Enhancement of Spike-Timing Precision by Autaptic Transmission in Neocortical Inhibitory Interneurons

Dynamics and conditions for inhibitory synaptic current to induce bursting and spreading depolarization in pyramidal neurons

Enhanced activity of inhibitory neurons, which is often used to suppress behaviors of pyramidal neurons to treat brain diseases, whereas can enhance spiking to a mixed-mode bursting (MMB) in recent experiments on migraine and seizure. The MMB contains a phase with high level of membrane potential/extracellular potassium concentration ([K+]o), which can propagate to form spreading depolarization (SD) wave. Different from the common view that the MMB/SD is often induced by enhanced positive effect or [K+]o, in the present paper, dynamics and conditions for the uncommon MMB/SD evoked by enhanced inhibitory synaptic current are obtained in a theoretical model. Firstly, in addition to the well-known positive threshold across which the common MMB is induced by positive effect, a spiking pyramidal neuron exhibits a novel negative threshold with a low level of [K+]o for the MMB. A long and strong inhibitory stimulation suppresses the spiking to silence phase via a saddle-node bifurcation on an invariant circle at first and then run across the negative threshold, triggering positive feedback to enhance membrane potential and [K+]o to levels high enough, then resulting in the uncommon MMB. Secondly, in a coupling model, enhanced inhibitory effect for enhanced spiking activity of interneuron and conductance of inhibitory synapse, and enhanced spiking activity of pyramidal neuron, are favorable for the uncommon MMB. Then, reducing these activities or parameters present potential measures to prevent the MMB. Finally, in network model, the uncommon MMB of a pyramidal neuron can induce SD wave. The results present a novel theoretical explanation to the uncommon MMB/SD, counterintuitive function of the inhibitory interneuron, and potential measures to treat the diseases.

Biologically inspired heterogeneous learning for accurate, efficient and low-latency neural network

The pursuit of artificial neural networks that mirror the accuracy, efficiency and low latency of biological neural networks remains a cornerstone of artificial intelligence (AI) research. Here, we incorporated recent neuroscientific findings of self-inhibiting autapse and neuron heterogeneity for innovating a spiking neural network (SNN) with enhanced learning and memorizing capacities. A bi-level programming paradigm was formulated to respectively learn neuron-level biophysical variables and network-level synapse weights for nested heterogeneous learning. We successfully demonstrated that our biologically inspired neuron model could reproduce neural statistics at both individual and group levels, contributing to the effective decoding of brain-computer interface data. Furthermore, the heterogeneous SNN showed higher accuracy (1%-10% improvement), superior efficiency (maximal 17.83-fold reduction in energy) and lower latency (maximal 5-fold improvement) in performing several AI tasks. For the first time, we benchmarked SNN for conducting cell type identification from scRNA-seq data. The proposed model correctly identified very rare cell types associated with severe brain diseases where typical SNNs failed.

A dendritic substrate for temporal diversity of cortical inhibition

In the mammalian neocortex, GABAergic interneurons (INs) inhibit cortical networks in profoundly different ways. The extent to which this depends on how different INs process excitatory signals along their dendrites is poorly understood. Here, we reveal that the functional specialization of two major populations of cortical INs is determined by the unique association of different dendritic integration modes with distinct synaptic organization motifs. We found that somatostatin (SST)-INs exhibit NMDAR-dependent dendritic integration and uniform synapse density along the dendritic tree. In contrast, dendrites of parvalbumin (PV)-INs exhibit passive synaptic integration coupled with proximally enriched synaptic distributions. Theoretical analysis shows that these two dendritic configurations result in different strategies to optimize synaptic efficacy in thin dendritic structures. Yet, the two configurations lead to distinct temporal engagement of each IN during network activity. We confirmed these predictions with in vivo recordings of IN activity in the visual cortex of awake mice, revealing a rapid and linear recruitment of PV-INs as opposed to a long-lasting integrative activation of SST-INs. Our work reveals the existence of distinct dendritic strategies that confer distinct temporal representations for the two major classes of neocortical INs and thus dynamics of inhibition.

intensity- and frequency-specific effects of transcranial alternating current stimulation are explained by network dynamics

Objective. Transcranial alternating current stimulation (tACS) can be used to non-invasively entrain neural activity and thereby cause changes in local neural oscillatory power. Despite its increased use in cognitive and clinical neuroscience, the fundamental mechanisms of tACS are still not fully understood.Approach. We developed a computational neuronal network model of two-compartment pyramidal neurons (PY) and inhibitory interneurons, which mimic the local cortical circuits. We modeled tACS with electric field strengths that are achievable in human applications. We then simulated intrinsic network activity and measured neural entrainment to investigate how tACS modulates ongoing endogenous oscillations.Main results. The intensity-specific effects of tACS are non-linear. At low intensities (<0.3 mV mm-1), tACS desynchronizes neural firing relative to the endogenous oscillations. At higher intensities (>0.3 mV mm-1), neurons are entrained to the exogenous electric field. We then further explore the stimulation parameter space and find that the entrainment of ongoing cortical oscillations also depends on stimulation frequency by following an Arnold tongue. Moreover, neuronal networks can amplify the tACS-induced entrainment via synaptic coupling and network effects. Our model shows that PY are directly entrained by the exogenous electric field and drive the inhibitory neurons.Significance. The results presented in this study provide a mechanistic framework for understanding the intensity- and frequency-specific effects of oscillating electric fields on neuronal networks. This is crucial for rational parameter selection for tACS in cognitive studies and clinical applications.

Characterizing the role of autaptic feedback in enhancing precision of neuronal firing times

In a chemical synapse, information flow occurs via the release of neurotransmitters from a presynaptic neuron that triggers an Action potential (AP) in the postsynaptic neuron. At its core, this occurs via the postsynaptic membrane potential integrating neurotransmitter-induced synaptic currents, and AP generation occurs when potential reaches a critical threshold. This manuscript investigates feedback implementation via an autapse, where the axon from the postsynaptic neuron forms an inhibitory synapse onto itself. Using a stochastic model of neuronal synaptic transmission, we formulate AP generation as a first-passage time problem and derive expressions for both the mean and noise of AP-firing times. Our analytical results supported by stochastic simulations identify parameter regimes where autaptic feedback transmission enhances the precision of AP firing times consistent with experimental data. These noise attenuating regimes are intuitively based on two orthogonal mechanisms - either expanding the time window to integrate noisy upstream signals; or by linearizing the mean voltage increase over time. Interestingly, we find regimes for noise amplification that specifically occur when the inhibitory synapse has a low probability of release for synaptic vesicles. In summary, this work explores feedback modulation of the stochastic dynamics of autaptic neurotransmission and reveals its function of creating more regular AP firing patterns.

