Impact of GABAA and GABAB Inhibition on Cortical Dynamics and Perturbational Complexity during Synchronous and Desynchronized States

Exploring effects of anesthesia on complexity, differentiation, and integrated information in rat EEG

To investigate mechanisms underlying loss of consciousness, it is important to extend methods established in humans to rodents as well. Perturbational complexity index (PCI) is a promising metric of "capacity for consciousness" and is based on a perturbational approach that allows inferring a system's capacity for causal integration and differentiation of information. These properties have been proposed as necessary for conscious systems. Measures based on spontaneous electroencephalography recordings, however, may be more practical for certain clinical purposes and may better reflect ongoing dynamics. Here, we compare PCI (using electrical stimulation for perturbing cortical activity) to several spontaneous electroencephalography-based measures of signal diversity and integrated information in rats undergoing propofol, sevoflurane, and ketamine anesthesia. We find that, along with PCI, the spontaneous electroencephalography-based measures, Lempel-Ziv complexity (LZ) and geometric integrated information (ΦG), were best able to distinguish between awake and propofol and sevoflurane anesthesia. However, PCI was anti-correlated with spontaneous measures of integrated information, which generally increased during propofol and sevoflurane anesthesia, contrary to expectations. Together with an observed divergence in network properties estimated from directed functional connectivity (current results) and effective connectivity (earlier results), the perturbation-based results seem to suggest that anesthesia disrupts global cortico-cortical information transfer, whereas spontaneous activity suggests the opposite. We speculate that these seemingly diverging results may be because of suppressed encoding specificity of information or driving subcortical projections from, e.g., the thalamus. We conclude that certain perturbation-based measures (PCI) and spontaneous measures (LZ and ΦG) may be complementary and mutually informative when studying altered states of consciousness.

Stationary stable cross-correlation pattern and task specific deviations in unresponsive wakefulness syndrome as well as clinically healthy subjects

Brain dynamics is highly non-stationary, permanently subject to ever-changing external conditions and continuously monitoring and adjusting internal control mechanisms. Finding stationary structures in this system, as has been done recently, is therefore of great importance for understanding fundamental dynamic trade relationships. Here we analyse electroencephalographic recordings (EEG) of 13 subjects with unresponsive wakefulness syndrome (UWS) during rest and while being influenced by different acoustic stimuli. We compare the results with a control group under the same experimental conditions and with clinically healthy subjects during overnight sleep. The main objective of this study is to investigate whether a stationary correlation pattern is also present in the UWS group, and if so, to what extent this structure resembles the one found in healthy subjects. Furthermore, we extract transient dynamical features via specific deviations from the stationary interrelation pattern. We find that (i) the UWS group is more heterogeneous than the two groups of healthy subjects, (ii) also the EEGs of the UWS group contain a stationary cross-correlation pattern, although it is less pronounced and shows less similarity to that found for healthy subjects and (iii) deviations from the stationary pattern are notably larger for the UWS than for the two groups of healthy subjects. The results suggest that the nervous system of subjects with UWS receive external stimuli but show an overreaching reaction to them, which may disturb opportune information processing.

Action of GABAB receptor on local network oscillation in somatosensory cortex of oral part: focusing on NMDA receptor

The balance of activity between glutamatergic and GABAergic networks is particularly important for oscillatory neural activities in the brain. Here, we investigated the roles of GABAB receptors in network oscillation in the oral somatosensory cortex (OSC), focusing on NMDA receptors. Neural oscillation at the frequency of 8-10 Hz was elicited in rat brain slices after caffeine application. Oscillations comprised a non-NMDA receptor-dependent initial phase and a later NMDA receptor-dependent oscillatory phase, with the oscillator located in the upper layer of the OSC. Baclofen was applied to investigate the actions of GABAB receptors. The later NMDA receptor-dependent oscillatory phase completely disappeared, but the initial phase did not. These results suggest that GABAB receptors mainly act on NMDA receptor, in which metabotropic actions of GABAB receptors may contribute to the attenuation of NMDA receptor activities. A regulatory system for network oscillation involving GABAB receptors may be present in the OSC.

