity pattern consisted of periods of interictal depression alternating with seizures of 40–180 s duration. Below the intracellular trace the estimated conductance values are plotted, coded according to the type of cellular activity (depolarizations and hyperpolarizations during SW complexes, and fast runs, as indicated by symbols). A gradual increase in cellular conductance preceded the start of the seizure (left part) and was most pronounced during the depolarizations. During the seizure the conductance remained high, and then gradually returned to the initial values during the interictal period. Thus, a similar dynamic evolution of the cellular conductance was observed in spontaneously occurring seizures and in seizures evoked by electrical stimulation or bicuculline
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Fig. 1. Spontaneously occurring seizure developing without discontinuity from the slow sleep-like oscillation. Intracellular recording from area 5 fastrhythmic-bursting (FRB) neuron together with depth-EEG from the vicinity in area 5. Seizure is indicated by arrows. Detail 1 shows typical activity during slow oscillation. During 2 there are clear pre-seizure changes in the activity of the cell, whereas the depth-EEG is not significantly altered. Detail 3 shows typical SW complexes at around 2 Hz in the depth-EEG. The cell displayed high-frequency spike-bursts, with an intraburst frequency of 300–600 Hz. The fourth depth-negativity in the EEG had a polyspike-wave pattern, similar to the start of the fast run, depicted in 4; the cell also displayed high-frequency spikebursts during the fast runs and remained tonically depolarized in this period. The Vm is indicated with an arrow.
diffusion. There were no systematic differences in the observed magnitude of the conductance changes. In the following, we will report the results for all seizures together, without considering how they were evoked. Membrane conductance during the slow oscillation compared with spike-wave seizures Figure 4 shows the variations in conductance during the two main (depolarizing and hyperpolarizing) components of the slow oscillation and during the two (“spike”-related depolarization and “wave”-related hyperpolarization) components of a SW seizure. Square hyperpolarizing pulses of 60 ms and 0.5 nA were injected every 100 ms (A). During the slow oscillation three distinct phases in the
EEG could be discerned: the depth-positive EEG wave (1), the depth-negative EEG wave (2), and a phase of varying duration (marked by asterisk in panel B), with low amplitude fast frequency activity, preceding the next depthpositive EEG wave. The responses to 20 hyperpolarizing pulses delivered during each of these three phases were averaged (C). Similarly to the results from a previous study, 3 we found the conductance to be smallest during the depth-positive wave (in this neuron: 36 nS; observed range in recorded neurons: 19–74 nS), maximal during the depth-negative wave (in this neuron: 54 nS; observed range: 36–120 nS), and intermediate during the period preceding the depth-positive wave (in this neuron: 42 nS). At the level of 98 neurons, the conductance decreased by 36% during the depth-positive phase with respect to the
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Fig. 2. Conductance changes during spontaneously occurring seizure. (A) Intracellular recording from area 7 neuron together with depth-EEG from the vicinity in area 7. During this period, square current pulses of 1 nA amplitude and 50 ms duration were injected through the recording pipette every 200 ms. The estimated conductance is plotted below at the corresponding time-point (Conductance). The values are coded according to the type of cellular activity at the time of the pulse. Conductance values from pulses that were delivered during the depolarized phase of the slow oscillation or the depolarized phase of the paroxysmal activity are plotted as crosses ( 1 ). Values from pulses that were delivered during the hyperpolarized phase of the slow oscillation or hyperpolarized phase of the paroxysmal activity are plotted as dots (.). Values from pulses during the fast runs (where the duration of the hyperpolarized and depolarized phase are too short to allow for a separate estimation of the two) are plotted as open triangles. For the method used to estimate apparent cellular input resistance during fast runs, see Fig. 6. (B1–B3) show details from slow oscillation, SW seizure, and fast run. The detail below shows a superimposition of a pulse from slow oscillation and a pulse from the SW seizure. In A, the Vm is indicated with an arrow.
