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Unité de Neurosciences Intégratives et Computationnelles, Centre National de la Recherche Scientifique, Gif-sur-Yvette, France; Howard Hughes Medical Institute and the Salk Institute; Department of Biology, University of California at San Diego, La Jolla, California
ABSTRACT I. INTRODUCTION A. Brain Rhythms B. The Building Blocks of EEG Rhythms C. Interaction Between Intrinsic and Synaptic Conductances D. Thalamocortical Loops II. SINGLE-CELL PACEMAKERS: OSCILLATIONS AND BURSTS EMERGING FROM THE INTERPLAY OF INTRINSIC CONDUCTANCES IN SINGLE NEURONS A. Thalamic Relay Cells 1. Rebound bursts in thalamic relay cells 2. Models of the rebound burst and the role of dendrites 3. Bursts in awake animals 4. Intrinsic oscillations in thalamic relay cells 5. Models of the conductance interplay to generate intrinsic oscillations 6. Waxing-and-waning oscillations 7. Models of waxing-and-waning oscillations B. Thalamic Reticular Neurons 1. Rebound bursts in thalamic reticular cells 2. Models of the rebound burst in RE cells and the role of dendrites 3. Physiological consequences of dendritic calcium currents 4. Intrinsic oscillations in thalamic reticular cells 5. Models of the interacting conductances underlying intrinsic oscillations III. NETWORK PACEMAKERS: OSCILLATIONS THAT DEPEND ON BOTH INTRINSIC AND SYNAPTIC CONDUCTANCES A. Experimental Characterization of Thalamic Oscillations 1. Early experiments 2. Different hypotheses for generating spindles B. Models of the Thalamic Reticular Pacemaker 1. Early models 2. Models of oscillatory behavior in networks of reticular neurons C. Models of the TC-RE Pacemaker 1. Elementary TC-RE oscillator 2. Oscillations generated by TC-RE networks 3. Traveling patterns of spindle waves in vitro 4. Dynamic clamp reconstruction of the TC-RE oscillator D. Reconciling Different Pacemaker Mechanisms IV. THALAMOCORTICAL PACEMAKERS: CONTROL AND SYNCHRONIZATION OF OSCILLATIONS FROM INTERACTING NETWORKS A. The Large-Scale Synchrony of Slow-Wave Oscillations 1. Experimental characterization of large-scale synchrony 2. Mechanisms underlying large-scale synchrony in the thalamocortical system 3. Traveling patterns of spindle waves in vivo 4. The contribution of cortico-cortical connectivity to large-scale coherence B. Pathological Behavior: Absence Seizures 1. Thalamic and cortical contributions to generalized seizures 2. The receptor types involved in seizure activity 3. Models of paroxysmal discharges in the thalamus 4. Model of absence seizures in the thalamocortical system 5. Control of thalamic oscillations by corticothalamic feedback C. Computational Roles of Synchronized Oscillations 1. Evidence for memory reprocessing during slow-wave sleep 2. The spatiotemporal structure of slow-wave sleep 3. The impact of slow waves on cortical neurons 4. Cellular mechanisms for memory reprocessing during slow-wave sleep V. SUMMARY AND CONCLUSIONS A. A Framework for Thalamic and Thalamocortical Oscillations B. Successful, Unsuccessful, and Untested Predictions 1. Successful predictions 2. Unsuccessful or unclear predictions 3. Yet untested predictions C. Concluding Remarks
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I. INTRODUCTION |
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The rhythmic nature of electrical activity in the brain was first discovered in electroencephalographic (EEG) recordings from the scalp by Caton in 1875, and later by Berger in humans (25). They observed that the frequency and amplitude of the oscillations vary widely across different behavioral states. Awake and attentive states are characterized by low-amplitude, high-frequency EEG activity, with significant power in the beta (20-30 Hz) and gamma (30-80 Hz) frequency bands. Large-amplitude alpha rhythms (8-12 Hz) appear mostly in occipital cortex in aroused states with eyes closed and are reduced with eyes open (25). The early stages of sleep are characterized by spindle waves (7-14 Hz), which consist of short bursts of oscillations lasting a few seconds and displaying a typical waxing-and-waning appearance. When sleep deepens, slow-wave complexes, such as delta (1-4 Hz) and slower waves (
1 Hz), progressively dominate the EEG. Slow-wave sleep is interrupted by periods of rapid-eye-movement (REM) sleep, during which the EEG activity has a low amplitude and high frequencies, similar to that during arousal. Finally, the cortex participates in several forms of epileptic seizures, such as the 3-Hz "spike-and-wave" complexes (241).
B. The Building Blocks of EEG Rhythms
The earliest explanation for the EEG rhythmicity was the "circus movement theory" proposed by Rothberger in 1931 (cited in Ref. 38). According to this theory, the rhythms are due to action potentials traveling along chains of interconnected neurons. The period of the rhythmicity corresponded to the time needed for a volley of action potentials to traverse a loop in the chain. Inspired by the circus movement theory, Bishop (28) proposed the concept of "thalamocortical reverberating circuits," in which the rhythmicity was generated by action potentials traveling back and forth between thalamus and cortex. Although the reverberating circuit theory remained prevalent for several years, subsequent experiments demonstrated that the EEG activity is not generated by action potentials (260), invalidating a fundamental premise of the circus movement theory.
An alternative proposal by Bremer (38-40) suggested instead that brain rhythms reflect the autorhythmic properties of cortical neurons and that the EEG is generated by nonpropagated potentials, in analogy with the electrotonic potentials in the spinal cord (33). Bremer (39) also proposed that cortical oscillations should depend on the "excitability cycle" of cortical neurons. He emphasized that cortical neurons are endowed with intrinsic properties that participate in rhythm generation and that brain rhythms should not be described as the passive driving of the cerebral cortex by impulses originating from pacemakers (37, 40). Bremer's proposal for the genesis of EEG rhythmicities rested on four core ideas: 1) the EEG rhythmicity is generated by the oscillatory activity of cortical neurons; 2) the genesis of these oscillations depends on properties intrinsic to cortical neurons; 3) EEG oscillations are generated by the synchronization of oscillatory activity in large assemblies of cortical neurons; and 4) the mechanisms responsible for synchronization are due to intracortical excitatory connections. Most of these assumptions have been validated, and the modern view of EEG genesis is largely based on these principles (see below).