Laminar evoked responses in mouse somatosensory cortex suggest a special role for deep layers in cortical complexity

It has been suggested that consciousness is closely related to the complexity of the brain. The perturbational complexity index (PCI) has been used in humans and rodents to distinguish conscious from unconscious states based on the global cortical responses (recorded by electroencephalography, EEG) to local cortical stimulation (CS). However, it is unclear how different cortical layers respond to CS and contribute to the resulting intra- and inter-areal cortical connectivity and PCI. A detailed investigation of the local dynamics is needed to understand the basis for PCI. We hypothesized that the complexity level of global cortical responses (PCI) correlates with layer-specific activity and connectivity. We tested this idea by measuring global cortical dynamics and layer-specific activity in the somatosensory cortex (S1) of mice, combining cortical electrical stimulation in deep motor cortex, global electrocorticography (ECoG) and local laminar recordings from layers 1-6 in S1, during wakefulness and general anaesthesia (sevoflurane). We found that the transition from wake to sevoflurane anaesthesia correlated with a drop in both the global and local PCI (PCIst ) values (complexity). This was accompanied by a local decrease in neural firing rate, spike-field coherence and long-range functional connectivity specific to deep layers (L5, L6). Our results suggest that deep cortical layers are mechanistically important for changes in PCI and thereby for changes in the state of consciousness.

Electroencephalogram changes over time in zolpidem withdrawal seizure: A case study

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Spontaneous slow wave oscillations in extracellular field potential recordings reflect the alternating dominance of excitation and inhibition

In the resting state, cortical neurons can fire action potentials spontaneously but synchronously (Up state), followed by a quiescent period (Down state) before the cycle repeats. Extracellular recordings in the infragranular layer of cortex with a micro-electrode display a negative deflection (depth-negative) during Up states and a positive deflection (depth-positive) during Down states. The resulting slow wave oscillation (SWO) has been studied extensively during sleep and under anaesthesia. However, recent research on the balanced nature of synaptic excitation and inhibition has highlighted our limited understanding of its genesis. Specifically, are excitation and inhibition balanced during SWOs? We analyse spontaneous local field potentials (LFPs) during SWOs recorded from anaesthetised rats via a multi-channel laminar micro-electrode and show that the Down state consists of two distinct synaptic states: a Dynamic Down state associated with depth-positive LFPs and a prominent dipole in the extracellular field, and a Static Down state with negligible (≈ 0 mV $ \approx 0{\mathrm{\;mV}}$ ) LFPs and a lack of dipoles extracellularly. We demonstrate that depth-negative and -positive LFPs are generated by a shift in the balance of synaptic excitation and inhibition from excitation dominance (depth-negative) to inhibition dominance (depth-positive) in the infragranular layer neurons. Thus, although excitation and inhibition co-tune overall, differences in their timing lead to an alternation of dominance, manifesting as SWOs. We further show that Up state initiation is significantly faster if the preceding Down state is dynamic rather than static. Our findings provide a coherent picture of the dependence of SWOs on synaptic activity. KEY POINTS: Cortical neurons can exhibit repeated cycles of spontaneous activity interleaved with periods of relative silence, a phenomenon known as 'slow wave oscillation' (SWO). During SWOs, recordings of local field potentials (LFPs) in the neocortex show depth-negative deflection during the active period (Up state) and depth-positive deflection during the silent period (Down state). Here we further classified the Down state into a dynamic phase and a static phase based on a novel method of classification and revealed non-random, stereotypical sequences of the three states occurring with significantly different transitional kinetics. Our results suggest that the positive and negative deflections in the LFP reflect the shift of the instantaneous balance between excitatory and inhibitory synaptic activity of the local cortical neurons. The differences in transitional kinetics may imply distinct synaptic mechanisms for Up state initiation. The study may provide a new approach for investigating spontaneous brain rhythms.

