Inhibitory Coupling Research Articles

Selective tracking of FFAR3-expressing neurons supports receptor coupling to N-type calcium channels in mouse sympathetic neurons

Activation of short-chain free fatty acid receptors 3 (FFAR3) has been suggested to promote sympathetic outflow in postganglionic sympathetic neurons or hamper it by a negative coupling to N-type calcium (CaV2.2) channels. Heterogeneity of FFAR3 expression in sympathetic neurons, however, renders single neurons studies extremely time-consuming in wild-type mice. Previous studies demonstrated large variability of the degree of CaV2.2 channel inhibition by FFAR3 in a global population of rat sympathetic neurons. Therefore, we focused on a small subpopulation of mouse sympathetic neurons using an FFAR3 antibody and an Ffar3 reporter mouse to perform immunofluorescent and electrophysiological studies. Whole-cell patch-clamp recordings of identified FFAR3-expressing neurons from reporter mice revealed a 2.5-fold decrease in the CaV2.2-FFAR3 inhibitory coupling variability and 1.5-fold increase in the mean ICa2+ inhibition, when compared with unlabeled neurons from wild-type mice. Further, we found that the ablation of Ffar3 gene expression in two knockout mouse models led to a complete loss-of-function. Subpopulations of sympathetic neurons are associated with discrete functional pathways. However, little is known about the neural pathways of the FFAR3-expressing subpopulation. Our data indicate that FFAR3 is expressed primarily in neurons with a vasoconstrictor phenotype. Thus, fine-tuning of chemically-coded neurotransmitters may accomplish an adequate outcome.

Rhythmic control of oscillatory sequential dynamics in heteroclinic motifs

Cognitive/behavioral brain functions are implemented through temporary correlated sequential activity of many brain elements that form universal anatomical and functional motifs, i.e., characteristic functional interactions among brain nodes, at different levels of the neural hierarchy. Such motif dynamics is determined by both the interconnections among nodes and their intrinsic oscillations. This paper focuses on heteroclinic motifs, i.e., those built in networks of oscillatory nodes that interact through asymmetric inhibitory coupling in a winnerless competitive way. We introduce a basic rate-phase motif model – based on a generalization of the well-known ecological Lotka–Volterra model – for the analysis and prediction of control processes that emerge in interacting heteroclinic motifs under periodic stimulation. This approach describes both intensity and phase in each node. We study how a rhythmic signal, which can be linked to internal or external sources, can functionally change the heteroclinic network and produce a rich gallery of motifs in the form of coordinated sequential activations. In computer simulations of the model in a “master-slave” approximation, we report phenomena such as dynamical filtering, encoding enhancement and transition to chaos. Our results are relevant in the context of several experimental protocols related to the role of brain rhythms and/or the use of external rhythmic stimulation, in particular in the context of transcranial control and evoked potentials, to assess cognitive functions and their associated pathologies.

Dynamics of a large system of spiking neurons with synaptic delay

We analyze a large system of heterogeneous quadratic integrate-and-fire (QIF) neurons with time delayed, all-to-all synaptic coupling. The model is exactly reduced to a system of firing rate equations that is exploited to investigate the existence, stability and bifurcations of fully synchronous, partially synchronous, and incoherent states. In conjunction with this analysis we perform extensive numerical simulations of the original network of QIF neurons, and determine the relation between the macroscopic and microscopic states for partially synchronous states. The results are summarized in two phase diagrams, for homogeneous and heterogeneous populations, which are obtained analytically to a large extent. For excitatory coupling, the phase diagram is remarkably similar to that of the Kuramoto model with time delays, although here the stability boundaries extend to regions in parameter space where the neurons are not self-sustained oscillators. In contrast, the structure of the boundaries for inhibitory coupling is different, and already for homogeneous networks unveils the presence of various partially synchronized states not present in the Kuramoto model: Collective chaos, quasiperiodic partial synchronization (QPS), and a novel state which we call modulated-QPS (M-QPS). In the presence of heterogeneity partially synchronized states reminiscent to collective chaos, QPS and M-QPS persist. In addition, the presence of heterogeneity greatly amplifies the differences between the incoherence stability boundaries of excitation and inhibition. Finally, we compare our results with those of a traditional (Wilson Cowan-type) firing rate model with time delays. The oscillatory instabilities of the traditional firing rate model qualitatively agree with our results only for the case of inhibitory coupling with strong heterogeneity.