Experiments on motoneurons in the spinal cord (110) provided convincing evidence that the EEG reflects summated postsynaptic potentials. To explain the slow time course of EEG waves, Eccles (110) postulated that distal dendritic potentials, and their slow electrotonic propagation to soma, participate in the genesis of the EEG. This assumption was confirmed by intracellular recordings from cortical neurons, which demonstrated a close correspondence between the EEG and synaptic potentials (68, 69, 184). This view of the genesis of the EEG is still widely held (243).
C. Interaction Between Intrinsic and Synaptic Conductances
Spinal motoneurons integrate synaptic activity and, when a threshold membrane potential is reached, emit an action potential that is followed by a prolonged hyperpolarization (43, 110). This led to an early model of the neuron based on the concept of "integrate and fire" followed by a reset. Early views about activity in other parts of the central nervous system, particularly the cerebral cortex, were strongly influenced by studies of motoneurons, and brain activity was thought to arise by interactions between similar neurons connected in different ways. In this "connectionist" view, the function of a brain area was determined primarily by its pattern of connectivity (110).
Studies on invertebrates during the 1970s revealed that neurons are endowed with complex intrinsic firing properties that depart from the traditional integrate-andfire model (2, 55-57, 176). Further evidence against the integrate-and-fire view came from studies of small invertebrate ganglia showing that connectivity was insufficient by itself to specify function (126, 274) and that the modulation of intrinsic properties needed to be taken into account (146). The generality of these results was confirmed in intracellular recordings from vertebrate slice preparations (6, 171, 172, 204-207), which revealed that central neurons also have complex intrinsic properties (202).
The nonlinear interactions between ionic conductances are complex. Computational models can make a significant contribution in linking the microscopic properties of ion channels and cellular behavior. This approach was used by Hodgkin and Huxley (157) to understand the genesis of action potentials, and essentially the same approach has been used in modeling studies to understand the complex behavior of central neurons. Perhaps the best characterized neurons in the vertebrate brain are those in the thalamus, which we review here (see sect. II).
In addition to having complex intrinsic properties, neurons also interact in various ways, including chemical synaptic transmission, electrical coupling through gap junctions, and ephaptic interactions through electric fields. Whole cell and patch-clamp recording techniques (264) have been used to investigate the detailed mechanisms underlying the conductances of ionic channels involved in synaptic transmission. An extraordinarily rich variety of dynamic properties of synaptic interactions between central neurons has been uncovered on a wide range of time scales. Many neurotransmitters and receptor types have been identified in the thalamocortical system (222), each of which confers characteristic temporal properties to synaptic interactions. The properties of the main receptor types mediating synaptic interactions are now well understood.
It is now well accepted that rhythmicity arises from both intrinsic and synaptic properties (106b, 310, 312). Some neurons generate oscillations through intrinsic properties and interact with other types of neurons through multiple types of synaptic receptors. These complex interactions generate large-scale coherent oscillations. Understanding how the interactions between ionic conductances can generate rhythms is difficult, and computational models can help in exploring the underlying mechanisms. This review shows how this approach has been used to understand how the interplay between intrinsic and synaptic conductances generate oscillations at the network level (see sect. III).
We focus here on two types of rhythms: spindle oscillations and absence seizures, both of which are generated in the thalamocortical system schematized in Figure 1. Sensory inputs from visual, auditory, and somatosensory receptors do not reach the cerebral cortex directly, but synapse first on thalamocortical (TC) relay cells in specific regions of the thalamus. These relay cells in turn project to their respective area in primary sensory cortex. These topographically organized forward projections are matched by feedback projections from layer 6 of cortex to the corresponding afferent thalamic nucleus (174, 278).
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Within the thalamus, there are reciprocal connections between TC and thalamic reticular (RE) neurons. The RE cells are GABAergic and send their projections exclusively to relay nuclei, but they also receive excitatory collaterals from both ascending (thalamocortical) and descending (corticothalamic) fibers. Thalamocortical loops therefore include both bidirectional excitatory interactions between the cortex and thalamus and inhibition through the collaterals of ascending and descending fibers to GABAergic neurons. These inhibitory interactions are needed to explain the large-scale synchrony of thalamocortical oscillations (see sect. IV).
Several types of brain rhythms originate in the thalamocortical system. Spindle waves are by far the best understood type of rhythmicity in this system, in part because they can be enhanced by anesthetics such as barbiturates (8, 81). The thalamic origin of spindles was first suggested by Bishop (28), who observed the suppression of rhythmic activity in the cortex after sectioning connections with the thalamus and was confirmed in experiments on decorticated animals (3, 234). The cellular events underlying this rhythmic activity have been identified in vivo (305, 310) and in isolated thalamic slices in vitro (346). The biophysical mechanisms underlying spindle rhythmicity were uncovered in slice preparations, particularly the voltage-dependent conductances and receptor types involved. Theories for the genesis and termination of spindle oscillations need to be rigorously tested.
