Content uploaded by Sean L. Hill
Author content
All content in this area was uploaded by Sean L. Hill on Feb 08, 2015
Content may be subject to copyright.
A preview of the PDF is not available
Breakdown of Effective Connectivity During Slow Wave Sleep: Investigating the Mechanism Underlying a Cortical Gate Using Large-Scale Modeling
Abstract and Figures
Effective connectivity between cortical areas decreases during slow wave sleep. This decline can be observed in the reduced interareal propagation of activity evoked either directly in cortex by transcranial magnetic stimulation (TMS) or by sensory stimulation. We present here a large-scale model of the thalamocortical system that is capable of reproducing these experimental observations. This model was constructed according to a large number of physiological and anatomical constraints and includes over 30,000 spiking neurons interconnected by more than 5 million synaptic connections and organized into three cortical areas. By simulating the different effects of arousal promoting neuromodulators, the model can produce a waking or a slow wave sleep-like mode. In this work, we also seek to explain why intercortical signal transmission decreases in slow wave sleep. The traditional explanation for reduced brain responses during this state, a thalamic gate, cannot account for the reduced propagation between cortical areas. Therefore we propose that a cortical gate is responsible for this diminished intercortical propagation. We used our model to test three candidate mechanisms that might produce a cortical gate during slow wave sleep: a propensity to enter a local down state following perturbation, which blocks the propagation of activity to other areas, increases in potassium channel conductance that reduce neuronal responsiveness, and a shift in the balance of synaptic excitation and inhibition toward inhibition, which decreases network responses to perturbation. Of these mechanisms, we find that only a shift in the balance of synaptic excitation and inhibition can account for the observed in vivo response to direct cortical perturbation as well as many features of spontaneous sleep.
Content may be subject to copyright.
... The declining tendency of the connectivity magnitude that was observed at many channel pairs under each level of daily fatigue may be associated with the fading of consciousness [27,49]. A cortical gate is created through the reductions in cortico-cortical connectivity, and it may disconnect the brain from the external environment and, thus, block sensory inputs [27,50]. ...
A significant issue for traffic safety has been drowsy driving for decades. A number of studies have investigated the effects of acute fatigue on spectral power; and recent research has revealed that drowsy driving is associated with a variety of brain connections in a specific cortico-cortical pathway. In spite of this, it is still unclear how different brain regions are connected in drowsy driving at different levels of daily fatigue. This study identified the brain connectivity-behavior relationship among three different daily fatigue levels (low-, median- and high-fatigue) with the EEG data transfer entropy. According to the results, only low- and medium-fatigue groups demonstrated an inverted U-shaped change in connectivity from high performance to poor behavioral performance. In addition, from low- to high-fatigue groups, connectivity magnitude decreased in the frontal region and increased in the occipital region. These study results suggest that brain connectivity and driving behavior would be affected by different levels of daily fatigue.
... As the search for the neural correlates of consciousness (NCC) has been refined over the years by distilling the proper NCC from its prerequisites and consequences, the same should be attempted in the search for the NC of (dis)connected consciousness. Although there is suggestive evidence indicating that a breakdown in cortical effective connectivity (Massimini et al., 2005) might underlie the loss of consciousness in anesthesia (Boly et al., 2012) and sleep (Esser et al., 2009), the challenge heightens when attempting to pinpoint the specific mechanism responsible for the loss of environmental connection during these states. While we know that sensory stimuli reach primary sensory regions during presumed unconscious and dream states, it is unknown how they are processed in disconnected states in both primary and secondary regions. ...
Background
Disconnected consciousness describes a state in which subjective experience (i.e., consciousness) becomes isolated from the external world. It appears frequently during sleep or sedation, when subjective experiences remain vivid but are unaffected by external stimuli. Traditional methods of differentiating connected and disconnected consciousness, such as relying on behavioral responsiveness or on post-anesthesia reports, have demonstrated limited accuracy: unresponsiveness has been shown to not necessarily equate to unconsciousness and amnesic effects of anesthesia and sleep can impair explicit recollection of events occurred during sleep/sedation. Due to these methodological challenges, our understanding of the neural mechanisms underlying sensory disconnection remains limited.