intermediate epoch, while it increased by 20% during the depth-negative phase. The SW seizure depicted in the right column of Fig. 4 occurred spontaneously in the same neuron, 6 min later. We averaged the responses to 20 pulses from the depth-positive EEG phase corresponding to the “wave” (1) and from the depth-negative EEG wave corresponding to the “spike” (2). The conductance was increased relative to the respective phase of the slow oscillation. During the depth-positive “wave” component the conductance was 45 nS (observed range 41–140 nS; median: 71 nS), while it increased to 144 nS during the depth-negative “spike” (observed range: 90– .400 nS; median 252 nS). Within the depth-negative “spike” component, there was a considerable variation in the observed conductance over a short period of time, the conductance depending on the interval from the onset of the cellular depolarization to the start of the hyperpolarizing
pulse (Fig. 5). Shorter intervals were associated with larger conductance values. Indeed, when the intervals were very short, no precise estimates could be made of the conductance, because the voltage deflection was too small relative to the spontaneous variation in Vm. We measured the conductance during SW seizures in a sample of 98 neurons. During the “wave” component, the mean conductance was 78.4 nS (S.D. 28.8), while during the “spike” component, the mean conductance was 245.7 (S.D. 75.6). Cellular conductance during fast runs During the fast runs, the continuously fluctuating Vm made it difficult to directly measure a voltage deflection; also, we could not estimate conductance for the hyperpolarized and depolarized phases of fast runs separately. Figure 6 shows
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Fig. 3. Seizures induced by electrical stimulation (A) and bicuculline diffusion (B) show similar patterns of changes in membrane conductance. Both panels show intracellular recording from a neuron in area 5b together with depth-EEG from the vicinity. Panel A illustrates a seizure evoked by three trains of 200 pulses at 100 Hz to cortical area 5a. Square current pulses of 1 nA amplitude and 30 ms duration were injected through the recording pipette every 100 ms. A1 shows a detail from the preceding slow oscillation. A2 shows the cellular monosynaptic response to the cortical stimuli at 100 Hz. A3 shows a detail from the SW part of the evoked seizure. A4 shows a detail from the fast runs. Vm of 270 mV is indicated in all panels. Panel B shows a seizure resulting from the insertion of a syringe with 10 ml 0.2 mM bicuculline in area 5a. The neuron and field potentials were recorded in area 5b. Several hours after the insertion of the syringe, the activity pattern of the brain consisted of paroxysms separated by periods of interictal depression. Square current pulses of 1 nA amplitude and 50 ms duration were injected though the recording pipette every 200 ms. The calculated conductance values are plotted below at the corresponding time-point (Conductance). They are coded according to the type of cellular activity at the time of the pulse as explained in the legend of Fig. 2. The Vm is indicated with an arrow.
the cellular response to square current pulses (1 nA, 100 ms) injected through the recording pipette every 200 ms during a fast run. In A, the responses to 10 pulses that had an onset during the first half of an oscillation cycle after a nadir were aligned at the time of the pulse (see current monitor below). To estimate the mean conductance during the fast runs we realigned these responses at the time and the Vm of the nadir preceding the pulse (B, arrows). Since the mean Vms of the preceding and following nadir were equal, we may assume that the observed shift in mean Vm in the intervening nadir was caused by the current pulses. There was no consistent relationship between the time since the onset of the current
pulse and the observed Vm of the intervening nadir; hence, the time-constant was short enough to allow the average apparent Rin to be estimated in this way (5.9 MV, corresponding to a cellular conductance of 169 nS; observed range in recorded neurons: 92–350 nS). The bottom panel in Fig. 6 shows a comparison of the averaged responses (n 20) in this cell during the hyperpolarized phase of the slow oscillation (1), and during the “wave” (2) and “spike” (3) components of a SW seizure. Apparent cellular conductances were 62, 104 and 222 nS, respectively. We measured the mean conductance during the fast runs of SW seizures in a sample of 40 neurons (out of those 98 that
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Fig. 4. Neuronal conductance increases during the SW seizure, compared with the slow sleep-like oscillation. Intracellular recording from an area 5 neuron together with depth-EEG from the vicinity in area 5. (A) Square current pulses of 0.5 nA amplitude and 60 ms duration were injected through the recording pipette every 100 ms during slow oscillation (left) and during a spontaneous SW seizure, 6 min later (right). (B) Superimposition of averaged fragments of the EEG, extracted around the times when the pulses were applied during slow oscillation (left), and SW seizure (right). The fragments were positioned to create averaged oscillation cycles. (C) Left column: 20 pulses were averaged from each of the three phases of the slow oscillation (1: the EEG depth-positive phase associated with the cell’s hyperpolarization; 2: the EEG depth-negative phase associated with cellular depolarization; and *: the relatively stable period, intermediate level, that separated each positive–negative cycle). C, Right column: 20 pulses were averaged (1: the “wave” associated with cellular hyperpolarization; and 2: the “spike” associated with cellular depolarization during the SW seizure). The conductance was increased during SW seizures compared with the slow oscillation. This was true both for the hyperpolarized (1) and depolarized (2) phases.