Influence of inhibitory autapses on synchronization of inhibitory network gamma oscillations

A recent experimental study showed that inhibitory autapses favor firing synchronization of parvalbumin interneurons in the neocortex during gamma oscillations. In the present paper, to provide a comprehensive and deep understanding to the experimental observation, the influence of inhibitory autapses on synchronization of interneuronal network gamma oscillations is theoretically investigated. Weak, middle, and strong synchronizations of a globally inhibitory coupled network composed of Wang-Buzsáki model without autapses appear at the bottom-left, middle, and top-right of the parameter plane with the conductance (gsyn) and the decay constant (τsyn) of inhibitory synapses taken as the x-axis and y-axis, respectively. After introducing inhibitory autapses, the border between the strong and middle synchronizations in the (gsyn, τsyn) plane moves to the top-right with increasing the conductance (gaut) and the decay constant (τaut) of autapses, due to that interspike interval of the single neuron becomes longer, leading to that larger τsyn is needed to ensure the strong synchronization. Then, the synchronization degree of middle and strong synchronizations around the border in the (gsyn, τsyn) plane decreases, while of strong synchronization in the remaining region remains unchanged. The synchronization degree of weak synchronization increases with increasing τaut and gaut, due to that the inhibitory autaptic current becomes strong and long to facilitate synchronization. The enhancement of weak synchronization modulated by inhibitory autapses is also simulated in the random, small-world, and scale-free networks, which may provide explanations to the experimental observation. These results present complex dynamics of synchronization modulated by inhibitory autapses, which needs future experimental demonstrations.

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.

Functional Autapses Form in Striatal Parvalbumin Interneurons but not Medium Spiny Projection Neurons

Autapses selectively form in specific cell types in many brain regions. Previous studies have also found putative autapses in principal spiny projection neurons (SPNs) in the striatum. However, it remains unclear whether these neurons indeed form physiologically functional autapses. We applied whole-cell recording in striatal slices and identified autaptic cells by the occurrence of prolonged asynchronous release (AR) of neurotransmitters after bursts of high-frequency action potentials (APs). Surprisingly, we found no autaptic AR in SPNs, even in the presence of Sr2+. However, robust autaptic AR was recorded in parvalbumin (PV)-expressing neurons. The autaptic responses were mediated by GABAA receptors and their strength was dependent on AP frequency and number. Further computer simulations suggest that autapses regulate spiking activity in PV cells by providing self-inhibition and thus shape network oscillations. Together, our results indicate that PV neurons, but not SPNs, form functional autapses, which may play important roles in striatal functions.

Error correction and improved precision of spike timing in converging cortical networks

The brain propagates neuronal signals accurately and rapidly. Nevertheless, whether and how a pool of cortical neurons transmits an undistorted message to a target remains unclear. We apply optogenetic white noise signals to small assemblies of cortical pyramidal cells (PYRs) in freely moving mice. The directly activated PYRs exhibit a spike timing precision of several milliseconds. Instead of losing precision, interneurons driven via synaptic activation exhibit higher precision with respect to the white noise signal. Compared with directly activated PYRs, postsynaptic interneuron spike trains allow better signal reconstruction, demonstrating error correction. Data-driven modeling shows that nonlinear amplification of coincident spikes can generate error correction and improved precision. Over multiple applications of the same signal, postsynaptic interneuron spiking is most reliable at timescales ten times shorter than those of the presynaptic PYR, exhibiting temporal coding. Similar results are observed in hippocampal region CA1. Coincidence detection of convergent inputs enables messages to be precisely propagated between cortical PYRs and interneurons.

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PYR-to-interneuron spike transmission exhibits error correction and improved precision

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Interneuron precision is higher when a larger pool of presynaptic PYRs is recruited

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Error correction and improved precision are consistent with coincidence detection

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Interneurons activated by synaptic transmission act as temporal coders

Interlayer Connectivity Affects the Coherence Resonance and Population Activity Patterns in Two-Layered Networks of Excitatory and Inhibitory Neurons

The firing patterns of neuronal populations often exhibit emergent collective oscillations, which can display substantial regularity even though the dynamics of individual elements is very stochastic. One of the many phenomena that is often studied in this context is coherence resonance, where additional noise leads to improved regularity of spiking activity in neurons. In this work, we investigate how the coherence resonance phenomenon manifests itself in populations of excitatory and inhibitory neurons. In our simulations, we use the coupled FitzHugh-Nagumo oscillators in the excitable regime and in the presence of neuronal noise. Formally, our model is based on the concept of a two-layered network, where one layer contains inhibitory neurons, the other excitatory neurons, and the interlayer connections represent heterotypic interactions. The neuronal activity is simulated in realistic coupling schemes in which neurons within each layer are connected with undirected connections, whereas neurons of different types are connected with directed interlayer connections. In this setting, we investigate how different neurophysiological determinants affect the coherence resonance. Specifically, we focus on the proportion of inhibitory neurons, the proportion of excitatory interlayer axons, and the architecture of interlayer connections between inhibitory and excitatory neurons. Our results reveal that the regularity of simulated neural activity can be increased by a stronger damping of the excitatory layer. This can be accomplished with a higher proportion of inhibitory neurons, a higher fraction of inhibitory interlayer axons, a stronger coupling between inhibitory axons, or by a heterogeneous configuration of interlayer connections. Our approach of modeling multilayered neuronal networks in combination with stochastic dynamics offers a novel perspective on how the neural architecture can affect neural information processing and provide possible applications in designing networks of artificial neural circuits to optimize their function via noise-induced phenomena.

Dopaminergic modulation of primary motor cortex: From cellular and synaptic mechanisms underlying motor learning to cognitive symptoms in Parkinson's disease

The primary motor cortex (M1) is crucial for movement execution, especially dexterous ones, but also for cognitive functions like motor learning. The acquisition of motor skills to execute dexterous movements requires dopamine-dependent and -independent plasticity mechanisms within M1. In addition to the basal ganglia, M1 is disturbed in Parkinson's disease (PD). However, little is known about how the lack of dopamine (DA), characteristic of PD, directly or indirectly impacts M1 circuitry. Here we review data from studies of PD patients and the substantial research in non-human primate and rodent models of DA depletion. These models enable us to understand the importance of DA in M1 physiology at the behavioral, network, cellular, and synaptic levels. We first summarize M1 functions and neuronal populations in mammals. We then look at the origin of M1 DA and the cellular location of its receptors and explore the impact of DA loss on M1 physiology, motor, and executive functions. Finally, we discuss how PD treatments impact M1 functions.