Methods
To overcome these methodological challenges, we employ a distinctive strategy by combining a serial awakening paradigm with auditory stimulation during mild propofol sedation. While under sedation, participants are systematically exposed to auditory stimuli and questioned about their subjective experience (to assess consciousness) and their awareness of the sounds (to evaluate connectedness/disconnectedness from the environment). The data collected through interviews are used to categorize participants into connected and disconnected consciousness states. This method circumvents the requirement for responsiveness in assessing consciousness and mitigates amnesic effects of anesthesia as participants are questioned while still under sedation. Functional MRI data are concurrently collected to investigate cerebral activity patterns during connected and disconnected states, to elucidate sensory disconnection neural gating mechanisms. We examine whether this gating mechanism resides at the thalamic level or results from disruptions in information propagation to higher cortices. Furthermore, we explore the potential role of slow-wave activity (SWA) in inducing disconnected consciousness by quantifying high-frequency BOLD oscillations, a known correlate of slow-wave activity.
Discussion
This study represents a notable advancement in the investigation of sensory disconnection. The serial awakening paradigm effectively mitigates amnesic effects by collecting reports immediately after regaining responsiveness, while still under sedation. Ultimately, this research holds the potential to understand how sensory gating is achieved at the neural level. These biomarkers might be relevant for the development of sensitive anesthesia monitoring to avoid intraoperative connected consciousness and for the assessment of patients suffering from pathologically reduced consciousness.
Clinical trial registration
European Union Drug Regulating Authorities Clinical Trials Database (EudraCT), identifier 2020-003524-17.
... This fulfills our hypothesis since our task was visual sustained attention, and the occipital lobe is strongly correlated with visual information processing [63]. The lower connectivity in the occipital region might suggest the cortical gate mechanism that prevents the brain from the external sensory output [64]. Furthermore, our model revealed lower interregional connectivity in drowsiness, which might indicate that the state of the brain network changed to allow more efficient local information processing in drowsy states. ...
Drowsy driving is one of the primary causes of driving fatalities. Electroencephalography (EEG), a method for detecting drowsiness directly from brain activity, has been widely used for detecting driver drowsiness in real-time. Recent studies have revealed the great potential of using brain connectivity graphs constructed based on EEG data for drowsy state predictions. However, traditional brain connectivity networks are irrelevant to the downstream prediction tasks. This article proposes a connectivity-aware graph neural network (CAGNN) using a self-attention mechanism that can generate task-relevant connectivity networks via end-to-end training. Our method achieved an accuracy of 72.6% and outperformed other convolutional neural networks (CNNs) and graph generation methods based on a drowsy driving dataset. In addition, we introduced a squeeze-and-excitation (SE) block to capture important features and demonstrated that the SE attention score can reveal the most important feature band. We compared our generated connectivity graphs in the drowsy and alert states and found drowsiness connectivity patterns, including significantly reduced occipital connectivity and interregional connectivity. Additionally, we performed a post hoc interpretability analysis and found that our method could identify drowsiness features such as alpha spindles. Our code is available online1.
... A related notion is that of 'cortical gating,' in which information reaching sensory cortices would not efficiently propagate across cortical areas. This mechanism has been hypothesised to depend on a breakdown in functional connectivity caused by the spontaneous alternation of hyperpolarized ('on') and depolarized ('off') states of neuronal populations that underlie typical slow waves (< 4 Hz) of NREM sleep (Esser et al., 2009). Interestingly, recent work suggested that a similar mechanism could be active in primary sensory cortices also during REM sleep (Baird et al., 2018;Bernardi et al., 2019;Funk et al., 2016). ...