Increased excitability and reduced GABAergic levels in somatosensory cortex under chronic spinal cord injury

The complete or partial damage of ascending somatosensory pathways produced by a spinal cord injury triggers changes in the somatosensory cortex consisting in a functional expansion of activity from intact cortical regions towards deafferented ones, a process known as cortical reorganization. However, it is still unclear whether cortical reorganization depends on the severity of the spinal cord damage or if a spinal cord injury always leads to a similar cortical reorganization process in the somatosensory cortex. To answer these open questions in the field, we obtained longitudinal somatosensory evoked responses from bilateral hindlimb and forelimb cortex from animals with chronic full-transection or contusive spinal cord injury at thoracic level (T9-T10) to induce sensory deprivation of hindlimb cortex while preserving intact the forelimb cortex. Electrophysiological recordings from the four locations were obtained before lesion and weekly for up to 4 weeks. Our results show that cortical reorganization depends on the type of spinal cord injury, which tends to be more bilateral in full transection while is more unilateral in the model of contusive spinal cord injury. Moreover, in full transection of spinal cord, the deafferented and intact cortex exhibited similar increments of somatosensory evoked responses in both models of spinal cord injury - a feature observed in about 80% of subjects. The other 20% were unaffected by the injury indicating that cortical reorganization does not undergo in all subjects. In addition, we demonstrated an increased probability of triggered up-states in animals with spinal cord injury. This data indicates increased cortical excitability that could be proposed as a new feature of cortical reorganization. Finally, decreased levels of GABA marker GAD67 across cortical layers were only found in those animals with increased somatosensory evoked responses, but not in the unaffected population. In conclusion, cortical reorganization depends on the types of spinal cord injuries, and suggest that the phenomenon is strongly determined by cortical circuits. Moreover, changes in GABAergic transmission at the deprived cortex may be considered one of the mechanisms underlying the process of cortical reorganization and increased excitability.

Nonlinear mechanism for the enhanced bursting activities induced by fast inhibitory autapse and reduced activities by fast excitatory autapse

The paradoxical phenomena that excitatory modulation does not enhance but reduces or inhibitory modulation not suppresses but promotes neural firing activities have attracted increasing attention. In the present study, paradoxical phenomena induced by both fast excitatory and inhibitory autapses in a "Fold/Big Homoclinic" bursting are simulated, and the corresponding nonlinear and biophysical mechanisms are presented. Firstly, the enhanced conductance of excitatory autapse induces the number of spikes per burst and firing rate reduced, while the enhanced inhibitory autapse cause both indicators increased. Secondly, with fast-slow variable dissection, the burst of bursting is identified to locate between a fold bifurcation and a big saddle-homoclinic orbit bifurcation of the fast subsystem. Enhanced excitatory or inhibitory autapses cannot induce changes of both bifurcation points, i.e., burst width. However, width of slow variable between two successive spikes within a burst becomes wider for the excitatory autapse and narrower for the inhibitory autapse, resulting in the less and more spikes per burst, respectively. Last, the autaptic current of fast autapse mainly plays a role during the peak of action potential, differing from the slow autaptic current with exponential decay, which can play roles following the peak of action potential. The fast excitatory autaptic current enhances the amplitude of the action potential and reduces the repolarization of the action potential to lengthen the interspike interval (ISI) of the spiking of the fast subsystem, resulting in the wide width of slow variable between successive spikes. The fast inhibitory autaptic current reduces the amplitude of action potential and ISI of spiking, resulting in narrow width of slow variable. The novel example of the paradoxical responses for both fast modulations and nonlinear mechanism extend the contents of neurodynamics, which presents potential functions of the fast autapse.

M-current modulation of cortical slow oscillations: Network dynamics and computational modeling

The slow oscillation is a synchronized network activity expressed by the cortical network in slow wave sleep and under anesthesia. Waking up requires a transition from this synchronized brain state to a desynchronized one. Cholinergic innervation is critical for the transition from slow-wave-sleep to wakefulness, and muscarinic action is largely exerted through the muscarinic-sensitive potassium current (M-current) block. We investigated the dynamical impact of blocking the M-current on slow oscillations, both in cortical slices and in a cortical network computational model. Blocking M-current resulted in an elongation of Up states (by four times) and in a significant firing rate increase, reflecting an increased network excitability, albeit no epileptiform discharges occurred. These effects were replicated in a biophysical cortical model, where a parametric reduction of the M-current resulted in a progressive elongation of Up states and firing rate. All neurons, and not only those modeled with M-current, increased their firing rates due to network recurrency. Further increases in excitability induced even longer Up states, approaching the microarousals described in the transition towards wakefulness. Our results bridge an ionic current with network modulation, providing a mechanistic insight into network dynamics of awakening.

