Impact of Network Activities on Neuronal Properties in Corticothalamic Systems

M. Steriade

Laboratoire de Neurophysiologie, Faculté de Médecine, Université Laval, Quebec G1K 7P4, Canada


    ABSTRACT
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IMPACT OF NETWORK ACTIVITY...
DEVELOPMENT OF NORMAL BRAIN...
REFERENCES

Steriade, M.. Impact of Network Activities on Neuronal Properties in Corticothalamic Systems. J. Neurophysiol. 86: 1-39, 2001. Data from in vivo and in vitro experiments are discussed to emphasize that synaptic activities in neocortex and thalamus have a decisive impact on intrinsic neuronal properties in intact-brain preparations under anesthesia and even more so during natural states of vigilance. Thus the firing patterns of cortical neuronal types are not inflexible but may change with the level of membrane potential and during periods rich in synaptic activity. The incidences of some cortical cell classes (defined by their responses to depolarizing current pulses) are different in isolated cortical slabs in vivo or in slices maintained in vitro compared with the intact cortex of naturally awake animals. Network activities, which include the actions of generalized modulatory systems, have a profound influence on the membrane potential, apparent input resistance, and backpropagation of action potentials. The analysis of various oscillatory types leads to the conclusion that in the intact brain, there are no "pure" rhythms, generated in simple circuits, but complex wave sequences (consisting of different, low- and fast-frequency oscillations) that result from synaptic interactions in corticocortical and corticothalamic neuronal loops under the control of activating systems arising in the brain stem core or forebrain structures. As an illustration, it is shown that the neocortex governs the synchronization of network or intrinsically generated oscillations in the thalamus. The rhythmic recurrence of spike bursts and spike trains fired by thalamic and cortical neurons during states of decreased vigilance may lead to plasticity processes in neocortical neurons. If these phenomena, which may contribute to the consolidation of memory traces, are not constrained by inhibitory processes, they induce seizures in which the neocortex initiates the paroxysms and controls their thalamic reflection. The results indicate that intact-brain preparations are necessary to investigate global brain functions such as behavioral states of vigilance and paroxysmal activities.


    INTRODUCTION
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ABSTRACT
INTRODUCTION
IMPACT OF NETWORK ACTIVITY...
DEVELOPMENT OF NORMAL BRAIN...
REFERENCES

This article emphasizes that network synaptic activities modulate, and often overwhelm, intrinsic neuronal properties. I certainly wish that this claim would become a truism for neuroscientists. However, with the advent of in vitro preparations, which provided not only some technical advantages over the work in vivo but also helped to achieve a better understanding of brain operations, a climate arose in which simplistic concepts sometimes appeared, such as the idea that the firing patterns induced by current pulses, taken to define the electrophysiological properties of a given neuronal type, are inflexible. This belief stands in contrast with data showing that patterns of neuronal activity change at various levels of membrane potential and with synaptic activity during shifts in behavioral states. There is also a tendency toward obtaining pure rhythms arising in simple circuits, whereas the intact brain displays oscillations of different types that are grouped together within complex wave sequences due to interactions between a variety of structures. Some investigators working in brain slices use their data to infer normal and pathological processes that require global operations in an intact brain.

Clearly both simplified preparations and normally operating networks are needed, but so far there are too few attempts to regard isolated networks within the context of the whole brain. The development of methods has succeeded in dissecting the brain and transforming it into reduced neuronal circuits. While behavioral and system neuroscience stands to gain from the achievements of biophysics and molecular biology in simplified preparations, the logic of life requires orchestration of the different parts composing the whole. The goal is to apply the information obtained from studies of isolated neurons and simple networks within the context of an intact brain. I will discuss the impact of synaptic activities on neuronal properties, as well as these effects during normal and paroxysmal oscillations in corticothalamic neuronal loops.


    IMPACT OF NETWORK ACTIVITY ON INTRINSIC NEURONAL PROPERTIES
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ABSTRACT
INTRODUCTION
IMPACT OF NETWORK ACTIVITY...
DEVELOPMENT OF NORMAL BRAIN...
REFERENCES

The intrinsic properties of neocortical and thalamic neurons were first revealed in brain slices. The major advantages of these simplified preparations are the control of the extracellular ionic environment, the simultaneous exploration of different neuronal compartments, and the possibility of investigating the actions of neurotransmitters on identified neuronal types after blockage of synaptic transmission. Presently, some of these techniques are not possible in vivo. In contrast with the earlier view of nerve cells acting in a purely reflex way, with little consideration for the role of their intrinsic properties, the host of voltage- and transmitter-gated conductances discovered in vitro (Gutnick and Crill 1995; Huguenard 1996; Llinás 1988) have provided new insights into the functions of different brain structures and changed our thinking on the electrical properties of central neurons. The ionic nature of different types of conductances has been investigated in cortical and thalamic neurons (Crill 1996; Gutnick and Mody 1995; Llinás 1988; Schwindt et al. 1988a,b, 1989). Multiple intracellular recordings from various cell types in neocortical slices, and from different compartments of single neurons, have revealed single-axon excitatory and inhibitory postsynaptic potentials (EPSPs and IPSPs) between identified neurons, investigated the mechanisms for coupling the inputs reaching various cortical layers, and demonstrated that synaptic transmission is differentially exerted by the same axon of a pyramidal neuron innervating another pyramidal cell and a local inhibitory interneuron, with synaptic depression in the former case and facilitation in the latter (Markram 1997; Markram et al. 1997, 1998; Thomson and Deuchars 1997; Thomson et al. 1993). These effects are important for understanding the rules underlying frequency-dependent plasticity. Paired-cell recordings revealed networks of electrically and chemically coupled inhibitory interneurons (Galarreta and Hestrin 1999; Gibson et al. 1999).

However, investigators in vitro recommended that the enthusiasm for work in slices must be tempered with caution (Connors and Gutnick 1990). They emphasized the biological and physical reactions occurring in the traumatized tissue and concluded that some neuronal properties described in vitro may be different from those seen in the living organism. Moreover, the overwhelming majority of studies have been conducted on slices from one structure, leaving all related systems aside. The disadvantages of brain slices arise not only because of absence of long-range connectivity but also from the fact that different research groups use animals at various early developmental stages, with different temperature and dissimilar extracellular bathing milieu, which, as shown in the following text (see Neocortex: changing firing patterns during different functional states), may drastically change neuronal properties.

This article addresses the effects exerted by synaptic activity on intrinsic neuronal properties with emphasis on normal and paroxysmal oscillations. In this first section, I will discuss the properties of cortical and thalamic neurons, as investigated in brain slices, when these neurons are embedded in intact-bain circuits and are subject to spontaneous shifts in behavioral states. This part mainly refers to the actions of synaptic activities arising in corticothalamic and generalized modulatory systems on the firing patterns and incidence of some neuronal classes in different types of experiments, membrane potential, apparent input resistance, backpropagation of action potentials, plateau potentials, and regularity of firing patterns. Next I will compare different oscillatory types occurring in the simplified circuits of cortical and thalamic slices with rhythmic activities during natural events that occur in brains with preserved connectivity.

Neocortex: changing firing patterns during different functional states

The morphological diversity of neocortical neurons has been recognized since Ramón y Cajal (1911), and their electrophysiological properties are quite complex (reviewed in Gutnick and Crill 1995). Since the early 1980s, the electrophysiological properties of neocortical neurons were characterized intracellularly by their responses to depolarizing current pulses, first in slices maintained in vitro (Connors et al. 1982; McCormick et al. 1985), thereafter in acutely prepared animals under deep anesthesia (Gray and McCormick 1996; Nuñez et al. 1993; Steriade et al. 1996a, 1998b) and, finally, during chronic experiments in awake cats (Steriade et al. 2001; Timofeev et al. 2001b).

Four cellular types are usually described. 1) Regular-spiking (RS) neurons constitute the majority of cortical neurons. They display trains of single spikes that adapt quickly or slowly to maintained stimulation. 2) Intrinsically bursting (IB) neurons generate clusters of action potentials, with clear spike inactivation, followed by hyperpolarization and neuronal silence. During prolonged depolarizing current pulses, the spike bursts of IB neurons may recur rhythmically at 5-10 Hz. 3) Fast-rhythmic-bursting (FRB) neurons give rise to high-frequency (300-600 Hz) spike bursts recurring at fast rates (generally 30-50 Hz). And 4) fast-spiking (FS) neurons fire thin action potentials and sustain tonically very high firing rates without frequency adaptation.

Generally, RS and IB neurons are pyramidal-shaped neurons, while FS firing patterns are conventionally regarded as local GABAergic cells (but see following text). Neurons displaying FRB firing patterns are either pyramidal-shaped neurons or local-circuit, sparsely spiny or aspiny interneurons. The firing patterns described in cats under anesthesia are similar to those described in vitro or in awake animals. As to the duration of intracellularly recorded action potentials at half-amplitude, measured during the state of natural waking in chronically implanted cats, RS neurons show modes between 0.6 and 1 ms (slightly longer spikes are fired by IB neurons); in contrast, both FRB and FS neurons demonstrate much shorter action potentials, with modes at about 0.3 ms (Steriade et al. 2001).

The preceding classification in four neuronal types had a temporarily heuristic value. However, data discussed below show that this systematization does not implicate strict, distinctly different, categories. Initially, electrophysiologists were impressed by the peculiar properties of some cortical neurons. Because of the virtual absence of spontaneous activity in slices, the characterization of these neurons could not take into consideration the role of synaptic activities generated in neocortex and/or thalamus in modifying the firing patterns resulting from intrinsic cellular properties. The morphological correlate, laminar location, and electrophysiological feature of IB neurons have been thought to be so precise that they were qualified as the signature of layer V and having a unique physiology (Connors and Amitai 1995). This is possibly why consciousness was thought by some theoreticians to result from the activity of a special (bursting) neuronal type (Crick 1994; Crick and Koch 1998). These authors wondered whether the visual representation is largely confined to certain neurons in deep cortical layers and further suggested that there are special sets of awareness neurons in the cortex, specifying layer V bursting cells. It would be a mystery why a peculiar cell class, IB neurons, which do not exceed 5% of cortical neurons in awake preparations (Steriade et al. 2001), would be so privileged that their activity gives rise to global states of awareness and consciousness.

In reality, each of the aforementioned firing patterns does not necessarily apply to a single class of neurons; the electrophysiological characteristics of different cortical cell types are much more flexible than conventionally thought; their location is far from being exclusively confined to distinct cortical layers; and their relative proportions vary with the type of preparation (intact cortex or isolated cortical slabs, anesthetized or nonanesthetized animals).

Thus although FS-firing neurons were previously equated to GABAergic interneurons, it is now known that some local-circuit inhibitory neurons fire like RS or bursting cells (Thomson et al. 1996). That the firing pattern of one neuronal type may be transformed, under certain physiological conditions, into another type became obvious from investigations on various neuronal classes. A reorganization of firing patterns may occur with shifts in the state of vigilance, from deafferented to brain-active behavioral states. The maintained depolarization of IB neurons results in burst inactivation (Mason and Larkman 1990; Timofeev et al. 2000) (Fig. 1A). It was then proposed that thick layer V neurons could operate in two modes, switching between bursts and tonic discharges, as a function of modulatory neurotransmitters (Mason and Larkman 1990). Indeed, the enhanced synaptic activity during brain activation by setting into action the ascending brain stem reticular systems (Steriade et al. 1993a), and in vitro application of some neurotransmitters (Wang and McCormick 1993) released in the intact brain by generalized activating systems (Steriade and McCarley 1990), are all conditions that may transform IB into RS firing patterns (Fig. 1B).



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Fig. 1. Transformation of bursting to tonic firing patterns in neocortical neurons by changing the membrane potential (Vm) and synaptic activity. A: responses of intrinsically bursting (IB) neuron in isolated cortical slab from suprasylvian gyrus in vivo (cat under ketamine-xylazine anesthesia) to the same intensity of depolarizing current pulse (0.5 nA) at the resting Vm (-70 mV) and under slight depolarization (+0.2 nA, -63 mV). A typical burst is expanded at right (right-arrow). B: area 7 neuron in cat under urethan anesthesia recorded in vivo. An IB cell (as identified by depolarizing current pulses) fired spike bursts during the slow-sleep oscillation and transformed this burst firing into tonic, single-action potentials following brain activation produced by stimulation (horizontal bar, 1.8 s, 30 Hz) of the pedunculopontine tegmental (PPT) nucleus. right-arrow, an expanded detail showing a spike burst followed by single spikes. A, modified from Timofeev et al. (2000). B, modified from Steriade et al. (1993a).

The idea of transformation from IB into RS firing patterns, based on previous results from anesthetized animals (Steriade et al. 1993a), is now substantiated by a similar transformation during shifts from the natural state of slow-wave sleep to either wakefulness or rapid-eye-movement (REM) sleep when the membrane potential of cortical neurons is slightly depolarized (Steriade et al. 2001). Figure 2 shows different (IB and RS) firing patterns of the same neuron, evoked by depolarizing current pulses applied during slow-wave and REM sleep, respectively. Also, the mode of interspike intervals during the spontaneous activity in slow-wave sleep was at 3-3.5 ms, reflecting the presence of spike bursts, while this mode was absent in REM sleep, and there were many more longer intervals (20-100 ms) during REM sleep, reflecting the single spike firing in the latter state.



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Fig. 2. Changes in firing patterns of an IB cortical neuron from area 7 during slow-wave sleep (SWS) and rapid-eye-movement (REM) sleep in chronically implanted cat. Top: electroencephalo- and electromyographic (EEG and EMG) patterns characterizing the 2 states as well as intracellular recording of this neuron together with 3 depolarizing current pulses (indicated by current monitor). Below: responses to depolarizing current pulses (the 1st response is indicated by * in the top panel). Note spike doublets in SWS and single spiking in REM sleep. Bottom: examples of spontaneous firing of this neuron during SWS and REM sleep. The interspike interval histograms in each state show a mode at 3-3.5 ms in SWS (reflecting bursting activity), absence of this mode in REM sleep, and many more longer intervals (20-100 ms) in REM sleep, reflecting single spike firing. Modified from Steriade et al. (2001).

Moreover, antidromically identified and intracellularly stained corticothalamic (glutamatergic and excitatory) neurons, recorded in vivo, may fire like FRB neurons in response to depolarizing current pulses, but below that level they fire like RS neurons and, at more depolarized levels, like FS neurons (Fig. 3A). Similar voltage-dependent changes, from RS to FRB and further to FS firing patterns, are observed in formally identified local-circuit basket cells (Fig. 3B) (Steriade et al. 1998b). Work in cortical slices also showed that RS neurons may develop their type of discharges into those of FRB neurons by repeated application of depolarizing current pulses (Kang and Kayano 1994). The transformation of output pattern, from RS single-spike firing to FRB burst discharges (Fig. 3), may render unreliable cortical synapses reliable (Lisman 1997). In vitro, FRB neurons are not seen in animals that are <4 mo of age (Brumberg et al. 2000). An additional factor that complicates the recording of this neuronal type in cortical slices is the composition of the ionic medium that requires 1.2 mM [Ca2+]o, while most in vitro studies use [Ca2+]o of 2 mM or more. Therefore a certain level of increased excitability in neuronal tissue by decreasing [Ca2+]o (Hille 1992) may lead to the transformation of neuronal firing patterns, from an RS into an FRB type. With an ionic composition in vitro closer to that in the intact brain, FRB neurons could eventually be recorded in slices (Brumberg et al. 2000).