Sleep is commonly regarded as a state of disconnection from the environment. Yet, instances of external sensory stimuli affecting the course of dreams have been reported for centuries. Importantly, understanding the impact of external stimuli on dreams could shed light on the origin and generation of dreams, the functional mechanisms that preserve sleep continuity, and the processes that underlie conscious awareness. Moreover, the possibility of using sensory stimuli for dream engineering could potentially benefit patients suffering from alterations in the intensity or content of sleep conscious experiences. Here, we performed a systematic review following PRISMA guidelines to evaluate the robustness of the current evidence regarding the influence of external sensory stimulation during sleep on dreams experiences. In a literature search using PsycNET, PubMed, ScienceDirect, and Scopus, we selected any experimental work presenting dream data obtained from a confirmed sleep episode during which visual, auditory, olfactory, gustatory, or somatosensory stimulation was administered. A methodological assessment of the included studies was performed using an adapted version of the Downs and Black’s (1998) checklist. Fifty-one publications met the inclusion criteria, of which 21 reported data related to auditory stimulation, 10 to somatosensory stimulation, 8 to olfactory stimulation, 4 to visual stimulation, 2 to vestibular stimulation, and 1 to multi-modal stimulation (audio-visual). Furthermore, 9 references involved pre-conditioned associative stimulation procedures: 6 relied on targeted memory reactivation protocols and 3 on targeted lucid reactivation protocols. The reported frequency of stimulus-dependent dream changes across studies ranged from 0% to ~90%. Such a variability likely reflects the considerable heterogeneity of experimental and methodological approaches. Overall, the literature analysis identified a lack of substantial understanding of the key mechanisms, functions, and correlates of stimulus-dependent dream changes. We believe that a paradigm shift is required for meaningful and significant advancement in the field. We hope that this review will serve as a starting point for such a shift.
... A related notion is that of 'cortical gating,' in which information reaching sensory cortices would not efficiently propagate across cortical areas. This mechanism has been hypothesised to depend on a breakdown in functional connectivity caused by the spontaneous alternation of hyperpolarized ('on') and depolarized ('off') states of neuronal populations that underlie typical slow waves (< 4 Hz) of NREM sleep (Esser et al., 2009). Interestingly, recent work suggested that a similar mechanism could be active in primary sensory cortices also during REM sleep (Baird et al., 2018;Bernardi et al., 2019;Funk et al., 2016). ...
Sleep is commonly regarded as a state of disconnection from the environment. Yet, instances of external sensory stimuli affecting the course of dreams have been reported for centuries. Importantly, understanding the impact of external stimuli on dreams could shed light on the origin and generation of dreams, the functional mechanisms that preserve sleep continuity, and the processes that underlie conscious awareness. Moreover, the possibility of using sensory stimuli for dream engineering could potentially benefit patients suffering from alterations in the intensity or content of sleep conscious experiences. Here, we performed a systematic review following PRISMA guidelines to evaluate the robustness of the current evidence regarding the influence of external sensory stimulation during sleep on dreams experiences. In a literature search using PsycNET, PubMed, ScienceDirect, and Scopus, we selected any experimental work presenting dream data obtained from a confirmed sleep episode during which visual, auditory, olfactory, gustatory, or somatosensory stimulation was administered. A methodological assessment of the included studies was performed using an adapted version of the Downs and Black's (1998) checklist. Fifty-one publications met the inclusion criteria, of which 21 reported data related to auditory stimulation, 10 to somatosensory stimulation, 8 to olfactory stimulation, 4 to visual stimulation, 2 to vestibular stimulation, and 1 to multi-modal stimulation (audio-visual). Furthermore, 9 references involved pre-conditioned associative stimulation procedures: 6 relied on targeted memory reactivation protocols and 3 on targeted lucid reactivation protocols. The reported frequency of stimulus-dependent dream changes across studies ranged from 0% to ~90%. Such a variability likely reflects the considerable heterogeneity of experimental and methodological approaches. Overall, the literature analysis identified a lack of substantial understanding of the key mechanisms, functions, and correlates of stimulus-dependent dream changes. We believe that a paradigm shift is required for meaningful and significant advancement in the field. We hope that this review will serve as a starting point for such a shift.
... Studies have shown that the light anesthetic regimen employed in our study could be analogous to slow wave sleep, both in terms of the slow rhythms (Torao-Angosto et al., 2021) and FC patterns Bettinardi et al., 2015). Thalamus can be decoupled from cortex (in terms of tonic thalamic activity) during some general anesthesia conditions (Suzuki and Larkum, 2020), and thalamocortical connectivity is often reduced during anesthesia and deep sleep (Esser et al., 2009;Hudetz, 2012;Picchioni et al., 2014). On the other hand, IHFC of thalamic nuclei and intrathalamic FC, both increased after TTA-P2 administration, though the differences were not significant (paired t-test, p > 0.05). ...
