An increasing number of EEG and resting state fMRI studies in both humans and animals indicate that spontaneous low frequency fluctuations in cerebral activity at <0.1 Hz (infra-slow oscillations, ISOs) represent a fundamental component of brain functioning, being known to correlate with faster neuronal ensemble oscillations, regulate behavioural performance and influence seizure susceptibility. Although these oscillations have been commonly indicated to involve the thalamus their basic cellular mechanisms remain poorly understood. Here we show that various nuclei in the dorsal thalamus in vitro can express a robust ISO at ∼0.005–0.1 Hz that is greatly facilitated by activating metabotropic glutamate receptors (mGluRs) and/or Ach receptors (AchRs). This ISO is a neuronal population phenomenon which modulates faster gap junction (GJ)-dependent network oscillations, and can underlie epileptic activity when AchRs or mGluRs are stimulated excessively. In individual thalamocortical neurons the ISO is primarily shaped by rhythmic, long-lasting hyperpolarizing potentials which reflect the activation of A1 receptors, by ATP-derived adenosine, and subsequent opening of Ba2+-sensitive K+ channels. We argue that this ISO has a likely non-neuronal origin and may contribute to shaping ISOs in the intact brain.
The slow (<1 Hz) rhythm is an EEG hallmark of resting sleep. In thalamocortical (TC) neurons this rhythm correlates with a slow (<1 Hz) oscillation comprising recurring UP and DOWN membrane potential states. Recently, we showed that metabotropic glutamate receptor (mGluR) activation brings about an intrinsic slow oscillation in thalamocortical (TC) neurons of the cat dorsal lateral geniculate nucleus (LGN) in vitro which is identical to that observed in vivo. The aim of this study was to further assess the properties of this oscillation and compare them with those observed in TC neurons of three other thalamic nuclei in the cat (ventrobasal complex, VB; medial geniculate body, MGB; ventral lateral nucleus, VL) and two thalamic nuclei in rats and mice (LGN and VB). Slow oscillations were evident in all of these additional structures and shared several basic properties including, i) the stereotypical, rhythmic alternation between distinct UP and DOWN states with the UP state always commencing with a low-threshold Ca2+ potential (LTCP), and ii) an inverse relationship between frequency and injected current so that slow oscillations always increase in frequency with hyperpolarization, often culminating in delta (δ) activity at ~1-4 Hz. However, beyond these common properties there were important differences in expression between different nuclei. Most notably, 44% of slow oscillations in the cat LGN possessed UP states that comprised sustained tonic firing and/or high-threshold (HT) bursting. In contrast, slow oscillations in cat VB, MGB and VL TC neurons exhibited such UP states in only 16%, 11% and 10% of cases, respectively, whereas slow oscillations in the LGN and VB of rats and mice did so in <12% of cases. Thus, the slow oscillation is a common feature of TC neurons that displays clear species- and nuclei-related differences. The potential functional significance of these results is discussed.
EEG; delta waves; T-type calcium channels; metabotropic glutamate receptor
Thalamo-cortical networks generate specific patterns of oscillations during distinct vigilance states and epilepsy, well characterized by electroencephalography (EEG). Oscillations depend on recurrent synaptic loops, which are controlled by GABAergic transmission. In particular, GABAA receptors containing the α3 subunit are expressed predominantly in cortical layer VI and thalamic reticular nucleus (nRT) and regulate the activity and firing pattern of neurons in relay nuclei. Therefore, ablation of these receptors by gene targeting might profoundly affect thalamo-cortical oscillations. Here, we investigated the role of α3-GABAA receptors in regulating vigilance states and seizure activity by analyzing chronic EEG recordings in α3 subunit knockout (α3-KO) mice. The presence of postsynaptic α3-GABAA receptors/gephyrin clusters in the nRT and GABAA-mediated synaptic currents in acute thalamic slices were also examined.
EEG spectral analysis showed no difference between genotypes during non rapid-eye movement (NREM) sleep or at waking-NREM sleep transitions. EEG power in the spindle frequency range (10–15 Hz) was significantly lower at NREM-REM sleep transitions in mutant compared to wild-type mice. Enhancement of sleep pressure by 6 h sleep deprivation did not reveal any differences in the regulation of EEG activities between genotypes. Finally, the waking EEG showed a slightly larger power in the 11–13-Hz band in α3-KO mice. However, neither behavior nor the waking EEG showed alterations suggestive of absence seizures. Furthermore, α3-KO mice did not differ in seizure susceptibility in a model of temporal lobe epilepsy. Strikingly, despite the disruption of postsynaptic gephyrin clusters, whole-cell patch clamp recordings revealed intact inhibitory synaptic transmission in the nRT of α3-KO mice. These findings show that the lack of α3-GABAA receptors is extensively compensated for to preserve the integrity of thalamo-cortical function in physiological and pathophysiological situations.
Thalamo-cortical network; EEG rhythms; spectral analysis; gephyrin; spike-wave discharges; sleep deprivation
Slow oscillation is the main brain rhythm observed during deep sleep in mammals. Although several studies have demonstrated its neocortical origin, the extent of the thalamic contribution is still a matter of discussion. Using electrophysiological recordings in vivo on cats and computational modeling, we found that the local thalamic inactivation or the complete isolation of the neocortical slabs maintained within the brain dramatically reduced the expression of slow and fast oscillations in affected cortical areas. The slow oscillation began to recover 12 h after thalamic inactivation. The slow oscillation, but not faster activities, nearly recovered after 30 h and persisted for weeks in the isolated slabs. We also observed an increase of the membrane potential fluctuations recorded in vivo several hours after thalamic inactivation. Mimicking this enhancement in a network computational model with an increased postsynaptic activity of long-range intracortical afferents or scaling K+ leak current, but not several other Na+ and K+ intrinsic currents was sufficient for recovering the slow oscillation. We conclude that, in the intact brain, the thalamus contributes to the generation of cortical active states of the slow oscillation and mediates its large-scale synchronization. Our study also suggests that the deafferentation-induced alterations of the sleep slow oscillation can be counteracted by compensatory intracortical mechanisms and that the sleep slow oscillation is a fundamental and intrinsic state of the neocortex.