Control of noise-induced coherent oscillations in three-neuron motifs

The phenomenon of self-induced stochastic resonance (SISR) requires a nontrivial scaling limit between the deterministic and the stochastic timescales of an excitable system, leading to the emergence of coherent oscillations which are absent without noise. In this paper, we numerically investigate SISR and its control in single neurons and three-neuron motifs made up of the Morris–Lecar model. In single neurons, we compare the effects of electrical and chemical autapses on the degree of coherence of the oscillations due to SISR. In the motifs, we compare the effects of altering the synaptic time-delayed couplings and the topologies on the degree of SISR. Finally, we provide two enhancement strategies for a particularly poor degree of SISR in motifs with chemical synapses: (1) we show that a poor SISR can be significantly enhanced by attaching an electrical or an excitatory chemical autapse on one of the neurons, and (2) we show that by multiplexing the motif with a poor SISR to another motif (with a high SISR in isolation), the degree of SISR in the former motif can be significantly enhanced. We show that the efficiency of these enhancement strategies depends on the topology of the motifs and the nature of synaptic time-delayed couplings mediating the multiplexing connections.

Dynamics of a disinhibitory prefrontal microcircuit in controlling social competition

Social competition plays a pivotal role in determining individuals' social status. While the dorsomedial prefrontal cortex (dmPFC) is essential in regulating social competition, it remains unclear how information is processed within its local networks. Here, by applying optogenetic and chemogenetic manipulations in a dominance tube test, we reveal that, in accordance with pyramidal (PYR) neuron activation, excitation of the vasoactive intestinal polypeptide (VIP) or inhibition of the parvalbumin (PV) interneurons induces winning. The winning behavior is associated with sequential calcium activities initiated by VIP and followed by PYR and PV neurons. Using miniature two-photon microscopic (MTPM) and optrode recordings in awake mice, we show that VIP stimulation directly leads to a two-phased activity pattern of both PYR and PV neurons-rapid suppression followed by activation. The delayed activation of PV implies an embedded feedback tuning. This disinhibitory VIP-PV-PYR motif forms the core of a dmPFC microcircuit to control social competition.

Extensive Structural Remodeling of the Axonal Arbors of Parvalbumin Basket Cells during Development in Mouse Neocortex

Parvalbumin-containing (PV+) basket cells are specialized cortical interneurons that regulate the activity of local neuronal circuits with high temporal precision and reliability. To understand how the PV+ interneuron connectivity underlying these functional properties is established during development, we used array tomography to map pairs of synaptically connected PV+ interneurons and postsynaptic neurons from the neocortex of mice of both sexes. We focused on the axon-myelin unit of the PV+ interneuron and quantified the number of synapses onto the postsynaptic neuron, length of connecting axonal paths, and their myelination at different time points between 2 weeks and 7 months of age. We find that myelination of the proximal axon occurs very rapidly during the third and, to a lesser extent, fourth postnatal weeks. The number of synaptic contacts made by the PV+ interneuron on its postsynaptic partner meanwhile is significantly reduced to about one-third by the end of the first postnatal month. The number of autapses, the synapses that PV+ interneurons form on themselves, however, remains constant throughout the examined period. Axon reorganizations continue beyond postnatal month 2, with the postsynaptic targets of PV+ interneurons gradually shifting to more proximal locations, and the length of axonal paths and their myelin becoming conspicuously uniform per connection. These continued microcircuit refinements likely provide the structural substrate for the robust inhibitory effects and fine temporal precision of adult PV+ basket cells.SIGNIFICANCE STATEMENT The axon of adult parvalbumin-containing (PV+) interneurons is highly specialized for fast and reliable neurotransmission. It is myelinated and forms synapses mostly onto the cell bodies and proximal dendrites of postsynaptic neurons for maximal impact. In this study, we follow the development of the PV+ interneuron axon, its myelination and synapse formation, revealing a rapid sequence of axonal reorganization, myelination of the PV+ interneuron proximal axon, and pruning of almost two-thirds of the synapses in an individual connection. This is followed by a prolonged period of axon refinement and additional myelination leading to a remarkable precision of connections in the adult mouse cortex, consistent with the temporal precision and fidelity of PV+ interneuron action.

Conventional measures of intrinsic excitability are poor estimators of neuronal activity under realistic synaptic inputs

Activity-dependent regulation of intrinsic excitability has been shown to greatly contribute to the overall plasticity of neuronal circuits. Such neuroadaptations are commonly investigated in patch clamp experiments using current step stimulation and the resulting input-output functions are analyzed to quantify alterations in intrinsic excitability. However, it is rarely addressed, how such changes translate to the function of neurons when they operate under natural synaptic inputs. Still, it is reasonable to expect that a strong correlation and near proportional relationship exist between static firing responses and those evoked by synaptic drive. We challenge this view by performing a high-yield electrophysiological analysis of cultured mouse hippocampal neurons using both standard protocols and simulated synaptic inputs via dynamic clamp. We find that under these conditions the neurons exhibit vastly different firing responses with surprisingly weak correlation between static and dynamic firing intensities. These contrasting responses are regulated by two intrinsic K-currents mediated by Kv1 and Kir channels, respectively. Pharmacological manipulation of the K-currents produces differential regulation of the firing output of neurons. Static firing responses are greatly increased in stuttering type neurons under blocking their Kv1 channels, while the synaptic responses of the same neurons are less affected. Pharmacological blocking of Kir-channels in delayed firing type neurons, on the other hand, exhibit the opposite effects. Our subsequent computational model simulations confirm the findings in the electrophysiological experiments and also show that adaptive changes in the kinetic properties of such currents can even produce paradoxical regulation of the firing output.

Coherence and cognition in the cortex: the fundamental role of parvalbumin, myelin, and the perineuronal net

The calcium binding protein parvalbumin is expressed in interneurons of two main morphologies, the basket and chandelier cells, which target perisomatic domains on principal cells and are extensively interconnected in laminar networks by synapses and gap junctions. Beyond its utility as a convenient cellular marker, parvalbumin is an unambiguous identifier of the key role that these interneurons play in the fundamental functions of the cortex. They provide a temporal framework for principal cell activity by propagating gamma oscillation, providing coherence for cortical information processing and the basis for timing-dependent plasticity processes. As these parvalbumin networks mature, they are physically and functionally stabilised by axonal myelination and development of the extracellular matrix structure termed the perineuronal net. This maturation correlates with the emergence of high-speed, highly energetic activity and provides a coherent foundation for the unique ability of the cortex to cross-correlate activity across sensory modes and internal representations.