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Fig. 3. Corticothalamic neurons and local-circuit (basket-type) neurons display fast-rhythmic-bursting (FRB) firing patterns that develop into fast-spiking (FS) patterns. Intracellular recordings in cats under ketamine-xylazine anesthesia. A: corticothalamic neuron from area 7, projecting to the lateroposterior (LP) nucleus. Depolarizing current pulses at different intensities (shown) elicited changing patterns, from single spikes (1) to spike-bursts at 25-35 Hz (2 and 3) and, eventually, FS patterns (4). A depolarizing afterpotential (DAP) is indicated by down-arrow  in 1. Below: antidromic identification of a corticothalamic neuron, displaying the same changes in firing patterns. Stimulus (black-triangle) was applied to the thalamic LP nucleus. Note failure of antidromic response membrane potentials more negative than -58 mV and appearance of excitatory postsynaptic potentials (EPSPs). This is an example of neuron interposed in a corticothalamocortical loop. B: morphologically local-circuit (basket-type) cell located in layer III of area 7. Spontaneous action potentials showed their very brief duration (0.3 ms at half-amplitude; not depicted). Changes in firing patterns, from regular-spiking (RS in 1) to FRB (2-3) and finally to FS patterns (4), similarly to those shown in A for a corticothalamic neuron. DAPs are marked (down-arrow ) in 2 and 3. Right: camera-lucida reconstruction of this neuron (see photomicrograph in Steriade et al. 1998b). Modified from Steriade et al. (1998b).

The difficulty in maintaining the strict classification in four distinctly separate cortical cell classes (RS, IB, FRB, and FS) also stems from the fact that neurons with thin (<0.5 ms) action potentials and tonic firing without frequency adaptation (like FS-firing cells), conventionally regarded as local GABAergic neurons, were actually identified as corticothalamic cells (see Fig. 3A). The transformation from FRB to FS patterns was similarly demonstrated in intracellularly stained corticothalamic and local-circuit aspiny or sparsely spiny basket (presumably inhibitory) neurons (Fig. 3, A and B). Note that these transformations in discharge patterns, from those defining the firing of a cell type into another, are not just the result of delivering current pulses because similar changes in membrane potential occur spontaneously when an animal passes from natural slow-wave sleep, characterized by prolonged hyperpolarizing episodes, to either waking or REM sleep (Steriade et al. 2001) (see also following text, Fig. 16). The difficulty of considering a simple dichotomy between the two major cell groups, long-axoned pyramidal (RS) and GABAergic local-circuit (FS) neurons, arises not only from the diversity of inhibitory interneurons in the neocortex (Jones 1988, 1995), expressing different electrophysiological features in at least five anatomical classes (Gupta et al. 2000), but also from the fact that intracellularly stained cells, with the same FRB firing pattern, proved to be either deeply lying pyramidal cells or local-circuit basket cells (Steriade et al. 1998b) (Fig. 3). As remarked in a study by Markram's group working in cortical slices (Gupta et al. 2000), the usual classification of RS, IB, and FS neurons, stemming from previous in vitro experiments (Connors et al. 1982; McCormick et al. 1985), is too vague to encompass the diversity of responses.

Network activity during various functional states is decisive in altering the firing patterns generated by intrinsic neuronal properties. Thus typical FRB patterns, which are evoked during the silent background activity of interspindle lulls (as in slices), are dramatically changed during epochs with rich synaptic activity produced by intracortical or thalamocortical volleys (Fig. 4) and develop into patterns resembling the FS firing (Steriade et al. 1998b).



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Fig. 4. Changes in responses of a corticothalamic neuron from area 21 (antidromically identified from the LP nucleus) to depolarizing current pulses with different intensities during periods poor and rich in synaptic activity. Cat under barbiturate anesthesia. Field potentials were simultaneously recorded from the related thalamic LP nucleus and from the depth of cortical areas 5, 7, and 21 (the latter in the immediate vicinity of the impaled neuron). Depolarizing current pulses (duration, 200 ms) with 3 intensities (0.4, 1 and 1.2 nA) were applied during interspindle lulls, with negligible or absence of synaptic activity (as in slices), and during spindle sequences, rich in synaptic activity generated by thalamocortical volleys. Note the transformation from rhythmic (35 Hz) spike bursts into tonic firing (450 Hz) without frequency adaptation during neuronal silence, and disruption of intrinsically generated rhythmic spike bursts by network synaptic activity. Modified from Steriade et al. (1998b).

To fully realize the importance of synaptic activity in a living animal, compared with slices, and the striking difference in connectivity as well as incidence of synaptic potentials between slightly different sizes of slices, here are the results of two in vitro studies on sensorimotor neocortex (Thomson 1997; Thomson et al. 1996). Out of 595 dual recordings in which an interneuron was recorded simultaneously with a pyramidal neuron in slices 400-µm thick, 39 yielded monosynaptic, single axon IPSPs, i.e., an average probability of 1:15 of each recorded inhibitory interneuron contacting a neighboring pyramidal cell; however, with slices 500-µm thick, the probability rose about three times. Thomson also reported a significantly higher incidence of connections and an increase in spontaneous activity in 500-µm, compared with 400-µm, slices. The dramatic increase in connectivity on increasing the slice thickness by just 0.1 mm may explain the differences between some results from slices, compared with those from the intact brain. Other dissimilarities, from works in the cerebral cortex, thalamus and related systems, are fully discussed elsewhere (Steriade 2001).

The preceding data show that changes in membrane potential and a high degree of synaptic activity in the intact brain decisively modulate, and even transform, the firing patterns due to intrinsic neuronal properties and expressed by responses to direct depolarization. The ideas on the discrete laminar localization of various neuronal types in neocortex also evolved. IB neurons were initially found in layer V, but IB neurons were later recorded also from layers IV and III (Connors and Amitai 1995; Montoro et al. 1988; Steriade et al. 1993e). The FRB neurons (also termed "chattering") were described as exclusively located in supragranular layers II-III of the visual cortex (Gray and McCormick 1996), but the same type of rhythmic bursting neurons was found in all cortical layers, from II to VI, of sensory-motor and association areas (Steriade et al. 1998b); their deep location is corroborated by antidromic identification as corticothalamic neurons (see Fig. 3A).

The proportions of FS and IB firing patterns in nonanesthetized, awake animals (Steriade et al. 2001) are quite different from those found in anesthetized animals with intact cortex (Nuñez et al. 1993; Steriade et al. 1998b) or small isolated slabs in vivo (Timofeev et al. 2000); the latter type of experiments partially reproduce the in vitro condition. Neurons displaying the firing patterns of FS neurons are much more numerous in naturally alert animals (24%) than in the intact cortex of anesthetized animals (12%) or in small isolated cortical slabs (4%). The FS (putative inhibitory) neurons have been implicated in the generation of fast (20-40 Hz) rhythms (Buzsáki and Chrobak 1995; Llinás et al. 1991; Lytton and Sejnowski 1991; Traub et al. 1999) that characterize the spontaneous activity in the waking state and dreaming mentation in humans and animals (Llinás and Ribary 1993; Steriade et al. 1996a,b). These states of network activity, accompanied by relatively depolarized levels of membrane potential, may transform neurons with other firing patterns (i.e., FRB) into FS-type neurons (see Fig. 3). This would result in an increased proportion of neurons identified as FS. On the contrary, neurons displaying IB firing patterns are found in <5% of neurons of awake animals (Steriade et al. 2001), whereas they represent ~15% of neurons in anesthetized animals (Nuñez et al. 1993; Steriade et al. 1998b) and may reach 40% of neurons in isolated cortical slabs in vivo (Timofeev et al. 2000) or in some studies in vitro that reported proportions of <= 64% IB neurons (Yang et al. 1996). The strikingly diminished proportion of IB firing patterns in the alert condition is likely due to the enhanced synaptic activity and increased release of some modulatory neurotransmitters, i.e., conditions that may transform IB into RS firing patterns (Steriade et al. 1993a; Wang and McCormick 1993).

To sum up, the bursting and regular (tonic) firing patterns represent a continuum of discharge properties and the electrophysiological distinctions between various neuronal classes are much less clear-cut in nonanesthetized animals than were conventionally thought in the early studies on cortical slices or in anesthetized preparations.

The impact of spontaneous synaptic activity on intrinsic neuronal properties was further studied with emphases on the membrane potential (Vm), the apparent input resistance (Rin, a measure resulting from passive electrical neuronal properties and balanced changes in excitatory and inhibitory inputs from specific and modulatory pathways), backpropagation of action potentials from the axonal initial segment to dendrites, and plateau potentials after blockage of K+ currents. These issues are discussed below.

MEMBRANE POTENTIAL AND INPUT RESISTANCE. The isolated cortical slab in vivo (10 × 6 mm) is a new preparation that was introduced to examine the necessary number of interconnected neurons for the presence of sleep-like oscillations and that has the advantages of both in vitro and in vivo preparations; that is, it does not drastically change the milieu of the neurons in the network (Timofeev et al. 2000). In this preparation, triple intracellular recordings have been first performed in vivo. The mean Vm in small isolated neocortical slabs in vivo is -70 mV and the Rin is 49 MOmega , whereas in intact (adjacent) cortical areas of the same animal the values are -62 mV and 22 MOmega , respectively. In another study (Paré et al. 1998b), the differences between in vivo and in vitro recordings of the same type of pyramidal neurons are as follows: the standard deviation of the intracellular signal is 10-17 times lower in vitro than in vivo and the Rin measured in vivo during relatively quiescent periods (37 ± 3.9 MOmega ) is reduced by <= 70% during epochs associated with intense synaptic activity, and increases by <= 70%, approaching the in vitro values (66.14 ± 1.3 MOmega ), after tetrodotoxin (TTX) application in vivo (Fig. 5).



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Fig. 5. Comparison of spontaneous synaptic activity displayed by neocortical neurons in vivo and in vitro and impact of synaptic activity on the resting properties of neocortical neurons. A: intracellular recording of an infragranular RS neuron from cat suprasylvian gyrus under barbiturate anesthesia, together with EEG activity (rest, -64 mV). B: intracellular recording of an infragranular neuron from a slice of cat suprasylvian gyrus, recorded at 34°C (rest, -76 mV). C: intracellularly stained suprasylvian cortical neuron with Neurobiotin in vivo. D: effect of tetrodotoxin (TTX) dialysis in vivo on apparent input resistance (Rin) of an infragranular RS neuron and on amplitude of response to a cortical stimulus (D1) and voltage response to a hyperpolarizing current pulse of constant amplitude (0.2 nA; D2). down-arrow  the onset of TTX dialysis. Insets: comparison of cortically evoked response and voltage response to current pulses before and 20 min after onset of TTX dialysis (averages of 20 sweeps, same scaling). Modified from Paré et al. (1998b).

One would expect that Rin will be diminished during the state of wakefulness, when so many conductances are open because of the increased synaptic activity due to inputs from thalamocortical, intracortical, and generalized activating systems. This simple assumption does not take into consideration that some neuromodulators released during brain-active states (such as the cholinergic neurons of nucleus basalis and thalamocortical neurons releasing glutamate acting at metabotropic receptors) increase the Rin of cortical neurons (McCormick 1992; Steriade et al. 1997b) and thus may lead to unexpected effects.

We therefore investigated the Rin during the tonic depolarization in the natural state of quiet waking of chronically implanted cats and compared it to the Rin during REM sleep and the depolarizing components of the slow oscillation (<1 Hz) in resting (non-REM) sleep (Steriade et al. 2001) (Fig. 6). Natural states of vigilance are diverse with qualitatively different epochs even within the same state of vigilance. This is the case of the hyperpolarizing and depolarizing phases of the slow oscillation in non-REM sleep or of the epochs without or with ocular saccades in REM sleep. The results of this recent study are as follows.



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Fig. 6. Apparent input resistance (Rin) of neocortical neurons during natural states of vigilance in chronically implanted cat. Top: 3 periods of intracellular recording from the same RS neuron during SWS, REM sleep and waking. Rin was measured by applying 0.1-s hyperpolarizing current pulses, every 0.5 s. Bottom: averages of responses of this neuron during different epochs in the 3 states of vigilance (note differences between the hyperpolarizing and depolarizing phases of the slow oscillation in SWS and between epochs with and without ocular saccades in REM; see text). Modified from Steriade et al. (2001).

In a sample of 24 neurons, the Rin was almost double during the hyperpolarizing phase of the slow oscillation in non-REM sleep (30.8 ± 4.3 MOmega ) compared with the depolarizing phase of this oscillation (16.8 ± 2.3 MOmega ). This indicates that GABAergic processes do not mediate the prolonged hyperpolarizations as the latter are associated with increased membrane conductance. Moreover, recordings with Cl--filled pipettes showed that the prolonged and cyclic hyperpolarizations during natural slow-wave sleep remained largely unaffected (see following text, Fig. 16) (Timofeev et al. 2001b). However, a very short part in the initial phase of the long-lasting hyperpolarization was reduced when recording with Cl--filled pipettes in anesthetized animals (see Fig. 8 in Steriade et al. 1993e), suggesting that, under anesthesia, the prolonged hyperpolarizations may be initiated by (but not entirely ascribed to) GABAA-mediated IPSPs. Studies on anesthetized animals showed that none of the formally identified, intracellularly stained basket (local inhibitory) interneurons fired during the prolonged hyperpolarizing phase of the slow oscillation (Contreras and Steriade 1995). The increased Rin during the hyperpolarizing phase, compared with the depolarizing one (Contreras et al. 1996b), indicates that disfacilitation is the major mechanism underlying the prolonged hyperpolarizing phases during slow-wave sleep. The disfacilitation may be explained by a decrease in extracellular [Ca2+]o during the hyperpolarization, following a progressive depletion of [Ca2+]o during the depolarizing phase of the slow oscillation (Massimini and Amzica 2001). This would produce a decrease in synaptic efficacy, and an avalanche reaction would eventually lead to the functional disconnection of cortical networks.

The Rin was higher (26.4 ± 2.1 MOmega ) during tonically activated REM sleep epochs, without ocular saccades, compared with periods with ocular saccades (15.8 ± 2.4 MOmega ). This indicates that an increased membrane conductance occurs during saccades (Steriade et al. 2001), and, indeed, FS interneurons impose GABAergic inhibitory potentials onto pyramidal neurons during ocular saccades (Timofeev et al. 2001b). Earlier work, using extracellular recordings in chronically implanted, naturally aroused and sleeping animals also showed that putative local interneurons in neocortex fire quasi-selectively during the ocular saccades in REM sleep (Steriade 1978).