Frequency locking and travelling burst sequences in community structured network of inhibitory neurons with differing time-scales

We report the emergent dynamics of a community structured modular network of chaotic Hindmarsh-Rose (HR) neurons with inhibitory synapses. We find the inhibitory coupling between the neuronal modules lead to complete synchronization of neurons in a module, and also pushes modules into interesting sequences of travelling burst patterns. When dynamical time-scales vary for neurons in different modules, hence breaking the symmetry among them, we see specific sequences of travelling burst patterns that are characteristic of the time-scale mismatch and coupling strengths. Thus for a modular network with two time-scales, the neuronal communities enter into synchronized frequency locked clusters with the bursting sequences having recurring patterns. Our study provides a complete characterization of the spatio-temporal regularity in terms of frequency locking for temporal order and burst sequence patterns for spatial order in the collective dynamics of the neuronal clusters. Our results have significance in the process of information coding in terms of frequency of firing dynamics among neurons and in selective communication based on the sequences of bursts.

Spatial patterns in a network composed of neurons with different excitabilities induced by autapse

It has been identified that autapse can modulate dynamics of single neurons and spatial patterns of neuronal networks. In the present paper, based on the results that autapse can induce type II excitability changed to type I excitability, spatial pattern transitions are simulated in a two-dimensional neuronal network composed of excitatory coupled neurons with autapse which can induce excitability transition. Different spatial patterns including random-like pattern, irregular wave, regular wave, and nearly synchronous behavior are simulated with increasing the percentage (σ) of neurons with type I excitability. When noise is introduced, spiral waves are induced. By calculating signal-to-noise ratio from the spatial structure function and the mean firing probability of neurons, regular waves and spiral waves exhibit optimal spatial correlation, implying the occurrence of spatial coherence resonance phenomenon. The changes of mean firing probability of neurons show that different firing frequency between type I excitability and type II excitability may be an important factor to modulate the spatial patterns. The results are helpful to understand the spatial patterns including spiral waves observed in the biological experiment on the rat cortex perfused with drugs which can induce single neurons changed from type II excitability to type I excitability and block the inhibitory couplings between neurons. The excitability transition, absence of inhibitory coupling, noise as well as the autapse are important factors to modulate the spatial patterns including spiral waves.

Inhibitory Connectivity Dominates the Fan Cell Network in Layer II of Lateral Entorhinal Cortex.

Fan cells in layer II of the lateral entorhinal cortex (LEC) form a main component of the projection to the dentate gyrus, CA3 and CA2 of the hippocampal formation. This projection has a counterpart originating from stellate cells in layer II of the medial entorhinal cortex (MEC). Available evidence suggests that the two pathways carry different information, exemplified by a difference in spatial tuning of cells in LEC and MEC. The grid cell, a prominent position-modulated cell type present in MEC, has been postulated to derive its characteristic hexagonal firing pattern from dominant disynaptic inhibitory connections between hippocampal-projecting stellate cells. Given that grid cells have not been described in LEC, we aim to describe the local synaptic connectivity of fan cells, to explore whether the network architecture is similar to that of the MEC stellate cell. Using a combination of in vitro multicell electrophysiological and optogenetic approaches in acute slices from rodents of either sex, we show that excitatory connectivity between fan cells is very sparse. Fan cells connect preferentially with two distinct types of inhibitory interneurons, suggesting disynaptic inhibitory coupling as the main form of communication among fan cells. These principles are similar to those reported for stellate cells in MEC, indicating an overall comparable local circuit architecture of the main hippocampal-projecting cell types in the lateral and medial entorhinal cortex.SIGNIFICANCE STATEMENT Our data provide the first description of the synaptic microcircuit of hippocampal-projecting layer II cells in the lateral entorhinal cortex. We show that these cells make infrequent monosynaptic connections with each other, and that they preferentially communicate through a disynaptic inhibitory network. This is similar to the microcircuit of hippocampal-projecting stellate cells in layer II of the medial entorhinal cortex, but dissimilar to the connectivity observed in layer 2 of neocortex. In medial entorhinal cortex, the observed network structure has been proposed to underlie the firing pattern of grid cells. This opens the possibility that layer II cells in lateral entorhinal cortex exhibit regular firing patterns in an unexplored domain.