Paradoxical pharmacological dissociations result from drugs that enhance delta oscillations but preserve consciousness

Low-frequency (<4 Hz) neural activity, particularly in the delta band, is generally indicative of loss of consciousness and cortical down states, particularly when it is diffuse and high amplitude. Remarkably, however, drug challenge studies of several diverse classes of pharmacological agents-including drugs which treat epilepsy, activate GABA_B receptors, block acetylcholine receptors, or produce psychedelic effects-demonstrate neural activity resembling cortical down states even as the participants remain conscious. Of those substances that are safe to use in healthy volunteers, some may be highly valuable research tools for investigating which neural activity patterns are sufficient for consciousness or its absence.

A deep generative adversarial network capturing complex spiral waves in disinhibited circuits of the cerebral cortex

BACKGROUND

In the cerebral cortex, disinhibited activity is characterized by propagating waves that spread across neural tissue. In this pathological state, a widely reported form of activity are spiral waves that travel in a circular pattern around a fixed spatial locus termed the center of mass. Spiral waves exhibit stereotypical activity and involve broad patterns of co-fluctuations, suggesting that they may be of lower complexity than healthy activity.

RESULTS

To evaluate this hypothesis, we performed dense multi-electrode recordings of cortical networks where disinhibition was induced by perfusing a pro-epileptiform solution containing 4-Aminopyridine as well as increased potassium and decreased magnesium. Spiral waves were identified based on a spatially delimited center of mass and a broad distribution of instantaneous phases across electrodes. Individual waves were decomposed into "snapshots" that captured instantaneous neural activation across the entire network. The complexity of these snapshots was examined using a measure termed the participation ratio. Contrary to our expectations, an eigenspectrum analysis of these snapshots revealed a broad distribution of eigenvalues and an increase in complexity compared to baseline networks. A deep generative adversarial network was trained to generate novel exemplars of snapshots that closely captured cortical spiral waves. These synthetic waves replicated key features of experimental data including a tight center of mass, a broad eigenvalue distribution, spatially-dependent correlations, and a high complexity. By adjusting the input to the model, new samples were generated that deviated in systematic ways from the experimental data, thus allowing the exploration of a broad range of states from healthy to pathologically disinhibited neural networks.

CONCLUSIONS

Together, results show that the complexity of population activity serves as a marker along a continuum from healthy to disinhibited brain states. The proposed generative adversarial network opens avenues for replicating the dynamics of cortical seizures and accelerating the design of optimal neurostimulation aimed at suppressing pathological brain activity.

Deterministic and Stochastic Components of Cortical Down States: Dynamics and Modulation

Slow oscillations are an emergent activity of the cerebral cortex network consisting of alternating periods of activity (Up states) and silence (Down states). Up states are periods of persistent cortical activity that share properties with that of underlying wakefulness. However, the occurrence of Down states is almost invariably associated with unconsciousness, both in animal models and clinical studies. Down states have been attributed relevant functions, such as being a resetting mechanism or breaking causal interactions between cortical areas. But what do Down states consist of? Here, we explored in detail the network dynamics (e.g., synchronization and phase) during these silent periods in vivo (male mice), in vitro (ferrets, either sex), and in silico, investigating various experimental conditions that modulate them: anesthesia levels, excitability (electric fields), and excitation/inhibition balance. We identified metastability as two complementary phases composing such quiescence states: a highly synchronized "deterministic" period followed by a low-synchronization "stochastic" period. The balance between these two phases determines the dynamical properties of the resulting rhythm, as well as the responsiveness to incoming inputs or refractoriness. We propose detailed Up and Down state cycle dynamics that bridge cortical properties emerging at the mesoscale with their underlying mechanisms at the microscale, providing a key to understanding unconscious states.SIGNIFICANCE STATEMENT The cerebral cortex expresses slow oscillations consisting of Up (active) and Down (silent) states. Such activity emerges not only in slow wave sleep, but also under anesthesia and in brain lesions. Down states functionally disconnect the network, and are associated with unconsciousness. Based on a large collection of data, novel data analysis approaches and computational modeling, we thoroughly investigate the nature of Down states. We identify two phases: a highly synchronized "deterministic" period, followed by a low-synchronization "stochastic" period. The balance between these two phases determines the dynamic properties of the resulting rhythm and responsiveness to incoming inputs. This finding reconciles different theories of slow rhythm generation and provides clues about how the brain switches from conscious to unconscious brain states.

