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NEUROSCIENCE |
1 INSERM U666, physiopathologie clinique et expérimentale de la schizophrénie, Faculté de Médecine, 11 rue Humann, F-67085 Strasbourg, France
2 Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, PO Box 67 H-1450, Hungary
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Abstract |
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(Received 27 February 2006;
accepted after revision 13 April 2006;
first published online 20 April 2006)
Corresponding author D. Pinault: INSERM U666, Faculté de Médecine, 11, rue Humann, F-67085 Strasbourg Cedex, France. Email: pinault{at}neurochem.u-strasbg.fr
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Introduction |
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However, typical well-organized absence-related SWDs occur especially during immobile, inattentive wakefulness or drowsiness (Niedermeyer, 1965; Mirsky et al. 1986; Halasz, 1991; Loiseau, 1992), whereas sleep spindles characterize the early phase of sleep (Steriade et al. 1993). Thus, it is not clear in which behavioural state sleep spindles could initiate paroxysmal oscillations. In genetic absence epilepsy rats from Strasbourg (GAERS), SWDs develop during the immobile state in the TC system from wake-related normal 5–9 Hz oscillations (Pinault et al. 2001). In those rats, SWDs (6–8 spike-and-wave complexes s–1) correspond to hypersynchronous 5–9 Hz oscillations, which are launched by corticothalamic (CT) neurons (Pinault, 2003). Physiological 5–9 Hz oscillations occur during awake immobility and are distinguishable from sleep-related spindle (7–15 Hz) oscillations in electrocorticographic recordings (Pinault et al. 2001). Since both oscillation types share a common frequency band, one could be the derivative of the other. To clarify the relationship of spindle-like (7–15 Hz) and 5–9 Hz oscillations, and their similarity or difference to SWDs, it is essential to systematically compare the thalamic cellular mechanisms of these two types of oscillations.
In this study we conducted extracellular and current-clamp intracellular recordings in the thalamus of GAERS and control non-epileptic (NE) rats (free of spontaneous SWDs) under neuroleptic analgesia in combination with the EEG of the frontoparietal cortex (primary motor and somatosensory cortices). Because barbiturates are well known for inducing spindle-like oscillations in the TC system (Gandolfo et al. 1985; Contreras et al. 1997; Mackenzie et al. 2004), the incidence of spindle-like oscillations was increased either following intravenous injection of pentobarbital at subanaesthetic doses in rats under neuroleptic analgesia (in GAERS and in control NE rats) or under pentobarbital–fentanyl anaesthesia. Our findings support the hypothesis that, in GAERS, SWDs are generated by a wake-related CT resonance, and not by sleep-related TC oscillations.
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Methods |
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Experiments were conducted on inbred, adult male Wistar rats (35 GAERS and 58 control NE rats, 280–350 g), complying with our institutionally recommended procedures for animal use and care (Comité Régional d'Ethique en Matière d'Expérimentation Animale, Strasbourg).
Anaesthesia and surgery
All surgical procedures were done under deep general anaesthesia (pentobarbital: 40 mg kg–1, I.P., Sanofi, Libourne, France; and ketamine: 50 mg kg–1, I.M., Merial, Lyon, France). Tracheotomy and catheterization of the penile vein were performed, and the animal was placed in a stereotaxic frame (David Kopf Instruments, Tujunga, CA, USA). A new stabilizing craniotomy–duratomy technique (Pinault, 2005) was systematically performed to improve the success rate of single-cell electrophysiology experiments, to increase the precision of the stereotaxical approach to single neurons in the target region, and to considerably reduce undesirable non-neuronal rhythms (heart beat and breathing) during intracellular recordings. Before the end of this general pentobarbital–ketamine anaesthesia, the rat was subjected either to neuroleptic analgesia (35 GAERS and 52 control NE rats) or barbiturate–fentanyl anaesthesia (6 control NE rats) (see below).
All rats were artificially ventilated (SAR-830; CWE, Ardmore, PA, USA) in the pressure mode (8–12 cmH2O; 60–65 breaths min–1) using an O2-enriched gas mixture (70–50% air and 30–50% O2). The rat's rectal temperature was maintained at its physiological level (37–38.3°C) using a thermoregulated blanket (Fine Science Tools Inc., Heidelberg, Germany). The EEG, which spontaneously displayed synchronized slow oscillations (see Results), and the heart rate were also under continuous monitoring to maintain a steady depth of anaesthesia by adjusting the injection rate of the anaesthetic solution.