cortex; in vivo; model; plasticity; slow oscillation; thalamus
Brain cortex activity, as variously recorded by scalp or cortical electrodes in the electroencephalography (EEG) frequency range, probably reflects the basic strategy of brain information processing. Various hypotheses have been advanced to interpret this phenomenon, the most popular of which is that suitable combinations of excitatory and inhibitory neurons behave as assemblies of oscillators susceptible to synchronization and desynchronization. Implicit in this view is the assumption that EEG potentials are epiphenomena of action potentials, which is consistent with the argument that voltage variations in dendritic membranes reproduce the postsynaptic effects of targeting neurons. However, this classic argument does not really fit the discovery that firing synchronization over extended brain areas often appears to be established in about 1 ms, which is a small fraction of any EEG frequency component period. This is in contrast with the fact that all computational models of dynamic systems formed by more or less weakly interacting oscillators of near frequencies take more than one period to reach synchronization. The discovery that the somatodendritic membranes of specialized populations of neurons exhibit intrinsic subthreshold oscillations (ISOs) in the EEG frequency range, together with experimental evidence that short inhibitory stimuli are capable of resetting ISO phases, radically changes the scheme described above and paves the way to a novel view. This paper aims to elucidate the nature of ISO generation mechanisms, to explain the reasons for their reliability in starting and stopping synchronized firing, and to indicate their potential in brain information processing. The need for a repertoire of extraneuronal regulation mechanisms, putatively mediated by astrocytes, is also inferred. Lastly, the importance of ISOs for the brain as a parallel recursive machine is briefly discussed.
Subthreshold oscillations; Subthreshold oscillation control; Neuron-firing synchronization; EEG; Brainweb; Phasic and tonic inhibitions
Intrathalamic oscillations related to sleep and epilepsy depend on interactions between synaptic mechanisms and intrinsic membrane excitability. One intrinsic conductance implicated in the genesis of thalamic oscillations is the H current – a cationic current activated by membrane hyperpolarization. Activation of H current promotes rebound excitation of thalamic relay neurons and can thus enhance recurrent network activity.
We examined the effects of H current modulation on bicuculline-enhanced network oscillations (2-4 Hz) in rat thalamic slices. The adrenergic agonist norepinephrine, a known regulator of H current, caused an alteration of the internal structure of the oscillations – they were enhanced and accelerated as the interval between bursts was shortened. The acceleration was blocked by the β-adrenergic antagonist propranolol. The β agonist isoproterenol mimicked the effect of norepinephrine on oscillation frequency and truncated the responses suggesting that a β-adrenergic upregulation of H current modifies the internal structure (frequency) of thalamic oscillations. Consistent with this, we found that H channel blockade by Cs+ or ZD7288 could decelerate the oscillations and produce more robust (longer lasting) responses. High concentrations of either Cs+ or ZD7288 blocked the oscillations.
These results indicate that a critical amount of H current is necessary for optimal intrathalamic oscillations in the delta frequency range. Up- or downregulation of H current can not only alter the oscillation frequency but also retard or promote the development of thalamic synchronous oscillations. This conclusion has important implications regarding the development of epilepsy in thalamocortical circuits.
H current; ZD7288; adrenergic; pacemaking
Slow waves represent one of the prominent EEG signatures of non-rapid eye movement (non-REM) sleep and are thought to play an important role in the cellular and network plasticity that occurs during this behavioral state. These slow waves of natural sleep are currently considered to be exclusively generated by intrinsic and synaptic mechanisms within neocortical territories, although a role for the thalamus in this key physiological rhythm has been suggested but never demonstrated. Combining neuronal ensemble recordings, microdialysis, and optogenetics, here we show that the block of the thalamic output to the neocortex markedly (up to 50%) decreases the frequency of slow waves recorded during non-REM sleep in freely moving, naturally sleeping-waking rats. A smaller volume of thalamic inactivation than during sleep is required for observing similar effects on EEG slow waves recorded during anesthesia, a condition in which both bursts and single action potentials of thalamocortical neurons are almost exclusively dependent on T-type calcium channels. Thalamic inactivation more strongly reduces spindles than slow waves during both anesthesia and natural sleep. Moreover, selective excitation of thalamocortical neurons strongly entrains EEG slow waves in a narrow frequency band (0.75–1.5 Hz) only when thalamic T-type calcium channels are functionally active. These results demonstrate that the thalamus finely tunes the frequency of slow waves during non-REM sleep and anesthesia, and thus provide the first conclusive evidence that a dynamic interplay of the neocortical and thalamic oscillators of slow waves is required for the full expression of this key physiological EEG rhythm.