Absence seizures also originate in the thalamocortical system. Because they are generalized and involve large-scale synchrony, Jasper and Kershman (173) suggested that they may have foci in thalamic nuclei that widely project to cortex. This hypothesis was supported by chronic recordings during absence seizures in humans, showing that signs of a seizure were observed first in the thalamus before appearing in the cortex (360; but see Ref. 240). Experimental models of absence seizures, such as the penicillin model in cats (256), showed that although the thalamus is critical for generating seizures, it was not sufficient to explain all of their properties. Seizures can be obtained from injection of convulsants limited to cerebral cortex, but not when the same drugs are injected into the thalamus (130, 258, 302). It is now clear that both the thalamus and the cortex are necessary partners in these experimental models of absence seizures, but the exact mechanisms are unknown (74, 129). Computational models can help identify the critical parameters involved in the genesis of pathological behavior, as well as suggest ways to resolve apparently inconsistent experimental observations, as explored in section IV.
Despite progress in understanding how the EEG is generated, the possible significance of brain oscillations for the large-scale organization of information processing in the brain remains a mystery. After summarizing current knowledge of the mechanisms that generate spindle oscillations, absence seizures, and other types of thalamocortical oscillations, we explore possible functions for these rhythms (see sect. IVC) suggested by the computational models.
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II. SINGLE-CELL PACEMAKERS: OSCILLATIONS AND BURSTS EMERGING FROM THE INTERPLAY OF INTRINSIC CONDUCTANCES IN SINGLE NEURONS |
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1. Rebound bursts in thalamic relay cells
In addition to relaying sensory input to cortex, TC neurons have intrinsic properties that allow them to generate activity endogenously. Following inhibition, these cells can under some circumstances produce bursts of action potentials, called a "low-threshold spike" (LTS) or "postinhibitory rebound." The importance of the rebound response of TC cells was first established by Andersen and Eccles (9), who called it "postanodal exaltation." It was later characterized in vitro by Llinás and Jahnsen (209) and in vivo by Deschênes et al. (84) and has become generally known as the "rebound burst" or LTS. Andersen and Eccles (9) were the first to show that TC cells display bursts of action potentials tightly correlated with the offset of inhibitory postsynaptic potentials (IPSPs).
In vitro studies (209, 171) demonstrated that TC cells possess two different firing modes. In the "tonic" mode, near the resting membrane potential (approximately -60 mV), the relay neuron fires trains of action potentials at a frequency proportional to the amplitude of the injected current (Fig. 2A, left panel). This is similar to the response of many other neurons and is explained by the voltage-dependent Na+ and K+ currents that generate action potentials. In contrast, at hyperpolarized membrane potentials, thalamic neurons can enter a "burst mode" (Fig. 2A, right panel), firing high-frequency bursts of action potentials (300 Hz) at the offset of hyperpolarizing current injection. A burst can also occur following a strong IPSP, which provides hyperpolarization and return to rest similar to the conditions simulated by current injection. The response of a neuron to a depolarizing current injection depends on its previous state, producing a steady low-frequency firing rate if injected at a depolarized level, but eliciting a burst followed by a long afterhyperpolarization if injected in a sufficiently hyperpolarized state.
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The ionic mechanism underlying the "low-threshold" behavior of thalamic neurons is a slow, low-threshold Ca2+ current (171, 172), which was characterized in voltage-clamp experiments (67, 71, 148, 319). This current is carried by low-voltage activated Ca2+ channels described previously (49, 50) and later called "T-type" Ca2+ channels (242). Cloning of the T-type channels revealed several distinct subunits, which may account for functional difference according to the type of subunit assembling the channel (192). Like the Na+ current described by Hodgkin and Huxley (157), the T current (IT) of thalamic neurons is transient and shows activation followed by inactivation. However, the voltage range over which IT activates is close to the resting potential, in contrast to the Na+ current, which activates at more depolarized levels. The kinetics of IT are considerably slower than the Na+ current. A voltage-clamp characterization of the IT in thalamic cells performed in dissociated TC cells by Huguenard and Prince (163) provided the quantitative data on the kinetics of activation and inactivation of this current used in the computational models below.
2. Models of the rebound burst and the role of dendrites
Hodgkin and Huxley (157) introduced computational models to determine whether the ionic mechanisms identified in their voltage-clamp measurements were sufficient to account for the generation of the action potential. The same approach was taken to study the genesis of bursting behavior. Hodgkin-Huxley-type models of TC neurons were first introduced by McMullen and Ly (230) and Rose and Hindmarsh (262) based on the experiments of Jahnsen and Llinás (171). The more recent characterization of the IT by voltage-clamp methods (see above) provided precise measurements for the time constants and steady-state values of activation and inactivation processes. Several Hodgkin-Huxley-type models based on voltage-clamp data replicate the rebound-burst properties of TC cells (95, 96, 106, 162, 214, 225, 332, 352, 356). The most salient features of the rebound burst can be reproduced by single-compartment models containing Na+,K+, and T-type currents described by Hodgkin-Huxley-type kinetics (Fig. 2B). Simplified "integrate-fire and burst" models have also successfully reproduced the most salient features of TC cells bursts (284). However, to reproduce all the features of the rebound burst in TC cells, the IT must be concentrated in the dendrites, where a large number of synaptic terminals are located (174, 197).
Imaging experiments clearly show dendritic calcium signals during bursts in TC cells (238, 373), consistent with results from current-clamp and voltage-clamp experiments (106, 371). The dendritic localization of the IT was shown by direct measurements of channel activity in dendrites (361). To estimate the IT density in dendrites, a TC neuron was recorded in slices of the ventrobasal thalamus (163), stained with biocytin, and reconstructed using a computerized camera lucida (106). Two sets of data were used to constrain the amount of calcium current in dendrites. First, recordings of the IT were made from dissociated TC cells (163), which lack most of the dendritic structure and are electrotonically compact, therefore minimizing voltage-clamp errors. These recordings were then compared with voltage-clamp measurements of the IT in intact TC cells, which were 5-14 times larger than in dissociated cells (106).