Impacts of autapse on chaotic resonance in single neurons and small-world neuronal networks

Chaotic resonance (CR) is a new phenomenon induced by an intermediate level of chaotic signal intensity in neuronal systems. In the current study, we investigated the effects of autapse on the CR phenomenon in single neurons and small-world (SW) neuronal networks. In single neurons, we assume that the neuron has only one autapse modelled as electrical, excitatory chemical and inhibitory chemical synapse, respectively. Then, we analysed the effects of each one on the CR, separately. Obtained results revealed that, regardless of its type, autapse significantly increases the chaotic resonance of the appropriate autaptic parameter's values. It is also observed that, at the optimal chaotic current intensity, the multiple CR emerges depending on autaptic time delay for all the autapse types when the autaptic delay time or its integer multiples match the half period or period of the weak signal. In SW networks, we investigated the effects of chaotic activity on the prorogation of pacemaker activity, where pacemaker neurons have different kinds of autapse as considered in single neuron cases. Obtained results revealed that excitatory and electrical autapses prominently increase the prorogation of pacemaker activity, whereas inhibitory autapse reduces or does not change it. Also, the best propagation was obtained when the autapse was excitatory. This article is part of the theme issue 'Vibrational and stochastic resonance in driven nonlinear systems (part 2)'.

Asynchronous Glutamate Release at Autapses Regulates Spike Reliability and Precision in Mouse Neocortical Pyramidal Cells

Autapses are self-synapses of a neuron. Inhibitory autapses in the neocortex release GABA in 2 modes, synchronous release and asynchronous release (AR), providing precise and prolonged self-inhibition, respectively. A subpopulation of neocortical pyramidal cells (PCs) also forms functional autapses, activation of which promotes burst firing by strong unitary autaptic response that reflects synchronous glutamate release. However, it remains unclear whether AR occurs at PC autapses and plays a role in neuronal signaling. We performed whole-cell recordings from layer-5 PCs in slices of mouse prefrontal cortex (PFC). In response to action potential (AP) burst, 63% of PCs showed robust long-lasting autaptic AR, much stronger than synaptic AR between neighboring PCs. The autaptic AR is mediated predominantly by P/Q-type Ca2+ channels, and its strength depends on the intensity of PC activity and the level of residual Ca2+. Further experiments revealed that autaptic AR enhances spiking activities but reduces the temporal precision of post-burst APs. Together, the results show the occurrence of AR at PC autapses, the delayed and persistent glutamate AR causes self-excitation in individual PCs but may desynchronize the autaptic PC population. Thus, glutamatergic autapses should be essential elements in PFC and contribute to cortical information processing.

Fast-spiking Interneurons Contribute to Propofol-induced Facilitation of Firing Synchrony in Pyramidal Neurons of the Rat Insular Cortex

BACKGROUND

The general anesthetic propofol induces frontal alpha rhythm in the cerebral cortex at a dose sufficient to induce loss of consciousness. The authors hypothesized that propofol-induced facilitation of unitary inhibitory postsynaptic currents would result in firing synchrony among postsynaptic pyramidal neurons that receive inhibition from the same presynaptic inhibitory fast-spiking neurons.

METHODS

Multiple whole cell patch clamp recordings were performed from one fast-spiking neuron and two or three pyramidal neurons with at least two inhibitory connections in rat insular cortical slices. The authors examined how inhibitory inputs from a presynaptic fast-spiking neuron modulate the timing of spontaneous repetitive spike firing among pyramidal neurons before and during 10 μM propofol application.

RESULTS

Responding to activation of a fast-spiking neuron with 150-ms intervals, pyramidal cell pairs that received common inhibitory inputs from the presynaptic fast-spiking neuron showed propofol-dependent decreases in average distance from the line of identity, which evaluates the coefficient of variation in spike timing among pyramidal neurons: average distance from the line of identity just after the first activation of fast-spiking neuron was 29.2 ± 24.1 (mean ± SD, absolute value) in control and 19.7 ± 19.2 during propofol application (P < 0.001). Propofol did not change average distance from the line of identity without activating fast-spiking neurons and in pyramidal neuron pairs without common inhibitory inputs from presynaptic fast-spiking neurons. The synchronization index, which reflects the degree of spike synchronization among pyramidal neurons, was increased by propofol from 1.4 ± 0.5 to 2.3 ± 1.5 (absolute value, P = 0.004) and from 1.5 ± 0.5 to 2.2 ± 1.0 (P = 0.030) when a presynaptic fast-spiking neuron was activated at 6.7 and 10 Hz, respectively, but not at 1, 4, and 13.3 Hz.

CONCLUSIONS

These results suggest that propofol facilitates pyramidal neuron firing synchrony by enhancing inhibitory inputs from fast-spiking neurons. This synchrony of pyramidal neurons may contribute to the alpha rhythm associated with propofol-induced loss of consciousness.

EDITOR’S PERSPECTIVE

Synaptic inhibition in the neocortex: Orchestration and computation through canonical circuits and variations on the theme

The neocortex plays a crucial role in all basic and abstract cognitive functions. Conscious mental processes are achieved through a correct flow of information within and across neocortical networks, whose particular activity state results from a tight balance between excitation and inhibition. The proper equilibrium between these indissoluble forces is operated with multiscale organization: along the dendro-somatic axis of single neurons and at the network level. Fast synaptic inhibition is assured by a multitude of inhibitory interneurons. During cortical activities, these cells operate a finely tuned division of labor that is epitomized by their detailed connectivity scheme. Recent results combining the use of mouse genetics, cutting-edge optical and neurophysiological approaches have highlighted the role of fast synaptic inhibition in driving cognition-related activity through a canonical cortical circuit, involving several major interneuron subtypes and principal neurons. Here we detail the organization of this cortical blueprint and we highlight the crucial role played by different neuron types in fundamental cortical computations. In addition, we argue that this canonical circuit is prone to many variations on the theme, depending on the resolution of the classification of neuronal types, and the cortical area investigated. Finally, we discuss how specific alterations of distinct inhibitory circuits can underlie several devastating brain diseases.

Autaptic Cultures: Methods and Applications

Neurons typically form daisy chains of synaptic connections with other neurons, but they can also form synapses with themselves. Although such self-synapses, or autapses, are comparatively rare in vivo, they are surprisingly common in dissociated neuronal cultures. At first glance, autapses in culture seem like a mere curiosity. However, by providing a simple model system in which a single recording electrode gives simultaneous access to the pre- and postsynaptic compartments, autaptic cultures have proven to be invaluable in facilitating important and elegant experiments in the area of synaptic neuroscience. Here, I provide detailed protocols for preparing and recording from autaptic cultures (also called micro-island or microdot cultures). Variations on the basic procedure are presented, as well as practical tips for optimizing the outcomes. I also illustrate the utility of autaptic cultures by reviewing the types of experiments that have used them over the past three decades. These examples serve to highlight the power and elegance of this simple model system, and will hopefully inspire new experiments for the interrogation of synaptic function.