A number of studies point to slow (0.1–2 Hz) brain rhythms as the basis for the resting-state functional magnetic resonance imaging (rsfMRI) signal. Slow waves exist in the absence of stimulation, propagate across the cortex, and are strongly modulated by vigilance similar to large portions of the rsfMRI signal. However, it is not clear if slow rhythms serve as the basis of all neural activity reflected in rsfMRI signals, or just the vigilance-dependent components. The rsfMRI data exhibit quasi-periodic patterns (QPPs) that appear to increase in strength with decreasing vigilance and propagate across the brain similar to slow rhythms. These QPPs can complicate the estimation of functional connectivity (FC) via rsfMRI, either by existing as unmodeled signal or by inducing additional wide-spread correlation between voxel-time courses of functionally connected brain regions. In this study, we examined the relationship between cortical slow rhythms and the rsfMRI signal, using a well-established pharmacological model of slow wave suppression. Suppression of cortical slow rhythms led to significant reduction in the amplitude of QPPs but increased rsfMRI measures of intrinsic FC in rats. The results suggest that cortical slow rhythms serve as the basis of only the vigilance-dependent components (e.g., QPPs) of rsfMRI signals. Further attenuation of these non-specific signals enhances delineation of brain functional networks.
Sleep and depression have a complex, bidirectional relationship, with sleep-associated alterations in brain dynamics and structure impacting a range of symptoms and cognitive abilities. Previous work describing these relationships has provided an incomplete picture by investigating only one or two types of sleep measures, depression, or neuroimaging modalities in parallel. We analyze the correlations between brainwide neural signatures of sleep, cognition, and depression in task and resting-state data from over 30,000 individuals from the UK Biobank and Human Connectome Project. Neural signatures of insomnia and depression are negatively correlated with those of sleep duration measured by accelerometer in the task condition but positively correlated in the resting-state condition. Our results show that resting-state neural signatures of insomnia and depression resemble that of rested wakefulness. This is further supported by our finding of hypoconnectivity in task but hyperconnectivity in resting-state data in association with insomnia and depression. These observations dispute conventional assumptions about the neurofunctional manifestations of hyper- and hypo-somnia, and may explain inconsistent findings in the literature.
In this deliverable D1.4 (issue 2, month 46), we report the progress that has been accomplished on a computational model for EEG in consciousness studies. The development of such a model is a tremendous challenge. Fortunately, it will benefit from the background, the results and the know-how acquired during a previous European project called HIVE (Hyper Interaction Viability Experiments, FP7-FET Open-222079, 2008-13) that was coordinated by STARLAB and in which INSERM partner has led WP1 dedicated to biophysical and biological models of the brain under tCS conditions. This available background explains why the first section (section 2: A computational model of EEG accounting for tCS effects: background from the "HIVE" project) provides a synthetic review on the main aspects and results obtained in the HIVE project. We preferred writing this summary instead of just referring to papers in order to i) gather the essential elements of modeling in the present document and ii) facilitate the reading of reviewers and colleagues. In addition, this section was intended to point at the limitations of models developed in HIVE and therefore the work to be done to build an even more insightful model that can be useful for consciousness studies, which is one of the ambitious goals of the LUMINOUS project. From section 3 (Computational modeling of EEG for consciousness studies), we describe the work accomplished over the period spanning from April 2016 to February 2017. Starting from the main advantages and current limitations of the existing model and considering the theoretical models of consciousness reported in D1.1, we performed a comprehensive literature review about the neurophysiological mechanisms that should be "ideally" integrated in the envisioned computational modeling of EEG for consciousness studies. We then provide an update on recent (at M12) modeling advances regarding the cortical response to TMS and the Perturbational Complexity Index (PCI), based on the experimental work performed by UMIL (Milano, Italy). In brief, we have developed a model of local brain tissue activity, in response to brief (< 100 ms) pulses of stimulation, such as those used to calculate the PCI. Interestingly, preliminary results (M12) show that a neural field model composed of 10 populations, connected through a biologically plausible distribution of time delays, can capture the basic properties of TMS-evoked responses in humans. We then computed the PCI values for two states of consciousness and showed that they are consistent with PCI values measured for similar conditions. We also provide an update regarding the progress we made on the thalamo-cortical model and the simulation of EEG in two different states of consciousness, i.e. wakefulness and sleep conditions. The key