Transition Dynamics of Epileptic Seizures in the Coupled Thalamocortical Network Model

In this paper, based on the two-compartment unidirectionally coupled thalamocortical model network, we investigated the transition dynamics of epileptic seizures, by considering the inhibitory coupling strength from cortical inhibitory interneuronal (IN) population to excitatory pyramidal (PY) neuronal population as the key bifurcation parameter. The results show that in the single compartment thalamocortical model, inner-compartment inhibitory functions of IN can make the system transit from the absence seizures to the tonic oscillations. In the case of two-compartment coupled thalamocortical model network, the inter-compartment inhibitory coupling functions from the first compartment can drive the second compartment to more easily initiate the absence and tonic seizures at the lower inhibitory coupling strengths, respectively. Also, the driven functions can make the amplitudes of these seizures vary irregularly. Detailed investigations reveal that along with the various state transitions, the system consecutively undergoes Hopf bifurcations, fold of cycles bifurcations and torus bifurcations, respectively. In particular, the reinforcing inter-compartment inhibitory coupling function can induce the chaotic dynamics. We highlight the unidirectional coupling functions between two compartments which might give new insights into the propagation and evolution dynamics of epileptic seizures.

Chaos in small networks of theta neurons.

We consider small networks of instantaneously coupled theta neurons. For inhibitory coupling and fixed parameter values, some initial conditions give chaotic solutions while others give quasiperiodic ones. This behaviour seems to result from the reversibility of the equations governing the networks' dynamics. We investigate the robustness of the chaotic behaviour with respect to changes in initial conditions and parameters and find the behaviour to be quite robust as long as the reversibility of the system is preserved.

Dragon-king-like extreme events in coupled bursting neurons.

We present evidence of extreme events in two Hindmarsh-Rose (HR) bursting neurons mutually interacting via two different coupling configurations: chemical synaptic- and gap junctional-type diffusive coupling. A dragon-king-like probability distribution of the extreme events is seen for combinations of synaptic coupling where small- to medium-size events obey a power law and the larger events that cross an extreme limit are outliers. The extreme events originate due to instability in antiphase synchronization of the coupled systems via two different routes, intermittency and quasiperiodicity routes to complex dynamics for purely excitatory and inhibitory chemical synaptic coupling, respectively. For a mixed type of inhibitory and excitatory chemical synaptic interactions, the intermittency route to extreme events is only seen. Extreme events with our suggested distribution is also seen for gap junctional-type diffusive, but repulsive, coupling where the intermittency route to complexity is found. A simple electronic experiment using two diffusively coupled analog circuits of the HR neuron model, but interacting in a repulsive way, confirms occurrence of the dragon-king-like extreme events.

Age-related Decline of Visual Working Memory: Behavioral Results Simulated with a Dynamic Neural Field Model.

Visual working memory (VWM) is essential for executive function and is known to be compromised in older adults. Yet, the cognitive and neural processes associated with these age-related changes remain inconclusive. The purpose of this study was to explore such factors with a dynamic neural field (DNF) model that was manipulated to replicate the behavioral performances of younger and older adults in a change detection task. Although previous work has successfully modeled children and younger adult VWM performance, this study represents the first attempt to model older adult VWM performance within the DNF architecture. In the behavioral task, older adults performed worse than younger adults and exhibited a characteristic response bias that favored "same" over "different" responses. The DNF model was modified to capture the age group differences, with three parameter manipulations producing the best fit for the behavioral performances. The best-fitting model suggests that older adults operate through altered excitatory and inhibitory coupling and decreased inhibitory signals, resulting in wider and weaker neural signals. These results support a dedifferentiation account of brain aging, with older adults operating with wider and weaker neural signals because of decreased intracortical inhibition rather than increased stochastic neural noise.

Synchronous high-frequency oscillations in inhibitory-dominant network motifs consisting of three dentate gyrus-CA3 systems.