Different dynamical behaviors induced by slow excitatory feedback for type II and III excitabilities

Neuronal excitability is classified as type I, II, or III, according to the responses of electronic activities, which play different roles. In the present paper, the effect of an excitatory autapse on type III excitability is investigated and compared to type II excitability in the Morris-Lecar model, based on Hopf bifurcation and characteristics of the nullcline. The autaptic current of a fast-decay autapse produces periodic stimulations, and that of a slow-decay autapse highly resembles sustained stimulations. Thus, both fast- and slow-decay autapses can induce a resting state for type II excitability that changes to repetitive firing. However, for type III excitability, a fast-decay autapse can induce a resting state to change to repetitive firing, while a slow-decay autapse can induce a resting state to change to a resting state following a transient spike instead of repetitive spiking, which shows the abnormal phenomenon that a stronger excitatory effect of a slow-decay autapse just induces weaker responses. Our results uncover a novel paradoxical phenomenon of the excitatory effect, and we present potential functions of fast- and slow-decay autapses that are helpful for the alteration and maintenance of type III excitability in the real nervous system related to neuropathic pain or sound localization.

A dynamical model exploring sensory integration in the insect central complex substructures

It is imperative that an animal has the ability to contextually integrate received sensory information to formulate appropriate behavioral responses. Determining a body heading based on a multitude of ego-motion cues and visual landmarks is an example of such a task that requires this context dependent integration. The work presented here simulates a sensory integrator in the insect brain called the central complex (CX). Based on the architecture of the CX, we assembled a dynamical neural simulation of two structures called the protocerebral bridge (PB) and the ellipsoid body (EB). Using non-spiking neuronal dynamics, our simulation was able to recreate in vivo neuronal behavior such as correlating body rotation direction and speed to activity bumps within the EB as well as updating the believed heading with quick secondary system updates. With this model, we performed sensitivity analysis of certain neuronal parameters as a possible means to control multi-system gains during sensory integration. We found that modulation of synapses in the memory network and EB inhibition are two possible mechanisms in which a sensory system could affect the memory stability and gain of another input, respectively. This model serves as an exploration in network design for integrating simultaneous idiothetic and allothetic cues in the task of body tracking and determining contextually dependent behavioral outputs.

Robust perisomatic GABAergic self-innervation inhibits basket cells in the human and mouse supragranular neocortex

Inhibitory autapses are self-innervating synaptic connections in GABAergic interneurons in the brain. Autapses in neocortical layers have not been systematically investigated, and their function in different mammalian species and specific interneuron types is poorly known. We investigated GABAergic parvalbumin-expressing basket cells (pvBCs) in layer 2/3 (L2/3) in human neocortical tissue resected in deep-brain surgery, and in mice as control. Most pvBCs showed robust GABA_AR-mediated self-innervation in both species, but autapses were rare in nonfast-spiking GABAergic interneurons. Light- and electron microscopy analyses revealed pvBC axons innervating their own soma and proximal dendrites. GABAergic self-inhibition conductance was similar in human and mouse pvBCs and comparable to that of synapses from pvBCs to other L2/3 neurons. Autaptic conductance prolonged somatic inhibition in pvBCs after a spike and inhibited repetitive firing. Perisomatic autaptic inhibition is common in both human and mouse pvBCs of supragranular neocortex, where they efficiently control discharge of the pvBCs.

Impaired Reliability and Precision of Spiking in Adults But Not Juveniles in a Mouse Model of Fragile X Syndrome

Fragile X syndrome (FXS) is the most common source of intellectual disability and autism. Extensive studies have been performed on the network and behavioral correlates of the syndrome, but our knowledge about intrinsic conductance changes is still limited. In this study, we show a differential effect of FMRP knockout in different subsections of hippocampus using whole-cell patch clamp in mouse hippocampal slices. We observed no significant change in spike numbers in the CA1 region of hippocampus, but a significant increase in CA3, in juvenile mice. However, in adult mice we see a reduction in spike number in the CA1 with no significant difference in CA3. In addition, we see increased variability in spike numbers in CA1 cells following a variety of steady and modulated current step protocols. This effect emerges in adult mice (8 weeks) but not juvenile mice (4 weeks). This increased spiking variability was correlated with reduced spike number and with elevated AHP. The increased AHP arose from elevated SK currents (small conductance calcium-activated potassium channels), but other currents involved in medium AHP, such as I_h and M, were not significantly different. We obtained a partial rescue of the cellular variability phenotype when we blocked SK current using the specific blocker apamin. Our observations provide a single-cell correlate of the network observations of response variability and loss of synchronization, and suggest that the elevation of SK currents in FXS may provide a partial mechanistic explanation for this difference.

Propofol decreases spike firing frequency with an increase in spike synchronization in the cerebral cortex

Little is known about how propofol modulates the spike firing correlation between excitatory and inhibitory cortical neurons in vivo. We performed extracellular unit recordings from rat insular cortical neurons, and classified neurons with high spontaneous firing frequency, bursting, and short spike width as high frequency with bursting neurons (HFB; pseudo fast-spiking GABAergic neurons) and other neurons with low spontaneous firing frequency and no bursting were classified as non-HFB. Intravenous administration of propofol (12 mg/kg) from the caudal vein reduced the firing frequency of HFB, whereas propofol initially increased (within 30 s) and then decreased the firing frequency of non-HFB. Both HFB and non-HFB spontaneous action potential discharge was depressed by propofol with a greater depression seen for HFB. Cross-correlograms and auto-correlograms demonstrated propofol-induced increases in the ratio of the peak, which were mostly observed around 0-10 ms divided to baseline amplitude. The analysis of interspike intervals showed a decrease in spike firing at 20-100 Hz and a relative increase at 8-15 Hz. These results suggest that propofol induces a larger suppression of firing frequency in HFB and an enhancement of synchronized neural activities in the α frequency band in the cerebral cortex (192 words).

Strong preference for autaptic self-connectivity of neocortical PV interneurons facilitates their tuning to γ-oscillations

Parvalbumin (PV)-positive interneurons modulate cortical activity through highly specialized connectivity patterns onto excitatory pyramidal neurons (PNs) and other inhibitory cells. PV cells are autoconnected through powerful autapses, but the contribution of this form of fast disinhibition to cortical function is unknown. We found that autaptic transmission represents the most powerful inhibitory input of PV cells in neocortical layer V. Autaptic strength was greater than synaptic strength onto PNs as a result of a larger quantal size, whereas autaptic and heterosynaptic PV-PV synapses differed in the number of release sites. Overall, single-axon autaptic transmission contributed to approximately 40% of the global inhibition (mostly perisomatic) that PV interneurons received. The strength of autaptic transmission modulated the coupling of PV-cell firing with optogenetically induced γ-oscillations, preventing high-frequency bursts of spikes. Autaptic self-inhibition represents an exceptionally large and fast disinhibitory mechanism, favoring synchronization of PV-cell firing during cognitive-relevant cortical network activity.