served for conductance measure during the “spike” and “wave” components; see above) and found it to be 226.5 nS (S.D. 69.2). Cellular conductance during postictal and interictal depression Figure 7 shows how cellular conductance decreased from the last part of a seizure through the interictal depression. In A responses from the hyperpolarized phase of the seizure (1) and the early phase of the interictal depression (2–4) illustrate that the membrane conductance during the interictal depression is lower than the observed values during the hyperpolarizing phases of the preceding SW complexes. In B the measured conductance in four different neurons during
postictal depression is plotted normalized in time (expressed as per cent duration of the postictal depression) and conductance (expressed as per cent of the observed conductance during the hyperpolarizing phase of the slow oscillation). The magnitude and evolution are similar to those observed during interictal depression. The solid line represents an exponential model, which provided the best fit in the majority of neurons. Dynamic changes of cellular conductance in simultaneously recorded neurons The time relations between simultaneously recorded neurons can vary during a seizure. 16 Figure 8A depicts a dual simultaneous intracellular recording from areas 5 and
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Fig. 5. The apparent cellular conductance during a paroxysmal depolarization depended on the time since the onset of the depolarization. Intracellular recording from a regular-spiking area 5 neuron. Square current pulses of 1 nA amplitude and 30 ms duration were injected through the recording pipette every 100 ms Left: five pulses delivered at different times since the onset of a paroxsysmal depolarizing shift (PDS). They are aligned at the time of the pulse. Right: a plot of calculated cellular conductance versus time since the onset of PDS ( 1 ) and the exponential fit (dotted line).
7. The neuron recorded in area 5 generated spikes tonically during most of the interictal depression which was apparent in the depth-EEG. The neuron in area 7 depolarized the most during the seizure, and its action potentials were inactivated during the fast run. The time relation between the two cells is illustrated below, throughout the seizure. The neuron in area 5 preceded the neuron in area 7 early in the seizure (see 1, lines upwards). Later (2–3), the area 7 neuron preceded the area 5
neuron (lines downwards). The time lags displayed here were calculated between the onset of corresponding depolarizations (PDSs) in the two neurons, as explained in the legend. Expanded details of responses to hyperpolarizing pulses during the three epochs (1–3) are provided in panel B. To compare the dynamic changes of time-relations to the changes in conductance, square current pulses (50 ms, 1 nA, every 200 ms) were injected simultaneously in both neurons.