In contrast to the two sleep states, the Rin was remarkably stable during the steady state of waking, and it reached higher values (31.3 ± 2.4 MOmega ) than in REM sleep or the depolarizing phase of the slow oscillation in non-REM sleep (Fig. 6). The explanation of the increase in Rin in these experiments on nonanesthetized, naturally alert animals is probably the higher release of acetylcholine (ACh) in cortex during wakefulness (Jasper and Tessier 1971) and the ACh-induced increase in Rin of neocortical neurons (Krnjevic' et al. 1971; McCormick 1992). The increased Rin during wakefulness may be related to earlier extracellular recordings showing an enhanced antidromic and synaptic responsiveness of monkey's neocortical neurons during this behavioral state, compared with slow-wave sleep (Steriade et al. 1974).

BACKPROPAGATION OF ACTION POTENTIALS. The backpropagation of action potentials (APs) has two aspects. The first refers to the propagation of APs generated at ectopic sites (regions remote from the axon hillock) toward the soma. Ectopically generated APs generally occur in pathological conditions, such as thalamic (Gutnick and Prince 1972; Schwartzkroin et al. 1974) or callosal (Schwartzkroin et al. 1975) neurons projecting to cortical epileptic foci. The second aspect of backpropagation, which is still a disputable issue because of differences in results from in vitro and in vivo experiments (see following text), is the initiation of APs in the axon hillock and its propagation into the dendrites of various neuronal types, thus providing a retrograde signal of neuronal output to the dendritic tree (Häusser et al. 2000; Stuart and Sakmann 1994; Stuart et al. 1997). The functional consequences of APs, backpropagated from the axon hillock to dendrites, may be an influx of Ca2+ without evoking a Ca2+ AP (Larkum et al. 1999). This would imply a facilitation of the initiation of Ca2+ APs when backpropagating APs coincide (within a time window of ~10 ms) with distal dendritic inputs and is regarded as a mechanism for coupling inputs reaching cortical neurons at different layers. The backpropagating APs may signal the level of neuronal output to the dendritic sites receiving synaptic inputs, thus serving as a link between output and input.

On a priori grounds, the backpropagation of APs into the distal dendritic tree, shown in slices in which the spontaneous activity is poor or absent, would be weakened or canceled in vivo because of the continuous bombardment of EPSPs and IPSPs. Corticospinal and corticothalamic cells fire during natural states of vigilance at rates 5-10 Hz (Evarts 1964; Steriade 1978; Steriade et al. 1974, 2001), and, as each AP leaves in its wake a period of decreased availability of Na+ channels, this would significantly alter the backpropagation of APs into the dendrites. Dendritic Ca2+ dynamics in neocortical vibrissae cortex was investigated in studies performed in vivo and showed that the greatest number of APs in response to whisker deflections occurred in the proximal part of apical dendrites, while it decreased steeply with increasing distance from the soma (Svoboda et al. 1997, 1999). These studies showed that, in vivo, APs do not evoke significant Ca2+ transients in distal dendrites. The failure of backpropagation in pyramidal cells of supragranular layers in the neocortex is due to shunting excitatory and inhibitory synaptic activities that occur spontaneously in vivo, to the actions of generalized modulatory systems, as well as to other factors changing dendritic channel properties. The inhibitory control of voltage-dependent Ca2+ influx into the dendrites and the strong attenuation of backpropagation of fast APs in vivo was also reported in studies on CA3-CA1 hippocampal pyramidal neurons, both in acute and chronic preparations (Buzsáki et al. 1996; Kamondi et al. 1998). The effect of synaptic inputs on soma-dendritic interactions was investigated using both intracellular recordings and computational models and led to the conclusion that IPSPs of sufficient amplitude can reduce or prevent the backpropagation of APs into the dendrites (Paré et al. 1998b). Stimuli applied to deep cortical layers were most effective at reducing the amplitude of APs generated by layer V neurons. Simulations related to these experimental results found that "proximal" IPSPs were effective in preventing the backpropagation of somatic APs to distal parts of the dendritic arbor.

PLATEAU POTENTIALS. Plateau potentials in neocortical neurons are elicited after blockage of K+ currents and are due to a class of high-voltage-activated Ca2+ channels in dendrites (Reuveni et al. 1993; Yuste et al. 1994). The high background activity in vivo may block the Ca2+ plateau potentials. Synaptic inputs lead to the termination of plateaus (Paré et al. 1998a). Using dual intracellular recordings in vivo, with one pipette filled with potassium acetate to control network activity and the other pipette filled with cesium acetate to block K+ currents, we showed that synaptic inputs, generated by corticipetal volleys during thalamically generated spindle oscillations, consistently shut off plateaus (Contreras et al. 1997c). Similarly, PSPs evoked by electrical thalamic stimulation blocked the Cs+-induced plateaus (Fig. 7). The dendritic Ca2+ electrogenesis in cortical neurons (Kim and Connors 1993; Llinás 1988) may play an important role in synaptic plasticity (Swanson 1989). The fact that Cs+-induced plateaus are blocked (but sometimes triggered) by synaptic inputs suggests that coherent oscillations in thalamocortical networks may have a role in plasticity by modifying Ca2+ electrogenesis.



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Fig. 7. Thalamic-evoked PSPs block the plateau potentials evoked by blockage of K+ currents. Cat under barbiturate anesthesia. A: depolarizing current pulses of constant amplitude and duration were applied at rest to 2 simultaneously recorded cells, 1 with cesium acetate (cell 1)- and the other with potassium acetate (cell 2)-filled pipettes. Stimulation of thalamic LP, delivered during the depolarizing pulse, blocked the plateaus in cell 1, while eliciting an EPSP and a spike burst in cell 2. Consecutive sweeps were displaced vertically and horizontally for clarity. B: 5 depolarizing pulses of increasing amplitude were applied to both cells. In cell 1, pulses triggered plateaus with progressively shorter latency that were shut off by thalamic stimulation. In cell 2, responses to pulses were passive except for a highest-amplitude pulse that triggered a direct spike; thalamic-evoked EPSPs became suprathreshold with increasing depolarization (up-arrow , response during highest amplitude pulse). Pulse protocols indicated in A and B. From Contreras et al. (1997c).

REGULAR FIRING PATTERNS DURING BRAIN-ACTIVE BEHAVIORAL STATES. The reliability of firing patterns increases with fluctuating current waveforms resembling synaptic activity (Mainen and Sejnowski 1995). Suprathreshold current pulses to the soma elicit spike trains with a progressive lack of reliability in precise timing, whereas fluctuating current waveforms evoke precise and stable timing throughout the length of the trials (Fig. 8). In the latter condition, the action potentials may be separated by 100 ms, yet they occur with the precision of most responses in the range of 1-2 ms (see also Nowak et al. 1997). These data suggest that currents resembling synaptic inputs may be repeatedly encoded into spike patterns with millisecond precision. The results regarding the regularity of firing evoked by depolarizing current pulses with added fluctuating waveforms, which simulate synaptic activity, fit well with the relative regularity of firing seen during behavioral states of vigilance associated with a high degree of synaptic activity as in wakefulness and REM sleep (Evarts 1964; Steriade 1978; Steriade et al. 1974). The firing regularity during these two brain-active states is expressed by Gaussian-like interspike interval histograms with virtual absence of very short (<25 ms) and very long (>150 ms) intervals (see Fig. 7 in Steriade et al. 1974). During slow-wave sleep, when the cerebral cortex is disconnected from the outside world because of the blockade of synaptic transfer within the thalamus (Steriade et al. 1969; Timofeev et al. 1996), there is a much greater irregularity of firing patterns because the presence of spike bursts, reflected by very short interspike intervals, interspersed with long periods of silence.



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Fig. 8. Reliability of firing patterns of cortical neurons evoked by constant and fluctuating current. A: a suprathreshold DC current pulse (150 pA, 900 ms) evoked trains of action potentials (~14 Hz) in a RS neuron from layer V of rat visual cortex, in vitro. Responses are shown superimposed (1st 10 trials, top) and as a raster plot of spike times over spike times (25 consecutive trials, bottom). B: the same cell as in A was again stimulated repeatedly, but this time with a fluctuating stimulus (Gaussian white noise). From Mainen and Sejnowski (1995).

Thalamus: effects of synaptic inputs on neuronal properties and local oscillations

There are three main classes of thalamic neurons: thalamocortical (TC), which are all glutamatergic, thus excitatory; thalamic reticular (RE), which send their axons to the dorsal thalamus and are all GABAergic, thus inhibitory; and local-circuit GABAergic neurons whose axonal domain is confined within the limits of the thalamic nucleus where their somata are located. With few exceptions, the three types of thalamic neurons are homogenous in terms of morphology (Jones 1985) and electrophysiological properties (Steriade et al. 1997b). This stands in contrast with the variety and complexity of neocortical neurons.

Most schemes of thalamic functioning include only TC and RE neurons. However, all dorsal thalamic nuclei of cats and primates (and the lateral geniculate nucleus of rodents) also possess an important proportion (25%) of local-circuit inhibitory interneurons (Jones 1985). About 8-10% of RE neurons project to local thalamic interneurons (Liu et al. 1995), and although apparently minor, this GABAergic-to-GABAergic projection may produce significant effects on the ultimate targets, TC neurons, eventually leading to their disinhibition. Indeed, a greatly increased incidence of IPSPs in TC neurons was observed after destruction of RE neurons, reflecting the release from the inhibition of local interneurons after the excitotoxic lesion of RE perikarya (Steriade et al. 1985). The connection between the two types of thalamic GABAergic cells, RE and local-circuit interneurons, may be important for focusing attention to relevant signals (Steriade 1999). Figure 9 illustrates this hypothesis. The top RE neuron, part of the RE pool that is directly connected to the top TC (Th-cx) neuron, contributes to enhancement of relevant activity by inhibiting the appropriate pool of local-circuit elements. Simultaneously, the activity in adjacent RE areas is suppressed by RE-to-RE GABAergic contacts within the nucleus. The consequence would be the disinhibition of related local interneurons (bottom L-circ cell) and the inhibition of weakly excited TC neurons in areas adjacent to the active focus.



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Fig. 9. Relations between GABAergic thalamic reticular (RE) and local-circuit (L-circ) neurons, and their effects on thalamocortical (Th-cx) neurons. The top Th-cx in the figure receives prevalent excitation from the afferent fiber (Aff.) while the bottom Th-cx receive less collaterals from the Aff. axon. The RE neurons, which are directly connected to the top Th-cx neuron (the top RE neuron is part of this pool), contribute to further enhancing the relevant activity by inhibiting the pool of L-circ elements (the top L-circ neuron is part of this pool). Simultaneously, the activity in adjacent RE areas (bottom RE neuron) is suppressed by axonal collateralization and dendro-dendritic synapses within the RE nucleus. The consequence would be the released activity of target L-circ neurons (bottom L-circ cell) and inhibition of weakly excited Th-cx neurons (bottom Th-cx neurons) in areas adjacent to the active focus. This hypothesis derived from a study on the activity of RE neurons during the natural waking-sleep cycle of chronically implanted cats (Steriade et al. 1986). The circuit was proposed in Steriade (1991) and was redrawn by E. G. Jones.

Here, I will focus on the impact exerted by synaptic activity, arising locally or in distant structures, on a major intrinsic property of thalamic neurons (the low-threshold spike, LTS) as well as on related oscillatory phenomena in these neurons, the network generated sleep spindles and the intrinsically generated clock-like (delta) rhythm. Other intrinsic properties of TC and RE neurons, their ionic bases, and the biophysical models of ionic currents, are discussed in two recent monographs (Destexhe and Sejnowski 2001; Steriade et al. 1997b).

THE LTS. The ability of thalamic neurons to display a paradoxical form of excitation resulting from their hyperpolarization was known since the late 1960s (Andersen and Andersson 1968; see also Maekawa and Purpura 1967), but systematic studies on the postinhibitory rebound and the discovery of the Ca2+-dependent low-threshold current (IT) underlying this intrinsic neuronal property were only possible with the advent of slice studies (Jahnsen and Llinás 1984a,b; reviewed in Huguenard 1996; Llinás 1988). More recent studies reported that the LTS of TC neurons also contains a component mediated by a persistent Na+ current (INa(p)) (Parri and Crunelli 1998).

Tonic firing at depolarized levels, at which IT is inactivated, and burst firing at hyperpolarized levels, at which IT is de-inactivated, were also described in vivo (Deschênes et al. 1984; Steriade and Deschênes 1984). The Ca2+-mediated rebound LTS, which is de-inactivated by membrane hyperpolarization, is probably the best example of a similarity between results obtained in vitro and in vivo. In intact-brain preparations, the LTSs crowned by Na+-mediated spike bursts are indispensable for the transfer of thalamically generated oscillations to the cerebral cortex. The LTS' refractory period was found to be quite long (170-200 ms) in most thalamic neurons. A special class of large-size TC neurons, recorded in vivo from the dorsolateral part of cat centrolateral (CL) intralaminar nucleus, has a much shorter refractory period of the LTS (60-70 ms), which allows them to display unusually high-frequency spike bursts (900-1,000 Hz) in virtually all successive spindle oscillations at a frequency of 10 Hz or even higher (Steriade et al. 1993c). Very-high-frequency spike bursts in CL thalamic neurons were also found in rats, and these rostral intralaminar neurons displayed a differential behavior, compared with other TC neurons, during spike-wave seizures in a genetic model of absence epilepsy (Seidenbecher and Pape 2001).

The LTS appears at a given level of hyperpolarization of thalamic neurons (generally at a Vm more negative than -70 mV), and, to be elicited, it requires a certain intensity of direct depolarization or EPSP. The LTSs of RE neurons generate peculiar spike bursts during natural slow-wave sleep compared with those of TC neurons (Domich et al. 1986), and they are located in dendrites (Huguenard and Prince 1992). Presumed intradendritic recordings of RE neurons in vivo revealed the graded nature of dendritic LTSs and showed that the prolonged spike bursts of these GABAergic neurons are modulated by synaptic activity, mainly arising in corticothalamic projections, thus generating a broad range of integrative properties (Contreras and Steriade 1996; Contreras et al. 1992, 1993). In TC neurons too, the time to peak as well as amplitudes of LTSs are graded (Fig. 10) and influenced by the degree of synaptic activity. This makes LTSs highly variable; this is a major factor in the desynchronization of oscillatory neurons and, consequently, the termination of spindle sequences (Timofeev et al. 2001a). That synaptic activity is effective in greatly modifying the LTSs is also demonstrated by reduction or abolition of LTSs and the crowning spike bursts under the influence of fast oscillations (<= 100 Hz), which consist of EPSPs arising cerebellothalamic neurons (Timofeev and Steriade 1997). Barrages of EPSPs tonically depolarize TC neurons prevent the appearance of spindles in intracellularly recorded TC neurons, and disrupt the long-range synchronization of this sleep oscillation (Bazhenov et al. 2000). Powerful effects are also exerted by GABAA-B-mediated IPSPs that, because of the associated increased membrane conductance (Crunelli and Leresche 1991; Uhlrich and Huguenard 1997), have a shunting influence on LTSs by significantly delaying them, thus also contributing to the desynchronization of rhythmic thalamic activity.