Deep Brain Stimulation (DBS) of thalamus has been demonstrated to be an effective for treatment of epilepsy. To investigate mechanism of action of thalamic DBS, we examined the effects of high frequency stimulation (HFS) on spindle oscillations in thalamic brain slices from ferrets. We recorded intracellular and extracellular electrophysiological activity in the nucleus Reticularis thalami (nRt) and in thalamocortical relay (TC) neurons in the lateral geniculate nucleus, stimulated the slice using a concentric bipolar electrode, and recorded the level of glutamate within the slice. HFS (100 Hz) of TC neurons generated excitatory post-synaptic potentials (EPSPs), increased the number of action potentials in both TC and nRt neurons, reduced the input resistance, increased the extracellular glutamate concentration, and abolished spindle wave oscillations. High frequency stimulation of the nRt also suppressed spindle oscillations. In both locations, HFS was associated with significant and persistent elevation in extracellular glutamate levels and suppressed spindle oscillations for many seconds after the cessation of stimulation. We simulated HFS within a computational model of the thalamic network, and HFS also disrupted spindle wave activity, but the suppression of spindle activity was short-lived. Simulated HFS disrupted spindle activity for prolonged periods of time only after glutamate release and glutamate-mediated activation of a hyperpolarization-activated current (Ih) were incorporated into the model. Our results suggest that the mechanism of action of thalamic DBS as used in epilepsy may involve the prolonged release of glutamate, which in turn modulates specific ion channels such as Ih, decreases neuronal input resistance, and abolishes thalamic network oscillatory activity.
high frequency stimulation (HFS); deep brain stimulation (DBS); spindle oscillations
Circadian rhythms modulate behavioral processes over a 24 h period through clock gene expression. What is largely unknown is how these molecular influences shape neural activity in different brain areas. The clock gene Per2 is rhythmically expressed in the striatum and the cerebellum and its expression is linked with daily fluctuations in extracellular dopamine levels and D2 receptor activity. Electrophysiologically, dopamine depletion enhances striatal local field potential (LFP) oscillations. We investigated if LFP oscillations and synchrony were influenced by time of day, potentially via dopamine mechanisms. To assess the presence of a diurnal effect, oscillatory power and coherence were examined in the striatum and cerebellum of rats under urethane anesthesia at four different times of day zeitgeber time (ZT1, 7, 13 and 19—indicating number of hours after lights turned on in a 12:12 h light-dark cycle). We also investigated the diurnal response to systemic raclopride, a D2 receptor antagonist. Time of day affected the proportion of LFP oscillations within the 0–3 Hz band and the 3–8 Hz band. In both the striatum and the cerebellum, slow oscillations were strongest at ZT1 and weakest at ZT13. A 3–8 Hz oscillation was present when the slow oscillation was lowest, with peak 3–8 Hz activity occurring at ZT13. Raclopride enhanced the slow oscillations, and had the greatest effect at ZT13. Within the striatum and with the cerebellum, 0–3 Hz coherence was greatest at ZT1, when the slow oscillations were strongest. Coherence was also affected the most by raclopride at ZT13. Our results suggest that neural oscillations in the cerebellum and striatum, and the synchrony between these areas, are modulated by time of day, and that these changes are influenced by dopamine manipulation. This may provide insight into how circadian gene transcription patterns influence network electrophysiology. Future experiments will address how these network alterations are linked with behavior.
local field potential oscillation; coherence; dopamine; circadian; urethane
Brain electrical activity is largely composed of oscillations at characteristic frequencies. These rhythms are hierarchically organized and are thought to perform important pathological and physiological functions. The slow wave is a fundamental cortical rhythm that emerges in deep non-rapid eye movement sleep. In animals, the slow wave modulates delta, theta, spindle, alpha, beta, gamma and ripple oscillations, thus orchestrating brain electrical rhythms in sleep. While slow wave activity can enhance epileptic manifestations, it is also thought to underlie essential restorative processes and facilitate the consolidation of declarative memories. Animal studies show that slow wave activity is composed of rhythmically recurring phases of widespread, increased cortical cellular and synaptic activity, referred to as active- or up-state, followed by cellular and synaptic inactivation, referred to as silent- or down-state. However, its neural mechanisms in humans are poorly understood, since the traditional intracellular techniques used in animals are inappropriate for investigating the cellular and synaptic/transmembrane events in humans. To elucidate the intracortical neuronal mechanisms of slow wave activity in humans, novel, laminar multichannel microelectrodes were chronically implanted into the cortex of patients with drug-resistant focal epilepsy undergoing cortical mapping for seizure focus localization. Intracortical laminar local field potential gradient, multiple-unit and single-unit activities were recorded during slow wave sleep, related to simultaneous electrocorticography, and analysed with current source density and spectral methods. We found that slow wave activity in humans reflects a rhythmic oscillation between widespread cortical activation and silence. Cortical activation was demonstrated as increased wideband (0.3–200 Hz) spectral power including virtually all bands of cortical oscillations, increased multiple- and single-unit activity and powerful inward transmembrane currents, mainly localized to the supragranular layers. Neuronal firing in the up-state was sparse and the average discharge rate of single cells was less than expected from animal studies. Action potentials at up-state onset were synchronized within ±10 ms across all cortical layers, suggesting that any layer could initiate firing at up-state onset. These findings provide strong direct experimental evidence that slow wave activity in humans is characterized by hyperpolarizing currents associated with suppressed cell firing, alternating with high levels of oscillatory synaptic/transmembrane activity associated with increased cell firing. Our results emphasize the major involvement of supragranular layers in the genesis of slow wave activity.
current source density; unit activity; laminar recording; slow wave activity; sleep
Recordings of ongoing neural activity with EEG and MEG exhibit oscillations of specific frequencies over a non-oscillatory background. The oscillations appear in the power spectrum as a collection of frequency bands that are evenly spaced on a logarithmic scale, thereby preventing mutual entrainment and cross-talk. Over the last few years, experimental, computational and theoretical studies have made substantial progress on our understanding of the biophysical mechanisms underlying the generation of network oscillations and their interactions, with emphasis on the role of neuronal synchronization. In this paper we ask a very different question. Rather than investigating how brain rhythms emerge, or whether they are necessary for neural function, we focus on what they tell us about functional brain connectivity. We hypothesized that if we were able to construct abstract networks, or “virtual brains”, whose dynamics were similar to EEG/MEG recordings, those networks would share structural features among themselves, and also with real brains. Applying mathematical techniques for inverse problems, we have reverse-engineered network architectures that generate characteristic dynamics of actual brains, including spindles and sharp waves, which appear in the power spectrum as frequency bands superimposed on a non-oscillatory background dominated by low frequencies. We show that all reconstructed networks display similar topological features (e.g. structural motifs) and dynamics. We have also reverse-engineered putative diseased brains (epileptic and schizophrenic), in which the oscillatory activity is altered in different ways, as reported in clinical studies. These reconstructed networks show consistent alterations of functional connectivity and dynamics. In particular, we show that the complexity of the network, quantified as proposed by Tononi, Sporns and Edelman, is a good indicator of brain fitness, since virtual brains modeling diseased states display lower complexity than virtual brains modeling normal neural function. We finally discuss the implications of our results for the neurobiology of health and disease.