role of the thalamo-cortical (TC) circuitry as a neural correlate of consciousness has been reported in most theories of consciousness, including the Dynamic Core Hypothesis (DCH) and the Integrated Information Theory (IIT) (see D1.1). We have described the developed model, including a cortical module, a thalamic module, and a reticular module. The model was implemented in a user-friendly environment. At this stage, preliminary results indicate that it can simulate background activity, alpha waves and some rhythms associated with sleep (k-complexes and SWS). Finally, one important objective of LUMINOUS is to develop novel metrics of consciousness. In section 4, we provided a first illustrative example of the approach we can follow to evaluate metrics of consciousness based on physiologically-relevant models of EEG. At this stage (M12), we simulated local field potentials from a simple neural mass model (mesoscopic level, similar to models envisioned in LUMINOUS) and computed various metrics based on the Hurst exponents on simulated signals. From this combination (model/signal processing), we could determine some specific conditions for which an insightful relationship can be derived regarding i) the values provided by considered metrics and ii) model parameters directly related to cortical excitability. LUMINOUS Deliverable D1.4 "Computational model for EEG in consciousness"
Dose-response curves for activation of excitatory amino acid receptors on mouse embryonic hippocampal neurons in culture were recorded for 15 excitatory amino acids, including the L-isomers of glutamate, aspartate, and a family of endogenous sulfur amino acids. In the presence of 3 microM glycine, with no extracellular Mg, micromolar concentrations of 11 of these amino acids produced selective activation of N-methyl-D-aspartate (NMDA) receptors. L-Glutamate was the most potent NMDA agonist (EC50 2.3 microM) and quinolinic acid the least potent (EC50 2.3 mM). Dose-response curves were well fit by the logistic equation, or by a model with 2 independent agonist binding sites. The mean limiting slope of log-log plots of NMDA receptor current versus agonist concentration (1.93) suggests that a 2-site model is appropriate. There was excellent correlation between agonist EC50S determined in voltage clamp experiments and KdS determined for NMDA receptor binding (Olverman et al., 1988). With no added glycine, and 1 mM extracellular Mg, responses to NMDA were completely blocked; responses to kainate and quisqualate were unchanged. Under these conditions, glutamate and the sulfur amino acids activated a rapidly desensitizing response, similar to that evoked by micromolar concentrations of quisqualate and AMPA, but mM concentrations of L- aspartate, homoquinolinic acid, and quinolinic acid failed to elicit a non-NMDA receptor-mediated response. Except for L-glutamate (EC50 480 microM), the low potency of the sulfur amino acids prevented the study of complete dose-response curves for the rapidly desensitizing response at quisqualate receptors. Small-amplitude nondesensitizing quisqualate receptor responses were activated by much lower concentrations of all quisqualate receptor agonists. Full dose-response curves for the nondesensitizing response were obtained for 9 amino acids; L-glutamate was the most potent endogenous agonist (EC50 19 microM). Domoate (EC50 13 microM) and kainate (EC50 143 microM) activated large-amplitude, nondesensitizing responses.
(1) In order to investigate the effects of acetylcholine (ACh) on synaptic transmission in the rat hippocampus, extracellular and intracellular recordings were made from pyramidal neurons in an in vitro slice preparation while synaptic inputs to the cell population were stimulated. ACh was applied ionophoretically into somatic and dendritic layers of the slice. (2) ACh applied into the apical dendritic layer of the CA1 region reduced the size of the locally evoked field excitatory postsynaptic potential (EPSP) without altering the size of the afferent fiber volley. Likewise, dendritically applied ACh reduced the size of intracellularly recorded EPSPs. This effect of ACh appeared to be muscarinic since it was not affected by hexamethonium (up to 3 X 10-5 M) but was antagonized by atropine in a dose-dependent manner. (3) The distribution of Ach-sensitive sites matched closely the spatial distribution of activated synapses on the pyramidal cell dendrites as shown by ionophoretic mapping experiments. (4) In contrast to the effects of dendritic applications of ACh, ionophoresis of ACh into the cell layer resulted in an increase and prolongation of EPSPs and a transient decrease in the size of recurrent somatic inhibitory postsynaptic potentials (IPSPs). These effects on synaptic potentials could not be explained by the observed changes in membrane potential and input resistance following somatic application of ACh. (5) Short dendritic applications of ACh had no consistent effect on the membrane potential or slope conductance of pyramidal neurons and did not attenuate the depolarization evoked by brief dendritic applications of glutamate. In addition, the time course of ACh-reduced EPSPs was not different from control. (6) We conclude that ACh exerts a presynaptic inhibitory effect on both excitatory and inhibitory afferents to hippocampal pyramidal neurons. This effect of ACh is widespread, occurring in all regions of Ammon's horn tested as well as in stratum moleculare of fascia dentata.