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Fig. 10. Low-threshold spikes (LTSs) in cat thalamocortical (TC) neurons are graded in amplitude during spindle oscillation. A: ketamine-xylazine anesthesia. Intracellular recording from the thalamic ventrolateral (VL) nucleus. Fluctuations in time to peak and amplitude of LTS at the break of the threshold hyperpolarizing current pulse (0.8 nA, 0.1 s). Conditioning Vm is the Vm just before the end of the current pulse; amplitude of maximal depolarization was calculated from baseline Vm. B: barbiturate anesthesia. Simultaneous field potential from cortical area 4 and VL nucleus, together with intracellular from VL nucleus. Right: an expanded spindle sequence, further expanded below (down-arrow ). Modified from Timofeev et al. (2001a).

Anterior thalamic neurons display LTS-generated spike bursts with the same characteristics as those found in other thalamic neurons (Mulle et al. 1985; Paré et al. 1987). As anterior thalamic neurons do not receive synaptic inputs from the RE nucleus of cats (Steriade et al. 1984; Velayos et al. 1989) (Fig. 11) and the RE nucleus is the spindle pacemaker (see following text), spindles are absent in anterior thalamic nuclei (Fig. 11) as well as in limbic cortical areas where these nuclei project (Paré et al. 1987). Similarly, the fact that the lateral habenular neurons do not receive inputs from the RE nucleus (Velayos et al. 1989) explains the absence of spindles in those neurons despite the fact that they have similar intrinsic properties and ionic conductances as other thalamic neurons (Wilcox et al. 1988). Instead of spindles, lateral habenular neurons display fluctuations in their membrane potential within the frequency range of the theta rhythm, generated in the hippocampus.



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Fig. 11. Anterior thalamic (AT) nuclei of cat are devoid of afferences from the RE nucleus and, despite the fact that the intrinsic property of LTS is present in AT neurons, they do not display spindles because of absence of synaptic connections from the pacemaking RE nucleus. Left: the RE projections to various dorsal thalamic nuclei, as resulting from retrograde tracing experiments in cats. Heavy lines indicate prominent projections to intralaminar nuclei. Note absence of projections to AT nuclei. AD, AM, and AV: anterodorsal, anteromedial, and anteroventral nuclei; CA, caudate nucleus; CL-PC, central lateral and paracentral (rostral intralaminar) nuclei; CM-PF, center median-parafascicular (caudal intralaminar) nuclei; MD, mediodorsal nucleus; PARA, paraventricular nucleus; VA, ventroanterior nucleus; VL, ventrolateral nucleus; VM, ventromedial nucleus; VB, ventrobasal complex; RE, reticular nucleus; V3, third ventricle. Right: simultaneous recordings of field potentials (filtered for spindles, Sp., between 7 and 14 Hz) from CL and AV nuclei in cat. Unanesthetized cerveau isolé (collicular-transected) preparation. Abscissae indicate real time (hr, min, s). Data were obtained by applying each filtered EEG signal (see above CL trace, filtered EEG spindles, the 1st sequence corresponding to the 1 depicted below) to a full-wave rectifier, a voltage-controlled oscillator, and to a laboratory computer (see technical details in that paper). Note regularly recurring spindle sequences in CL nucleus and absence of spindles in the AV nucleus. Bottom: intracellular recording of an AT neuron, showing tonic firing at a relatively depolarized Vm (-60 mV), LTSs crowned by spike bursts under steady hyperpolarization when the Vm reaches -72 mV, and recovery of tonic firing at -60 mV. Modified from Steriade et al. (1984) and Paré et al. (1987).

These data emphasize the requirement of appropriate synaptic connections for the generation of synchronized oscillations. They also show the importance of connections with the RE nucleus for the induction of spindle oscillations and the fact that activities in long-range synaptic networks, rather than intrinsic properties, may generate different types of brain rhythms.

EFFECTS OF SYNAPTIC ACTIVITY IN ASCENDING AND CORTICOTHALAMIC PROJECTIONS ON TERMINATION AND WIDE SYNCHRONIZATION OF THALAMICALLY GENERATED SPINDLE OSCILLATIONS. Spindles (7-14 Hz) arise within the thalamus even after decortication and high brain stem transection (Morison and Bassett 1945). The RE nucleus is the pacemaker of spindle oscillations as demonstrated by the abolition of spindles in target thalamic nuclei and corresponding cortical areas after disconnection of TC neurons from the RE nucleus (Steriade et al. 1985) and the preservation of spindles in the RE nucleus disconnected from the remaining thalamus (Steriade et al. 1987). The different reasons explaining the failure to obtain spindles in the isolated RE nucleus of thalamic slices (Von Krosigk et al. 1993), among them the requirement of a larger and more intact collection of RE neurons than usually found in thalamic slices (see Steriade et al. 1993d) and the absence of some brain stem modulatory systems (Destexhe et al. 1984), are discussed elsewhere (Steriade et al. 1997a). Although this oscillation was recorded intracellularly within the thalamus, in the absence of cortex, both in vivo (Deschênes et al. 1984; Steriade and Deschênes 1984; Timofeev and Steriade 1996) and in vitro (Bal et al. 1995a,b; Von Krosigk et al. 1993), the neocortex contributes to the termination of individual spindle sequences, but on the other hand, it plays an important role in the synchronization of spindle sequences over widespread thalamic and cortical territories. Thus long-range projections in corticothalamic systems influence a thalamically generated oscillation, and although spindles arise in local intra-RE and RE-TC circuits, network activities originating in distant cortical areas are powerful enough to change the duration and synchronization patterns of this sleep oscillation. These data are discussed below.

The termination of spindle sequences may be ascribed to at least two factors. One of the them relies on an intrinsic property of TC neurons, the hyperpolarization-activated cation current IH, which produces a depolarizing sag (Curró Dossi et al. 1992; Leresche et al. 1990, 1991; McCormick and Pape 1990; Soltesz et al. 1991). It was proposed that during the waxing phase of spindles, the progressive hyperpolarization of TC neurons, due to spike bursts of GABAergic RE neurons, activates the IH, and this current brings TC neurons to a more positive level of membrane potential, thus preventing low-threshold spike bursts (Bal and McCormick 1996). The other factor for the termination of spindle sequences is network desynchronization, first hypothesized by Andersen and Andersson (1968), who invoked intrathalamic processes. This mechanism is partially valid, as shown by the generation of IPSPs at different delays during spindles (see Fig. 10), with the consequence of asynchronous firing between TC neurons and their targets, RE neurons. Another source of network desynchronization is the barrage of EPSPs arising in the cerebellothalamic pathway, which depolarize TC neurons, preventing them from firing rebound spike bursts and thus obliterating the operations in the TC-to-RE loop (Bazhenov et al. 2000). Probably the most important factor for the network desynchronization of spindles is corticothalamic activity. As shown in the preceding text (Figs. 3-4), at slightly depolarized levels, corticothalamic neurons fire nonaccomodating spike trains throughout the spindle sequences. These neurons may recruit other cortical neurons and bring them into an activated state that is out of phase with that of TC neurons. Dual intracellular recordings from cortical and TC neurons in vivo demonstrate that during the late phase of spindle sequences, neocortical become tonically depolarized, and this continues after the end of spindle sequence, while TC neurons terminate the spindles (Timofeev et al. 2001a). Computational models of these experimental data tested and confirmed the hypothesis that the tonic activity of corticothalamic neurons could strongly depolarize RE and TC neurons, resulting in spindle termination due to inactivation of rebound spike bursts in thalamic cells. It was then proposed that 1) the first part of a spindle sequence is generated in the pacemaker RE nucleus (Steriade et al. 1987); 2) during the first two to four IPSPs composing the spindles, TC neurons do not display rebound spike bursts (Bazhenov et al. 2000), thus they do not return signals to RE neurons and do not contribute to this phase of a spindle sequence; 3) the middle part of a spindle sequence is due to the activity in the RE-TC-RE loop (Steriade et al. 1993d; Von Krosigk et al. 1993); and 4) the termination of spindles is due to the depolarizing action of IH (Bal and McCormick 1996) and/or the desynchronizing action exerted by corticothalamic activity (Timofeev et al. 2001a).

Another function of corticothalamic projections is to facilitate the widespread synchronization of spindles. Indeed, thalamic spindles propagate in vitro (Kim et al. 1995) but are nearly simultaneous in vivo in both cats and humans (Fig. 12) (Contreras et al. 1997a). We hypothesized that the contrast between the simultaneity of spindle sequences in vivo and spindle propagation in vitro was due to the absence of the cortex in thalamic slices. In fact, after decortication in cat, the simultaneity of spindle sequences throughout the thalamus is disorganized without, however, showing systematic propagation as in thalamic slices (Fig. 12). The difference between in vivo and in vitro results was further investigated by changing the excitability of the cat neocortex. A diminished spatiotemporal coherence of spindle oscillations was observed during barbiturate anesthesia, when corticothalamic neurons display poor spontaneous activity, as well as during cortical depression produced by applying a highly concentrated potassium acetate solution (Contreras et al. 1997b). The spatiotemporal coherence of simulated oscillations was also studied in network models. Compared to in vitro conditions in which oscillatory activity begins in one or two sites and progressively invades the network, with enhanced cortical excitability, the simultaneity of oscillations is increased and the phase shift is reduced (Destexhe et al. 1999). The increased activity of corticothalamic neurons operates through inhibition of TC neurons via RE neurons, indicating that corticothalamic feedback should lead to large-scale coherent activity by recruiting thalamic circuitry through prevalent projections to RE nucleus (Destexhe et al. 1998). Recent studies, combining electron microscopy and analysis of excitatory postsynaptic currents (EPSCs), quantified the greater efficacy of corticothalamic projections acting on GABAergic RE neurons compared with the cortical projection to TC neurons (Golshani et al. 2001; Liu et al. 2001), thus eventually leading to the inhibition of TC neurons (see also Paroxysmal activities developing from sleep oscillations).



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Fig. 12. Cortical spindle sequences occur nearly simultaneously during natural sleep of humans and cats, but decortication disorganizes the widespread coherence of thalamic spindles. Top: illustrating natural sleep (human), spindles were recorded from 6 standard EEG derivations (indicated in the schematic at right, black-triangle) in a normal subject, during sleep stage 2. Cross-correlations of individual spindle sequences (n = 15) were calculated between C3A2 and each 1 of the other channels. Averaged correlations (cross) showed rhythmicity at 14 Hz and central peak values between 0.7 and 0.9. Bottom: spindles are simultaneously recorded from 7 leads in the thalamus of intact-cortex cat under barbiturate anesthesia. Note the virtual simultaneity of spindle sequences. After decortication (see scheme), recordings from virtually same thalamic sites show disorganization of spindle simultaneity. From Contreras et al. (1996a, 1997a).

These data point to the role of corticothalamic neurons in synchronizing spindle sequences, an oscillation generated in the thalamus and whose features are conventionally thought as being exclusively dependent on intrathalamic processes. This emphasizes that operations in simple thalamic circuits may be studied in vitro to reveal biophysical processes and different receptor types activated by synaptic conductances, but the real patterns and synchronization of various oscillatory types, as in real life, should be investigated in brains with intact connectivity. The major factor that accounts for the role of corticothalamic neurons in governing the widespread synchronization of spindles is the cortical slow oscillation, which is discussed in the next section.

CORTICAL SYNCHRONIZATION OF AN INTRINSIC (CLOCK-LIKE DELTA) THALAMIC OSCILLATION. The other thalamically generated oscillation is the clock-like delta rhythm (usually 2-4 Hz), due to the interplay between two currents, IH and IT, that are activated and de-inactivated, respectively, by membrane hyperpolarization (Curró Dossi et al. 1992; Leresche et al. 1990, 1991; McCormick and Pape 1990; Soltesz et al. 1991). This oscillation is modulated by different substances that act on purinergic and adrenergic receptors and up- or downregulate the H current (Pape 1996; Pape and Mager 1992; Pape and McCormick 1989; Yue and Huguenard 2001). Although intrinsic to TC neurons (Fig. 13A), this oscillation, which represents only one component of delta waves seen on the EEG during slow-wave sleep, is subject to influences arising in neocortex. Corticothalamic volleys synchronize TC neurons (Fig. 13B) by primarily exciting GABAergic RE neurons that fulfill two basic requirements: they set the Vm of TC neurons at the appropriate level of hyperpolarization for the appearance of the two currents (IH and IT) and they project to different dorsal thalamic nuclei, thus synchronizing not only nearby but also distant TC neurons (Steriade et al. 1991).



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Fig. 13. Clock-like delta oscillation (1-4 Hz) in TC neurons, and synchronization of this intrinsic oscillation in different TC neurons by corticothalamic synaptic volleys. Cats under urethane anesthesia. A: neuron from the thalamic lateroposterior nucleus. At "rest," the neuron oscillated spontaneously at 1.7 Hz. A 0.5-nA depolarizing current (between up-arrow ) prevented the oscillation, and its removal set the cell back in the oscillatory mode. Three cycles after removal of depolarizing current in 1 are expanded in 2 to show high-frequency spike bursts crowning LTSs. B: auto- and cross-correlograms of 2 cells (a and b), recorded simultaneously in the thalamic ventrolateral nucleus. Four correlograms (before and after cortical stimulation) depict, from top to bottom, autocorrelogram of cells a and b, and cross-correlograms of both cells (cell b is the reference cell) with different bins (2 and 20 ms). Note before cortical stimulation, delta rhythm (1.6 Hz) of cell a, flat contour (absence of rhythmicity in cell b), and absence of coupling between these neurons. After corticothalamic synaptic volleys, the background noise in cell a was reduced, cell b became rhythmic at the same frequency as cell a (1.6 Hz), and cross-correlograms show that cell a firing preceded cell b firing by ~10-20 ms. Modified from Steriade et al. (1991).

The preceding data demonstrate that synaptic activities in corticothalamic systems decisively control the synchronization of network oscillations generated synaptically and intrinsically within the thalamus. Further investigations in vitro should consider the role of long-range synaptic activities by enlarging thalamic slices to include the cerebral cortex.