Neuroleptic analgesia was initiated and then maintained by a continuous intravenous injection (0.5 ml h–1) of the following mixture: d-tubocurarine chloride (0.4 mg; Sigma-Aldrich, Saint-Quentin Fallavier, France), fentanyl (1 µg; Janssen, Boulogne-Billancourt, France), Haldol (100 µg; Janssen), and glucose (25 mg). (The adequacy of the neuroleptic analgesia was established in the absence of neuromuscular blockade.)
Barbiturate–fentanyl anaesthesia was initiated and maintained using a continuous intravenous injection (0.5 ml h–1) of the following mixture (quantity given per hour for a rat of 300 g): d-tubocurarine chloride (0.4 mg), fentanyl (1 µg), pentobarbital (3.5–8.2 mg) and glucose (25 mg).
Electrophysiology
Glass micropipettes (30–70 M
) were filled with a solution containing 1.5%
N-(2-aminoethyl)biotinamide hydrochloride (Neurobiotin; Vector Laboratories, Burlingame, CA, USA) dissolved in either 1 M CH3COOK, or in 3 M KCl. The pipette was lowered with a stepping microdriver (Burleigh, Fishers, NY, USA) into the somatosensory or motor thalamus to reach a single TC or thalamic reticular nucleus (TRN) neuron, which was extracellularly and/or intracellularly recorded simultaneously along with the EEG of the primary motor and somatosensory cortices. Dual extracellular single-unit TC–TRN recordings were simultaneously performed with the EEG.
Multi-unit recordings were done in the thalamus using glass micropipettes (tip diameter: 2–3.5 µm) in conjunction with the cortical EEG. The location of the recording sites was identified histologically following extracellular application (500–600 nA, 200 ms on/200 ms off, 5–10 min) of Neurobiotin.
Signal conditioning
Electrophysiological data were processed with band passes of 0.1–1200 Hz for the EEG, of 0–6 kHz for cellular activity, and of 0.3–6 kHz for multi-unit recordings (Cyber-Amp 380; Axon Instruments, Union City, CA, USA). Signals were digitized at a sampling rate >18 kHz. During the intracellular recording session, a current pulse in the range of –0.2 to –0.5 nA was applied every 2 s to keep the Wheatstone bridge well balanced. Using square-wave current pulses (range of ± 3 nA), the input membrane resistance and intrinsic firing patterns of thalamic, relay and reticular neurons could be assessed.
Histology
At the end of the recording session, the neurons were individually labelled using the juxtacellular (Pinault, 1996) or intracellular tracer microiontophoresis technique for standard histological identification. For the paired single-unit recording experiments, the juxtacellular filling procedure was applied only in the two neurons of the last pair that had been recorded. After a survival period of at least 30 min, the animal was killed with an intravenous overdose of pentobarbital. Then it was transcardially perfused with a fixative containing 4% paraformaldehyde and 0.25% glutaraldehyde in 10 mM phosphate-buffered saline, and the brain tissue was processed using standard histological techniques for retrieving the tracer-filled neurons.
Data analysis
Electrophysiological recordings were analysed with Axon software (Clampex, v7; Axon Instruments), and the tracer-filled neurons were examined with a light microscope (E600; Nikon France, Champigny-sur-Marne, France). Some of the neurons were reconstructed using the Neurolucida system (Microbrightfield, Colchester, VT, USA). The location of any marked cell was ascertained by referring to a stereotaxic atlas (Paxinos & Watson, 1986).
Fast Fourier transformations (FFT) were computed using DataWave softwares (SciWorks, v4; DataWave Technologies, Berthoud, CO, USA). Fourier Transform analysis was based on 1.6 s epochs, with a resolution of 0.6 Hz, and was applied on segments of EEG or extracellular field potential signals (re-digitized at a sampling rate of 2.5 kHz) of at least 2 min. Autocorrelograms of action potential (AP) trains were also performed with DataWave software.
The background noise of the membrane potential of the recorded thalamic neurons, which contained spontaneously occurring intrinsic and synaptic oscillations, was quantified using spectral analysis. A series of 25–35 successive FFTs (epochs of 0.3 s) of the membrane potential, which oscillated between –80 mV and –100 mV (current-clamp mode), was computed. The values of the total power were extracted for 4 frequency bands: slow (1–15 Hz), ß (16–30 Hz), 
1 (31–49 Hz), and 2 (51–100 Hz). The 50 Hz values were discarded to avoid contamination from possible AC noise.
Data are presented as means ± S.E.M. They were evaluated for statistical significance using Student's t test, the significance level being set to 0.05.