In this first intracellular study of neocortical activities during waking and sleep states, we hypothesized that synaptic activities during natural states of vigilance have a decisive impact on the observed electrophysiological properties of neurons that were previously studied under anesthesia or in brain slices. We investigated the incidence of different firing patterns in neocortical neurons of awake cats, the relation between membrane potential fluctuations and firing rates, and the input resistance during all states of vigilance. In awake animals, the neurons displaying fast-spiking firing patterns were more numerous, whereas the incidence of neurons with intrinsically bursting patterns was much lower than in our previous experiments conducted on the intact-cortex or isolated cortical slabs of anesthetized cats. Although cortical neurons displayed prolonged hyperpolarizing phases during slow-wave sleep, the firing rates during the depolarizing phases of the slow sleep oscillation was as high during these epochs as during waking and rapid-eye-movement sleep. Maximum firing rates, exceeding those of regular-spiking neurons, were reached by conventional fast-spiking neurons during both waking and sleep states, and by fast-rhythmic-bursting neurons during waking. The input resistance was more stable and it increased during quiet wakefulness, compared with sleep states. As waking is associated with high synaptic activity, we explain this result by a higher release of activating neuromodulators, which produce an increase in the input resistance of cortical neurons. In view of the high firing rates in the functionally disconnected state of slow-wave sleep, we suggest that neocortical neurons are engaged in processing internally generated signals
Dual and triple intracellular recordings with biocytin labelling in slices of adult neocortex explored small circuits of synaptically connected neurons. 679 paired recordings in rat and 319 in cat yielded 135 and 42 excitatory postsynaptic potentials (EPSPs) and 37 and 26 inhibitory postsynaptic potentials (IPSPs), respectively. Patterns of connectivity and synaptic properties were similar in the two species, although differences of scale and in the range of morphologies were observed. Excitatory ‘forward’ projections from layer 4 to 3, like those from layer 3 to 5, targeted pyramidal cells and a small proportion of interneurons, while excitatory ‘back’ projections from layer 3 to 4 selected interneurons, including parvalbumin immuno-positive basket cells. Layer 4 interneurons that inhibited layer 3 pyramidal cells included both basket cells and dendrite-targeting cells. Large interneurons, resembling cells previously described as large basket cells, in layers 4 and 3 (cat), with long myelinated horizontal axon collaterals received frequent excitatory inputs from both layers. A very high rate of connectivity was observed between pairs of interneurons, often with quite different morphologies, and the resultant IPSPs, like the EPSPs recorded in interneurons, were brief compared with those recorded in pyramidal and spiny stellate cells.
The thalamus has long been seen as responsible for relaying information on the way to the cerebral cortex, but it has not been until the last decade or so that the functional nature of this relay has attracted significant attention. Whereas earlier views tended to relegate thalamic function to a simple, machine-like relay process, recent research, reviewed in this article, demonstrates complicated circuitry and a rich array of membrane properties underlying the thalamic relay. It is now clear that the thalamic relay does not have merely a trivial function. Suggestions that the thalamic circuits and cell properties only come into play during certain phases of sleep to effectively disconnect the relay are correct as far as they go, but they are incomplete, because they fail to take into account interesting and variable properties of the relay that, we argue, occur during normal waking behavior. Although the specific function of the circuits and cellular properties of the thalamic relay for waking behavior is far from clear, we offer two related hypotheses based on recent experimental evidence. One is that the thalamus is not used just to relay peripheral information from, for example, visual, auditory, or cerebellar inputs, but that some thalamic nuclei are arranged instead to relay information from one cortical area to another. The second is that the thalamus is not a simple, passive relay of information to cortex but instead is involved in many dynamic processes that significantly alter the nature of the information relayed to cortex.