    DEVELOPMENT OF NORMAL BRAIN RHYTHMS TO PAROXYSMAL ACTIVITY
TOP
ABSTRACT
INTRODUCTION
IMPACT OF NETWORK ACTIVITY...
DEVELOPMENT OF NORMAL BRAIN...
REFERENCES

In this section, I shall first focus on intrinsic cell properties and network operations underlying the major rhythm that characterizes sleep, the slow oscillation at 0.5-1 Hz that is present throughout all (light and deep) stages of natural slow-wave sleep in animals (Steriade and Amzica 1998) and humans (Achermann and Borbély 1997; Amzica and Steriade 1997). Although spontaneously occurring brain rhythms are sometimes regarded as bearing little or no functional significance, the spontaneous electrical activity is information-rich, provides signals that influence neighboring cells, and accounts for changes in evoked responses (Arieli et al. 1996; Bullock 1997). It was proposed that the rhythmic spike bursts or spike trains fired by thalamic and neocortical neurons during sleep oscillations lead to reorganization of neocortical networks and consolidation of memory traces formed during the waking state (Steriade et al. 1993b,d). This hypothesis was tested and will lead me to discuss the synaptic changes, related to plasticity, during sleep oscillations. Finally, I will elaborate on the development from normal sleep oscillations into paroxysmal events mimicking some types of clinical seizures associated with loss of consciousness.

Fast brain rhythms (20-60 Hz), which occur mainly, but not exclusively, during states of brain alertness (Herculano-Houzel et al. 1999; Llinás and Paré 1991; Llinás and Ribary 1993; Murthy and Fetz 1997; Rougeul-Buser 1994; Singer 1993; Steriade et al. 1996a,b), and their relation with discrete conscious events, are discussed elsewhere (Steriade 2000, 2001).

No pure rhythms, no simple circuits: the slow oscillation groups cortical and thalamic rhythms

The slow oscillation (generally 0.5-1 Hz) was initially described using intracellular recordings from cortical neurons in cats under anesthesia and EEG recordings during human natural sleep (Steriade et al. 1993e). Although the frequency of the slow oscillation may reach 1 Hz and even slightly exceed this frequency during late periods of natural sleep, the slow oscillation is different from waves in the delta frequency band (1-4 Hz), as the former groups both cortically and thalamically generated delta waves into rhythmic wave-sequences (Steriade et al. 1993e,f). This indicates the distinct nature of the two (slow and delta) oscillations. Human sleep recordings add further support for the differences between slow and delta activities: the typical decline in delta waves (2-4 Hz) from the first to the second episode during EEG-synchronized sleep is not present at lower frequencies that characterize the slow oscillation (Achermann and Borbély 1997). The slow oscillation was also recorded, with the same characteristics as initially described in animals, using magnetic (MEG) recordings during natural sleep in humans (Simon et al. 2000).

The cortical origin of the slow oscillation was demonstrated by its presence in neocortex after thalamectomy (Steriade et al. 1993f), the disruption of its long-range synchronization after interrupting corticocortical links (Amzica and Steriade 1995a), and its absence in the thalamus of decorticated animals (Timofeev and Steriade 1996). That the slow oscillation arises in intracortical networks was confirmed by the presence of this rhythmic activity in vitro using a bathing milieu more similar to that present in vivo (Sanchez-Vives and McCormick 2000) than the ion concentrations usually employed in cortical slices. Because the cortex projects to many subcortical structures, the slow oscillation was also recorded not only in the thalamus (Steriade et al. 1993b) but also in the caudate nucleus, the subthalamic-pallidus network, basal forebrain, mesopontine, and medullary brain stem nuclei (Magill et al. 2000; Mariño et al. 2000; Nuñez 1996; Steriade et al. 1994a; Wilson and Kawaguchi 1996). In many of these subcortical sites, the slow oscillation disappeared after functional inactivation of cortex or decortication.

Single and dual intracellular recordings from neocortical neurons in vivo, together with multi-site field potentials, show that the slow oscillation is built up by synchronous sequences of prolonged depolarizations and hyperpolarizations, each lasting <= 0.4-0.7 s (Amzica and Steriade 1995a,b; Contreras and Steriade 1995; Steriade et al. 1993e,f, 1994b) (Fig. 14, cat). These data, first obtained under different types of anesthetics, are now confirmed during the natural slow-wave sleep of chronically implanted cats (Steriade et al. 2001; Timofeev et al. 2001b). The long-lasting hyperpolarizations are obliterated on natural awakening in behaving animals (Fig. 15), and they appear as distinct events from the very onset of slow-wave sleep.



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Fig. 14. The cortical slow oscillation groups thalamically generated spindles. Cat 1: intracellular recording in cat under urethan anesthesia from area 7 (1.5-mm depth). Electrophysiological identification (at right) shows orthodromic response to stimulation of thalamic CL intralaminar nucleus and antidromic response to stimulation of LP nucleus. Note slow oscillation of neuron and related EEG waves. One cycle of the slow oscillation is framed in dots. Part marked by horizontal bar below the intracellular trace (at left) is expanded above (right) to show spindles following the depolarizing envelope of the slow oscillation. Cat 2: dual simultaneous intracellular recordings from right and left cortical area 4. Note spindle during the depolarizing envelope of the slow oscillation and synchronization of EEG when both neurons synchronously display prolonged hyperpolarizations. Human: the K complex (KC) in natural sleep. Scalp monopolar recordings with respect to the contralateral ear are shown (see figurine). Traces show a short episode from a stage 3 non-REM sleep. The 2 arrows point to 2 KCs, consisting of a surface-positive wave, followed (or not) by a sequence of spindle (sigma) waves. Note the synchrony of KCs in all recorded sites. At right, frequency decomposition of the electrical activity from C3 lead (see A) into 3 frequency bands: slow oscillation (S, 0-1 Hz), delta waves (Delta , 1-4 Hz) and spindles (sigma , 12-15 Hz). Modified from Steriade et al. (1993f, 1994b, cat) and from Amzica and Steriade (1997, human).



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Fig. 15. The slow oscillation during natural SWS and its obliteration during transition to wakefulness. Chronically implanted cat. Five traces depict (from top to bottom): depth-EEG from right area 7 and left areas 3 and 5; intracellular activity of RS neuron from left area 7; and EMG. Two epochs marked by horizontal bars are expanded below (down-arrow ). Cyclic hyperpolarizations characterize neocortical neurons during SWS, but their firing rate during the depolarizing phases of the slow sleep oscillation is as high as during the activated behavioral state of waking. Note phasic hyperpolarizations in area 7 neuron, related to depth-positive EEG field potentials, during SWS, tonic firing on awakening marked by EEG activation and increased muscular tone, and slight depolarization occurring only after a few seconds after awakening and blockage of hyperpolarizations. Modified from Steriade et al. (2001).

All major types of neocortical neurons (RS, IB, FRB, and FS; see Neocortex: changing firing patterns during different functional states) behave similarly during the slow oscillation. Namely, they discharge during the depolarizing phase associated with depth-negative field potentials and are silent during the hyperpolarizing phase associated with depth-positive field potentials. The depolarizations are due to a combination of a persistent Na+ current and N-methyl-D-aspartate (NMDA)- as well as non-NMDA-mediated EPSPs, but they also include IPSPs (Steriade et al. 1993e). The fact that no cellular type, including FS neurons, some of them formally identified as short-axoned basket-type neurons (Contreras and Steriade 1995), discharges during the hyperpolarization (Fig. 16B) indicates that this component of the slow oscillation is not mediated by GABAergic processes. Also, the major part of the prolonged hyperpolarizing potentials is not affected by recordings with Cl--filled pipettes (Fig. 16B; see also Timofeev et al. 2001b). The hyperpolarizations are mainly produced by Ca2+-dependent K+ currents and disfacilitation processes (Contreras et al. 1996b; Timofeev et al. 2001b).



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Fig. 16. Changes in membrane potential and firing patterns during natural wake and sleep states in chronically implanted cats. A: RS neuron from posterior association suprasylvian area 21 was intracellularly recorded (together with EMG and EEG from area 5) during transition from wake to SWS and, further, to REM sleep (there is a nondepicted period of 18 min during SWS). Periods marked by horizontal bars are expanded below (down-arrow ). Note tonic firing during both waking and REM sleep and cyclic hyperpolarizations associated with depth-positive EEG field potentials during SWS. B: activity of FS neuron (characterized by fast and tonic firing without frequency adaptation; see at right responses to depolarizing current pulses) during waking, SWS, and REM sleep. Recording with KCl-filled pipette. Tonic firing during waking and REM sleep was interrupted during SWS by long periods of hyperpolarizations and spindles, corresponding to EEG depth-positive waves and spindles. Some prolonged hyperpolarizations during SWS are indicated (*). From Steriade et al. (2001).

The initiation and termination of the hyperpolarizing phase of the slow oscillation, which sculpts the firing of neocortical neurons during slow-wave sleep, may be explained by the following scenario (Contreras et al. 1996b). During the depolarizing phase of the slow oscillation, synaptic currents (Isyn) are maintained at a high level of activity in intracortical circuits. Small decreases in Isyn will allow the passive leak current (Ileak) to dominate the scene, hyperpolarizing the neuron and decreasing its firing probability. As a consequence, the target cortical cells will reduce their firing rates, eventually leading, by an avalanche effect, to generalized neuronal silence. During the prolonged hyperpolarization, the space constant will increase due to a decrease in Isyn, the cell will become more compact, and, toward the end of this phase, neurons may reach firing threshold. At this stage, firing from any small group of cortical or thalamic neurons would rapidly bring the whole system back to the depolarizing state and evoke action potentials, which would explain the steep uprising phase of the depolarizing phase. Even during abnormally synchronized EEG activity, with burst-suppression patterns, volleys applied during prolonged periods of neuronal silence are sufficient to restore neuronal activity and spiking in corticothalamic networks (Steriade et al. 1994a). The rebound spike bursts fired by TC neurons, due to IT de-inactivation toward the end of the hyperpolarizing phase (Contreras and Steriade 1995), may be an important factor in triggering new cycles of the slow oscillation. However, cortical neurons certainly preserve this ability as the slow oscillation can be recorded in the absence of the thalamus (Steriade et al. 1993f). The relationship between neurons and glial cells, whose intracellular activities were recorded simultaneously (Amzica and Neckelmann 1999; Amzica and Steriade 1998b, 2000), suggests that glial cells might also play a role in pacing the slow oscillation and, when sleep oscillations develop to seizures, in triggering paroxysmal events (see following text).

Three other rhythms, generated in the thalamus and cortex, sleep spindles and delta waves as well as fast rhythms, are grouped by the slow cortical oscillation in complex wave sequences. This defies a strict dissociation of different brain rhythms and justifies the title of this subsection, which maintains that, in the living brain, oscillations are not generated in circumscribed neuronal networks but in interconnected neuronal loops between the cerebral cortex and thalamus, under the control of modulatory systems of the brain stem core, hypothalamus, and basal forebrain.

During the sharp depth-negative field potential of the slow oscillation, the summated activity of corticothalamic neurons sets into action thalamic (RE and TC) neurons, thus triggering spindles that are fed back to cortex (see Fig. 14, cat). The grouping of thalamically generated spindles by the slow cortical oscillation is at the origin of the KC, a major element of sleep EEG in humans and animals, which consists of an ample surface-positive (depth-negative) wave, followed by a spindle sequence (Amzica and Steriade 1997, 1998a; Contreras and Steriade 1995). The power spectrum of human sleep EEG reveals a peak at ~0.7 Hz reflecting the slow oscillation, a peak at ~13-14 Hz reflecting spindles, and a spectral content between 1 and 4 Hz reflecting delta waves that are due to the shape and duration of KCs (Fig. 14, human). KCs may also be triggered by sensory stimulation during sleep. However, evoked KCs are rather the exception (compared with the "spontaneously" occurring ones, in fact elicited by the slow cortical oscillation) as sleep generally occurs in environments free from sensory stimuli.

The slow oscillation also groups delta waves (1-4 Hz). One type of delta activity is generated in the thalamus and is due to the interplay of two currents in TC neurons, IH and IT, dependent on their hyperpolarization (Curró Dossi et al. 1992; Leresche et al. 1990, 1991; McCormick and Pape 1990; Soltesz et al. 1991). Although intrinsically generated in single TC neurons, this clock-like delta activity can be synchronized in pools of TC cells by synaptic activity in corticothalamic systems (see preceding text, Fig. 13). When pools of delta-oscillating TC neurons are synchronized, their clock-like activity is reflected at the cortical level and seen in conjunction with the slow oscillation (Fig. 17A). The other type of delta activity is generated in neocortex as it survives thalamectomy (Steriade et al. 1993f; Villablanca 1974) and can be partially generated through the intrinsic properties of neocortical neurons, as seen by rhythmic responses of IB cells to depolarizing current pulses. The depolarizing phase of the slow oscillation is composed of activity in the delta frequency range (Amzica and Steriade 1998b; Steriade 1997). The combined slow and delta oscillations in a bursting cell and in two simultaneously recorded cortical neurons are illustrated in Fig. 17, B and C. Cortical delta waves are under the control of cholinergic nucleus basalis neurons (Buzsáki et al. 1988).



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Fig. 17. Combined slow (<1 Hz) and delta (1-4 Hz) oscillations in neocortex. Cats under urethan anesthesia. A: clock-like delta activity, generated in the thalamus (see text), occurs between depolarizing cycles of slow oscillation in neuron from area 5. Period marked by horizontal bar is expanded below to show an inhibitory PSP (IPSP, *) during the depolarizing phase of the slow oscillation. B: extracellular recording of a bursting neuron at 0.6 mm in suprasylvian area 7, convergently excited by stimulation of LP and CL thalamic nuclei. Below the cellular traces, focal waves (field potentials) recorded through the same micropipette and EEG waves recorded from the cortical surface are depicted. The sequences of spike bursts marked by * or ** are expanded below. Note delta waves grouped by the slow rhythm. C: autocorrelogram (auto) of 2 (a and b) neurons recorded simultaneously by the same extracellular microelectrode at a depth of 1.3 mm in motor area 4. Autocorrelograms (0.1-s binwidth) show the slow rhythm in both cells. The delta rhythm (2.5 Hz) within the slowly (0.2 Hz) recurring discharge sequences in cell b is depicted in the expanded inset (up-arrow ). Modified from Steriade et al. (1993f).

Finally, fast rhythms appear during the depolarizing phase of the slow sleep oscillation (Steriade et al. 1996a,b). The fact that the slow oscillation groups not only other sleep rhythms but also generates fast rhythms (20-50 Hz) stands in contrast with the idea that these rhythms are reliable indicators of alertness and conscious states. Fast neocortical rhythms are voltage (depolarization) dependent (Gutfreund et al. 1995; Llinás et al. 1991; Nuñez et al. 1992), and thus they appear over the depolarizing component of the slow sleep oscillation but are obliterated during the hyperpolarizing phase (Steriade et al. 1996a,b). The difference between fast oscillations in the aroused and sleeping brain is that in the former case, these rhythms are continuous, whereas in the latter, they are cyclically interrupted by hyperpolarizations. Spontaneous fast rhythms are distributed without phase reversal throughout the cortical depth (Steriade and Amzica 1996). Time lags between surface and depth activities, action potentials superimposed on the negative phase of fast field potentials in superficial and deep layers, and absence of fast activity in the white matter underlying the cortex, indicate that the fast fields are not volume-conducted but locally generated (Steriade et al. 1996a).