Models based on the reconstructed dendritic morphology of TC cells were used to explore the consequences of varying the density of the current in the different dendritic and somatic regions (106). The low amplitude of IT in dissociated cells could be reconciled with the high-amplitude currents observed in intact cells if the concentration of T-type calcium channels was 4.5-7.6 times higher in the dendrites than in the soma (106). The same density gradient of calcium channels in the model also reproduced the bursts of spikes evoked in the current-clamp protocols (106). Similar findings were reported in another modeling study (12), which predicted that the dendrites of TC cells must contain the IT (in addition to delayed-rectifier K+ current IKd). This was needed for the model to generate tonic or burst firing with the correct voltage-dependent behavior and oscillations (12).
The predicted high densities of T-type calcium channels in the dendrites of TC cells were confirmed by direct measurements of channel activity using cell-attached recordings (361). The density was, however, not uniform, but was concentrated mostly in stem dendrites up to 40 µm from the soma, while distal dendrites had low T-channel densities. The results based on this type of distribution were equivalent to those based on the distribution of IT density discussed above.1 Thus it is essential that most of the T channels are dendritic, but how they are distributed within the dendrites is not critical. A similar conclusion about dendritic currents was reached in a model of delta oscillations in TC cells (113).
The localization of dendritic calcium currents in dendrites has several functional consequences. First, the presence of the calcium current at the same sites as inhibitory synapses is likely to enhance the rebound responses of TC cells (106c). Second, the shunting effects of tonic excitatory cortical synapses and inhibitory synapses on burst generation would be more effective if the IT were dendritic (106). As a consequence, the activity of corticothalamic synapses can counteract bursting, and rapidly switch the TC neuron from the burst mode (cortical synapses silent) to the tonic mode (sustained cortical drive). Local dendritic interactions thus allow corticothalamic feedback to potentially control the state of thalamic neurons on a millisecond time scale compared with conventional neuromodulatory mechanisms, which operate over hundreds of milliseconds (222).
The TC cells in the thalamus generate powerful synchronized bursts of action potentials during sleep; in comparison, the activity in alert animals is dominated by single-spike (tonic) firing (201, 309). There is, however, evidence for the presence of bursts in the thalamus of awake animals (142, 143, 278). These thalamic bursts may represent a special type of information in alert states, such as novelty detection (278). However, the occurrence of bursts is rare in the thalamus of aroused animals and may instead signify that the animal is drowsy (296); this possibility is supported by observations that thalamic bursts are negatively correlated with attention (357).
The occurrence of bursts as a rebound to inhibition during oscillatory states similar to sleep oscillations (9, 305, 312) has been intensively studied with computational models (reviewed in Ref. 106b), but bursts following excitatory inputs have not been as well studied (106c). Excitatory stimulation by sensory synapses was modeled by a constant density of glutamatergic (AMPA) synapses on proximal TC dendrites (174, 197), up to 40 µm from the soma. The threshold for action potential generation was estimated by increasing the conductance of this synapse and, as expected, when the cell was hyperpolarized (less than -65 mV), the synaptic stimulus could evoke bursts of action potentials. At more depolarized resting values (more than -65 mV), excitatory stimuli evoked tonic firing. In control conditions, the region of membrane potential corresponding to the burst mode was large, and the minimal excitatory postsynaptic potential (EPSP) amplitude to evoke a burst was about 0.035 µS (106c), which represents 230-350 simultaneously releasing glutamatergic synapses, based on an estimated quantal amplitude of 100-150 pS (246, 247). Models therefore predict that an excitatory stimulus should efficiently evoke bursts only when the TC cell is in the right range of membrane potentials.
In contrast, when the membrane of model TC cells was more leaky, as occurs during tonic activity of the network in vivo, the burst region narrowed, and there was a large range of stimulus amplitudes for which the only possible spike output was the tonic mode (106c). Under these conditions, the minimal EPSP amplitude needed to evoke bursts was 0.09 µS, which corresponds to 600-900 simultaneously releasing synapses. In the visual thalamus, the evoked conductance from a single retinal afferent is 0.6-3.4 nS (1.7 nS on average), which represents from 4 to 27 quantal events (246). This suggests that the simultaneous release of all terminal sites from 8 to 87 retinal axons are required to evoke bursts in relay cells (from 22 to 220 under in vivo conditions). However, one morphological study reported that a single retinal axon can make a large number of synaptic terminals onto the same relay neuron, forming a significant proportion of all of its retinal synapses (145). It is therefore possible that the convergence of a relatively small number of afferent axons could evoke bursts, which would support the notion that bursts are easily triggered by afferent excitatory synapses. More precise measurements of the number of synaptic terminals from single axons are needed to determine the convergence of afferent activity needed to trigger bursts in relay cells.
Models of TC neurons based on reconstructed morphologies and dendritic IT therefore suggest that sensory-initiated bursts are possible, but they require a large convergence of excitatory stimuli and are more likely to occur under conditions of low activity. This is consistent with the view that in burst mode the thalamus strongly filters afferent information (223). This also supports the view that bursts may be a "wake-up call" signal during drowsiness or inattentive states (278), although it is not clear how the cortex would distinguish these "wake-up" bursts from bursts occurring spontaneously (or in an oscillation) during states of low vigilance.
4. Intrinsic oscillations in thalamic relay cells
In addition to displaying burst and tonic modes, TC cells can also generate sustained oscillations. In experiments performed in cats in vivo, TC cells generated oscillations in the delta frequency range (0.5-4 Hz) after removal of the cortex (73). Oscillations in the same frequency range were also observed in TC cells in vitro (190, 191, 226). These intrinsic slow oscillations consisted of rebound bursts recurring periodically and have been also called "pacemaker oscillations" (190, 191). These slow oscillations were resistant to tetrodotoxin, suggesting that they were generated by mechanisms intrinsic to the TC cell.