The fact that the brain generates weak but measurable electromagnetic waves has intrigued neuroscientists for over a century. Even more remarkable is the fact that these oscillations of brain activity correlate with the state of awareness and that their frequency and amplitude display reproducible features that are different in health and disease. In healthy conditions, oscillations of different frequency bands tend to minimize interference. This is similar to radio stations avoiding overlap between frequency bands to ensure clear transmission. During epileptic seizures, mutual entrainment, analogous to interference of radio signals, has also been reported. Moreover, in schizophrenia and autism, there is a loss of higher frequency oscillations. Most studies thus far have focused on the mechanisms generating the oscillations, as well as on their functional relevance. In contrast, our study focuses on what brain rhythms tell us about the functional network organization of the brain. Using a reverse-engineering approach, we construct abstract networks (virtual brains) that display oscillations of actual brains. These networks reveal that brain rhythms reflect different levels of hierarchical organization in health and disease. We predict specific alterations in brain connectivity in the aforementioned diseases and explain how clinicians and experimentalists can test our predictions.
The suprachiasmatic nuclei (SCN) host a robust, self-sustained circadian pacemaker that coordinates physiological rhythms with the daily changes in the environment. Neuronal clocks within the SCN form a heterogeneous network that must synchronize to maintain timekeeping activity. Coherent circadian output of the SCN tissue is established by intercellular signaling factors, such as vasointestinal polypeptide. It was recently shown that besides coordinating cells, the synchronization factors play a crucial role in the sustenance of intrinsic cellular rhythmicity. Disruption of intercellular signaling abolishes sustained rhythmicity in a majority of neurons and desynchronizes the remaining rhythmic neurons. Based on these observations, the authors propose a model for the synchronization of circadian oscillators that combines intracellular and intercellular dynamics at the single-cell level. The model is a heterogeneous network of circadian neuronal oscillators where individual oscillators are damped rather than self-sustained. The authors simulated different experimental conditions and found that: (1) in normal, constant conditions, coupled circadian oscillators quickly synchronize and produce a coherent output; (2) in large populations, such oscillators either synchronize or gradually lose rhythmicity, but do not run out of phase, demonstrating that rhythmicity and synchrony are codependent; (3) the number of oscillators and connectivity are important for these synchronization properties; (4) slow oscillators have a higher impact on the period in mixed populations; and (5) coupled circadian oscillators can be efficiently entrained by light–dark cycles. Based on these results, it is predicted that: (1) a majority of SCN neurons needs periodic synchronization signal to be rhythmic; (2) a small number of neurons or a low connectivity results in desynchrony; and (3) amplitudes and phases of neurons are negatively correlated. The authors conclude that to understand the orchestration of timekeeping in the SCN, intracellular circadian clocks cannot be isolated from their intercellular communication components.
Circadian rhythms, characterized by a period close to 24 h, are observed in nearly all living organisms, from cyanobacteria to plants, insects, and mammals. In mammals, the central circadian clock is located in the suprachiasmatic nucleus (SCN) of the hypothalamus, where it receives light signals from the retina. In turn, the SCN controls circadian rhythms in peripheral tissues and behavioral activity. The SCN is composed of about 20,000 neurons characterized by a small size and a high density. Within each individual neuron, clock genes and proteins compose interlocked regulatory feedback loops that generate circadian oscillations on the molecular level. SCN neurons dispersed in cell cultures display cell-autonomous oscillations, with periods ranging from 20 h to 28 h. The ventrolateral part of the SCN receives light input from the retina, serving as a relay for the dorsomedial part. Coupling and synchronization among SCN neurons are ensured by neurotransmitters. A desire to understand how such a network of heterogeneous circadian oscillators achieves a synchronous and coherent output rhythm has motivated extensive experimental and theoretical work. In this paper, we present a molecular model combining intracellular and extracellular dynamics for the SCN circadian system, and propose a novel synchronization mechanism. Our results predict a dual role for the coupling factors within the SCN, both in maintaining the rhythmicity and in promoting the synchronization between the circadian oscillators.
Field potential oscillations in the ~10 Hz range are known as the alpha rhythm. The genesis and function of alpha has been the subject of intense investigation for the past 80 years. Whereas early work focused on the thalamus as the pacemaker of alpha rhythm, subsequent slice studies revealed that pyramidal neurons in the deep layers of sensory cortices are capable of oscillating in the alpha frequency range independently. How thalamic and cortical generating mechanisms in the intact brain might interact to shape the organization and function of alpha oscillations remains unclear. We addressed this problem by analyzing laminar profiles of local field potential (LFP) and multi-unit activity (MUA) recorded with linear array multielectrodes from the striate cortex of two macaque monkeys performing an intermodal selective attention task. Current source density (CSD) analysis was combined with CSD-MUA coherence to identify intracortical alpha current generators and assess their potential for pacemaking. Coherence and Granger causality analysis was applied to delineate the patterns of interaction among different alpha current generators. We found that: (1) separable alpha current generators are located in superficial, granular and deep layers, with both layer 4C and deep layers containing primary local pacemaking generators, suggesting the involvement of the thalamocortical network, and (2) visual attention reduces the magnitude of alpha oscillations as well as the level of alpha interactions, consistent with numerous reports of occipital alpha reduction with visual attention in human EEG. There is also indication that alpha oscillations in the lateral geniculate cohere with those in V1.