Fig. 6. Estimation of apparent cellular conductance during fast runs. Intracellular recording from an area 5 neuron. Square current pulses of 1 nA amplitude and 100 ms duration were injected through the recording pipette every 200 ms. The fast runs ( < 10–15 Hz) showed a continuously fluctuating Vm which made it difficult to directly measure apparent input resistance. This is seen in (A), where 10 traces that had a current pulse onset during the first half of an oscillation cycle after a nadir are aligned on the time of the pulse (see current monitor below). To overcome this problem, the traces were realigned (B) at the time and Vm of the nadir preceding the pulse (arrows). Since the mean Vms of the preceding and following nadir are equal, it can be assumed that the observed shift in mean Vm in the intervening nadir was caused by the current pulses. Since there was no consistent relationship between time since onset of pulse and the observed Vm of the intervening nadir, we can assume that the time constant was short enough to allow the average apparent cellular input resistance to be estimated in this way (5.9 MV, thus apparent cellular conductance was 169 nS). In the detail below, there is a superimposition of the averaged cellular responses (n 20) in this cell during the hyperpolarized phase of slow oscillation (1), and during the hyperpolarized (2) and the depolarized (3) phase of a SW seizure. Apparent cellular conductances were 62, 104 and 222 nS, respectively.
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Fig. 7. Membrane conductance decreased during the postictal depression (PID). Intracellular recording from area 5 neuron together with depth-EEG from the vicinity in area 5. The activity pattern was evoked by bicuculline diffusion, and consisted of paroxysms separated by periods of interictal depression. Square current pulses of 1 nA amplitude and 50 ms duration were injected through the recording pipette every 200 ms. The Vm is indicated with an arrow. (A) Pulse 1 is from the SW part of the seizure and pulses 2, 3 and 4 are from the PID, as indicated in the upper panel. It was an exponential decrease in apparent cellular conductance from the high levels observed during the last hyperpolarized phases of the SW seizure during the entire PID. To compare this decrease across several different cells, we have plotted the normalized conductance values from four cells in panel B. The conductance values are expressed as per cent of the observed conductance during the hyperpolarized phase of the slow oscillation in each cell. Since the duration of the PID varied both across and within animals, we used per cent duration of the PID as ordinate, rather than seconds. The line shows an exponential fit.
The ratio between the measured conductances of the two neurons was calculated for each pulse and plotted at the corresponding time (see Conductance ratio in panel A). In this analysis, we only included the pulses that were injected during the hyperpolarized component of the SW seizure and during the fast runs. The dotted line represents the ratio between the two neurons at the endpoint of the postictal depression (PID) following the seizure. There was a parallel evolution in the time-relation and conductance ratio. Initially, when the neuron in area 5 preceded (1), this neuron showed the largest increase in conductance. Later, as the neuron in area 7 started to preceed (2), its conductance increased. A detail from two pulses during the period where the area 5 neuron preceded is shown in B1 (taken from the period marked 1 in panel A). Later, the neuron in area 7 preceded (B2). The conductance in the area 7 neuron increased, while it was not changed in the area 5 neuron. During the fast run (B3) the area 7 neuron also preceded, and while the single responses to the current pulses were difficult to assess, the averages of realigned pulses (according to the method explained in Fig. 6) showed that the area 7 neuron had a larger conductance than the area 5 neuron (see C3). Averages of eight representative responses from each period (1–3) are shown in panel C. These aspects have also been found in other 37 dual intracellular recordings.
DISCUSSION
The intracellular and field potentials during the complex SW/PSW seizures described herein bear a striking resemblance to EEG records in some epileptic patients and we therefore postulate that the electrophysiological mechanisms of these cortically generated paroxysms are similar to those occurring in humans. The major findings from the present experiments are as follows. (1) The conductance increased at the onset of the seizure, and returned to control values only at the end of the postictal depression. (2) The fluctuation in conductance during the slow sleep oscillation, with minimal conductance during the hyperpolarization corresponding to the depth-positive EEG wave and maximal conductance during the depolarization corresponding to the depth-negative EEG wave, continued during the “spike” and “wave” components of SW complexes of seizures. During the depolarizing plateau corresponding to the EEG “spike”, the conductance was maximal close to the onset of the depolarization, and decayed thereafter. (3) The conductance was also highly elevated during the fast runs. (4) During the postictal depression, the conductance slowly returned to control values at the time when normal activity in the neuron and network resumed. (5) With dual simultaneous intracellular recordings which displayed time-lags, the neuron that preceded during the seizure also showed the largest increase in conductance.