Parvalbumin-positive interneurons modulate cortical activity via highly specialized connections to excitatory pyramidal neurons and other inhibitory cells. However, this study shows that fast autaptic self-inhibition is the major output of parvalbumin-positive basket cells in the neocortex and serves to modulate phase-locking of these interneurons during gamma-oscillations.

Distinctions among electroconvulsion- and proconvulsant-induced seizure discharges and native motor patterns during flight and grooming: quantitative spike pattern analysis in Drosophila flight muscles

In Drosophila, high-frequency electrical stimulation across the brain triggers a highly stereotypic repertoire of spasms. These electroconvulsive seizures (ECS) manifest as distinctive spiking discharges across the nervous system and can be stably assessed throughout the seizure repertoire in the large indirect flight muscles dorsal longitudinal muscles (DLMs) to characterize modifications in seizure-prone mutants. However, the relationships between ECS-spike patterns and native motor programs, including flight and grooming, are not known and their similarities and distinctions remain to be characterized. We employed quantitative spike pattern analyses for the three motor patterns including: (1) overall firing frequency, (2) spike timing between contralateral fibers, and (3) short-term variability in spike interval regularity (CV₂) and instantaneous firing frequency (ISI^-1). This base-line information from wild-type (WT) flies facilitated quantitative characterization of mutational effects of major neurotransmitter systems: excitatory cholinergic (Cha), inhibitory GABAergic (Rdl) and electrical (ShakB) synaptic transmission. The results provide an initial glimpse on the vulnerability of individual motor patterns to different perturbations. We found marked alterations of ECS discharge spike patterns in terms of either seizure threshold, spike frequency or spiking regularity. In contrast, no gross alterations during grooming and a small but noticeable reduction of firing frequency during Rdl mutant flight were found, suggesting a role for GABAergic modulation of flight motor programs. Picrotoxin (PTX), a known pro-convulsant that inhibits GABA_A receptors, induced DLM spike patterns that displayed some features, e.g. left-right coordination and ISI^-1 range, that could be found in flight or grooming, but distinct from ECS discharges. These quantitative techniques may be employed to reveal overlooked relationships among aberrant motor patterns as well as their links to native motor programs.

Autapses enhance bursting and coincidence detection in neocortical pyramidal cells

Autapses are synaptic contacts of a neuron’s axon onto its own dendrite and soma. In the neocortex, self-inhibiting autapses in GABAergic interneurons are abundant in number and play critical roles in regulating spike precision and network activity. Here we examine whether the principal glutamatergic pyramidal cells (PCs) also form functional autapses. In patch-clamp recording from both rodent and human PCs, we isolated autaptic responses and found that these occur predominantly in layer-5 PCs projecting to subcortical regions, with very few in those projecting to contralateral prefrontal cortex and layer 2/3 PCs. Moreover, PC autapses persist during development into adulthood. Surprisingly, they produce giant postsynaptic responses (∼5 fold greater than recurrent PC-PC synapses) that are exclusively mediated by AMPA receptors. Upon activation, autapses enhance burst firing, neuronal responsiveness and coincidence detection of synaptic inputs. These findings indicate that PC autapses are functional and represent an important circuit element in the neocortex.

While autapses are synapses made by a neuron onto itself, its functional significance in pyramidal cells are not clear. Here, the authors show that in the mammalian neocortex, autapses of pyramidal cells can enhance burst firing and coincidence detection from other inputs.

Long-Term Stress Disrupts the Structural and Functional Integrity of GABAergic Neuronal Networks in the Medial Prefrontal Cortex of Rats

Clinical and experimental data suggest that fronto-cortical GABAergic deficits contribute to the pathophysiology of major depressive disorder (MDD). To further test this hypothesis, we used a well characterized rat model for depression and examined the effect of stress on GABAergic neuron numbers and GABA-mediated synaptic transmission in the medial prefrontal cortex (mPFC) of rats. Adult male Wistar rats were subjected to 9-weeks of chronic mild stress (CMS) and based on their hedonic-anhedonic behavior they were behaviorally phenotyped as being stress-susceptible (anhedonic) or stress-resilient. Post mortem quantitative histopathology was used to examine the effect of stress on parvalbumin (PV)-, calretinin- (CR), calbindin- (CB), cholecystokinin- (CCK), somatostatin-(SST) and neuropeptide Y-positive (NPY+) GABAergic neuron numbers in all cortical subareas of the mPFC (anterior cingulate (Cg1), prelimbic (PrL) and infralimbic (IL) cortexes). In vitro, whole-cell patch-clamp recordings from layer II–III pyramidal neurons of the ventral mPFC was used to examine GABAergic neurotransmission. The cognitive performance of the animals was assessed in a hippocampal-prefrontal-cortical circuit dependent learning task. Stress exposure reduced the number of CCK-, CR- and PV-positive GABAergic neurons in the mPFC, most prominently in the IL cortex. Interestingly, in the stress-resilient animals, we found higher number of neuropeptide Y-positive neurons in the entire mPFC. The electrophysiological analysis revealed reduced frequencies of spontaneous and miniature IPSCs in the anhedonic rats and decreased release probability of perisomatic-targeting GABAergic synapses and alterations in GABA_B receptor mediated signaling. In turn, pyramidal neurons showed higher excitability. Anhedonic rats were also significantly impaired in the object-place paired-associate learning task. These data demonstrate that long-term stress results in functional and structural deficits of prefrontal GABAergic networks. Our findings support the concept that fronto-limbic GABAergic dysfunctions may contribute to emotional and cognitive symptoms of MDD.