Modeling cortical synaptic effects of anesthesia and their cholinergic reversal

General anesthetics work through a variety of molecular mechanisms while resulting in the common end point of sedation and loss of consciousness. Generally, the administration of common anesthetics induces reduction in synaptic excitation while promoting synaptic inhibition. Exogenous modulation of the anesthetics' synaptic effects can help determine the neuronal pathways involved in anesthesia. For example, both animal and human studies have shown that exogenously induced increases in acetylcholine in the brain can elicit wakeful-like behavior despite the continued presence of the anesthetic. However, the underlying mechanisms of anesthesia reversal at the cellular level have not been investigated. Here we apply a computational model of a network of excitatory and inhibitory neurons to simulate the network-wide effects of anesthesia, due to changes in synaptic inhibition and excitation, and their reversal by cholinergic activation through muscarinic receptors. We use a differential evolution algorithm to fit model parameters to match measures of spiking activity, neuronal connectivity, and network dynamics recorded in the visual cortex of rodents during anesthesia with desflurane in vivo. We find that facilitating muscarinic receptor effects of acetylcholine on top of anesthetic-induced synaptic changes predicts the reversal of anesthetic suppression of neurons' spiking activity, functional connectivity, as well as pairwise and population interactions. Thus, our model predicts a specific neuronal mechanism for the cholinergic reversal of anesthesia consistent with experimental behavioral observations.

GABAb- and GABAa- mediated regulation of Up and Down states across development

KEY POINTS

Slow oscillations (SOs), the EEG hallmark of non-REM sleep, and their cellular counterpart, Up-and-Down states (UDSs), are considered the default activity of the cerebral cortex and reflect the underlying neural connectivity. GABAb- and GABAa- receptor-mediated inhibition play a major role in regulating UDS activity. Although SOs and UDSs exhibit significant alterations as a function of age, it is unknown how developmental changes in inhibition contribute to the developmental profile of this activity. In this study, we reveal for the first time, age-dependent effects of GABAb and GABAa signalling on UDSs. We also document the differential subunit composition of postsynaptic GABAa receptors in young and adult animals, highlighting the α1-subunit as a major component of the age-differentiated regulation of UDSs. These findings help clarify the mechanisms that underlie the maturation of cortical network activity, and enhance our understanding regarding the emergence of neurodevelopmental disorders.

ABSTRACT

Slow oscillations, the hallmark of non-REM sleep, and their cellular counterpart, Up-and-Down states (UDSs), are considered a signature of cortical dynamics that reflect the intrinsic network organization. Although previous studies have explored the role of inhibition in regulating UDSs, little is known about whether this role changes with maturation. This is surprising since both slow oscillations and UDSs exhibit significant age-dependent alterations. To elucidate the developmental impact of GABAb and GABAa receptors on UDS activity, we conducted simultaneous LFP and intracellular recordings ex vivo, in brain slices of young and adult male mice, using selective blockers, CGP and non-saturating concentration of gabazine, respectively. Blockade of both GABAb- and GABAa- signalling showed age-differentiated functions. CGP caused an increase in Down state duration in young animals, but a decrease in adults. Gabazine evoked Spike-and-Wave-Discharges in both ages; however, while young networks became completely epileptic, adults maintained the ability to generate UDSs. Furthermore, voltage clamp recordings of mIPSCs revealed that gabazine selectively blocks phasic currents, particularly involving postsynaptic mechanisms. The latter exhibit clear maturational changes, suggesting a different subunit composition of GABAa receptors in young vs. adult animals. Indeed, subsequent LFP recordings under diazepam (nanomolar or micromolar concentrations) revealed that mechanisms engaging the drug's classical-binding-site, mediated by α1-subunit containing GABAa receptors, have a bigger contribution in Up state initiation in young networks compared to adults. Taken together, these findings help clarify the mechanisms that underlie the maturation of cortical network activity and enhance our understanding regarding the emergence of neurodevelopmental disorders. Abstract figure legend GABAb receptors' participation in Up state termination mechanisms is well-conserved across development. However, regulation of Down-to-Up transitions is age-dependent; GABAb receptors promote them in young while preventing them in adults. Up state maintenance is determined by age-dependent synaptic GABAa receptors' subunit composition and kinetics; α1-GABAa receptors dominate in young while non-α1-GABAa receptors dominate in adults. This article is protected by copyright. All rights reserved.