The intrinsic delta oscillations depend on the membrane potential (226). Oscillations were only possible if TC cells were maintained at relatively hyperpolarized potentials, within the range of the burst mode, suggesting that the IT actively participated in its generation. Another property, illustrated in Figure 3A, is that these oscillations disappeared following blockade of another current, called Ih (226) with Cs+. Ih is a mixed Na+/K+ cation current responsible for anomalous rectification in TC cells (253). In voltage-clamp, Ih is activated by hyperpolarization in the subthreshold range of potentials (226, 290). These data indicate that intrinsic oscillations in TC cells are generated by an interplay between IT and Ih.
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5. Models of the conductance interplay to generate intrinsic oscillations
Several computational models have shown that the interaction between Ih and IT can account for the genesis of low-frequency oscillations in TC cells (91, 95, 96, 214, 217, 225, 332, 352). In addition to IT (see above), these models included Hodgkin-Huxley-type models of Ih based on voltage-clamp data obtained in TC cells. Several types of models have been used for this current, beginning with simple one-variable models based on a single activation gate (96, 214, 217, 225, 332, 352). This class of models only has one gate and cannot account for the observation that the Ih activates slowly, with a time constant greater than 1 s at 36°C (226, 290), but deactivates faster (114, 125, 175, 335, 340). A model with a dual gating process, combining fast and slow activation gates, can reproduce the voltage-clamp behavior of Ih in detail (91, 95).
Although both types of models of Ih gave rise to slow oscillations when Ih is combined with IT, the double-activation model generated more complex oscillatory patterns, such as waxing-and-waning oscillations (see below). Figure 3B illustrates the oscillations generated by a single-compartment model of a TC cell comprising IT and Ih, as well as INa/IK responsible for action potentials. Examination of IT and Ih conductances during the oscillation revealed that the activation of Ih depolarizes the membrane slowly until a LTS is generated by activation of IT. During the depolarization provided by the LTS, Ih deactivates, and together with the termination of the LTS the membrane becomes hyperpolarized. This hyperpolarization allows IT to deinactivate to prepare for the next LTS, and as Ih slowly activates, the cycle restarts. The same mechanism has been explored, with minor variations, in several modeling studies that used different models of IT and Ih (91, 95, 96, 152, 214, 217, 225, 332, 352), suggesting that the interplay between IT and Ih is a highly robust way to generate slow oscillations. This conclusion is also supported by a dynamic-clamp study showing that delta oscillations are lost in TC cells if Ih is blocked, but can be restored by injection of a computer-generated Ih conductance (161).
6. Waxing-and-waning oscillations
The slow intrinsic oscillations generated by TC cells can be modulated by different factors. Cat TC cells studied in a low-Mg2+ medium in vitro displayed either a resting state, sustained slow oscillations, or intermittent "waxing-and-waning" oscillations (190, 191) (second trace in Fig. 3A). The latter consisted of an alternation between periods of oscillation (0.5-3.2 Hz), lasting 1-28 s, with periods of silence, lasting 5-25 s, during which the membrane progressively hyperpolarized. The waxing-and-waning envelope was resistant to tetrodotoxin (191), suggesting mechanisms intrinsic to the TC neuron. In analogy with the waxing and waning of spindles observed in vivo, they have also been called "spindlelike oscillations" (190,191). However, in vivo spindles oscillate at a higher frequency (7-14 Hz) and depend on interactions with neurons of the thalamic reticular nucleus (see sect. IIIC), which distinguishes them from the waxing-and-waning oscillations intrinsic to TC cells.
The pharmacology of intrinsic waxing-and-waning oscillations was investigated by Soltesz et al. (290), who found that they were dependent on Ih. Slow delta-like oscillations and waxing-and-waning oscillations can be observed in the same TC cell by altering Ih (290) (Fig. 3A). Increasing the amplitude of Ih by norepinephrine can transform delta-like oscillations into waxing-and-waning oscillations; application of Cs+, an Ih blocker, transforms the depolarized state into waxing-and-waning oscillations, the delta-like oscillations, and finally a hyperpolarized resting state (290) (Fig. 3A). In addition, the intrinsic waxing-and-waning oscillations can be transformed into sustained slow delta-like oscillations by applying a depolarizing current (190, 191).
7. Models of waxing-and-waning oscillations
Several ionic mechanisms for generating waxing-and-waning oscillations have been suggested. The first model (95) was inspired by experiments on the Ih current in heart cells demonstrating regulation of Ih by intracellular Ca2+ (144). The steady-state activation of Ih is dependent on the intracellular Ca2+ concentration ([Ca2+]i), shifting toward more positive membrane potentials with increasing [Ca2+]i (144). Because calmodulin and protein kinase C were not involved in the Ca2+ modulation of Ih, Ca2+ may affect the Ih channels directly (144), with the binding of Ca2+ increasing the conductance of Ih, or indirectly through the production of cAMP (213). Different variants of calcium-dependent regulation of Ih have been proposed (72, 85, 222).
The modulation of Ih by Ca2+ was studied in several bursting models of the TC cells. The simplest model was based on the assumption that Ca2+ bind directly to the open state of the channel, thereby "locking" Ih into the open configuration and shifting its voltage dependence as observed experimentally (95). Calcium upregulation was also proposed to occur according to a model in which the calcium indirectly affects the Ih channel through an intermediate messenger, which itself binds to the open state of Ih channels (96). Another ionic mechanism for waning has been proposed (350) based on activity-dependent adenosine production, which affects the voltage dependence of Ih but in the opposite direction (244). Waxing-and-waning oscillations were also modeled by the interaction between IT, Ih, and a slow potassium current (91, 152).