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Fig. 8. Time-relation and conductance ratio between two simultaneously recorded neurons covaried during seizures. Seizure evoked by insertion of a syringe with 10 ml 0.2 mM bicuculline in area 5. (A) For each cell and each depolarizing complex we selected the time-point of the steepest slope of the Vm (highest dVm/dt). We subtracted the time-point of the area 5 cell from the corresponding time-point of the area 7 cell, and plotted the resulting time lag along the ordinate as a line starting from 0 (see calibration bar from 0 to 20 ms at the extreme right). The lines are plotted at the time point of the area 7 neuron. Throughout the seizure square current pulses of 1 nA amplitude and 50 ms duration were injected through the recording pipettes every 200 ms in both neurons. The Conductance ratio between the two neurons (conductance of area 5 neuron divided by the conductance of area 7 neuron) during the cellular hyperpolarizations were plotted ( 1 ). In B, details from two pulses during the period where the neuron in area 5 preceded is shown in 1 (taken from the period marked 1 in A). Only the first pulse (during the hyperpolarization) was included in the analysis displayed in A. Later, the neuron in area 7 preceded (2). Whereas the conductance in the area 7 neuron increased, conductance remained unchanged in the area 5 neuron. During the fast runs, the individual pulses are difficult to assess, but the averages of realigned pulses (according to the method explained in Fig. 6) show that the conductance of the area 7 neuron was larger. (C) Averages of eight representative responses from each period (1–3).
Transition from sleep patterns to seizure: increased conductance during the seizure The high incidence of seizures under the experimental condition was reported and explained in a previous paper. 25 In brief, it is due to the hypersynchronization of corticothalamic activity during the sleep-like patterns produced by ketamine–xylazine anesthesia. The present data derived from only those cats that displayed paroxysms.
The cortically generated seizures arise without discontinuity from the slow sleep oscillation. 16,23,25,26 The relations between intracellular and field potentials activities are practically identical during sleep patterns and seizures, with the difference that the amplitude of the depth-EEG sharp negativity (the K-complex) during the slow sleep oscillation is increased to become a paroxysmal “spike” and the oscillatory frequency increases from less than 1 Hz during the slow oscillation to 2–4 Hz during SW/PSW seizures. 25 The variable
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duration of the “spike” (from < 70 ms to as long as 200– 250 ms) is accounted for by the history of the network. Indeed, the relative refractoriness of the “spike” explains why, when preceded by spontaneously occurring paroxysmal depolarizations, the duration of the “spike” is dramatically reduced (see Fig. 5 in Ref. 24). The conductance increased gradually in the period immediately preceding the onset of a seizure. There was no clear discontinuity in the conductance values during the transition from the slow oscillation to seizure. This stands in contrast to the idea 18 that there is a critical threshold conductance value for seizure development. The preceding increase in conductance was most pronounced during the depolarizations (see Fig. 3B). In the transition period from the slow oscillation to seizures, the amplitude of the depolarizing component of the slow oscillation increased, as did the number of action potentials per depolarization. The slope and amplitude of the shift in Vm from hyperpolarized to depolarized levels increased, and the neuron reached a more depolarized Vm during the depthnegative EEG “spike”. 25 Such changes in cellular activity patterns in a population are associated with increased postsynaptic potentials, both excitatory and inhibitory, and a series of voltage-gated as well as Na 1- and Ca 21-dependent currents is likely to be activated by the hypersynchronous input. As to the mechanisms underlying the increased conductance during the “wave”-related hyperpolarization, two possible factors, that have repeatedly been invoked, should first be considered. (1) The GABAA-mediated inhibitory postsynaptic potential (IPSP) has a short duration in neocortical neurons. 1 In our experiments, recordings with KClfilled pipettes did not significantly affect the “wave”-related hyperpolarized phase of SW seizures. 32 The GABABmediated IPSP has a longer duration and, in this respect, would be a better candidate. However, including QX-314 (60 mM) in the recording pipette to block the G-proteincoupled GABAB-evoked K 1 current 5,11 did not significantly affect the hyperpolarization (data not shown). Together, these data suggest that GABA-mediated currents are not important for the hyperpolarization during these cortically generated seizures. (2) The other factor relates to different K 1 currents. 