Keeping the Balance: GABAB Receptors in the Developing Brain and Beyond

The main neurotransmitter in the brain responsible for the inhibition of neuronal activity is γ-aminobutyric acid (GABA). It plays a crucial role in circuit formation during development, both via its primary effects as a neurotransmitter and also as a trophic factor. The GABA_B receptors (GABA_BRs) are G protein-coupled metabotropic receptors; on one hand, they can influence proliferation and migration; and, on the other, they can inhibit cells by modulating the function of K⁺ and Ca²⁺ channels, doing so on a slower time scale and with a longer-lasting effect compared to ionotropic GABA_A receptors. GABA_BRs are expressed pre- and post-synaptically, at both glutamatergic and GABAergic terminals, thus being able to shape neuronal activity, plasticity, and the balance between excitatory and inhibitory synaptic transmission in response to varying levels of extracellular GABA concentration. Furthermore, given their subunit composition and their ability to form complexes with several associated proteins, GABA_BRs display heterogeneity with regard to their function, which makes them a promising target for pharmacological interventions. This review will describe (i) the latest results concerning GABA_BRs/GABA_BR-complex structures, their function, and the developmental time course of their appearance and functional integration in the brain, (ii) their involvement in manifestation of various pathophysiological conditions, and (iii) the current status of preclinical and clinical studies involving GABA_BR-targeting drugs.

Linking Brain Structure, Activity, and Cognitive Function through Computation

Understanding the human brain is a “Grand Challenge” for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuroscience, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic principles and concepts interoperable, the Human Brain Project (HBP) has launched EBRAINS, a digital neuroscience research infrastructure, which brings together a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating insights and perspectives for societal benefits.

Spontaneous and Perturbational Complexity in Cortical Cultures

Dissociated cortical neurons in vitro display spontaneously synchronized, low-frequency firing patterns, which can resemble the slow wave oscillations characterizing sleep in vivo. Experiments in humans, rodents, and cortical slices have shown that awakening or the administration of activating neuromodulators decrease slow waves, while increasing the spatio-temporal complexity of responses to perturbations. In this study, we attempted to replicate those findings using in vitro cortical cultures coupled with micro-electrode arrays and chemically treated with carbachol (CCh), to modulate sleep-like activity and suppress slow oscillations. We adapted metrics such as neural complexity (NC) and the perturbational complexity index (PCI), typically employed in animal and human brain studies, to quantify complexity in simplified, unstructured networks, both during resting state and in response to electrical stimulation. After CCh administration, we found a decrease in the amplitude of the initial response and a marked enhancement of the complexity during spontaneous activity. Crucially, unlike in cortical slices and intact brains, PCI in cortical cultures displayed only a moderate increase. This dissociation suggests that PCI, a measure of the complexity of causal interactions, requires more than activating neuromodulation and that additional factors, such as an appropriate circuit architecture, may be necessary. Exploring more structured in vitro networks, characterized by the presence of strong lateral connections, recurrent excitation, and feedback loops, may thus help to identify the features that are more relevant to support causal complexity.