Studies on the structural-functional connectomes of the human brain have demonstrated the existence of synchronous firings in a specific brain network motif. In particular, synchronization of high-frequency oscillations (HFOs) has been observed in the experimental data sets of temporal lobe epilepsy (TLE). In addition, both clinical and experimental evidences have accumulated to demonstrate the effect of electrical stimulation on TLE, which, however, remains largely unexplored. In this work, we first employ our previously proposed dentate gyrus (DG)-CA3 network model to investigate the influence of an external electrical stimulus on the HFO transitions. The results indicate that the reinforcing stimulus can induce the HFO transitions of the DG-CA3 system from the gamma band to the fast ripples band. Along with that, the consistent oscillations of neurons within DG-CA3 can also be enhanced with the increasing of stimulus. Then, we expand into a simple motif of three coupled DG-CA3 systems in both the feedforward inhibition and feedback inhibition connections, to investigate the synchronous evolutions of HFOs by regulating both the stimulation strength and inhibitory function. It is shown that the comprehensive effects, which lead to band transition, are independent of the motif configurations. The enhanced external electrical stimulus weakens the synchronism and correlation of connected motifs. In contrast, we demonstrate that the increased inhibitory coupling could facilitate correlation to some extent. Overall, our work highlights the possible origin of synchronous HFOs of hippocampal motifs governed by external inputs and inhibitory connection, which might contribute to a better understanding of the interplay between synchronization dynamics and epileptic structure in the human brain.

Fenfluramine diminishes NMDA receptor-mediated seizures via its mixed activity at serotonin 5HT2A and type 1 sigma receptors.

Fenfluramine exhibits antiepileptic properties and thus diminishes epileptiform discharges in experimental animal models of Dravet syndrome. Fenfluramine is metabolized into norfenfluramine in vivo, which shows greater affinity and agonist activity at serotonin 5HT2 receptors (5HT2R) than fenfluramine. In this study, we found that fenfluramine and norfenfluramine disrupted the regulatory association of the sigma 1 receptor (σ1R) with NR1 subunits of glutamate N-methyl-D-aspartate receptors (NMDAR), an effect that was also produced by σ1R antagonists such as S1RA and prevented by σ1R agonists such as PPCC. The antagonists removed σ1R bound to NMDAR NR1 subunits enabling calcium-regulated calmodulin (CaM) to bind to those subunits. As a result, CaM may inhibit calcium permeation through NMDARs. The serotoninergic activity of fenfluramine at 5HT2AR, and likely also at 5HT2CR, collaborated with its activity at σ1Rs to prevent the convulsive syndrome promoted by NMDAR overactivation. Notably, fenfluramine enhanced the inhibitory coupling of G protein-coupled receptors such as 5HT1AR and cannabinoid type 1 receptor with NMDARs, thus allowing the more effective restrain of NMDAR activity. Thus, fenfluramine circumvents the negative side effects of direct NMDAR antagonists and may improve the quality of life of subjects affected by such proconvulsant dysfunctions.

Synchronization by uncorrelated noise: interacting rhythms in interconnected oscillator networks

Oscillators coupled in a network can synchronize with each other to yield a coherent population rhythm. How do multiple such rhythms interact with each other? Do these collective oscillations synchronize like individual oscillators? We show that this is not the case: for strong, inhibitory coupling rhythms can become synchronized by noise. In contrast to stochastic synchronization, this new mechanism synchronizes the rhythms even if the noisy inputs to different oscillators are completely uncorrelated. Key for the synchrony across networks is the reduced synchrony within the networks: it substantially increases the frequency range across which the networks can be entrained by other networks or by periodic pacemaker-like inputs. We demonstrate this type of robust synchronization for different classes of oscillators and network connectivities. The synchronization of different population rhythms is expected to be relevant for brain rhythms.