All models generated waxing-and-waning oscillations, but only those based on the upregulation of Ih by Ca2+ reproduced the slow periodicity, the slow oscillation frequency, and the progressive hyperpolarization of the membrane during the silent period. Moreover, the Ca2+-dependent models also displayed the correct coexistence of oscillatory and resting states in TC cells, as shown in Figure 3Bi. For fixed IT conductance, increasing Ih conductance led successively to slow oscillations in the delta range (1-4 Hz), then to waxing-and-waning slow oscillations and, finally, to the relay resting state, consistent with in vitro studies (290) (compare with Fig. 3A). According to this mechanism for waxing-and-waning oscillation (Fig. 3Bii), calcium enters through IT channels on each burst, resulting in an increase of Ca2+ (or Ca2+-bound messenger) and a gradual increase of Ih channels in the open state (OL). This produces a progressive afterdepolarization (ADP) following each burst until the cell ceases to oscillate (Fig. 3Bii). The membrane then progressively hyperpolarizes during the silent period, as Ih channels unbind the messenger.
The presence of this ADP was observed during waxing-and-waning oscillations in cat TC cells maintained in low magnesium in vitro (191), as well as in ferret thalamic slices (19). It is possible to artificially induce this ADP by evoking repetitive burst discharges in TC cells (19). The ADP is responsible for a marked diminution of input resistance in successive responses (19). These features were observed in a model based on the upregulation of Ih by Ca2+ (96).
Recent experiments provide direct evidence for the Ca2+-dependent regulation of Ih channels predicted in modeling studies. Although Ca2+ does not directly modulate Ih channels in thalamic neurons (44), experiments with caged Ca2+ in thalamic neurons have demonstrated an indirect calcium-dependent modulation of Ih (212), with cAMP acting as the intermediate messenger (213).
1. Rebound bursts in thalamic reticular cells
RE neurons recorded in awake animals fire tonically, but during slow-wave sleep the activity of these cells changes to rhythmic firing of bursts (307). A typical burst of action potentials in an RE cell during natural sleep shows an accelerando-decelerando pattern of action potentials (Fig. 4A). In intracellular recordings, both modes of firing in RE cells could be elicited, depending on the membrane potential. Depolarizing current pulses from -68 mV produced tonic firing, whereas the same pulse delivered at more hyperpolarized levels elicited a burst. The burst in a model RE cell shows a slowly rising phase and is broader than in TC cells, and there is always an accelerando-decelerando pattern of sodium spikes, typical of RE cells recorded from anesthetized, naturally sleeping animals as well as in animals under different anesthetics (59, 107, 237, 307) (Fig. 4A).
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The rebound burst of RE cells studied in vitro (14, 17), like that of TC cells, is mediated by a low-threshold Ca2+ current. However, the characterization of the T-type Ca2+ current in RE cells by voltage-clamp methods revealed marked differences with the IT of TC cells. In RE cells, the kinetics were slower and the activation was less steep and more depolarized than that found in TC cells (163). This current was named "slow IT", or ITs. In some preparations, however, the IT of RE cells appears to be similar to that of TC cells (333). Nevertheless, the observation of two distinct types of T channels is consistent with the differences observed after reconstitution of cloned T channels, which displayed different voltage dependence and kinetics and regional distribution (321). In particular, thalamic relay and reticular neurons express different T-channel subtypes (321), consistent with the electrophysiological differences found between TC and RE neurons (163).
2. Models of the rebound burst in RE cells and the role of dendrites
The properties of burst generation in RE cells were examined in Hodgkin and Huxley (157) types of models derived from voltage-clamp measurements. Early models (90, 355) used a IT similar to that found in TC cells, based on the data available at that time (14, 208, 228). More recent characterization of the kinetics of the IT in RE cells (163) has led to more accurate models of ITs in these cells (97, 348).
Although single-compartment Hodgkin-Huxley type models were able to account for the genesis of bursts in RE cells, not all features of these bursts were found. For example, the slowly rising phase of the burst, its broad structure, and the accelerando-decelerando pattern of sodium spikes within RE bursts were not apparent (14, 17, 99, 165). Another feature not found in the models was that RE bursts show qualitative differences between preparations: RE cells generate bursts in an all-or-none fashion in vitro (99, 165), but bursts can be activated gradually in vivo (59, 99).
The failure of a Hodgkin-Huxley model to simulate these properties could reflect an incomplete knowledge of the biophysical parameters of the IT because of errors in voltage-clamp measurements. This is unlikely, however, because these measurements were done in dissociated RE neurons, which are electrotonically compact, and the recordings had high resolution and low error. Another possibility, proposed previously (237), is that because the IT of intact cells is located in the dendrites, the electrophysiological behavior recorded in the soma is significantly distorted. This possibility was tested using compartmental models of the dendritic morphology of RE cells (99).
Following a similar approach to that taken with TC cells in section IIA2, an RE neuron was recorded in the reticular sector of the ventrobasal thalamus in rat thalamic slices (163), stained with biocytin, and reconstructed using a computerized camera lucida (Fig. 4B, left). Voltage-clamp recordings were also obtained from dissociated RE cells (163), which are mostly devoid of dendrites, and intact RE cells (99). Computational models were then used to estimate how much current density must be located in dendrites to reproduce all the experimental results. The conclusion was that high densities of IT must be located in dendrites to account for these measurements.
Bursts generated with dendritic IT are shown in Figure 4B. The calcium spike generated in the dendrites slowly injects current into the soma/axon, where action potentials are generated. The slowly rising phase of the burst as well as the accelerando-decelerando pattern result from an interaction between the soma and dendrites and the slow kinetics of the IT (99). Dendritic IT also accounts for the broader currents seen in intact RE cells under voltage clamp. Moreover, bursts were all or none under control conditions but were graded in simulations of in vivo conditions when synaptic background activity was included. These features were a direct consequence of dendritic Ca2+ currents and were confirmed by presumed intradendritic recordings (see details in Ref. 99).
3. Physiological consequences of dendritic calcium currents
In contrast to TC cells, RE cells are highly noncompact electrotonically. Comparing neurons reconstructed from the same animal, the maximal electrotonic length of TC cells was 0.34 (106), compared with 2.7 in RE neurons (99). Consequently, the dendrites are relatively decoupled from the soma in RE cells, and the dendritic localization of voltage-dependent currents is likely to have significant consequences in these cells.