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Results |
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Data base
The data reported in this paper are based on EEG recordings of five GAERS and five control NE rats, 32 simultaneous extracellular recordings of TC and TRN neurons and on individual intracellular recordings of 30 TC and 23 TRN neurons (30 GAERS, 58 control NE rats). All intracellular recordings had to fulfil the following three criteria: (1) a stable resting membrane potential without holding hyperpolarizing current (Table 1); (2) a firing pattern similar to that recorded extracellularly in the same or in other neurons of the same category; and (3) an overshooting of the APs. Following an intravenous injection of barbiturate, the resting membrane potential of the neurons being recorded became significantly more hyperpolarized and the membrane input resistance significantly increased (Table 1).
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In GAERS under neuroleptic analgesia, high-voltage (>0.5 mV) SWDs (6–8 spike-and-wave complexes s–1) occurred in alternation with small-voltage fast oscillations (< 0.2 mV, >15 Hz; Fig. 1A). Spike-and-wave discharges lasted a few seconds to a couple of minutes as described before (Pinault et al. 2001). In control NE rats under neuroleptic analgesia, the surface EEG of the frontoparietal cortex alternated between small-voltage fast oscillations and medium-voltage slower oscillations (< 0.5 mV, < 15 Hz). The latter occurred at 0.5–4 oscillations min–1, lasted on average 3.4 ± 0.9 s (0.5–20 s), and included 1–4 Hz and 5–9 Hz rhythmic waves, which could wax and wane in amplitude (Fig. 1B and Ca).
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Additional experiments were performed to check whether the spindle-like oscillations induced by a single subanaesthetic barbiturate injection under neuroleptic analgesia were similar to those recorded under continuous barbiturate–fentanyl anaesthesia (6 control NE rats). The cortical EEG and thalamic relay and reticular firings resembled those recorded in rats under neuroleptic analgesia that had received an intravenous injection of pentobarbital at subanaesthetic doses (data not shown).
Oscillations at 5–9 Hz occur in a more coherent manner in the TC system than spindle-like oscillations
Since 5–9 Hz oscillations gave rise to highly coherent SWDs in GAERS, whereas spindle-like oscillations did not, it was important to determine the degree of coherence in the TC system of both oscillation types. Oscillations at 5–9 Hz were obviously more prominent under neuroleptic analgesia, whereas short-lasting (<2 s) spindle-like oscillations were more prominent in the presence of barbiturates (Fig. 1). To assess the degree of coherence in the cerebral cortex and in the TC system of these two oscillation types, simultaneous EEG recordings were performed in the primary motor and somatosensory cortices and in the somatosensory thalamus in control NE rats, which were under neuroleptic analgesia or barbiturate influence. Spectral analysis was computed on periods of recording of at least 2 min. The values of total power were extracted and normalized for the 5–9 Hz (under neuroleptic analgesia) and 7–15 Hz (under barbiturate influence) bands and were plotted against time (Fig. 2Aa, b and Ba, b, upper graphs). These charts allowed the determination of the coincidence in time of a given oscillation in two regions. The relationship between the corresponding normalized FFT values was assessed using a parametric test (linear regression), which made it possible to compare the coherence tendencies of both types of oscillations using the correlation coefficient (R) (Fig. 2Aa, b and Ba, b, lower graphs). Thus, oscillations at 5–9 Hz recorded under neuroleptic analgesia consistently occurred in a more correlated manner in the frontoparietal cortex and in the related thalamus than barbiturate-induced spindle-like oscillations. This finding was consistent in all cases using different anaesthetic conditions (3 rats under neuroleptic analgesia, 2 rats under barbiturate–fentanyl anaesthesia, and 2 rats under neuroleptic analgesia that had received a subanaesthetic dose of pentobarbital).
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Under neuroleptic analgesia, the extracellular thalamic field potential oscillated during the occurrence of 5–9 Hz oscillations in the related cortex (Fig. 3A). Single APs or a burst of 2–4 APs at 200–500 Hz could occur on some of the cycles of the oscillation. When the recorded neurons were not strongly inhibited, a modulation at 5–9 Hz could be revealed using autocorrelation analysis (Fig. 3B).
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Under neuroleptic analgesia, all recorded TRN neurons displayed a rhythmic discharge pattern during the occurrence of 5–9 Hz oscillations in the related cortex (Fig. 5A). The rhythmic pattern is principally characterized by the occurrence of high-frequency bursts of APs, which did not systematically occur on every cycle of the oscillation. This was ascertained by the autocorrelogram (Fig. 5A). Under barbiturate influence, TRN cells principally fired recurrent (0.15 ± 0.06 Hz) short-lasting (1.1 ± 0.4 s) trains of high-frequency bursts of APs (Fig. 5B). The bursts in the trains occurred at a variable frequency (5–15 Hz; also see autocorrelogram in Fig. 5B). The trains were sometimes associated with spindle-like oscillations in the EEG of the related cortex (Fig. 5B). The intraburst firing characteristics of TRN cells were appreciably different during the 7–15 Hz-related versus the 5–9 Hz-related high-frequency bursts (Fig. 5D and E). The AP discharge frequency within a burst was on average significantly higher during spindle-like than during 5–9 Hz oscillations (361.1 ± 0.9 Hz versus 242.4 ± 1.0 Hz, Student's t test, P < 0.001). This was mainly caused by the shortening of the inter-AP intervals during the beginning of the bursts. Thus, the instantaneous frequency of two successive APs in a burst was significantly higher for the first nine APs during spindle-like oscillations than during 5–9 Hz oscillations (Student's t test, P < 0.001; Fig. 5E). Furthermore, the AP discharge in the 5–9 Hz bursts presented a less pronounced acceleration–deceleration pattern than that in spindle bursts.