Dynamics of transitions from anti-phase to multiple in-phase synchronizations in inhibitory coupled bursting neurons

Transition from anti-phase to in-phase synchronizations in inhibitory coupled bursting neurons is very important for locomotor rhythms of animals. Here, multiple in-phase (complete), anti-phase, and phase synchronous bursting patterns are simulated in inhibitory coupled map-based model neurons with bursting patterns, and synchronization transitions between these patterns are simulated in a two-dimensional parameter space of the coupling strength and time delay. Time delay-induced transition from anti-phase to in-phase synchronous bursting behaviors matches those observed in a biological experiment on the inhibitory coupled neurons in the stomatogastric ganglion of lobster. Furthermore, bursting patterns of the in-phase (complete) synchronous behaviors can be well interpreted with the dynamic responses of an isolated single neuron to a negative square current whose action time, duration, and strength are similar to those of the inhibitory coupling current modulated by the coupling strength and time delay. The burst of the synchronous behaviors manifests the same pattern as the square negative current-induced burst of the isolated single neuron, which is acquired with the fast–slow variable dissection method. The results not only present novel nonlinear phenomenon of the time delay-induced multiple synchronous behaviors and synchronization transitions, but also provide a reasonable interpretation with the different dynamic responses of map-based bursting model neuron to an external inhibitory stimulus applied at different phases.

Autonomous cycling between excitatory and inhibitory coupling in photosensitive chemical oscillators

Photochemically coupled Belousov-Zhabotinsky micro-oscillators are studied in experiments and simulations. The photosensitive oscillators exhibit excitatory or inhibitory coupling depending on the surrounding reaction mixture composition, which can be systematically varied. In-phase or out-of-phase synchronization is observed with predominantly excitatory or inhibitory coupling, respectively, and complex frequency cycling between excitatory and inhibitory coupling is found between these extremes. The dynamical behavior is characterized in terms of the corresponding phase response curves, and a map representation of the dynamics is presented.

Pulse-coupled Belousov-Zhabotinsky oscillators with frequency modulation

Inhibitory perturbations to the ferroin-catalyzed Belousov-Zhabotinsky (BZ) chemical oscillator operated in a continuously fed stirred tank reactor cause long term changes to the limit cycle: the lengths of the cycles subsequent to the perturbation are longer than that of the unperturbed cycle, and the unperturbed limit cycle is recovered only after several cycles. The frequency of the BZ reaction strongly depends on the acid concentration of the medium. By adding strong acid or base to the perturbing solutions, the magnitude and the direction of the frequency changes concomitant to excitatory or inhibitory perturbations can be controlled independently of the coupling strength. The dynamics of two BZ oscillators coupled through perturbations carrying a coupling agent (activator or inhibitor) and a frequency modulator (strong acid or base) was explored using a numerical model of the system. Here, we report new complex temporal patterns: higher order, partially synchronized modes that develop when inhibitory coupling is combined with positive frequency modulation (FM), and complex bursting patterns when excitatory coupling is combined with negative FM. The role of time delay between the peak and perturbation (the analog of synaptic delays in networks of neurons) has also been studied. The complex patterns found under inhibitory coupling and positive FM vanish when the delay is significant, whereas a sufficiently long time delay is required for the complex temporal dynamics to occur when coupling is excitatory and FM is negative.

Optimized inhibited-coupling Kagome fibers at Yb-Nd:Yag (8.5 dB/km) and Ti:Sa (30 dB/km) ranges.

We report on the development of hypocycloid core-contour inhibited-coupling (IC) Kagome hollow-core photonic crystal fibers (HC-PCFs) with record transmission loss and spectral coverage that include the common industrial laser wavelengths. Using the scaling of the confinement loss with the core-contour negative curvature and the silica strut thickness, we fabricated an IC Kagome HC-PCF for Yb and Nd:Yag laser guidance with record loss level of 8.5dB/km associated with a 225-nm-wide 3-dB bandwidth. A second HC-PCF is fabricated with reduced silica strut thickness while keeping the hypocycloid core contour. It exhibits a fundamental transmission window spanning down to the Ti:Sa spectral range and a loss figure of 30dB/km at 750nm. The fibers' modal properties and bending sensitivity show these HC-PCFs to be ideal for ultralow-loss, flexible, and robust laser beam delivery.

Dynamic modes in a network of five oscillators with inhibitory all-to-all pulse coupling.