10,20,21 Recordings with Cs 1-filled pipettes to nonselectively block K 1 currents showed that, during the “wave” component of SW seizures, pyramidal neurons displayed depolarizing potentials. 32 Thus, at least some role is played by K 1 currents, most probably IK(Ca) because in recordings with pipettes filled with BAPTA (100 mM) the “wave”-related hyperpolarizations were reduced and the Rin increased (I. Timofeev, F. Grenier and M. Steriade, unpublished data). A third factor, disfacilitation, that may be responsible for the “wave”-related hyperpolarization is discussed below. The conductance changes observed during the two major components of the slow sleep oscillation 3 continued during the respective (depolarizing and hyperpolarizing) components of SW seizures (Figs 2–4). Furthermore, we observed that the conductance during the depolarization depended on the interval from the onset of the cellular depolarization (Fig. 5). Shorter intervals were associated with larger conductance values. We did not observe any increase in conductance towards the end of cellular depolarization, as expected if a shunting inhibitory conductance was central to ending
the depolarization and initiating the hyperpolarization. Corroborating the results from the analysis of the slow oscillation and evoked hyperpolarizations, 3 disfacilitation similarly seems to be the most important mechanism underlying the hyperpolarization during cortically generated SW seizures. Hyperpolarization due to disfacilitation has been described in spinal cord 15 and corticostriatal 4 neurons. The fact that the Rin decreased during the “wave”-related hyperpolarization of SW seizures, compared with the Rin during the hyperpolarizing phase of the slow sleep oscillation (see trace 1 in Fig. 4C), indicates that the hyperpolarizations during SW seizure are due to the combined effect of disfacilitation, which would increase the Rin, and some K 1 current, mainly IK(Ca), which would decrease the Rin. Conductance during fast runs During fast runs, which are observed in a variety of experimental conditions, 34 most neurons showed maximal depolarized Vm, sometimes to levels that caused inactivation of action potentials (Figs 2 and 8). Despite this, the conductance rarely reached the levels observed during the early part of the “spike”-related depolarization during SW complexes. This might be caused, at least in part, by a methodological problem. Since there were no periods with a stable Vm long enough to estimate the apparent Rin during the depolarized and repolarized phases of the fast runs, we used the method described in Fig. 6. Whereas the Rin probably varies during the cycle similarly to that observed during a depolarization (Fig. 5), the estimate given represents a mean value for a complete (approximately 100 ms) cycle. A second cause could be the reduction in postsynaptic potentials because some neurons were inactivated, and probably did not release neurotransmitters. Conductance during the postictal depression The EEG postictal depression was associated with a hyperpolarization in all recorded neurons and most of them did not generate action potentials in this period (Figs 1, 3), but some did (area 5 neuron in Fig. 8A). We have reported great reductions in excitatory responses to depolarizing current pulses during the postictal depression (see Fig. 13 in Ref. 25). Still, the decreased conductance relative to the seizure from the very onset of the postictal depression (Fig. 7) contradicts earlier ideas that the corresponding hyperpolarization is the result of an active inhibition that shunts all excitation. 7,14 Relation between preceding site and neuronal conductance In a previous paper, we have reported that various components of cortically generated seizures may be paced from different sites. 16 When two neurons were recorded simultaneously during a seizure, they often took turns preceding. This occurred even when the seizures were evoked by a local intervention such as the diffusion of bicuculline. In this paper, we show that the leading neuron had the largest increase in conductance (Fig. 8). This may be expected if the preceding neuron is the target of a more synchronous neuronal population generating more action potentials with synaptic transmitter release. The evolution of the amplitude of the depth-EEG suggests that whereas the neuronal population generating the paroxysmal activity in area 5 was maximally synchronized from the onset, the neuronal population in area
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7 was progressively synchronized (as judged by the gradual increase in depth-EEG amplitude). These results would support the idea that there is no fixed anatomical focus in these seizures, but that there is a continuous variation of the localization of the site that paces the activity, a kind of equivalent to the clinical Jacksonian march.