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Intracellular recording of TC neurons
In TC neurons, the membrane potential events underlying the 5–9 Hz and spindle-like oscillations were readily distinguishable (Fig. 6). Oscillations at 5–9 Hz recorded under neuroleptic analgesia started from a significantly more depolarized membrane potential (–60.5 ± 1.2 mV; Student's t test, P < 0.05; Table 1; Fig. 6A) than spindle-like oscillations recorded under barbiturate influence (–64.5 ± 0.5 mV; Table 1; Fig. 6B). In GAERS, SWD-related TC oscillations recorded under neuroleptic analgesia started from a membrane potential statistically similar to normal 5–9 Hz oscillations (–59.6 ± 0.9 mV; Table 1).
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, respectively; Student's t test, P < 0.05; Table 1), i.e. under neuroleptic analgesia, than before the occurrence of spindle-like oscillations (25.1 ± 3.3 M; Table 1), i.e. under barbiturate influence. The intracellular 5–9 Hz oscillations of TC cells consisted of the rhythmic occurrence of a threshold/subthreshold depolarizing wave–hyperpolarizing wave sequence (Pinault, 2003; Fig. 6A). In contrast, spindle-like oscillations were characterized by rhythmic hyperpolarizations (Fig. 6B and Da) with an occasional AP discharge between two successive hyperpolarizations (Fig. 6Da). Following intravenous injections of pentobarbital at subanaesthetic doses, these spindle-like episodes regularly occurred every 2–5 s (Fig. 6B).
For both the 5–9 Hz and the spindle-like oscillations the rhythmic waves occurred in the trough of a long-lasting hyperpolarization (Fig. 6A and B). This hyperpolarizing envelope lasted as long as the membrane potential was oscillating. The hyperpolarizing envelope of the 5–9 Hz oscillations could not be abolished by applying sustained hyperpolarizing currents even at –92 mV (Fig. 6C). It resembled the SWD-related long-lasting hyperpolarization (Pinault et al. 1998). In contrast, the long-lasting hyperpolarization of spindle-like oscillations was reversed in polarity at a membrane potential ranging from –68 to –78 mV (Fig. 6Da–c). It became depolarizing either when the membrane potential was deeply hyperpolarized (Fig. 6Dc), or when recorded with KCl-filled micropipettes (n = 3 neurons, not shown).
The 5–9 Hz oscillation-related recurrent depolarization started with the summation of synaptic unitary events and could trigger an apparent low-threshold Ca2+ potential that launched a high-frequency burst of APs (Fig. 6E). On the other hand, during spindle-like oscillations, no TC cells displayed high-frequency bursts of APs induced by an apparent low-threshold Ca2+ potential in our sample (Fig. 6F), even when applying a holding hyperpolarizing current (Fig. 6Db and c). However, single APs could occur following the rhythmic hyperpolarization (Fig. 6F). All TC neurons tested could generate an apparent low-threshold Ca2+ potential spontaneously at the offset of a hyperpolarization evoked by a square pulse of cathodal current (Fig. 6Dd). Thus the lack of spontaneous rebound bursts was not the consequence of the suboptimal quality of our recordings. It should also be mentioned that the membrane potential displayed more powerful fast rhythmic activities when recorded under neuroleptic analgesia (Fig. 6C) than when recorded under barbiturate influence (Fig. 6Db) (see below).
Intracellular recording of TRN neurons
Intracellular recordings of TRN neurons revealed that the membrane events underlying the two rhythmic activities at 5–9 Hz and 7–15 Hz were readily distinguishable (Fig. 7). Similarly to TC cells, in TRN cells 5–9 Hz oscillations recorded under neuroleptic analgesia started from a significantly more depolarized membrane potential (–61.6 ± 1.2 mV; Student's t test, P < 0.05; Table 1; Fig. 7A) compared to the spindle-like oscillations recorded under barbiturate influence (–68.3 ± 1.3 mV; Table 1; Fig. 7B). In GAERS, SWD-related TRN oscillations recorded under neuroleptic analgesia started from a membrane potential statistically similar to normal 5–9 Hz oscillations (–60.9 ± 1.4 mV; Table 1).