The dynamic modes of five almost identical oscillators with pulsatile inhibitory coupling with time delay have been studied theoretically. The models of the Belousov-Zhabotinsky reaction and phase oscillators with all-to-all coupling have been considered. In the parametric plane Cinh-τ, where Cinh is the coupling strength and τ is the time delay between a spike in one oscillator and pulsed perturbations of all other oscillators, three main regimes have been found: regular modes, when each oscillator gives only one spike during the global period T, C (complex) modes, when the number of pulses of different oscillators is different, and OS (oscillations-suppression) modes, when at least one oscillator is suppressed. The regular modes consist of several cluster modes and are found at relatively small Cinh. The C and OS modes observed at larger Cinh intertwine in the Cinh-τ plane. In a relatively narrow range of Cinh, the dynamics of the C modes are very sensitive to small changes in Cinh and τ, as well as to the initial conditions, which are the characteristic features of the chaos. On the other hand, the dynamics of the C modes are periodic (but with different periods) and well reproducible. The number of different C modes is enormously large. At still larger Cinh, the C modes lose sensitivity to small changes in the parameters and finally vanish, while the OS modes survive.

Dynamics of a 1D array of inhibitory coupled chemical oscillators in microdroplets with global negative feedback.

We have investigated the effect of global negative feedback (GNF) on the dynamics of a 1D array of water microdroplets (MDs) filled with the reagents of the photosensitive oscillatory Belousov-Zhabotinsky (BZ) reaction. GNF is established by homogeneous illumination of the 1D array with the light intensity proportional to the number of BZ droplets in the oxidized state with the coefficient of proportionality ge. MDs are immersed in the continuous oil phase and diffusively coupled with the neighboring droplets via inhibitor Br2 which is soluble in the oil phase. At chosen concentrations of the BZ reactants, illumination suppresses the BZ oscillators. Without GNF, or at a very small ge < 0.29, local inhibitory coupling leads to out-of-phase oscillations of the neighboring BZ droplets with an almost constant phase shift Δφ between them, which makes a space-time plot of the BZ MDs look like a staircase. At 0.3 < ge < 0.6, regular oscillatory clusters consisting of distant BZ MDs (mostly 5-6 phase clusters) emerge. At 0.6 ≤ ge ≤ 1.0, chaotic clusters are observed. At 1.2 < ge < 1.8, regular (mostly 3-4-phase) clusters emerge again. At 1.8 < ge < (3-4), complex clusters with different (but multiple) periods of oscillation are observed. At the same time, some droplets stop oscillating. At large enough ge (>4), in the region of two-phase clusters (with several suppressed BZ MDs), final patterns seem to resemble the initial patterns. Intensive computer simulations with the ordinary differential equations support experimental results.

Spontaneous formation of ordered waves in chaotic neuronal network with excitory-inhibitory connections

Spiral waves are a particular form of propagating waves, which rotate around a center point known as a rotor. Spiral waves have been found to play an important role in cardiac arrhythmia. Using voltage-sensitive dye imaging, one can find that spiral waves and plannar waves can occur in the mammalian cortex in vivo. The electrode array conduces to discovering that the seizures may manifest as recurrent spiral waves which propagate in the neocortex. However, the formation mechanism of the ordered waves and its potential function in the nervous system remain uncertain. In order to understand the formation mechanism of the ordered waves, we construct a double-layer two-dimensional -network of neuron, which is composed of nearest-neighbor excitatory coupling and long-range inhibitory coupling layers. The inhibitory grid points account for 25% of total number of grid points in the network. We propose a modified Hindmarsh-Rose neuron model to study whether differently ordered waves can occur spontaneously in the chaotic neuronal network evolving from the initial state with a random phase distribution. The numerical simulation results show that when the inhibitory coupling strength is small the spontaneous formation of ordered wave does not generally appear in the network. The larger inhibitory coupling strength, the more easily the system generates an ordered wave for sufficiently large strength of excitatory coupling. The appearance of differently ordered waves is closely related to the initial state of the system and coupling strength. As the excitatory and inhibitory coupling strengths are appropriately selected, the system can spontaneously generate the maze pattern, planar wave, single spiral wave, multiple spiral wave, paired spiral waves rotating in the opposite directions, two-arm spiral wave, target wave and inward square wave and so on. The probability for spontaneously forming a single spiral wave is far less than that for forming a small spiral wave. The occurrence probabilities of spiral wave, maze pattern and inward square wave reach 27.5%, 21.5% and 10%, respectively. The maze pattern is composed of many plane waves with different propagation directions. The occurrence probabilities of other ordered waves are quite small. These results conduce to understanding the self-organization phenomena occurring in the cerebral cortex.