Computational Modeling of Information Propagation during the Sleep–Waking Cycle

Simple Summary

During the deep phases of sleep we do not normally wake up by a thunder, but we nevertheless notice it when awake. The exact same sound gets to our ears and cortex through the thalamus and still, it triggers two very different responses. There is growing experimental evidence that these two states of the brain—sleep and wakefulness—distribute sensory information in different ways across the cortex. In particular, during sleep, neuronal responses remain local and do not spread out across distant synaptically connected regions. On the contrary, during wakefulness, stimuli are able to elicit a wider spatial response. We have used a computational model of coupled cortical columns to study how these two propagation modes arise. Moreover, the transition from sleep-like to waking-like dynamics occurs in agreement with the synaptic homeostasis hypothesis and only requires the increase of excitatory conductances. We have found that, in order to reproduce the aforementioned observations, this parameter change has to be selectively applied: synaptic conductances between distinct columns have to be potentiated over local ones.

Abstract

Non-threatening familiar sounds can go unnoticed during sleep despite the fact that they enter our brain by exciting the auditory nerves. Extracellular cortical recordings in the primary auditory cortex of rodents show that an increase in firing rate in response to pure tones during deep phases of sleep is comparable to those evoked during wakefulness. This result challenges the hypothesis that during sleep cortical responses are weakened through thalamic gating. An alternative explanation comes from the observation that the spatiotemporal spread of the evoked activity by transcranial magnetic stimulation in humans is reduced during non-rapid eye movement (NREM) sleep as compared to the wider propagation to other cortical regions during wakefulness. Thus, cortical responses during NREM sleep remain local and the stimulus only reaches nearby neuronal populations. We aim at understanding how this behavior emerges in the brain as it spontaneously shifts between NREM sleep and wakefulness. To do so, we have used a computational neural-mass model to reproduce the dynamics of the sensory auditory cortex and corresponding local field potentials in these two brain states. Following the synaptic homeostasis hypothesis, an increase in a single parameter, namely the excitatory conductance g¯AMPA, allows us to place the model from NREM sleep into wakefulness. In agreement with the experimental results, the endogenous dynamics during NREM sleep produces a comparable, even higher, response to excitatory inputs to the ones during wakefulness. We have extended the model to two bidirectionally connected cortical columns and have quantified the propagation of an excitatory input as a function of their coupling. We have found that the general increase in all conductances of the cortical excitatory synapses that drive the system from NREM sleep to wakefulness does not boost the effective connectivity between cortical columns. Instead, it is the inter-/intra-conductance ratio of cortical excitatory synapses that should raise to facilitate information propagation across the brain.

Theta-Burst Stimulation of Forearm Muscles in Patients With Complex Regional Pain Syndrome: Influence on Brain and Clinical Outcomes

Objective: Complex regional pain syndrome (CRPS) is a common pain condition characterized by the changes in the brain that are not yet addressed by conventional treatment regimens. Repetitive peripheral magnetic stimulation (rPMS) of muscles is painless and non-invasive and can influence these changes (the induction of brain plasticity) to reduce pain and improve motricity. In patients with CRPS, this open-label pilot study tested rPMS after-effects on the pain intensity and sensorimotor control of the upper limb along with the excitability changes of the primary motor cortex (M1).

Methods: Eight patients with CRPS were enrolled in a single-session program. Patients were tested at pre- and post-rPMS over the flexor digitorum superficialis (FDS) muscle. The clinical outcomes were pain intensity, proprioception, active range of motion (ROM), and grip strength. M1 excitability was tested using the single- and paired-pulse transcranial magnetic stimulation (TMS) of M1.

Results: In our small sample study, rPMS reduced instant and week pain, improved proprioception and ROM, and reduced the hemispheric imbalance of several TMS outcomes. The more M1 contralateral to the CRPS side was hyperactivated at baseline, the more pain was reduced.

Discussion: This open-label pilot study provided promising findings for the use of rPMS in CRPS with a focus on M1 plastic changes. Future randomized, placebo-controlled clinical trials should confirm the existence of a causal relationship between the TMS outcomes and post-rPMS decrease of pain. This will favor the development of personalized treatments of peripheral non-invasive neurostimulation in CRPS.