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Acknowledgements—We thank P. Gigue`re and D. Drolet for technical assistance. This work was supported by the Medical Research Council (Grant MT-3689) and the Human Frontier Science Program (Grant RG-81/96). D. Neckelmann and F. Amzica have been postdoctoral fellows partly supported by the Norwegian Research Council (D. Neckelmann) and the Fonds de recherche en sante´ du Que´bec (F. Amzica).
REFERENCES
1. Connors B. W., Malenka R. C. and Silva L. R. (1988) Two inhibitory postsynaptic potentials, and GABAA and GABAB receptor-mediated responses in neocortex of rat and cat. J. Physiol., Lond. 406, 443–468. 2. Contreras D. and Steriade M. (1995) Cellular basis of EEG slow rhythms: a study of dynamic corticothalamic relationships. J. Neurosci. 15, 604–622. 3. Contreras D., Timofeev I. and Steriade M. (1996) Mechanisms of long-lasting hyperpolarizations underlying slow sleep oscillations in cat corticothalamic networks. J. Physiol., Lond. 494, 251–264. 4. Cowan R. L. and Wilson C. J. (1994) Spontaneous firing patterns and axonal projections of single corticostriatal neurons in the rat medial agranular cortex. J. Neurophysiol. 71, 17–32. 5. Deisz R. A., Billard J. M. and Zieglga¨nsberger W. (1997) Presynaptic and postsynaptic GABAB receptors of neocortical neurons of the rat in vitro: differences in pharmacology and ionic mechanisms. Synapse 25, 62–72. 6. Destexhe A. (1998) Spike-and-wave oscillations based on the properties of GABAB receptors. J. Neurosci. 18, 9099–9111. 7. Efron R. (1961) Post-epileptic paralysis: theoretical critique and report of a case. Brain 84, 381–394. 8. Giaretta D., Avoli M. and Gloor P. (1987) Intracellular recordings in pericruciate neurons during spike and wave discharges of feline generalized penicillin epilepsy. Brain Res. 405, 68–79. 9. Gray C. M. and McCormick D. A. (1996) Chattering cells: superficial pyramidal neurons contributing to the generation of synchronous oscillations in the visual cortex. Science 274, 109–113. 10. Halliwell J. V. (1986) M-current in human neocortical neurones. Neurosci. Lett. 67, 1–6. 11. Jensen M. S., Cherubini E. and Yaari Y. (1993) Opponent effects of potassium on GABAA-mediated postsynaptic inhibition in the rat hippocampus. J. Neurophysiol. 69, 764–771. 12. Johnston D. and Brown T. H. (1981) Giant synaptic potential hypothesis for epileptiform activity. Science 211, 294–297. 13. Johnston D. and Brown T. H. (1984) The synaptic nature of the paroxysmal depolarizing shift in hippocampal neurons. Ann. Neurol. 16, Suppl., S65–S75. 14. Levy R. and O’Leary R. L. (1965) Arrest of seizure activity. Epilepsia 6, 116–121. 15. Llina´s R. R. (1964) Mechanisms of supraspinal action upon spinal cord activities. Differences between reticular and cerebellar inhibitory action upon alpha extensor motorneurones. J. Neurophysiol. 27, 1117–1126. 16. Neckelmann D., Amzica F. and Steriade M. (1998) Spike-wave complexes and fast components of cortically generated seizures. III. Synchronizing mechanisms. J. Neurophysiol. 80, 1480–1494. 17. Niedermeyer, E. (1998) Abnormal EEG patterns: epileptic and paroxysmal. In Electroencephalography: Basic Principles, Clinical Applications, and Related Fields (eds Niedermeyer E. and Lopes da Silva F.), pp. 235–260. Williams and Wilkins, Baltimore. 