The first consequence is that the colocalization of dendritic IT with dendritic GABAergic synapses may enhance the rebound properties of these neurons. RE neurons contact their neighbors through GABAergic axon collaterals (21, 174, 197) or dendro-dendritic GABAergic synapses (83, 252, 368). Intracellular recordings revealed GABAergic IPSPs in RE cells (21, 97, 265, 266, 280, 336, 372), but they are of relatively low amplitude and might not be sufficient to elicit a rebound burst at short latency (338). However, if the IT is dendritic, IPSPs arising from neighboring RE cells might initiate rebound bursts in localized dendritic regions, without a trace of IPSP in somatic recordings (106c). The possibility that mutual inhibitory interactions between RE cells may generate rebound bursts and oscillatory behavior is considered in section IIIB.
Alternatively, if the dendrites of RE cells at rest are close to the reversal potential of the IPSPs, GABAergic inputs could counteract the initiation of burst discharges by shunting inhibition. In this case, mutual inhibition between RE cells would prevent them from generating large bursts, which may protect the cells from epileptic discharges (see sect. IVB). Thus interactions between RE cells will critically depend on the dendritic membrane potential and the reversal potential of IPSPs. The range of possible interactions, and their impact at the network level, is considered in section IIIB.
Dendritic IT make RE cells exquisitely sensitive to cortical EPSPs. Models have shown that glutamatergic (AMPA) EPSPs, which are subthreshold in the tonic mode, can evoke full-blown bursts of action potentials if the cell is more hyperpolarized (88, 106c). The threshold for burst generation by excitatory synapses was 0.03 µS and increased to 0.065 µS under in vivo conditions, somewhat less than for relay cells. Given that the quantal conductance of glutamatergic synapses on reticular neurons is 266 ± 48 pS (137), these threshold values predict a convergence of 113 excitatory releasing sites in control conditions, and 244 releasing sites under in vivo conditions. However, for focal or "hot-spot" distributions, the threshold was much lower, 0.007 µS, corresponding to 26 releasing sites, but it was not possible to evoke bursts under in vivo conditions in this case (106c).
This remarkable sensitivity occurs only if the dendrites contain a high density of ITs, and if they are hyperpolarized enough to deinactivate the IT. Consistent with this sensitivity, in vivo recordings show that corticothalamic excitatory volleys are extremely efficient in triggering bursts in RE cells and eliciting oscillations (59, 66). The sensitivity of RE cells to cortical EPSPs is the basis for the "inhibitory dominance" hypothesis (100), according to which cortical influence on the thalamus occurs primarily through the feed-forward inhibitory pathway through RE cells rather than the direct excitatory one onto TC cells and is critical for understanding the large-scale synchrony of oscillations (see sect. IVA).
With dendritic localization of ITs, high levels of synaptic background activity may prevent bursts (88, 99, 106c). This suppression of bursting does not occur in a single compartment model, suggesting that the interaction between the soma with sodium spikes and the dendrites with calcium spikes depends on the level of synaptic background activity. The dendrites of RE cells would "sample" the overall synaptic activity between the thalamus and the cortex and tune the responsiveness of the RE cells according to these inputs. For high levels of background activity, which occur during tonic activity in the thalamus and cortex, the RE cell does not have a tendency to fire bursts. For lower levels of background activity, or more phasic inputs such as during synchronized sleep, the dendrites would no longer be bombarded in a sustained manner, and bursting behavior would be enhanced. It is possible that this type of interplay of currents in the dendrites acts in concert with neuromodulation to efficiently switch the thalamus between tonic and bursting modes, which may be an efficient way to implement attentional mechanisms controlled by cortical activity (88).
4. Intrinsic oscillations in thalamic reticular cells
In addition to generating bursts, RE cells also participate in oscillations. In intracellular recordings from cat RE cells in vivo (59, 237), rhythmic bursting activity at a frequency of 8-12 Hz occurred either spontaneously or after stimulation of the internal capsule or thalamus. Typically, a depolarizing envelope accompanied this oscillatory behavior and a slow afterhyperpolarization (AHP) following each burst; the termination of the oscillatory sequence was followed by a tonic tail of spike activity (107). The same features were observed in intracellular recordings of RE cells in vitro (14, 17). A rebound sequence of rhythmic bursts could be elicited in RE cells after current injection. In an in vitro study of rodent RE cells (17), this rhythmic behavior was resistant to tetrodotoxin and was, therefore, intrinsic to the cell. The same study also showed that blocking the AHP with apamin, which blocks a class of calcium-activated potassium current [IK(Ca)], abolished the rhythmic activity. Rhythmic oscillations in RE cells therefore reflect interactions between the T-type Ca2+ current and IK(Ca).
In an in vitro study of spindles in thalamic slices (17), rhythmic oscillations at 7-12 Hz were often followed by a short tonic tail of spikes. Application of TTX revealed an ADP mediated by a nonspecific cation current, activated by intracellular calcium, called ICAN. This current, encountered in many other cell types in the nervous system (245), could underlie the tonic tail of spikes in RE cells (17).
5. Models of the interacting conductances underlying intrinsic oscillations
Several models have been introduced to investigate the repetitive bursting properties of RE cells. All models with ITs, Ca2+, and IK(Ca) robustly generated oscillations at low frequency (2-4 Hz) (97, 105, 355). These oscillations could be elicited as a rebound rhythmic bursting activity in response to a hyperpolarizing pulse. The 2- to 4-Hz frequency was mainly dependent on the level of the resting potential and on the kinetics of ITs and IK(Ca). This mechanism was similar to that suggested by current-clamp experiments (14): following an LTS, Ca2+ enters and activates IK(Ca), which then hyperpolarizes the membrane and deinactivates ITs. When the membrane depolarizes due to the deactivation of IK(Ca), a new LTS is produced and the cycle repeats. The robustness of this mechanism was confirmed in several modeling studies (97, 105, 151, 348, 355).