alpha rhythm; macaques; striate cortex; attention; lateral geniculate nucleus; laminar organization; current source density; Granger causality
Absence epilepsy is believed to be associated with the abnormal interactions between the cerebral cortex and thalamus. Besides the direct coupling, anatomical evidence indicates that the cerebral cortex and thalamus also communicate indirectly through an important intermediate bridge–basal ganglia. It has been thus postulated that the basal ganglia might play key roles in the modulation of absence seizures, but the relevant biophysical mechanisms are still not completely established. Using a biophysically based model, we demonstrate here that the typical absence seizure activities can be controlled and modulated by the direct GABAergic projections from the substantia nigra pars reticulata (SNr) to either the thalamic reticular nucleus (TRN) or the specific relay nuclei (SRN) of thalamus, through different biophysical mechanisms. Under certain conditions, these two types of seizure control are observed to coexist in the same network. More importantly, due to the competition between the inhibitory SNr-TRN and SNr-SRN pathways, we find that both decreasing and increasing the activation of SNr neurons from the normal level may considerably suppress the generation of spike-and-slow wave discharges in the coexistence region. Overall, these results highlight the bidirectional functional roles of basal ganglia in controlling and modulating absence seizures, and might provide novel insights into the therapeutic treatments of this brain disorder.
Epilepsy is a general term for conditions with recurring seizures. Absence seizures are one of several kinds of seizures, which are characterized by typical 2–4 Hz spike-and-slow wave discharges (SWDs). There is accumulating evidence that absence seizures are due to abnormal interactions between cerebral cortex and thalamus, and the basal ganglia may take part in controlling such brain disease via the indirect basal ganglia-thalamic pathway relaying at superior colliculus. Actually, the basal ganglia not only send indirect signals to thalamus, but also communicate with several key nuclei of thalamus through multiple direct GABAergic projections. Nevertheless, whether and how these direct pathways regulate absence seizure activities are still remain unknown. By computational modelling, we predicted that two direct inhibitory basal ganglia-thalamic pathways emitting from the substantia nigra pars reticulata may also participate in the control of absence seizures. Furthermore, we showed that these two types of seizure control can coexist in the same network, and depending on the instant network state, both lowing and increasing the activation of SNr neurons may inhibit the SWDs due to the existence of competition. Our findings emphasize the bidirectional modulation effects of basal ganglia on absence seizures, and might have physiological implications on the treatment of absence epilepsy.
The thalamus is the primary gateway that relays sensory information to the cerebral cortex. While a single recipient cortical cell receives the convergence of many principal relay cells of the thalamus, each thalamic cell in turn integrates a dense and distributed synaptic feedback from the cortex. During sensory processing, the influence of this functional loop remains largely ignored. Using dynamic-clamp techniques in thalamic slices in vitro, we combined theoretical and experimental approaches to implement a realistic hybrid retino-thalamo-cortical pathway mixing biological cells and simulated circuits. The synaptic bombardment of cortical origin was mimicked through the injection of a stochastic mixture of excitatory and inhibitory conductances, resulting in a gradable correlation level of afferent activity shared by thalamic cells. The study of the impact of the simulated cortical input on the global retinocortical signal transfer efficiency revealed a novel control mechanism resulting from the collective resonance of all thalamic relay neurons. We show here that the transfer efficiency of sensory input transmission depends on three key features: i) the number of thalamocortical cells involved in the many-to-one convergence from thalamus to cortex, ii) the statistics of the corticothalamic synaptic bombardment and iii) the level of correlation imposed between converging thalamic relay cells. In particular, our results demonstrate counterintuitively that the retinocortical signal transfer efficiency increases when the level of correlation across thalamic cells decreases. This suggests that the transfer efficiency of relay cells could be selectively amplified when they become simultaneously desynchronized by the cortical feedback. When applied to the intact brain, this network regulation mechanism could direct an attentional focus to specific thalamic subassemblies and select the appropriate input lines to the cortex according to the descending influence of cortically-defined “priors”.
Most of the sensory information in the early visual system is relayed from the retina to the primary visual cortex through principal relay cells in the thalamus. While relay cells receive ∼7–16% of their synapses from retina, they integrate the synaptic barrage of a dense cortical feedback, which accounts for more than 60% of their total input. This feedback is thought to carry some form of “prior” resulting from the computation performed in cortical areas, which influences the response of relay cells, presumably by regulating the transfer of sensory information to cortical areas. Nevertheless, its statistical nature (input synchronization, excitation/inhibition ratio, etc.) and the cellular mechanisms gating thalamic transfer are largely ignored. Here we implemented hybrid circuits (biological and modeled cells) reproducing the main features of the thalamic gate and explored the functional impact of various statistics of the cortical input. We found that the regulation of sensory information is critically determined by the statistical coherence of the cortical synaptic bombardment associated with a stochastic facilitation process. We propose that this tuning mechanism could operate in the intact brain to selectively filter the sensory information reaching cortical areas according to attended features predesignated by the cortical feedback.