The responses of vertebrate neurones to glutamate involve at least three receptor types. One of these, the NMDA receptor (so called because of its specific activation by N-methyl-D-aspartate), induces responses presenting a peculiar voltage sensitivity. Above resting potential, the current induced by a given dose of glutamate (or NMDA) increases when the cell is depolarized. This is contrary to what is observed at classical excitatory synapses, and recalls the properties of 'regenerative' systems like the Na+ conductance of the action potential. Indeed, recent studies of L-glutamate, L-aspartate and NMDA-induced currents have indicated that the current-voltage (I-V) relationship can show a region of 'negative conductance' and that the application of these agonists can lead to a regenerative depolarization. Furthermore, the NMDA response is greatly potentiated by reducing the extracellular Mg2+ concentration [( Mg2+]o) below the physiological level (approximately 1 mM). By analysing the responses of mouse central neurones to glutamate using the patch-clamp technique, we have now found a link between voltage sensitivity and Mg2+ sensitivity. In Mg2+-free solutions, L-glutamate, L-aspartate and NMDA open cation channels, the properties of which are voltage independent. In the presence of Mg2+, the single-channel currents measured at resting potential are chopped in bursts and the probability of opening of the channels is reduced. Both effects increase steeply with hyperpolarization, thereby accounting for the negative slope of the I-V relationship of the glutamate response. Thus, the voltage dependence of the NMDA receptor-linked conductance appears to be a consequence of the voltage dependence of the Mg2+ block and its interpretation does not require the implication of an intramembrane voltage-dependent 'gate'.
Abstract Synaptic transmission is a dynamic process. Postsynaptic responses wax and wane as presynaptic activity evolves. This prominent characteristic of chemical synaptic transmission is a crucial determinant of the response properties of synapses and, in turn, of the stimulus properties selected by neural networks and of the patterns of activity generated by those networks. This review focuses on synaptic changes that result from prior activity in the synapse under study, and is restricted to short-term effects that last for at most a few minutes. Forms of synaptic enhancement, such as facilitation, augmentation, and post-tetanic potentiation, are usually attributed to effects of a residual elevation in presynaptic [Ca2+]i, acting on one or more molecular targets that appear to be distinct from the secretory trigger responsible for fast exocytosis and phasic release of transmitter to single action potentials. We discuss the evidence for this hypothesis, and the origins of the different kinetic phases of synaptic enhancement, as well as the interpretation of statistical changes in transmitter release and roles played by other factors such as alterations in presynaptic Ca2+ influx or postsynaptic levels of [Ca2+]i. Synaptic depression dominates enhancement at many synapses. Depression is usually attributed to depletion of some pool of readily releasable vesicles, and various forms of the depletion model are discussed. Depression can also arise from feedback activation of presynaptic receptors and from postsynaptic processes such as receptor desensitization. In addition, glial-neuronal interactions can contribute to short-term synaptic plasticity. Finally, we summarize the recent literature on putative molecular players in synaptic plasticity and the effects of genetic manipulations and other modulatory influences.
Cortical neurons receive synaptic inputs from thousands of afferents that fire action potentials at rates ranging from less
than 1 hertz to more than 200 hertz. Both the number of afferents and their large dynamic range can mask changes in the spatial
and temporal pattern of synaptic activity, limiting the ability of a cortical neuron to respond to its inputs. Modeling work
based on experimental measurements indicates that short-term depression of intracortical synapses provides a dynamic gain-control
mechanism that allows equal percentage rate changes on rapidly and slowly firing afferents to produce equal postsynaptic responses.
Unlike inhibitory and adaptive mechanisms that reduce responsiveness to all inputs, synaptic depression is input-specific,
leading to a dramatic increase in the sensitivity of a neuron to subtle changes in the firing patterns of its afferents.
We combined fMRI and EEG recording to study the neurophysiological responses associated with auditory stimulation across the sleep-wake cycle. We found that presentation of auditory stimuli produces bilateral activation in auditory cortex, thalamus, and caudate during both wakefulness and nonrapid eye movement (NREM) sleep. However, the left parietal and, bilaterally, the prefrontal and cingulate cortices and the thalamus were less activated during NREM sleep compared to wakefulness. These areas may play a role in the further processing of sensory information required to achieve conscious perception during wakefulness. Finally, during NREM sleep, the left amygdala and the left prefrontal cortex were more activated by stimuli having special affective significance than by neutral stimuli. These data suggests that the sleeping brain can process auditory stimuli and detect meaningful events.