Despite the ease with which these low-frequency oscillations could be generated, none of the kinetic parameters tested for IK(Ca) was able to produce frequencies in the range 7-14 Hz. The correct oscillations frequencies occurred, however, when the outward current ICAN was included. This current produces a marked ADP after application of tetrodotoxin and apamin (17). In the model (97), such an ADP occurred in the presence of ITs and ICAN as a rebound following a hyperpolarizing pulse. Simulations of a single compartment containing the combination of currents ITs, IK(Ca), and ICAN produced a rebound bursting oscillations at 9- to 11-Hz frequencies. The activation of ICAN accelerated the rising phase of the burst and increased the frequency of the rebound burst sequence. The presence of ICAN also terminated the oscillatory behavior by producing a tonic tail of spikes before the membrane returned to its resting level. Varying the conductance of IK(Ca) and ICAN modulated both the frequency and the relative importance of rhythmic bursting relative to tonic tail activity. These results were confirmed in another modeling study (348), in which the same set of conductances was found to produce oscillations and tonic tail activity. In particular, this study reported a similar dependence of the repetitive firing frequency on the membrane potential, with in addition a dependence on the leak K+ conductance (348).
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III. NETWORK PACEMAKERS: OSCILLATIONS THAT DEPEND ON BOTH INTRINSIC AND SYNAPTIC CONDUCTANCES |
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A. Experimental Characterization of Thalamic Oscillations
In humans, spindle oscillations are grouped in short 1- to 3-s periods of 7- to 14-Hz oscillations, organized within a waxing-and-waning envelope, recurring periodically every 10-20 s. These oscillations typically appear during the initial stages of slow-wave sleep (stage II) and later during transitions between REM and slow-wave sleep. In cats and rodents, spindle waves with similar characteristics appear during slow-wave sleep and are typically more prominent at sleep onset. They are enhanced by some anesthetics, such as barbiturates, which, when administered at an appropriate dose, generate an EEG dominated by spindles (8).
Bishop (28) showed that rhythmical activity was suppressed in cerebral cortex following destruction of its connections with the thalamus and suggested that spindles are generated in the thalamus. Bremer (37) showed that rhythmical activity is still present in the white matter after destruction of the cortical mantle. Later, Adrian (3) and Morison and Bassett (234) observed that spindle oscillations persist in the thalamus upon removal of the cortex, providing strong evidence for the genesis of these oscillations in the thalamus. These experiments led to the development of the "thalamic pacemaker" hypothesis (8, 305), according to which rhythmic activity is generated in the thalamus and communicated to the cortex, where it entrains cortical neurons and is responsible for the rhythmical activity observed in the EEG.
Spindles have also been observed in thalamic slices from different preparations. In the ferret visual thalamus, slices that contain the dorsal (lateral geniculate nucleus or LGN) and reticular nuclei (perigeniculate nucleus or PGN) as well as the interconnections between them (346) can display spindles (Fig. 6A). Spindles have also been observed in mouse (351) and rat (170) thalamic slices, as well as in rat thalamocortical slices (322), where they survived in the thalamus following inactivation of the cortex. These in vitro observations are definitive proof that thalamic circuits are capable of endogenously generating spindle oscillations. Moreover, in vitro preparations have made it possible to precisely characterize the ionic mechanisms involved in spindle oscillations, as shown below.
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2. Different hypotheses for generating spindles
Based on their intracellular recordings of thalamic neurons during spindles, Andersen and Eccles (9) reported that TC cells fired bursts of action potentials interleaved with IPSPs. They suggested that TC cells fire in response to IPSPs (postinhibitory rebound), which was later demonstrated to be a characteristic electrophysiological feature of thalamic cells (see sect. IIA). In particular, they suggested that the oscillations arose from the reciprocal interactions between TC cells and inhibitory local-circuit interneurons. This mechanism was then incorporated into a computational model that provided a phenomenological description of the inhibitory rebound (10) (see also Ref. 210). Although remarkably forward looking, the mechanism of Andersen and Eccles (9) was not entirely correct. Reciprocal connections between TC cells and thalamic interneurons have not been observed in anatomical studies, but intrathalamic loops of varying complexity have been found between TC cells and the inhibitory neurons of the thalamic RE nucleus, which receive collaterals from corticothalamic and thalamocortical fibers and project to specific and nonspecific thalamic nuclei (269). That "TC-RE" loops could underlie recruitment phenomena and spindle oscillations was suggested by Scheibel and Scheibel (269-271), replacing the interneuron in the "TC-interneuron" loops of Andersen and Eccles with the reticular thalamic neurons. They specifically predicted that the output of the RE nucleus should be inhibitory (271) and that the inhibitory feedback from RE cells onto TC cells should be critical for the genesis of thalamic rhythmicity. This hypothesis was supported by the observation that the pattern of firing of RE neurons was tightly correlated with IPSPs in TC neurons (272, 305, 369).
Subsequent experiments have firmly established the involvement of the RE nucleus in the generation of spindles in cats in vivo (306, 308). First, cortically projecting thalamic nuclei lose their ability to generate spindle oscillations if deprived of input from the RE nucleus (306). Second, the isolated RE nucleus can itself generate rhythmicity in the spindle frequency range (308) (Fig. 5A). In these experiments, the thickest region of the RE nucleus, the rostral pole, was surgically isolated from dorsal thalamic and cortical afferents. This procedure created an isolated "island" of RE cells whose blood supply was preserved and in which the only remaining afferents were fibers from the brain stem and basal forebrain. Extracellular field potentials from the isolated RE nucleus showed rhythmicity in the same frequency range as in the intact thalamus (308) (Fig. 5A). This observation suggested that the RE nucleus is the pacemaker of spindle activity and that oscillations in TC cells were entrained by rhythmic IPSPs from RE cells.
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TC and 