Electrical oscillations in neuronal network activity are ubiquitous in the brain and have been associated with cognition and behavior. Intriguingly, the amplitude of ongoing oscillations, such as measured in EEG recordings, fluctuates irregularly, with episodes of high amplitude alternating with episodes of low amplitude. Despite the widespread occurrence of amplitude fluctuations in many frequency bands and brain regions, the mechanisms by which they are generated are poorly understood. Here, we show that irregular transitions between sub-second episodes of high- and low-amplitude oscillations in the alpha/beta frequency band occur in a generic neuronal network model consisting of interconnected inhibitory and excitatory cells that are externally driven by sustained cholinergic input and trains of action potentials that activate excitatory synapses. In the model, we identify the action potential drive onto inhibitory cells, which represents input from other brain areas and is shown to desynchronize network activity, to be crucial for the emergence of amplitude fluctuations. We show that the duration distributions of high-amplitude episodes in the model match those observed in rat prefrontal cortex for oscillations induced by the cholinergic agonist carbachol. Furthermore, the mean duration of high-amplitude episodes varies in a bell-shaped manner with carbachol concentration, just as in mouse hippocampus. Our results suggest that amplitude fluctuations are a general property of oscillatory neuronal networks that can arise through background input from areas external to the network.
Rhythmic changes in electrical activity are observed throughout the brain, and arise as a result of reciprocal interactions between excitatory and inhibitory neurons. Synchronized activity of a large number of neurons gives rise to macroscopic oscillations in electrical activity, which can be measured in EEG recordings and are thought to have a key role in learning and memory. Interestingly, the amplitude of ongoing oscillations fluctuates irregularly, with high-amplitude episodes alternating with low-amplitude episodes. Although these amplitude fluctuations occur in many brain regions, the mechanisms by which they are generated are still poorly known. To get insight into potential mechanisms, we investigated whether such fluctuations occur in a computational model of a neuronal network. We show that the model generates amplitude fluctuations that are similar to those observed in experimental data and that external input from other brain areas to the inhibitory cells of the network is essential for their generation. This input can disrupt the synchrony of activity, causing transitions between episodes of high synchrony (high oscillation amplitudes) and episodes of low synchrony (low oscillation amplitudes). Episodes of high synchrony are relevant for brain function because they provide favorable conditions for learning.
The state of non-REM sleep (NREM), or slow wave sleep, is associated with a synchronized EEG pattern in which sleep spindles and/or K complexes and high-voltage slow wave activity (SWA) can be recorded over the entire cortical surface. In humans, NREM is subdivided into stages 2 and 3–4 (presently named N3) depending on the proportions of each of these polygraphic events. NREM is necessary for normal physical and intellectual performance and behavior. An overview of the brain structures involved in NREM generation shows that the thalamus and the cerebral cortex are absolutely necessary for the most significant bioelectric and behavioral events of NREM to be expressed; other structures like the basal forebrain, anterior hypothalamus, cerebellum, caudal brain stem, spinal cord and peripheral nerves contribute to NREM regulation and modulation. In NREM stage 2, sustained hyperpolarized membrane potential levels resulting from interaction between thalamic reticular and projection neurons gives rise to spindle oscillations in the membrane potential; the initiation and termination of individual spindle sequences depends on corticothalamic activities. Cortical and thalamic mechanisms are also involved in the generation of EEG delta SWA that appears in deep stage 3–4 (N3) NREM; the cortex has classically been considered to be the structure that generates this activity, but delta oscillations can also be generated in thalamocortical neurons. NREM is probably necessary to normalize synapses to a sustainable basal condition that can ensure cellular homeostasis. Sleep homeostasis depends not only on the duration of prior wakefulness but also on its intensity, and sleep need increases when wakefulness is associated with learning. NREM seems to ensure cell homeostasis by reducing the number of synaptic connections to a basic level; based on simple energy demands, cerebral energy economizing during NREM sleep is one of the prevalent hypotheses to explain NREM homeostasis.
slow wave sleep; sleep need; thalamus–cerebral cortex unit; rostral hypnogenic system; caudal hypnogenic system; NREM sleep homeostasis
Basal ganglia dysfunction has being implied in both Parkinson's disease and dystonia. While these disorders probably involve different cellular and circuit pathologies within and beyond basal ganglia, there may be some shared neurophysiological pathways. For example, pallidotomy and pallidal Deep Brain Stimulation (DBS) are used in symptomatic treatment of both disorders. Both conditions are marked by alterations of rhythmicity of neural activity throughout basal ganglia-thalamocortical circuits. Increased synchronized oscillatory activity in beta band is characteristic of Parkinson's disease, while different frequency bands, theta and alpha, are involved in dystonia. We compare the effect of the activity of GPi, the output nuclei of the basal ganglia, on information processing in the downstream neural circuits of thalamus in Parkinson's disease and dystonia. We use a data-driven computational approach, a computational model of the thalamocortical (TC) cell modulated by experimentally recorded data, to study the differences and similarities of thalamic dynamics in dystonia and Parkinson's disease. Our analysis shows no substantial differences in TC relay between the two conditions. Our results suggest that, similar to Parkinson's disease, a disruption of thalamic processing could also be involved in dystonia. Moreover, the degree to which TC relay fidelity is impaired is approximately the same in both conditions. While Parkinson's disease and dystonia may have different pathologies and differ in the oscillatory content of neural discharge, our results suggest that the effect of patterning of pallidal discharge is similar in both conditions. Furthermore, these results suggest that the mechanisms of GPi DBS in dystonia may involve improvement of TC relay fidelity.
thalamocortical relay; Parkinson's disease; dystonia; basal ganglia; globus pallidus
Rhythms in the α frequency band (8-13 Hz) are a defining feature of the human EEG during relaxed wakefulness and are known to be influenced by the thalamus. In the early stages of sleep and in several neurological and psychiatric conditions α rhythms are replaced by slower activity in the θ (3-7 Hz) band. Of particular interest is how these α and θ rhythms are generated at the cellular level. Recently we identified a subset of thalamocortical (TC) neurons in the lateral geniculate nucleus (LGN) which exhibit rhythmic high-threshold (>-55 mV) bursting at ~2-13 Hz and which are interconnected by gap junctions (GJs). These cells combine to generate a locally synchronized continuum of α and θ oscillations, thus providing direct evidence that the thalamus can act as an independent pacemaker of α and θ rhythms. Interestingly, GJ coupled pairs of TC neurons can exhibit both in-phase and anti-phase synchrony and will often spontaneously alternate between these two states. This dictates that the local field oscillation amplitude is not simply linked to the extent of cell recruitment into a single synchronized neuronal assembly but also to the degree of destructive interference between dynamic, spatially overlapping, competing anti-phase groups of continuously bursting neurons. Thus, the waxing and waning of thalamic α/θ rhythms should not be assumed to reflect a wholesale increase and reduction, respectively, in underlying neuronal synchrony. We argue that these network dynamics might have important consequences for relating changes in the amplitude of EEG α and θ rhythms to the activity of thalamic networks.