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, respectively; Student's t test, P < 0.05; Table 1), i.e. under neuroleptic analgesia, than before the occurrence of spindle-like oscillations (47.4 ± 6.8 M; Table 1), i.e. under barbiturate influence. Both 5–9 Hz and spindle-like oscillation-related recurrent depolarizations regularly gave rise to a high-frequency burst of APs (200–500 Hz; up to 13 APs) in TRN neurons but with distinctive intraburst features (see above).
Fully developed 5–9 Hz oscillations occurred in the trough of a long-lasting hyperpolarization (Fig. 7A) similarly to SWD (Fig. 8). In contrast, spindle-like oscillations systematically emerged in parallel with the generation of a slow depolarizing envelope (Fig. 7B). Neither the 5–9 Hz-related nor the SWD-related steady hyperpolarization could be reversed by the application of sustained hyperpolarizing current even at –96 mV (Figs 7C and 8D). The long-lasting hyperpolarization, however, could be almost completely abolished at a membrane potential close to AP threshold (Fig. 8A). The spindle-like oscillation-related depolarizing envelope was also abolished at a membrane potential close to AP threshold (Fig. 7Da–c). The recurrent depolarization of normal and absence-related 5–9 Hz oscillations and of spindle-like oscillations was significantly reduced in amplitude when the membrane potential was held close to AP threshold. Both the 5–9 Hz and the spindle-like oscillation-related recurrent depolarizations began by the summation of synaptic and/or intrinsic unitary events (Fig. 7E and F, respectively). It is worth mentioning that the SWD-related recurrent depolarization also began by the summation of depolarizing unitary events (Pinault, 2003). The membrane potential of the recorded TRN cells displayed more powerful fast rhythmic activities when recorded under neuroleptic analgesia (Figs 7C and 8D) than when recorded under barbiturate influence (Fig. 7Dc).
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As described above our intracellular recordings have revealed that, both in TC and TRN neurons, normal and SWD-related 5–9 Hz oscillations started from a significantly more depolarized membrane potential than spindle-like oscillations. Therefore, we performed a spectral analysis of the fast, synaptic and intrinsic oscillations of the membrane potential, especially in the ß (16–30 Hz) and (31–100 Hz) frequency bands of TC and TRN neurons. The membrane potential of thalamic neurons displayed more powerful fast rhythmic activities before the occurrence of normal or epileptic 5–9 Hz oscillations than before the occurrence of spindle-like oscillations (Fig. 9A). The power of the ß and oscillations was significantly higher in between normal or SWD-related 5–9 Hz oscillations than in between spindle-like oscillations (Fig. 9B).
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Discussion |
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Oscillations at 5–9 Hz but not sleep spindles give rise to SWDs in GAERS
It is important to remember that, in humans, typical absence seizures are related more to arousal than to sleep (see Introduction). In undrugged GAERS, both SWDs and 5–9 Hz oscillations emerge from a relatively desynchronized EEG when compared to spindle oscillations (Pinault et al. 2001). From an EEG point of view, the neuroleptic analgesia maintains the rats in a state equivalent to inattentive and immobile wakefulness or drowsiness (Pinault et al. 2001). These experimental conditions are adequate for recording SWDs at a similar frequency of occurrence and duration to those recorded in freely moving animals (Pinault et al. 1998, 2001; Seidenbecher et al. 1998). Our data indicate that the cellular and network mechanisms underlying 5–9 Hz and spindle-like oscillations described in this study are similar to those of the undrugged intact brain.
The present study has shown that spindle-like oscillations and 5–9 Hz oscillations differ at the cellular level and show different pharmacological profiles. In rats under neuroleptic analgesia, 5–9 Hz oscillations occur in the cortex and in the thalamus in a more coherent manner than spindle-like oscillations. Pentobarbital at subanaesthetic doses abolished both SWDs and 5–9 Hz oscillations, whereas it increased the incidence of spindle-like oscillations. We have also demonstrated that the thalamic cellular mechanisms underlying 5–9 Hz and spindle-like oscillations are quite distinct, ruling out the possibility that one rhythm is a derivative of the other. However, the intracellular events underlying 5–9 Hz oscillations and SWDs have similar electrophysiological features (Pinault, 2003), suggesting that SWDs in GAERS more likely emerge from 5–9 Hz oscillations than from sleep spindles.