In humans, cortical activity during slow-wave sleep, measured by regional cerebral blood flow (rCBF), displays more changes in those areas that are implicated during wakefulness in heteromodal association processes and the control of emotions and social interactions (Maquet 2000; Maquet et al. 1996). The decreased rCBF in the thalamus and cerebral cortex during slow-wave sleep was reported in a series of studies (Braun et al. 1997; Fiset et al. 1999; Hofle et al. 1997; Kajimura et al. 1999; Maquet et al. 1997). The majority of these studies emphasized that, far from being associated with a global decrease in rCBF, slow-wave sleep is accompanied by local changes in the cerebrum.

In sum, the complexity of brain electrical activity, with wave-sequences composed of different rhythms, originating in interacting structures as well as the dependence of these rhythms on the activity of generalized activating systems emphasizes the need for studies conducted in intact-brain preparations.

Short-term plasticity follows rhythmic spike trains during sleep oscillations

Plasticity is defined as an activity-dependent alteration in the strength of connections among neurons and is a mechanism through which information is stored. Although hippocampal and neocortical mechanisms of plasticity have received the greatest emphasis in experimental studies (Martin et al. 2000; Tsumoto 1992), thalamic neurons also display reorganization after deafferentation (Jones 2000) and brain stem cholinergic stimulation produces a prolonged enhancement of thalamic synaptic responsiveness (Paré et al. 1990).

The surprisingly high discharge rates of all cortical cell types during the depolarizing phase of the slow oscillation in natural slow-wave sleep (see Figs. 15 and 16) suggests that during this behavioral state in which the brain is disconnected from the external world because of synaptic inhibition of messages in the thalamus, neocortical neurons are actively involved in processing internally generated signals. The hypothesis that during sleep oscillations neocortical neurons are implicated in plasticity processes and in consolidating memory traces acquired during wakefulness (Steriade et al. 1993b,d) may be related to a similar idea (Buzsáki 1989) that was tested in the hippocampal system (Pavlides and Winson 1989; Qin et al. 1997; Wilson and McNaughton 1994). In the following text, I will discuss data from experiments in which a thalamically generated oscillation, sleep spindles, was mimicked by stimulating the thalamus and neocortex within the frequency range of this rhythm (~10 Hz) to produce changes in synaptic responsiveness of neurons and self-sustained events following stimuli that are reminiscent of "memory" traces in reciprocal corticothalamic loops.

The experimental model of sleep spindles consists of augmenting (or incremental) responses (Morison and Dempsey 1942). Augmenting responses are generally defined as thalamically evoked cortical potentials that grow in size during the first stimuli at a frequency of 5-15 Hz, usually ~10 Hz, like the waxing of waves at the onset of spontaneously occurring spindle sequences. A series of investigators have attempted to make distinctions between various types of incremental responses and to emphasize the exclusive role of the thalamus, or the neocortex, in the generation of augmenting responses. The view expressed here is that although augmentation occurs in the thalamus of decorticated animals (Steriade and Timofeev 1997) and in the intact cortex of thalamic preparations (Steriade et al. 1993f) or even in cortical slices (Castro-Alamancos and Connors 1996b), the full development of augmenting responses, leading to self-sustained activities, requires interacting thalamic and cortical networks.

The idea that incremental thalamocortical responses are of two basically different types, augmenting and recruiting, was suggested on the basis that augmenting responses are elicited in appropriate localized cortical areas by stimulation of "specific" thalamic nuclei and their polarity is positive at the cortical surface, whereas recruiting responses are elicited by stimulation of "nonspecific" thalamic nuclei, are negative at the cortical surface, and occur with a longer latency than that of augmenting responses (Dempsey and Morison 1942). The longer latency of recruiting responses suggested a "diffuse multineuronal system" (Jasper 1949). This view continued during the 1950s when recruiting responses were regarded as implicating a recruitment through a divergent multineuronal chain with intralaminar nuclei serving as an intrathalamic association system. We now know that there are virtually no direct pathways linking different dorsal thalamic nuclei, that the longer latency of cortical recruiting responses is not due to the intrathalamic spread of activity but to slower conduction velocities of axons from some thalamic nuclei projecting directly to the neocortex, and that some recruiting (depth-positive) responses may display latencies as short as those of augmenting (depth-negative) responses. In fact, there are no pure augmenting or recruiting responses. Most are mixed responses, with augmenting preceding the recruiting or vice versa (Spencer and Brookhart 1961) because of the multi-laminar distribution of thalamic projections to cortex. As an illustration, thalamocortical incremental responses evoked by rhythmic stimulation of rostral intralaminar nuclei (conventionally known as typically inducing recruiting responses) are of the recruiting type in one cortical area and of the augmenting type in another area of the same gyrus (because intralaminar nuclei project preferentially to layer I but also to deep layers); moreover, the latencies of both augmenting and recruiting responses evoked by thalamic intralaminar stimulation are equally short (<4 ms) (see Fig. 4 in Steriade et al. 1998d). Therefore the distinction between augmenting and recruiting responses is no longer necessary. We can simply designate such responses as augmenting or incremental, describe their polarity, and keep in mind that thalamic neurons may project to middle, deep and more superficial cortical layers.

In the decorticated thalamus, TC neurons display two types of augmenting responses to local thalamic stimulation at 10 Hz. One type of intrathalamic augmenting responses is based on progressively increased LTSs, which are de-inactivated by the increasing hyperpolarization produced by repetitive stimuli in the train (Fig. 18B). The other type is associated with progressively decreased IPSPs elicited by successive stimuli in the train and with progressive depolarization of neurons leading to high-threshold spike bursts with increasing numbers of action potentials and spike inactivation (see below, Fig. 20A). The first type of augmentation (with progressively increased LTSs and rebound spike bursts) is due to the parallel excitation in a pool of thalamic RE GABAergic neurons, whereas the high-threshold form of augmenting is due to decremental responses in a pool of RE neurons (Timofeev and Steriade 1998). Then, the relations between RE and TC neurons are essential for the development of augmenting responses in decorticated animals. As augmenting responses mimic spindles, and spindles have been recorded in the deafferented RE nucleus (Steriade et al. 1987), augmenting responses as well as spindles were also obtained in models of isolated RE nucleus with synaptic interconnections including both GABAA and GABAB components (Bazhenov et al. 1998a). Patterns of propagated activity within isolated RE networks can occur if only a small fraction of RE neurons is hyperpolarized below the GABAA reversal potential and self-sustained oscillations within the frequency range of 10-15 Hz are found in two-dimensional network models when only 25% of RE neurons are hyperpolarized below the Cl- reversal potential (Houweling et al. 2000). Thus these models show that GABAA-mediated excitation in RE neurons can robustly generate sequences of spindle waves (Bazhenov et al. 1999), as was experimentally demonstrated in RE neurons disconnected from the remaining thalamus (Steriade et al. 1987).



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Fig. 18. Augmenting responses in thalamic neurons and in thalamocortical systems. A: hemidecortication (ipsilateral to thalamic recordings) and cut of corpus callosum. Nissl-stained section. CC, corpus callosum; F, fornix; Al and Abl, lateral and basolateral nuclei of amygdala; CLS, claustrum; GP, globus pallidus; OT, optic tract; s.rh., rhinal sulcus (arrowhead). B: intrathalamic augmenting responses in decorticated cat (see A). Intracellular recordings from the thalamic VL nucleus under ketamine-xylazine anesthesia show low-threshold augmenting responses of VL cell developing from progressive increase in IPSP-rebound sequences and followed by a self-sustained spindle. up-arrow , expanded spike burst (action potentials truncated). The part marked by horizontal bar and indicating augmenting responses is expanded at right. C: dual intracellular recording from cortical area 4 and thalamic VL nucleus in cat under ketamine-xylazine anesthesia. Bottom: average of 2nd and 3rd responses in cortical and VL cells. The area of secondary depolarization in cortical neuron (b), which develops during augmentation, is marked by dots. Right: area of secondary depolarization of cortical cell as a function of the number of stimuli in the pulse trains (the line represents the mean). During thalamically evoked augmenting responses, the cortical augmented component (secondary depolarization, b) follows the rebound spike burst in thalamocortical neuron, and the depolarization area in cortical neuron increases as a function of number of action potentials in the rebound spike burst of thalamocortical cell. In a sample of 92 cells, the maximum number of fast spikes of thalamocortical cells triggered by the LTS occurred at the 3rd to 5th stimuli. After having reached the maximum, the number of spikes in thalamocortical cells could decrease. The area of secondary depolarization of cortical cells also reached levels close to saturation at the 3rd to 5th stimuli; however, the decrease of the depolarizing area in cortical cells was only exceptionally observed. This suggests that high levels of cortical excitability may be maintained by intracortical mechanisms. Modified from Steriade and Timofeev (1997) (A and B) and Steriade et al. (1998d) (C).

Although the thalamus is capable of producing augmenting responses through its own network activity, we further investigated this phenomenon using dual intracellular recordings from TC and cortical neurons (Steriade et al. 1998d) and computational models (Bazhenov et al. 1998b). These studies revealed that the augmentation in neocortical neurons is expressed by a selective increase in the secondary depolarizing component of thalamically evoked responses and that the secondary cortical depolarization invariably follows by ~3 ms the rebound burst in simultaneously recorded TC neurons (Fig. 18C). Thus in intact-brain preparations, augmenting responses primarily depend on the LTS type of augmentation and related spike bursts in TC neurons. The comparative analysis of augmenting responses of neocortical neurons from different layers was performed by means of dual intracellular recordings of neurons that were stained and found to be located within deep (layers V-VI) and more superficial layers (Steriade et al. 1998d). Deeply lying pyramidal neurons, and especially FRB cells with thalamic projections (see Neocortex: changing firing patterns during different functional states), consistently showed a higher propensity, shorter latencies, and greater number of action potentials during augmenting responses, compared with more superficially located neurons. Other investigators emphasized the role of IB neurons in the process of augmentation as they investigated layer V in cortical slices (Castro-Alamancos and Connors 1996a). The difference between simultaneously recorded neocortical and TC neurons is that the former display postaugmenting oscillatory activities in the frequency range of responses, whereas the latter remained hyperpolarized because of the pressure from the GABAergic RE neurons (Fig. 19) (Steriade et al. 1998d). These data show that intracortical circuits have a major influence on the inputs from TC neurons and can amplify oscillatory activity arising in the thalamus (Grenier et al. 1998). Such a view is consistent with the fact that although spindles are generated in the thalamus, they are not passively reflected in cortex and cortical synaptic circuitry has a major role in modifying and amplifying thalamocortical volleys (Kandel and Buzsáki 1997).



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Fig. 19. Low-threshold augmenting responses in TC neuron precede cortical responses but cortical neuron displays self-sustained activity within the frequency range of augmenting responses, whereas TC neuron remains under a hyperpolarizing pressure. Dual intracellular recordings from TC neuron in the VL nucleus and cortical neuron from area 4 in cat under ketamine-xylazine anesthesia. Responses to 5-stimulus train at 10 Hz, applied to the VL nucleus. Spike-triggered averages of VL and cortical responses to 3rd, 4th, and 5th stimuli in the train (*, 1st action potentials in spike burst of TC cell triggered the average). Note self-sustained activity in cortical neuron, following augmentation, whereas TC neuron remained hyperpolarized because of hyperpolarizing pressure from GABAergic thalamic reticular neurons (see text). Unpublished data by M. Steriade, I. Timofeev, and F. Grenier.

To summarize, because of their high propensity to fire spike bursts, TC neurons trigger incremental responses in target neocortical neurons, but the latter have the ability to maintain and develop self-sustained oscillations.

What is the experimental evidence that such responses are associated with short-term plasticity processes? Although the augmentation phenomenon characterizes a state of vigilance, resting sleep, during which brain "utilitarian" processes are apparently suspended, incremental responses are associated with short-term plasticity in both thalamus and cortex. During repetitive thalamic stimuli at 10 Hz in decorticated animals, the IPSPs of TC neurons are progressively diminished and, conversely, the depolarization area of augmenting responses increases continuously with the repetition of pulse-trains at 10 Hz (Fig. 20A). Similar data can be elicited by using testing stimuli to the neocortex. After spontaneously occurring spindle sequences, single-spike responses of cortical association neurons, evoked by stimulating the same cortical area, are transformed into greatly increased responses, a potentiation that lasts for several minutes (Grenier et al. 1999). The same phenomenon occurs when mimicking spontaneously occurring spindles with pulse-trains within the frequency range (10 Hz) of spindles. In the cerebral cortex of animals with ipsilateral thalamectomy, augmenting responses progressively develop with the depolarization of membrane potential, and the spike bursts acquire more and more action potentials, eventually developing into self-sustained paroxysmal discharges as in a seizure (Steriade et al. 1993f).



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Fig. 20. Short-term plasticity from repetitive intrathalamic augmenting responses of the high-threshold type and development from corticothalamic augmenting responses to self-sustained activity. A: intracellular recording of VL neuron in cat with ipsilateral hemidecorticaion and callosal cut (as in Fig. 18A). Ketamine-xylazine anesthesia. Progressive and persistent increase in the area of depolarization by repeating the pulse trains. Pulse trains consisting of 5 stimuli at 10 Hz were applied to the VL every 2 s. The VL cell was recorded under +0.5 nA (-60 mV); at rest, the membrane potential was -72 mV. Responses to 4 pulse trains (1-4) are illustrated (1 and 2 were separated by 2 s; 3 and 4 were also separated by 2 s and followed 14 s after 2). The responses to 5-shock train consisted of an early antidromic spike, followed by orthodromic spikes displaying progressive augmentation and spike inactivation. Note that with repetition of pulse trains, IPSPs elicited by preceding stimuli in the train were progressively reduced until their complete obliteration and spike bursts contained more action potentials with spike inactivation. The graph depicts the increased area of depolarization from the 1st to the 5th responses in each pulse train as well as from pulse train 1 to pulse trains 3 and 4. B: brain stem-transected cat. Cortically evoked spike bursts in thalamic VL neuron (1). Motor cortex stimulation was applied with pulse trains at 10 Hz delivered every 1.3 s. In 1, the pattern of cortically evoked responses at the onset of rhythmic pulse-trains (faster speed than in 2-4); 2-4, responses at later stages of stimulation. Stimuli are marked by dots. In 2-4, stimuli and evoked spike bursts are aligned. Note progressive appearance of spontaneous spike bursts resembling the evoked ones, as a form of "memory" in the corticothalamic circuit. Modified from Steriade and Timofeev (1997) (A) and Steriade (1991) (B).