EEG; mu rhythm; dendrites; metabotropic glutamate receptor; gap junctions
Gamma oscillations (40–120 Hz), usually associated with waking functions, can be recorded in the deepest stages of sleep in animals. The full details of their large-scale coordination across multiple cortical networks are still unknown. Furthermore, it is not known whether oscillations with similar characteristics are also present in the human brain. In this study, we examined the existence of gamma oscillations during polysomnographically defined sleep–wake states using large-scale microelectrode recordings (up to 56 channels), with single-cell and spike-time precision, in epilepsy patients. We report that low (40–80 Hz) and high (80–120 Hz) gamma oscillations recurrently emerged over time windows of several hundreds of milliseconds in all investigated cortical areas during slow-wave sleep. These patterns were correlated with positive peaks of EEG slow oscillations and marked increases in local cellular discharges, suggesting that they were associated with cortical UP states. These gamma oscillations frequently appeared at approximately the same time in many different cortical areas, including homotopic regions, forming large spatial patterns. Coincident firings with millisecond precision were strongly enhanced during gamma oscillations but only between cells within the same cortical area. Furthermore, in a significant number of cases, cortical gamma oscillations tended to occur within 100 ms after hippocampal ripple/sharp wave complexes. These data confirm and extend earlier animal studies reporting that gamma oscillations are transiently expressed during UP states during sleep. We speculate that these high-frequency patterns briefly restore “microwake” activity and are important for consolidation of memory traces acquired during previous awake periods.
While sensory neurons carry behaviorally relevant information in responses that often extend over hundreds of milliseconds, the key units of neural information likely consist of much shorter and temporally precise spike patterns. The mechanisms and temporal reference frames by which sensory networks partition responses into these shorter units of information remain unknown. One hypothesis holds that slow oscillations provide a network-intrinsic reference to temporally partitioned spike trains without exploiting the millisecond-precise alignment of spikes to sensory stimuli. We tested this hypothesis on neural responses recorded in visual and auditory cortices of macaque monkeys in response to natural stimuli. Comparing different schemes for response partitioning revealed that theta band oscillations provide a temporal reference that permits extracting significantly more information than can be obtained from spike counts, and sometimes almost as much information as obtained by partitioning spike trains using precisely stimulus-locked time bins. We further tested the robustness of these partitioning schemes to temporal uncertainty in the decoding process and to noise in the sensory input. This revealed that partitioning using an oscillatory reference provides greater robustness than partitioning using precisely stimulus-locked time bins. Overall, these results provide a computational proof of concept for the hypothesis that slow rhythmic network activity may serve as internal reference frame for information coding in sensory cortices and they foster the notion that slow oscillations serve as key elements for the computations underlying perception.
Neurons in sensory cortices encode objects in our sensory environment by varying the timing and number of action potentials that they emit. Brain networks that ‘decode’ this information need to partition those spike trains into their individual informative units. Experimenters achieve such partitioning by exploiting their knowledge about the millisecond precise timing of individual spikes relative to externally presented sensory stimuli. The brain, however, does not have access to this information and has to partition and decode spike trains using intrinsically available temporal reference frames. We show that slow (4–8 Hz) oscillatory network activity can provide such an intrinsic temporal reference. Specifically, we analyzed neural responses recorded in primary auditory and visual cortices. This revealed that the oscillatory reference frame performs nearly as well as the precise stimulus-locked reference frame and renders neural encoding robust to sensory noise and temporal uncertainty that naturally occurs during decoding. These findings provide a computational proof-of-concept that slow oscillatory network activity may serve the crucial function as temporal reference frame for sensory coding.
It is widely accepted that corticothalamic neurons recruit the thalamus in slow oscillation, but global slow-wave thalamocortical dynamics have never been experimentally shown. We analyzed intracellular activities of neurons either from different cortical areas or from a variety of specific and nonspecific thalamic nuclei in relation to the phase of global EEG signal in ketamine-xylazine anesthetized mice. We found that, on average, slow-wave active states started off within frontal cortical areas as well as higher-order and intralaminar thalamus (posterior and parafascicular nuclei) simultaneously. Then, the leading edge of active states propagated in the anteroposterior/lateral direction over the cortex at ∼40 mm/s. The latest structure we recorded within the slow-wave cycle was the anterior thalamus, which followed active states of the retrosplenial cortex. Active states from different cortical areas tended to terminate simultaneously. Sensory thalamic ventral posterior medial and lateral geniculate nuclei followed cortical active states with major inhibitory and weak tonic-like “modulator” EPSPs. In these nuclei, sharp-rising, large-amplitude EPSPs (“drivers”) were not modulated by cortical slow waves, suggesting their origin in ascending pathways. The thalamic active states in other investigated nuclei were composed of depolarization: some revealing “driver”- and “modulator”-like EPSPs, others showing “modulator”-like EPSPs only. We conclude that sensory thalamic nuclei follow the propagating cortical waves, whereas neurons from higher-order thalamic nuclei display “hub dynamics” and thus may contribute to the generation of cortical slow waves.
cortex; dynamics; intracellular; slow oscillation; thalamus
A simultaneous EEG-fMRI study demonstrates that alpha-band activity in early visual cortex is associated with gating visual information to downstream regions, boosting attended information and suppressing distraction.