Why are spindle-like oscillations not pro-epileptogenic in GAERS, when they apparently contribute to SWD genesis in feline generalized penicillin epilepsy (Kostopoulos et al. 1981; Kostopoulos, 2000)? Using spectral analysis, the present study reveals that spindle-like oscillations occurred in a less coherent manner in the cortex and the thalamus in barbiturate-treated rats (i.e. in rats under neuroleptic analgesia that had received a subanaesthetic dose of pentobarbital, or in rats either lightly or deeply anaesthetized with pentobarbital and fentanyl) than 5–9 Hz oscillations (in rats under neuroleptic analgesia). The major factor that leads to synchronized spindle oscillations in the thalamus is the CT feedback in widespread thalamic regions in barbiturate-anaesthetized cats (Contreras et al. 1997). In our barbiturate-treated rats, the strength of CT connectivity was apparently not strong enough to generate synchronized discharges of high-frequency bursts in TRN cells and subsequently synchronized rebound responses in related TC neurons. This situation may be closer to the undrugged condition, since temporal synchrony in spindle-frequency oscillations between adjacent TRN neurons has not been recorded during normal sleep in rats (Marks & Roffwarg, 1993). Thus, the lack of a pro-epileptogenic effect of spindles might be the result of species-specific differences in the strength of CT synchrony between the rat and the cat. Alternatively CT synchrony during spindles may reach non-physiological levels in the penicillin model of cats.
Sleep-related TC spindle oscillation
The present data have demonstrated that the thalamic cellular and network mechanisms of spindle-like oscillations recorded in rats under neuroleptic analgesia are comparable to those of drowsiness- or sleep-related spindles recorded previously in the intact brain. Indeed, spindle-like membrane oscillations of TC and TRN neurons lasted as long as sleep spindles (< 2 s), had a periodicity similar to that of sleep spindles (2–5 s; Contreras et al. 1997), rarely occurred during a desynchronized EEG, and systematically occurred under the influence of barbiturate (Gandolfo et al. 1985; Contreras et al. 1997). In TRN cells, spindle-like oscillations were characterized by a rhythmic, threshold/subthreshold, depolarizing wave superimposed on a slow depolarizing envelope. The rhythmic depolarizing wave had electrophysiological features of EPSPs that could trigger an apparent low-threshold Ca2+ potential, especially at the beginning of spindle-like oscillations. These EPSPs were probably mediated by synchronized TC inputs (von Krosigk et al. 1993; Bal et al. 1995).
The depolarizing envelope, which disappears when holding the membrane potential close to AP threshold, has also been recorded in TRN neurons of barbiturate-anaesthetized cats (Mulle et al. 1986), but not in TRN cells in ferret thalamic slices (von Krosigk et al. 1993; Bal et al. 1995). It is worth mentioning that such a depolarizing envelope was not recorded in TRN cells during natural 5–9 Hz oscillations or SWDs (Pinault, 2003). The mechanism underlying this slow depolarization is unknown. One possible mechanism might involve the generation of a hyperpolarization-activated cation current, Ih, since genes coding for Ih channels are present in the TRN (Santoro et al. 2000). Another possible mechanism might involve a decrease of a K+ leak current similar to the one modulated by cholecystokinin (Cox et al. 1995).
In TC neurons, spindle-like oscillations were characterized by rhythmic hyperpolarizations, which appeared in parallel with a slow hyperpolarizing envelope. These intracellular events resemble those obtained earlier in the anaesthetized rat (Shosaku et al. 1989). Both the rhythmic hyperpolarization and the envelope reversed in polarity at a membrane potential close to –75 mV and also reversed to depolarizing events when recorded with chloride-filled micropipettes, suggesting that both intracellular events were mediated by the activation of GABAA receptors. These TC hyperpolarizing events are basically similar to those recorded during spindle-like oscillations in ferret thalamic slices (von Krosigk et al. 1993; Bal et al. 1995). Since the rat's somatosensory thalamus is devoid of GABAergic interneurons (Barbaresi et al. 1986; Harris & Hendrickson, 1987), and since the TC rhythmic hyperpolarizations mirrored the TRN rhythmic threshold depolarizations, the spindle-like oscillation-related TC hyperpolarizing events were most probably mediated by the TRN-induced activation of GABAA receptors.