Dynamical Mechanism of Hyperpolarization-Activated Non-specific Cation Current Induced Resonance and Spike-Timing Precision in a Neuronal Model

Hyperpolarization-activated cyclic nucleotide-gated cation current (I_h) plays important roles in the achievement of many physiological/pathological functions in the nervous system by modulating the electrophysiological activities, such as the rebound (spike) to hyperpolarization stimulations, subthreshold membrane resonance to sinusoidal currents, and spike-timing precision to stochastic factors. In the present paper, with increasing g_h (conductance of I_h), the rebound (spike) and subthreshold resonance appear and become stronger, and the variability of the interspike intervals (ISIs) becomes lower, i.e., the enhancement of spike-timing precision, which are simulated in a conductance-based theoretical model and well explained by the nonlinear concept of bifurcation. With increasing g_h, the stable node to stable focus, to coexistence behavior, and to firing via the codimension-1 bifurcations (Hopf bifurcation, saddle-node bifurcation, saddle-node bifurcations on an invariant circle, and saddle homoclinic orbit) and codimension-2 bifurcations such as Bogdanov-Takens (BT) point related to the transition between saddle-node and Hopf bifurcations, are acquired with 1- and 2-parameter bifurcation analysis. The decrease of variability of ISIs with increasing g_h is induced by the fast decrease of the standard deviation of ISIs, which is related to the increase of the capacity of resisting noisy disturbance due to the firing becomes far away from the bifurcation point. The enhancement of the rebound (spike) with increasing g_h builds up a relationship to the decrease of the capacity of resisting disturbance like the hyperpolarization stimulus as the resting state approaches the bifurcation point. The “typical”-resonance and non-resonance appear in the parameter region of the stable focus and node far away from the bifurcation points, respectively. The complex or “strange” dynamics, such as the “weak”-resonance for the stable node near the transition point between the stable node and focus and the non-resonance for the stable focus close to the codimension-1 and −2 bifurcation points, are discussed.

Autapses promote synchronization in neuronal networks

Neurological disorders such as epileptic seizures are believed to be caused by neuronal synchrony. However, to ascertain the causal role of neuronal synchronization in such diseases through the traditional approach of electrophysiological data analysis remains a controversial, challenging, and outstanding problem. We offer an alternative principle to assess the physiological role of neuronal synchrony based on identifying structural anomalies in the underlying network and studying their impacts on the collective dynamics. In particular, we focus on autapses - time delayed self-feedback links that exist on a small fraction of neurons in the network, and investigate their impacts on network synchronization through a detailed stability analysis. Our main finding is that the proper placement of a small number of autapses in the network can promote synchronization significantly, providing the computational and theoretical bases for hypothesizing a high degree of synchrony in real neuronal networks with autapses. Our result that autapses, the shortest possible links in any network, can effectively modulate the collective dynamics provides also a viable strategy for optimal control of complex network dynamics at minimal cost.

Dynamics of delay-coupled FitzHugh-Nagumo neural rings

This paper studies the dynamical behaviors of a pair of FitzHugh-Nagumo neural networks with bidirectional delayed couplings. It presents a detailed analysis of delay-independent and delay-dependent stabilities and the existence of bifurcated oscillations. Illustrative examples are performed to validate the analytical results and to discover interesting phenomena. It is shown that the network exhibits a variety of complicated activities, such as multiple stability switches, the coexistence of periodic and quasi-periodic oscillations, the coexistence of periodic and chaotic orbits, and the coexisting chaotic attractors.

Autapse-induced multiple stochastic resonances in a modular neuronal network

This study investigates the nontrivial effects of autapse on stochastic resonance in a modular neuronal network subjected to bounded noise. The resonance effect of autapse is detected by imposing a self-feedback loop with autaptic strength and autaptic time delay to each constituent neuron. Numerical simulations have demonstrated that bounded noise with the proper level of amplitude can induce stochastic resonance; moreover, the noise induced resonance dynamics can be significantly shaped by the autapse. In detail, for a specific range of autaptic strength, multiple stochastic resonances can be induced when the autaptic time delays are appropriately adjusted. These appropriately adjusted delays are detected to nearly approach integer multiples of the period of the external weak signal when the autaptic strength is very near zero; otherwise, they do not match the period of the external weak signal when the autaptic strength is slightly greater than zero. Surprisingly, in both cases, the differences between arbitrary two adjacent adjusted autaptic delays are always approximately equal to the period of the weak signal. The phenomenon of autaptic delay induced multiple stochastic resonances is further confirmed to be robust against the period of the external weak signal and the intramodule probability of subnetwork. These findings could have important implications for weak signal detection and information propagation in realistic neural systems.

Transitions between classes of neuronal excitability and bifurcations induced by autapse

Neuronal excitabilities behave as the basic and important dynamics related to the transitions between firing and resting states, and are characterized by distinct bifurcation types and spiking frequency responses. Switches between class I and II excitabilities induced by modulations outside the neuron (for example, modulation to M-type potassium current) have been one of the most concerning issues in both electrophysiology and nonlinear dynamics. In the present paper, we identified switches between 2 classes of excitability and firing frequency responses when an autapse, which widely exists in real nervous systems and plays important roles via self-feedback, is introduced into the Morris-Lecar (ML) model neuron. The transition from class I to class II excitability and from class II to class I spiking frequency responses were respectively induced by the inhibitory and excitatory autapse, which are characterized by changes of bifurcations, frequency responses, steady-state current-potential curves, and nullclines. Furthermore, we identified codimension-1 and -2 bifurcations and the characteristics of the current-potential curve that determine the transitions. Our results presented a comprehensive relationship between 2 classes of neuronal excitability/spiking characterized by different types of bifurcations, along with a novel possible function of autapse or self-feedback control on modulating neuronal excitability.

Neural plasticity and network remodeling: From concepts to pathology

Neuroplasticity has been subject to a great deal of research in the last century. Recently, significant emphasis has been placed on the global effect of localized plastic changes throughout the central nervous system, and on how these changes integrate in a pathological context. Specifically, alterations of network functionality have been described in various pathological contexts to which corresponding structural alterations have been proposed. However, considering the amount of literature and the different pathological contexts, an integration of this information is still lacking. In this paper we will review the concepts of neural plasticity as well as their repercussions on network remodeling and provide a possible explanation to how these two concepts relate to each other. We will further examine how alterations in different pathological contexts may relate to each other and will discuss the concept of plasticity diseases, its models and implications.

Spike Timing Rigidity Is Maintained in Bursting Neurons under Pentobarbital-Induced Anesthetic Conditions

Pentobarbital potentiates γ-aminobutyric acid (GABA)-mediated inhibitory synaptic transmission by prolonging the open time of GABA_A receptors. However, it is unknown how pentobarbital regulates cortical neuronal activities via local circuits in vivo. To examine this question, we performed extracellular unit recording in rat insular cortex under awake and anesthetic conditions. Not a few studies apply time-rescaling theorem to detect the features of repetitive spike firing. Similar to these methods, we define an average spike interval locally in time using random matrix theory (RMT), which enables us to compare different activity states on a universal scale. Neurons with high spontaneous firing frequency (>5 Hz) and bursting were classified as HFB neurons (n = 10), and those with low spontaneous firing frequency (<10 Hz) and without bursting were classified as non-HFB neurons (n = 48). Pentobarbital injection (30 mg/kg) reduced firing frequency in all HFB neurons and in 78% of non-HFB neurons. RMT analysis demonstrated that pentobarbital increased in the number of neurons with repulsion in both HFB and non-HFB neurons, suggesting that there is a correlation between spikes within a short interspike interval (ISI). Under awake conditions, in 50% of HFB and 40% of non-HFB neurons, the decay phase of normalized histograms of spontaneous firing were fitted to an exponential function, which indicated that the first spike had no correlation with subsequent spikes. In contrast, under pentobarbital-induced anesthesia conditions, the number of non-HFB neurons that were fitted to an exponential function increased to 80%, but almost no change in HFB neurons was observed. These results suggest that under both awake and pentobarbital-induced anesthetized conditions, spike firing in HFB neurons is more robustly regulated by preceding spikes than by non-HFB neurons, which may reflect the GABA_A receptor-mediated regulation of cortical activities. Whole-cell patch-clamp recording in the IC slice preparation was performed to compare the regularity of spike timing between pyramidal and fast-spiking (FS) neurons, which presumably correspond to non-HFB and HFB neurons, respectively. Repetitive spike firing of FS neurons exhibited a lower variance of ISI than pyramidal neurons both in control and under application of pentobarbital, supporting the above hypothesis.