Given the limited processing capabilities of the sensory system, it is essential that attended information is gated to downstream areas, whereas unattended information is blocked. While it has been proposed that alpha band (8–13 Hz) activity serves to route information to downstream regions by inhibiting neuronal processing in task-irrelevant regions, this hypothesis remains untested. Here we investigate how neuronal oscillations detected by electroencephalography in visual areas during working memory encoding serve to gate information reflected in the simultaneously recorded blood-oxygenation-level-dependent (BOLD) signals recorded by functional magnetic resonance imaging in downstream ventral regions. We used a paradigm in which 16 participants were presented with faces and landscapes in the right and left hemifields; one hemifield was attended and the other unattended. We observed that decreased alpha power contralateral to the attended object predicted the BOLD signal representing the attended object in ventral object-selective regions. Furthermore, increased alpha power ipsilateral to the attended object predicted a decrease in the BOLD signal representing the unattended object. We also found that the BOLD signal in the dorsal attention network inversely correlated with visual alpha power. This is the first demonstration, to our knowledge, that oscillations in the alpha band are implicated in the gating of information from the visual cortex to the ventral stream, as reflected in the representationally specific BOLD signal. This link of sensory alpha to downstream activity provides a neurophysiological substrate for the mechanism of selective attention during stimulus processing, which not only boosts the attended information but also suppresses distraction. Although previous studies have shown a relation between the BOLD signal from the dorsal attention network and the alpha band at rest, we demonstrate such a relation during a visuospatial task, indicating that the dorsal attention network exercises top-down control of visual alpha activity.
In complex environments, our sensory systems are bombarded with information. Only a fraction of this information is processed, whereas most is ignored. As such, our brain must rely on powerful mechanisms to filter the relevant information. It has been proposed that alpha band oscillations (8–13 Hz) gate task-relevant visual information to downstream areas and supress irrelevant visual information. We tested this hypothesis in a study that combined electroencephalography (EEG) and functional MRI (fMRI) recordings. From the EEG, we directly measured alpha band oscillations in early visual regions. Using fMRI, we quantified neuronal activity in downstream regions. The participants performed a spatial working memory task that required them to encode pictures of objects presented in the left field of view while ignoring objects in the right field (or vice versa). We found that suppression of alpha band activity in visual areas opened the gate for relevant visual information to be routed to downstream regions. Conversely, an increase in alpha oscillations suppressed visual information that was irrelevant to the task. These findings suggest that alpha band oscillations are directly involved in boosting attended information and suppressing distraction in the ventral visual stream.
High-frequency electrical stimulation of specific brain structures, known as deep brain stimulation (DBS), is an effective treatment for movement disorders, but mechanisms of action remain unclear. We examined the time-dependent effects of DBS applied to the entopeduncular nucleus (EP), the rat homolog of the internal globus pallidus, a target used for treatment of both dystonia and Parkinson’s disease (PD). We performed simultaneous multi-site local field potential (LFP) recordings in urethane-anesthetized rats to assess the effects of high-frequency (HF, 130 Hz; clinically effective), low-frequency (LF, 15 Hz; ineffective) and sham DBS delivered to EP. LFP activity was recorded from dorsal striatum (STR), ventroanterior thalamus (VA), primary motor cortex (M1), and the stimulation site in EP. Spontaneous and acute stimulation-induced LFP oscillation power and functional connectivity were assessed at baseline, and after 30, 60, and 90 minutes of stimulation. HF EP DBS produced widespread alterations in spontaneous and stimulus-induced LFP oscillations, with some effects similar across regions and others occurring in a region- and frequency band-specific manner. Many of these changes evolved over time. HF EP DBS produced an initial transient reduction in power in the low beta band in M1 and STR; however, phase synchronization between these regions in the low beta band was markedly suppressed at all time points. DBS also enhanced low gamma synchronization throughout the circuit. With sustained stimulation, there were significant reductions in low beta synchronization between M1-VA and STR-VA, and increases in power within regions in the faster frequency bands. HF DBS also suppressed the ability of acute EP stimulation to induce beta oscillations in all regions along the circuit. This dynamic pattern of synchronizing and desynchronizing effects of EP DBS suggests a complex modulation of activity along cortico-BG-thalamic circuits underlying the therapeutic effects of GPi DBS for conditions such as PD and dystonia.
Neuropeptide Y is the ligand of a family of G-protein coupled receptors (Y1 to Y6). In the thalamus, exogenous and endogenously released NPY can shorten the duration of thalamic oscillations in brain slices from P13 to P15 rats, an in vitro model of absence seizures. Here, we examine which Y receptors are involved in this modulation. Application of the Y1 receptor agonist Leu31Pro34NPY caused a reversible reduction in the duration of thalamic oscillations (−26.6 +/− 7.8%), while the Y2 receptor agonist peptideYY(3–36) and the Y5 receptor agonist BWX-46 did not exert a significant effect. No Y receptor agonist affected oscillation period. Application of antagonists of Y1, Y2 and Y5 receptors (BIBP3226, BIIE0246 and L152,806, respectively) produced results consistent with those obtained from agonists. BIBP3226 caused a reversible disinhibition, an effect that increases oscillation duration (18.2 +/− 9.7%) while BIIE0246 and L152,806 had no significant effect. Expression of NPY is limited to neurons in the reticular thalamic nucleus (nRt), but Y1 receptors are expressed in both nRt and adjacent thalamic relay nuclei. Thus, intra-nRt or nRt to relay nucleus NPY release could cause Y1 receptor mediated inhibition of thalamic oscillations.
Neuropeptide Y; absence seizures; spike-wave discharges; nRt; thalamus; thalamic oscillations