Surprisingly, we never recorded a high-frequency rebound burst of APs at the end of the rhythmic hyperpolarization in our experimental conditions (in rats under neuroleptic analgesia that had received a subanaesthetic dose of pentobarbital or in rats lightly or deeply anaesthetized with pentobarbital and fentanyl). Instead, single APs could be recorded between two successive hyperpolarizations. However, all our intracellularly recorded TC neurons tested could generate an apparent low-threshold Ca2+ spike whatever the value of their membrane input resistance, indicating that the intracellular micropipette did not affect the biophysical properties of the recorded neurons. Since high-frequency bursts occurring at 7–15 Hz could sometimes be recorded in individual extracellular recordings of TC neurons, we think that our TC cellular sample of intracellular recordings is not large enough to include bursting TC cells. Nevertheless, our data indicate that, under our experimental conditions, the probability of generation of a low-threshold Ca2+ potential during spindle-like oscillations is lower than that observed during 5–9 Hz oscillations (Pinault, 2003). This finding merits further discussion because it is at variance with previous in vitro (von Krosigk et al. 1993) and in vivo (Deschênes et al. 1984; Steriade & Deschênes, 1984) recordings, which have demonstrated that, in TC neurons, the high-frequency AP discharge caused by a low-threshold Ca2+ potential occurs at least at some cycles during spindle-like oscillations. Two non-exclusive possibilities might explain the lack of this intrinsic potential in our intracellular recordings. It might be due to the lack of coherent oscillations between the cortex and the related thalamus, which might lead to the arrival of asynchronous reticular IPSPs in TC cells. Indeed, multi-unit recordings with glass micropipettes demonstrated asynchronous burst discharges (phase lag > 5 ms) in the TRN during spontaneously occurring spindle-like oscillations (D. Pinault, unpublished observation). The lack of synchrony in spindle-frequency burst discharges between nearby TRN neurons has also been observed in freely moving rats (Marks & Roffwarg, 1993). Knowing that adjacent TRN cells can innervate the same territories (Pinault & Deschênes, 1998), asynchronous arrival of IPSPs might have shunted or abolished the low-threshold Ca2+ current and subsequently the high-frequency burst in TC neurons (Ulrich & Huguenard, 1997).
The second possibility might rest on particular cellular and network properties that are specific to the somatosensory TC system of rodents. Indeed, spindle-like oscillations could be recorded in thalamic slices of the visual system of ferrets (von Krosigk et al. 1993) but not in thalamic slices of the somatosensory system of mice (Warren et al. 1994) and rats (Jacobsen et al. 2001). This difference may reflect interspecies variations and can be explained to some extent by the absence of interneurons in the somatosensory thalamic nuclei of rodents (Barbaresi et al. 1986; Harris & Hendrickson, 1987).
It is well known from in vivo and in vitro studies that the pacemaker of sleep spindles is located in the thalamus (Steriade et al. 1993). This is well supported here by the systematic occurrence of rhythmic high-frequency burst discharges in TRN cells. In addition, our single- and multi-unit extracellular recordings could reveal rhythmic peaks of synchronized firings in subsets of TC neurons during spontaneously occurring spindle-like oscillations. The generation of pacemaking activity also involves reciprocal interactions between TC and TRN neurons and high-frequency burst discharges in both cellular types (von Krosigk et al. 1993; Steriade et al. 1993).
Wake-related CT 5–9 Hz oscillation
Our previous study has revealed that, in the somatosensory system, layer VI CT neurons start to fire at 5–9 Hz a few milliseconds before related TC and TRN neurons (Pinault, 2003). Therefore the 5–9 Hz oscillation-related rhythmic depolarization recorded intracellularly in TC and TRN cells is most likely mediated by a CT EPSP barrage. This input can trigger a low-threshold Ca2+ spike in both cell types.
This intrinsic Ca2+ spike is an important factor that determines the internal pattern of the high-frequency burst. The acceleration–deceleration pattern of TRN 5–9 Hz bursts is less pronounced than the well-known acceleration–deceleration pattern of TRN spindle bursts, which is caused by the underlying low-threshold Ca2+ potential (Mulle et al. 1986; Spreafico et al. 1988; Avanzini et al. 1989; Bal & McCormick, 1993; Contreras et al. 1993). In addition, the instantaneous frequency within 5–9 Hz bursts is significantly lower than that in spindle bursts. On the other hand, our data demonstrate that the SWD-related TRN bursts have the highest internal frequency (when compared with the 5–9 Hz-related and spindle-related bursts), which suggest that the epilepsy-related TRN bursts are underlain by at least (Pinault, 2003) a low-threshold Ca2+ potential that is on average more powerful than that underlying the 5–9 Hz-related and 7–15 Hz-related TRN bursts. This might be the result of cellular hypersynchronization associated with absence-related SWDs.