Thus although cortical augmenting responses mainly depend on spike bursts generated by an intrinsic property (the de-inactivation of IT in TC neurons), in brain-intact animals, the cortex has the necessary equipment to develop some forms of augmentation even after thalamectomy. The rich spontaneous firing of neocortical neurons and their preserved synaptic excitability and self-sustained oscillations following internally generated incoming signals during slow-wave sleep, together suggest that this deafferented behavioral state may sustain mental events. Indeed, repeated spike bursts evoked by volleys applied to corticothalamic pathways as well as occurring during spontaneous oscillations may lead to self-sustained activity patterns, resembling those evoked in the late stages of stimulation (Fig. 20B). Such changes are due to resonant activities in closed loops as in "memory" processes.

These data indicate that slow-wave sleep is not associated with a global annihilation of consciousness as previously assumed (Eccles 1961) but that some mental processes are taking place in this state. Indeed, recent studies demonstrate that the overnight improvement of visual-discrimination tasks requires several steps, some of them depending on the early night slow-wave sleep (Stickgold et al. 2000). The significant improvement of visual discrimination skills by early stages of sleep (associated with spindles and slow oscillation) led to the conclusion that procedural memory formation is prompted by slow-wave sleep (Gais et al. 2000). It was suggested that the massive Ca2+ entry in cortical pyramidal neurons during low-frequency sleep oscillations, such as spindling, activates a molecular "gate," for example mediated by protein kinase A, opening the door to gene expression and that this process could allow permanent changes to subsequent inputs following sleep spindles (Sejnowski and Destexhe 2000). That sleep spindles may lead to memory traces in corticothalamic circuits is indeed shown by experiments using volleys in the frequency range of spindles (Fig. 20B). Moreover, it is known that dreaming mentation is not confined to REM sleep but also appears with a different content (more logical, closer to real life events) in slow-wave sleep (Foulkes 1967; Hobson et al. 2000). The recall rate of dreaming mentation in quiet sleep is quite high (Nielsen 2000). If plasticity, triggered by volleys within the frequency range of sleep oscillations and resembling memory processes in the corticothalamic circuit (Steriade 1991) (Fig. 21B), is not constrained by inhibitory processes, they could develop into seizures (see Paroxysmal activities developing from sleep oscillations). This is indeed a puzzling development as memory and epilepsy are antinomies. The basic mechanisms of this relation are not fully elucidated yet, but they probably depend on a delicate balance between excitatory and inhibitory synaptic activities.



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Fig. 21. Neuronal activity during seizure with spike wave (SW) complexes at 3 Hz during natural drowsiness in the behaving monkey. Chronically implanted Macaca mulatta. Single neuron recorded from the arm area in the precentral gyrus. The top oscilloscopic traces (1-2) indicate the corresponding parts in the below depicted ink-written record (the 3 traces represent: unit spikes used to deflect a pen of the EEG machine; each deflection exceeding the common level representing a group of high-frequency spikes; focal slow waves, simultaneously recorded by the same microelectrode; and eye movements). black-down-triangle , stimuli applied to the appropriate thalamic nucleus for neuronal identification. When the experimenter observed a change in the evoked field potential (1), stimuli were interrupted and the seizure developed in the absence of any stimulus. Note spike bursts over the depth-negative field potential of the SW complexes (the EEG "spike") and silent firing during the late part of the depth-positive "wave" component of SW complexes. Also note tonic eye movements at the onset and end of the SW seizure. Modified from Steriade (1974).

Paroxysmal activities developing from sleep oscillations

Our current in vivo studies of mechanisms underlying paroxysmal activities use simultaneous intracellular recordings from two or three neocortical neurons or from neocortical and thalamic neurons; for obvious technical reasons, at this time, these experiments are conducted on anesthetized and paralyzed animals. The major electrographic aspects that reflect the paroxysms under scrutiny are spike-wave (SW) or polyspike-wave (PSW) complexes recurring at frequencies between 2 and 4 Hz, often associated with fast runs at 10-15 Hz (Steriade et al. 1998a), thus resembling the EEG pattern of the Lennox-Gastaut syndrome (see Niedermeyer 1999). In some instances, seizures consisting of pure SW complexes at 3 Hz occur during the natural state of drowsiness or light sleep, using extracellular recordings in behaving monkeys (Fig. 21) (see also Figs. 1-2 in Steriade et al. 1998a, for chronic experiments on cats). For the sake of simplicity, I shall term all these paroxysms SW or SW/PSW seizures. Needless to say, a disease entity is not just an electrographic pattern, and this is why I think that the term epileptic seizures should be limited to clinical studies. What neurophysiologists usually do is find the aspect that is closest to the clinical case and search for its neuronal substrates in terms of both intrinsic and network neuronal properties. Because of the stereotyped pattern of SW complexes, it is likely that the cellular correlates of these seizures in animals are close to those of corresponding epileptic fits in humans, more so when tonic eyelid movements are associated with the onset and end of SW seizures (Fig. 21), as in absence epilepsy. Still, I will refrain from calling epileptic the electrical seizures described in the following text. Seizure models should be considered distinct from epilepsy models (Colder et al. 1996). Regrettably, the term absence (or petit-mal) epilepsy is used in some experiments conducted in thalamic slices maintained in vitro.

I shall attempt to define the term seizure because even this simple, descriptive term is sometime used for forms of rhythmic activity that are characterized by changed frequencies and amplitudes of oscillations without however reaching the degree of paroxysms. This is the case with the slowed spindles induced by bicuculline injections in the thalamus (Bal et al. 1995a; Steriade and Contreras 1998) that are not seizures but continuously and regularly recurring oscillations whose only differences from barbiturate or natural spindles are the slowed frequency and increased number of action potentials in spike bursts. I use the term seizure to describe a transient episode whose electrical signs are in sharp contrast to the background activity and that, even if it emerges without apparent discontinuity from the previous sleep-like pattern, has a sudden end.

In what follows, I shall focus on the site of initiation and cellular mechanisms of SW/PSW seizures. There are many types of SW/PSW seizures. The thalamic or cortical origin of these seizures was, and continues to be, hotly debated. In reality, the corticothalamic system is a unified entity and, although studies on extremely simplified preparations or intact-brain animals pointed to one or another component of this system, experimental studies congruently reached the conclusion that neocortical excitability represents the leading factor in controlling thalamic events during this type of seizures (see following text).

The thalamic (or "centrencephalic") origin of such seizures was considered since the late 1940s in the light of experiments in which the medial thalamus was stimulated at 3 Hz (Jasper and Droogleever-Fortuyn 1949). In that study, only SW-like responses were evoked in cortex but no self-sustained activity. It is difficult to envisage the presence of a centrencephalic system as there are no bilaterally projecting thalamic neurons, and, on the other hand, brain stem core neurons with generalized projections disrupt, rather than produce, SW seizures (Danober et al. 1995). The conventional feature of clinical SW seizures, which was at the basis of the hypothesis pointing to a deeply located pacemaker, is their suddenly generalized appearance. This might be so on EEG recordings, but topographical analyses of SW complexes in humans show that the "spike" component propagates from one hemisphere to another with time lags as short as 15 ms (Lemieux and Blume 1986), which cannot be estimated by visual inspection. Earlier EEG studies and toposcopic analyses have also indicated that some SW seizures are locally generated and result from multiple, independent cortical foci (Jasper and Hawkes 1938; Petsche 1962). This explains why absence seizures are less detrimental than grand-mal epilepsy that implicates more widespread neuronal manifestations. Experiments using multi-site, extra- and intracellular recordings show that neocortical neurons become progressively entrained into the seizures, indicating that the buildup of SW seizures obeys the rule of synaptic circuits, sequentially distributed through short- and long-range circuits, with time lags as short as 15-20 ms, but also longer (100-150 ms), the latter being ascribable to inhibition-rebound sequences (Steriade and Amzica 1994). This aspect stands in contrast to the usual definition of "suddenly generalized, bilaterally synchronous" discharges, ascribed to SW seizures.

Since the earlier concept of thalamically generated SW seizures, views have changed and another hypothesis proposed that sleep spindles develop into SW seizures because of an enhanced excitability of neocortical neurons (Gloor et al. 1990). This was closer to reality as the major role in the induction of SW seizures was ascribed to the increased excitability of the neocortex. Although SW seizures may occur in thalamectomized animals, in which spindles are absent (Steriade and Contreras 1998), in the intact brain, spindles might lead to SW seizures. One likely possibility is that sleep spindles are prevalently linked with the occurrence of SW seizures in humans (Kellaway 1985), whereas the slow sleep oscillation distinctly leads to patterns resembling the Lennox-Gastaut syndrome or hypsarrhythmia (Steriade and Contreras 1995; Steriade et al. 1998a; reviewed in McCormick and Contreras 2001).

That focal SW seizures are initiated in circumscribed pools of neurons within the cortex was initially suggested on the basis of typical SW complexes at ~3 Hz occurring in the depth of monkey's cortex, even without reflection at the cortical surface, thus suggesting the involvement of a local pool of short-axoned interneurons (see Fig. 8 in Steriade 1974). Seizures with SW/PSW complexes can also be elicited by electrical stimulation in completely isolated neocortical slabs in vivo (Timofeev et al. 1998). Thus the SW/PSW seizures are initiated in neocortex, and multi-site recordings show that they spread from cortex to thalamus after a few seconds (Neckelmann et al. 1998) (Fig. 22).



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Fig. 22. SW seizures first appear in neocortical areas and spread intracortically before related thalamic nuclei were entrained. Cat under ketamine-xylazine anesthesia. Depth-EEGs from areas 7 and 5, and electrothalamogram (EThG) from the intralaminar CL nucleus during a spontaneously occurring seizure (top). A: expanded detail of the period marked A in the left panel. Middle: sequential cross-correlation of 500-ms windows from periods marked 1-3; peak amplitude on left ordinate; displacement of this peak from time 0 of the cross-correlation function (right ordinate; see calibration bar from 0 to 250 ms). Thick lines represent the cross-correlation of area 7 with area 5 (A7 × A5), thin line area 7 with thalamus (A7 × Th), and dotted line area 5 with thalamus (A5 × Th). The wave-triggered averages (n = 12) were taken from the period marked 1, 2 and 3, respectively (bottom 3 panels). The spiky negativity of SW complexes, immediately following a wave in area 7, was used as reference time. From Neckelmann et al. (1998).

The cortical and thalamic mechanisms underlying different components of SW/PSW seizures have been investigated using multi-site, including dual intracellular, recordings in cats under ketamine-xylazine anesthesia. In some instances, we recorded bicuculline-induced paroxysms, but we mainly investigated spontaneously occurring and electrically induced seizures in the absence of any convulsing substance. The high incidence of spontaneous SW/PSW seizures in acutely prepared cats under ketamine-xylazine anesthesia (30-50% of animals) is explained by the highly synchronized corticothalamic activity produced by this anesthetic in conjunction with the great number of recording and stimulating macroelectrodes that are inserted for the identification of input-output organization of neurons. It is known that repeated electrical stimulation is a favorable factor for the occurrence of seizures. A similar factor (stimuli applied for physiological identification of neuronal inputs and targets) is likely responsible for the appearance of spontaneous SW seizures in chronic experiments on monkeys (Steriade 1974) and cats (Steriade et al. 1998a). In view of this high incidence of spontaneous SW/PSW seizures, it is likely that many SW seizures occur in "normal" subjects during drowsiness or slow-wave sleep, and they are not recognized as such as these paroxysms may develop without discontinuity from the slow sleep oscillation (Steriade et al. 1998a) and stimulation within the frequency range of sleep oscillations leads to SW/PSW seizures (Amzica and Steriade 1999).

Dual simultaneous intracellular recordings from the cortex and thalamus, in vivo, show that seizures consisting of SW/PSW complexes at 2-3 Hz, often associated with fast runs (10-15 Hz) originate in the neocortex. Simultaneously, most (60%) TC neurons display a steady hyperpolarization as well as phasic IPSPs, closely related to the spike component of cortical SW complexes (Fig. 23A). At the end of the cortical seizure, TC neurons fire at high rates as if they were released from the inhibition that occurred during the seizure (the source of inhibition is in GABAergic RE neurons). These SW seizures develop, often without discontinuity, from preceding periods of sleep-like patterns. Indeed, the phase relations between cortical and thalamic neurons during sleep are preserved during seizures, but the amplitude of membrane excursions are accentuated (Fig. 23B). The similar relations between field potential and intracellular activities during slow-wave sleep and SW/PSW seizures are due to similar mechanisms that account for the depolarizing/hyperpolarizing components of the slow sleep oscillation, on one hand, and the spike/"wave" components of SW complexes, on the other hand (see below). Although these data point to cortically initiated SW seizures and to the steady hyperpolarization in a majority of thalamocortical neurons during such seizures, the remaining TC neurons are capable of firing rebound spike bursts during a cortical SW seizure (Steriade and Contreras 1995) and thus may potentiate and disseminate cortical seizures. Thus our data point to the intracortical origin of these seizures. After a few seconds, they irradiate to the ipsilateral thalamus (Fig. 22) as well as to other subcortical structures.



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Fig. 23. Dual intracellular recordings from neocortical (area 4) and thalamocortical (VL) neurons demonstrating hyperpolarization of VL neuron during SW seizure depolarization and spike bursts in area 4 neuron. Cat under ketamine-xylazine anesthesia. A: 5 traces depict simultaneous recordings of EEG from the skull over the right cortical area 4, surface and depth EEGs from the left area 4, as well as intracellular activities of left area 4 cortical neuron and thalamic VL neuron (below each intracellular trace, current monitor). The seizure was initiated by a series of EEG waves at 0.9 Hz in the depth of left area 4, continued with SW discharges at 2 Hz, and ended with high-amplitude, periodic EEG sequences consisting of wavelets at 14 Hz. All these periods were faithfully reflected in the intracellular activity of the cortical neuron, whereas the thalamic VL neuron displayed a tonic hyperpolarization throughout the seizure, with phasic sequences of IPSPs related to the large cortical paroxysmal depolarizations and spike bursts occurring at the end of the seizure. Note disinhibition of the VL neuron after cessation of cortical seizure. The part indicated by horizontal bar (below the depth-EEG trace) is expanded at right (superimposition of 6 successive traces). Note spiky depth-negative EEG deflections associated with depolarization of cortical neuron and rhythmic IPSPs of the thalamic VL neuron. B: phase relations between simultaneously intracellularly recorded cortical neuron (area 4) and thalamic (VL) neuron are preserved during the development from sleep to seizure activity. The 4 parts represent: 1 sleep period prior to seizure, 2 periods during the early and late parts of the seizure, and 1 period after the paroxysmal activity. Phase plots of averaged membrane voltage of area 4 cortical neuron (ordinate) against that of the VL neuron (abscissa). The development from sleep to seizure did not change the phase relations between neurons but accentuated the amplitude of the elements constituting the normal (sleep) oscillatory behavior preceding the epileptic seizure. Cortical depolarization (up-arrow ) preceded the hyperpolarization of the VL neuron (left-arrow ) in the 4 periods, although the amplitude of membrane excursions were considerably enhanced during the seizure. Modified from Steriade and Contreras (1995) (A) and unpublished data by M. Steriade and D. Contreras (B).