18. Oakley J. C., Sypert G. W. and Ward A. A. J. (1972) Conductance changes in neocortical propagated seizure: seizure initiation. Expl Neurol 37, 287–299. 19. Pollen D. A. (1964) Intracellular studies of cortical neurons during thalamic induced wave and spike. Electroenceph. clin. Neurophysiol. 17, 398–404. 20. Schwindt P. C., Spain W. J. and Crill W. E. (1989) Long-lasting reduction of excitability by a sodium-dependent potassium current in cat neocortical neurons. J. Neurophysiol. 61, 233–244. 21. Schwindt P. C., Spain W. J., Foehring R. C., Stafstrom C. E., Chubb M. C. and Crill W. E. (1988) Multiple potassium conductances and their functions in neurons from cat sensorimotor cortex in vitro. J. Neurophysiol. 59, 424–449. 22. Steriade M. (1974) Interneuronal epileptic discharges related to spike-and-wave cortical seizures in behaving monkeys. Electroenceph. clin. Neurophysiol. 37, 247–263. 23. Steriade M. and Amzica F. (1994) Dynamic coupling among neocortical neurons during evoked and spontaneous spike-wave seizure activity. J. Neurophysiol. 72, 2051–2069. 24. Steriade M. and Amzica F. (1999) Intracellular study of excitability in the seizure-prone neocortex in vivo. J. Neurophysiol. 82, 3108–3122. 25. Steriade M., Amzica F., Neckelmann D. and Timofeev I. (1998) Spike-wave complexes and fast components of cortically generated seizures. II. Extraand intracellular patterns. J. Neurophysiol. 80, 1456–1479. 26. Steriade M. and Contreras D. (1995) Relations between cortical and thalamic cellular events during transition from sleep patterns to paroxysmal activity. J. Neurosci. 15, 623–642. 27. Steriade M. and Contreras D. (1998) Spike-wave complexes and fast components of cortically generated seizures. I. Role of neocortex and thalamus. J. Neurophysiol. 80, 1439–1455. 28. Steriade M., Contreras D., Curro´ Dossi R. and Nun˜ez A. (1993) The slow (,1 Hz) oscillation in reticular thalamic and thalamocortical neurons: scenario of sleep rhythm generation in interacting thalamic and neocortical networks. J. Neurosci. 13, 3284–3299. 29. Steriade M., Nun˜ez A. and Amzica F. (1993) A novel slow (,1 Hz) oscillation of neocortical neurons in vivo: depolarizing and hyperpolarizing components. J. Neurosci. 13, 3252–3265. 30. Steriade M., Nunez A. and Amzica F. (1993) Intracellular analysis of relations between the slow (,1 Hz) neocortical oscillation and other sleep rhythms of the electroencephalogram. J. Neurosci. 13, 3266–3283. 31. Steriade M., Timofeev I., Du¨rmu¨ller N. and Grenier F. (1998) Dynamic properties of corticothalamic neurons and local cortical interneurons generating fast rhythmic (30–40 Hz) spike bursts. J. Neurophysiol. 79, 483–490. 32. Steriade M., Timofeev I. and Grenier F. (1998) Inhibitory components of cortical spike-wave seizures in vivo. Soc. Neurosci. Abstr. 24, 2143. 33. Timofeev I., Grenier F. and Steriade M. (1998) Spike-wave complexes and fast components of cortically generated seizures. IV. Paroxysmal fast runs in cortical and thalamic neurons. J. Neurophysiol. 80, 1495–1513. 34. Traub R. D., Borck C., Colling S. B. and Jefferys J. G. R. (1996) On the structure of ictal events in vitro. Epilepsia 37, 879–891. 35. Weir B. (1965) The morphology of the spike-wave complex. Electroenceph. clin. Neurophysiol. 19, 284–290. (Accepted 29 November 1999)