In the case of TC neurons, it is well established that during spontaneously occurring 5–9 Hz oscillations, high-frequency bursts of APs underlain by a low-threshold Ca2+ potential do occur at times. They are more frequent in subsets of TC cells having a relatively high membrane input resistance and a presumed Ih current (Pinault, 2003). Together this pacemaker current and the recurrent burst are well known to be pro-epileptogenic (Pape, 1996; Lüthi & McCormick, 1998). Furthermore, our previous (Pinault, 2003) and present data have demonstrated that 5–9 Hz oscillations and SWDs are underlain by similar intracellular events in thalamic neurons, strongly suggesting that CT 5–9 Hz oscillations but not TC spindle-like oscillations are essential for the generation of SWDs in the somatosensory system of GAERS. It is worth mentioning that intralaminar thalamic nuclei might also contribute to the generation of absence-related SWDs but, apparently, not in a pacemaker role (Seidenbecher & Pape, 2001).
In this study we have demonstrated that the membrane potentials of TRN and TC neurons are more depolarized when they are just about to display normal or epilepsy-related 5–9 Hz oscillations (under neuroleptic analgesia) than when they are just about to display spindle-like oscillations (under barbiturate influence). Also, the membrane input resistance of these neurons is lower before the occurrence of 5–9 Hz oscillations or SWDs than before the occurrence of spindle-like oscillations. Furthermore, spectral analysis has revealed that the membrane potential oscillations of these thalamic neurons include ß and rhythmic activities, which are more powerful in between 5 and 9 Hz oscillations or SWDs than those occurring in between spindle-like oscillations. Together, these findings suggest that TRN and TC neurons receive more incoming signals when their propensity is to oscillate at 5–9 Hz or to generate SWDs than to generate spindle-like oscillations. The majority of the excitatory inputs of these two thalamic cell types arise in layer VI of the neocortex. Thus, CT neurons might play a major role in determining the state of the membrane potential in thalamic neurons. This implies that CT cells are more active before the occurrence of 5–9 Hz oscillations or SWDs than before the occurrence of spindle-like oscillations. Indeed, tonic firing has been recorded in identified layer VI CT neurons in between 5–9 Hz oscillations or SWDs (Pinault, 2003). Our data thus indicate that desynchronized cortical activity (up state) may be a prerequisite for the initiation of 5–9 Hz oscillations and SWDs, but may not be necessary for the generation of sleep spindles.
The present study has further shown that, in TC and TRN neurons, a steady or tonic hyperpolarization develops in parallel with normal or absence-related 5–9 Hz oscillations (also see Pinault et al. 1998 and Slaght et al. 2002). At least four observations lead us to propose that this apparent steady hyperpolarization as well as normal-related or epilepsy-related 5–9 Hz oscillations are mainly mediated by layer VI CT neurons: (1) the steady hyperpolarization starts and ends with, respectively, the beginning and the end of 5–9 Hz oscillations; (2) both the steady hyperpolarization and normal-related or epilepsy-related 5–9 Hz oscillations are significantly reduced in amplitude when the membrane potential is close to AP threshold; (3) they cannot be abolished when applying strong hyperpolarizing DC current; and (4) the firing of layer VI cells becomes rhythmic with the development of 5–9 Hz oscillations (Pinault, 2003).
Therefore we propose that the apparent tonic hyperpolarization might well be a disfacilitation subsequent to an arrest of firing in excitatory inputs, especially from those originating in cortical layer VI. Indeed, layer VI CT inputs represent the greatest excitatory inputs in number and in density in the dorsal thalamus (Robertson & Rinvik, 1973; Singer, 1977), and they innervate simultaneously TC and TRN neurons (Bourassa et al. 1995). In addition, the normal or epilepsy-related 5–9 Hz TC and TRN rhythmic discharges are caused by the CT rhythmic firing (Pinault, 2003). This implies that the apparent tonic hyperpolarization in thalamic neurons would result in part from rhythmic synchronous inhibitions of layer VI CT cells. This mechanism does not exclude the contribution of potassium inwardly rectifying currents (Wilson, 1993; also see Pinault et al. 1998). Thus, a cortical up and down state sequence might play a large part in launching CT 5–9 Hz oscillations or absence-related SWDs in GAERS.
Conclusion
Despite the fact that spontaneously occurring 5–9 Hz and spindle-like oscillations share a common frequency band in the rat somatosensory TC system, the cellular mechanisms underlying these two rhythmic activities are different. More specifically, the intracellular events underlying spindle-like activity and 5–9 Hz oscillations are diametrically opposite to each other in both TC and TRN cells. Coherent 5–9 Hz oscillations in the TC system, which involve CT neurons as a leading device (Pinault, 2003), are required to trigger SWDs in GAERS, whereas when the network is in the state of spindle-like oscillations the conditions are not favourable for SWD genesis. Our findings demonstrate that for a given network, the raw EEG should be described not only in terms of frequency bands but also in terms of spatio-temporal dynamics of the cellular interactions in the system.
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