Subsequent research by other teams (Pinault et al. 1998; Slaght et al. 2000) using intracellular recordings from TC neurons during spontaneous SW discharges in a genetic model of absence epilepsy in rats similarly demonstrated that the main events which characterize the activity of an overwhelming majority (>90%) of TC neurons are a tonic hyperpolarization, present throughout the SW seizure, and rhythmic IPSPs. The results of these in vivo study emphasized that the intracellular activity of TC neurons during SW seizures does not involve rhythmic sequences of GABAB receptor-mediated IPSPs, but GABAA-mediated IPSPs as they appeared as depolarizing events when recorded with KCl-filled pipettes. The origin of the GABAA-mediated IPSPs in TC neurons should be searched for in the GABAergic RE neurons that faithfully fire spike bursts during SW seizures in response to each paroxysmal depolarizing shift of cortical neurons (Steriade and Contreras 1995; Timofeev et al. 1998). Modeling studies show that increasing the inhibitory strength from GABAergic RE neurons onto TC neurons favors the quiescent mode of the latter (Lytton et al. 1997). The cortically induced inhibition of TC neurons during SW seizures, mediated by GABAergic RE neurons, was recently corroborated by demonstrating that EPSCs elicited in RE neurons by minimal stimulation of corticothalamic axons are ~2.5 times larger than in TC neurons and GluR4 receptor subunits in RE neurons outnumber those in TC neurons by 3.7 times (Golshani et al. 2001). These data corroborate those in intact-brain animals showing that stimulation of corticothalamic projections evokes a strong excitation in RE cells, in parallel with prolonged IPSPs in TC cells that are due to the activation of GABAergic RE cells (see Fig. 1 in Steriade 2000).

During cortically generated seizures in vivo, neocortical neurons display a progressive depolarization on which SW complexes are superimposed, with paroxysmal spike bursts correlated with the EEG spike component and hyperpolarization correlated with the EEG wave component (Steriade and Contreras 1995; Steriade et al. 1998a). Eventually, the progressive depolarization leads to a state of tonic depolarization accompanied by fast (10-15 Hz) runs (Fig. 24). The fast runs, which constitute the polyspike component of PSW complexes, are also generated intracortically as they are unaffected by thalamic inactivation using tetrodotoxin (Castro-Alamancos 2000). This picture characterizes SW/PSW seizures recorded close to the initial focus. When SW seizures are recorded far (5-10 mm) from the cortical site where the seizures were initiated, the large depolarizing envelope may be absent, but basically the same features are observed: development from the slow sleep oscillation, even without discontinuity, and SW or PSW complexes at ~2 Hz, interrupted by short periods when fast runs (10-15 Hz) occur. While RS neurons fire single action potentials during the fast runs, FRB neurons fire high-frequency bursts during the fast runs (Steriade et al. 1998a). Simultaneous intracellular recordings from neurons and glial cells show, on one hand, that the glial membrane potential displays negative events related to the onset of paroxysmal depolarizing shifts (PDSs) in cortical neurons and, on the other hand, that the maximal glial depolarization is reached later than the end of the neuronal depolarization (Fig. 25). This may control the pace of paroxysmal oscillations (Amzica and Steriade 2000).



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Fig. 24. Spontaneously occurring seizure, developing without discontinuity from slow sleep-like oscillation. Intracellular recording from area 5 RS neuron together with depth-EEG from the vicinity in area 5, in cat under ketamine-xylazine anesthesia. A: smooth transition from slow oscillation to complex seizure consisting of SW complexes at ~2 Hz and fast runs at ~15 Hz. The seizure lasted for ~25 s. Epochs of slow oscillation preceding the seizure, SW complexes, and fast runs are indicated and expanded below. Note postictal depression (hyperpolarization) in the intracellularly recorded neuron (~6 s), associated with suppression of EEG slow oscillation (compare to left part of trace). B: wave-triggered-average during the slow oscillation, at the beginning of seizure and during the middle part of seizure. Averaged activity was triggered by the steepest part of the depolarizing component in cortical neuron ( · · · ), during the 3 epochs. The depth-negative field component of the slow oscillation (associated with cell's depolarization) is termed KC. During the seizure, the depolarizing component reaches the level of a paroxysmal depolarizing shift (PDS), associated with an EEG spike. Note fast runs developing on a plateau of depolarization during the SW seizure. From Steriade et al. (1998a).



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Fig. 25. Simultaneous intracellular recordings from cortical neurons and glial cells show that during seizures, glial transient negativities reflect neuronal depolarization and that glial depolarization outlasts that of neurons. Cats under ketamine-xylazine anesthesia. A and B: continuous recording with a double neuron-glia impalement (in A, pipettes separated by <1 mm) followed by neuronal-field recording (B). The transition from A to B is marked by withdrawal of the pipette from glia (oblique open arrowhead). Epoch within the squares are expanded above. Note the recurrent sharp negative intraglial deflections associated with neuronal depolarizing potentials (A). C: average (n = 50) of simultaneously recorded neuronal and glial activity during cortical seizure (several original traces are superimposed in the inset). Note the negative glial potential associated with neuronal depolarization and the glial depolarization outlasting the neuronal one (see text). Modified from Amzica and Steriade (2000).

Here, an interesting similarity between TC and some neocortical neurons should be mentioned. Although neocortical neurons generally display a tonic depolarization during SW/PSW seizures (Figs. 23-25), whereas most TC neurons are tonically hyperpolarized during these paroxysms (Fig. 23), due to summated IPSPs from RE neurons, we also observed seizures associated with an exclusively hyperpolarizing envelope in neocortical neurons. In such cases, the hyperpolarization of cortical neurons, which lasts throughout the seizure, is initiated from the very onset of the paroxysm, being coincident with the sharp depth-negative EEG spike that reflects summated PDSs in cortical neurons and gives rise to seizures consisting of fast events, 10-20 Hz, followed by PSW complexes at 2 Hz (Fig. 26A). During this prolonged hyperpolarization, cortical neurons exhibit voltage excursions that are synchronous with the SW field activity at 2 Hz but that only rarely reach the firing threshold. The input resistance is dramatically decreased during the hyperpolarizing periods associated with SW/PSW seizures (Fig. 26B). This suggests that such cortical neurons, displaying an exclusive and prolonged hyperpolarization during SW/PSW seizures, are the prevalent targets of local inhibitory neurons. The hyperpolarization of some RS neocortical cells during seizures is homologous to that of TC neurons that are targets of GABAergic RE neurons themselves driven by corticothalamic neurons during SW/PSW seizures.



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Fig. 26. Hyperpolarization throughout cortical SW/polyspike-wave (PSW) seizures, associated with decreased input resistance. Intracellular recordings of 2 RS neurons (A and B) from area 5, together with field potentials from area 7, in cats under ketamine-xylazine anesthesia. A: the end of a seizure and 2 other seizures. The last, prolonged (~25 s) seizure consisted of a short period with fast runs (20 Hz) followed by PSW complexes at 2 Hz. B: decreased input resistance (measured by hyperpolarizing current pulses; duration: 70 ms) during the hyperpolarization associated with cortical seizures. Unpublished data by M. Steriade and F. Amzica.

In previous studies on neocortex and hippocampus, the PDS component was commonly regarded as a giant EPSP (Ayala et al. 1973; Johnston and Brown 1981, 1984). While this is partially true, the PDS also contains GABAA-mediated inhibitory processes. The role of inhibitory processes in the genesis of cortical SW complexes was studied in our laboratory using intracellular recordings and measurements of membrane conductance in vivo. Briefly, neocortical neurons show a maximal conductance during the PDS component (EEG spike) of SW complexes and a significantly lower conductance during the hyperpolarization related to the EEG wave (Neckelmann et al. 2000). The difference between the increased membrane conductance during the PDSs of SW/PSW seizures and the lower membrane conductance during the wave component of these paroxysms is supported by the differential intracellular responsiveness to antidromic and synaptic volleys during these two components of SW seizures (Steriade and Amzica 1999). Thus synaptic responses leading to PDSs can be elicited during the wave (hyperpolarizing) component of SW complexes and antidromic responses can also be evoked by steadily depolarizing the neuron during the wave component, whereas antidromic responses, followed by orthodromic responses, can only be evoked during the declining (repolarizing) phase of the spike (PDS) component (Fig. 27).



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Fig. 27. Comparison between antidromic and orthodromic responses during the spike and wave components of spontaneously occurring SW seizure. Cat under ketamine-xylazine anesthesia. Intracellular recording of area 7 neuron activated antidromically and orthodromically from the posterior part of area 5. A: antidromic response to low (L), intermediate, and higher (H) intensities. To obtain antidromic responses, the neuron was steadily depolarized by injecting 1 nA through the recording pipette. The long latency of the antidromic spike was probably due to the low-intensity stimulation of a thin axonal collateral. Note take off from the baseline. Note also the depolarizing plateau potential whose amplitude and duration was a function of stimulus strength; at H intensity, single action potentials were occasionally triggered at a latency of 30-40 ms. B: during the "wave" of SW seizure, cortical stimulus (intensity H) elicited an antidromic spike followed, after 30-40 ms, by a PDS when the Vm was depolarized (-65 mV). The same stimulus elicited only a PDS at the resting Vm (-80 mV). C: during the spike, the antidromic response survived, but only toward the end of PDSs, when the Vm tended to hyperpolarize. Averages (n = 5) of cortically evoked early responses during wave, under steady depolarization (1) and at rest (2), are depicted at bottom left. Averages at different periods of the "spike" component (full depolarization, 2; and declining period, 1) are depicted at bottom right. From Steriade and Amzica (1999).

A great part of the increased conductance during the EEG spike (PDS) is due to an important inhibitory component, as recordings with Cl--filled pipette reveal depolarizing shifts by 15-30 mV during this part of SW seizures and conventional FS (presumably local inhibitory) neurons fire at very high rates (500-800 Hz) during the PDSs of SW/PSW complexes; on the other hand, the wave component of SW seizures is partly due to K+ currents, as shown using recordings with Cs+-filled pipettes (Steriade et al. 1998c; I. Timofeev, F. Grenier, and M. Steriade, in preparation). These and the preceding data on measurements of membrane conductance (Neckelmann et al. 2000) indicate that the major mechanism underlying the wave-related hyperpolarization of SW seizures does not mainly rely on active GABAergic inhibition as suggested in many previous studies, but on a mixture of disfacilitation and K+ currents. Similar mechanisms (disfacilitation and K+ currents) underlie the hyperpolarizing component of the slow sleep oscillation as indicated by measuring the input resistance of cortical neurons (Contreras et al. 1996) and recordings with Cs+-filled pipettes (Steriade et al. 1993e). This is one of the factors that explain similar relations between field potential and intracellular activities during slow sleep oscillation and SW seizures, the latter developing from the former (see preceding text and Fig. 24B).

To sum up, the aforementioned data lead to the conclusion that SW/PSW seizures are initiated in the cortex, that subsequently they spread to the thalamus, and that a majority of TC neurons are steadily hyperpolarized and display phasic IPSPs in close time relation with cortical PDSs that excite GABAergic RE neurons. The inhibition of TC neurons during SW seizures, and their inability to relay signals from the external world, may contribute in humans to the period of unconsciousness that is associated with petit-mal epilepsy.

The results of in vivo experiments showing that the neocortex is the leading factor in the generation of SW seizures, that most TC neurons are silent during these seizures, and that GABAergic RE neurons (driven by corticothalamic paroxysmal inputs) are responsible for the steady hyperpolarization and phasic IPSPs in TC neurons (Steriade and Contreras 1995), were corroborated by in vivo experiments conducted in a genetic model of SW seizures (Slaght et al. 2000). The same concept is now supported by a series of studies in slices. Thus corticothalamic stimulation induces bursting at 3 Hz in thalamic neurons; however, following the removal of cortex, such bursts can no longer be evoked in the thalamus (Kao and Coulter 1997). In mouse thalamocortical slices, prolonged paroxysmal depolarizing potentials elicited by GABAA-receptor antagonists were present in cortex isolated from the thalamus but not in thalamus isolated from the cortex (Golshani and Jones 1999). Finally the idea that corticofugal volleys are decisive in the induction of paroxysmal thalamic activity at 3-4 Hz is now confirmed in work conducted in vitro (Bal et al. 2000; Blumenfeld and McCormick 2000) in contrast to the previous hypothesis that thalamic networks are alone implicated in the genesis of SW seizures.

Concluding remarks

Several lines of evidence point to the powerful effects exerted by network synaptic activity on intrinsic neuronal properties of neocortical and thalamic neurons. Firing patterns of cortical neurons, as elicited by depolarizing current pulses, are transformed from one type to another with changes in Vm and increased synaptic volleys during shifts in the level of vigilance from disconnected to activated behavioral states. Basic intrinsic properties of thalamic neurons, such as the Ca2+-dependent LTS, are overwhelmed by barrages of PSPs in ascending and descending pathways, and local thalamic oscillations are not exclusively generated by intrinsic properties of TC neurons but rather by long-range synaptic connections involving the pacemaking GABAergic RE neurons. Instead of pure, simple rhythms generated in circumscribed territories, as found in simplified in vitro preparations, the global electrical activity of intact brains in living animals displays complex wave sequences consisting of grouped oscillations consisting of both low- and fast-frequency rhythms due to corticothalamic interactions under the control of generalized modulatory systems. The cerebral cortex controls the shape and synchronization patterns of thalamic neurons during both normally developing and paroxysmal activities. All this complexity of global operations requires investigation in intact-brain preparations.


    ACKNOWLEDGMENTS

I thank the following PhD students and postdoctoral fellows for skillful and creative collaboration in experiments performed in recent years (in alphabetical order): F. Amzica, D. Contreras, R. Curró Dossi, F. Grenier, D. Neckelmann, A. Nuñez, D. Paré, and I. Timofeev. Collaboration with T. J. Sejnowski, A. Destexhe, W. W. Lytton, and M. Bazhenov was instrumental in computational studies. The assistance of P. Giguère was essential for the technical development of my laboratory.

Personal experiments discussed in this article are supported by grants from the Canadian Institutes for Health Research (MT-3689 and MOP-36545), Natural Sciences and Engineering Research Council of Canada (170538), Human Frontier Science Program (RG0131), and National Institute of Neurological Disorders and Stroke (1-R01 NS-40522-01).


    FOOTNOTES

Author E-mail: mircea.steriade{at}phs.ulaval.ca.

Received 20 November 2000; accepted in final form 7 March 2001.


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