Spike-timing-dependent plasticity enhanced synchronization transitions induced by autapses in adaptive Newman-Watts neuronal networks

In this paper, we numerically study the effect of spike-timing-dependent plasticity (STDP) on synchronization transitions induced by autaptic activity in adaptive Newman-Watts Hodgkin-Huxley neuron networks. It is found that synchronization transitions induced by autaptic delay vary with the adjusting rate A_p of STDP and become strongest at a certain A_p value, and the A_p value increases when network randomness or network size increases. It is also found that the synchronization transitions induced by autaptic delay become strongest at a certain network randomness and network size, and the values increase and related synchronization transitions are enhanced when A_p increases. These results show that there is optimal STDP that can enhance the synchronization transitions induced by autaptic delay in the adaptive neuronal networks. These findings provide a new insight into the roles of STDP and autapses for the information transmission in neural systems.

Identified Cellular Correlates of Neocortical Ripple and High-Gamma Oscillations during Spindles of Natural Sleep

Ultra-high-frequency network events in the hippocampus are instrumental in a dialogue with the neocortex during memory formation, but the existence of transient ∼200 Hz network events in the neocortex is not clear. Our recordings from neocortical layer II/III of freely behaving rats revealed field potential events at ripple and high-gamma frequencies repeatedly occurring at troughs of spindle oscillations during sleep. Juxtacellular recordings identified subpopulations of fast-spiking, parvalbumin-containing basket cells with epochs of firing at ripple (∼200 Hz) and high-gamma (∼120 Hz) frequencies detected during spindles and centered with millisecond precision at the trough of spindle waves in phase with field potential events but phase shifted relative to pyramidal cell firing. The results suggest that basket cell subpopulations are involved in spindle-nested, high-frequency network events that hypothetically provide repeatedly occurring neocortical temporal reference states potentially involved in mnemonic processes.

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Field potential events at ripple and high-gamma frequencies occur at spindle troughs

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Interneurons fire in phase with spindle ripple and spindle high-gamma oscillations

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Pyramidal cells fire sporadically and phase shifted relative to interneurons

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Spindle ripple events might provide neocortical reference states in mnemonic processes

Dynamic transition of neuronal firing induced by abnormal astrocytic glutamate oscillation

The gliotransmitter glutamate released from astrocytes can modulate neuronal firing by activating neuronal N-methyl-D-aspartic acid (NMDA) receptors. This enables astrocytic glutamate(AG) to be involved in neuronal physiological and pathological functions. Based on empirical results and classical neuron-glial "tripartite synapse" model, we propose a practical model to describe extracellular AG oscillation, in which the fluctuation of AG depends on the threshold of calcium concentration, and the effect of AG degradation is considered as well. We predict the seizure-like discharges under the dysfunction of AG degradation duration. Consistent with our prediction, the suppression of AG uptake by astrocytic transporters, which operates by modulating the AG degradation process, can account for the emergence of epilepsy.

Autapse-induced multiple coherence resonance in single neurons and neuronal networks

We study the effects of electrical and chemical autapse on the temporal coherence or firing regularity of single stochastic Hodgkin-Huxley neurons and scale-free neuronal networks. Also, we study the effects of chemical autapse on the occurrence of spatial synchronization in scale-free neuronal networks. Irrespective of the type of autapse, we observe autaptic time delay induced multiple coherence resonance for appropriately tuned autaptic conductance levels in single neurons. More precisely, we show that in the presence of an electrical autapse, there is an optimal intensity of channel noise inducing the multiple coherence resonance, whereas in the presence of chemical autapse the occurrence of multiple coherence resonance is less sensitive to the channel noise intensity. At the network level, we find autaptic time delay induced multiple coherence resonance and synchronization transitions, occurring at approximately the same delay lengths. We show that these two phenomena can arise only at a specific range of the coupling strength, and that they can be observed independently of the average degree of the network.

Regulation of Irregular Neuronal Firing by Autaptic Transmission

The importance of self-feedback autaptic transmission in modulating spike-time irregularity is still poorly understood. By using a biophysical model that incorporates autaptic coupling, we here show that self-innervation of neurons participates in the modulation of irregular neuronal firing, primarily by regulating the occurrence frequency of burst firing. In particular, we find that both excitatory and electrical autapses increase the occurrence of burst firing, thus reducing neuronal firing regularity. In contrast, inhibitory autapses suppress burst firing and therefore tend to improve the regularity of neuronal firing. Importantly, we show that these findings are independent of the firing properties of individual neurons, and as such can be observed for neurons operating in different modes. Our results provide an insightful mechanistic understanding of how different types of autapses shape irregular firing at the single-neuron level, and they highlight the functional importance of autaptic self-innervation in taming and modulating neurodynamics.

Wiring Specificity and Synaptic Diversity in the Mouse Lateral Central Amygdala

The central amygdala (CeA) nucleus, a subcortical structure composed of mostly GABA-releasing (GABAergic) neurons, controls fear expression via projections to downstream targets in the hypothalamus and brainstem. The CeA consists of the lateral (CeL) and medial (CeM) subdivisions. The CeL strongly gates information transfer to the CeM, the main output station of the amygdala, but little is known about the functional organization of local circuits in this region. Using cluster analysis, we identified two major electrophysiologically distinct CeL neuron classes in mouse amygdala slices, the early-spiking (ES) and late-spiking (LS) neurons. These two classes displayed distinct autaptic transmission. Compared with LS neurons, ES neurons had strong and depressing autapses, which enhanced spike-timing precision. With multiple patch-clamp recordings, we found that CeL neurons made chemical, but not electrical, synapses. Analysis of individual connections revealed cannabinoid type 1 receptor-mediated suppression of the ES, but not of the LS cell output synapse. More interestingly, the efficacy of the ES→LS or LS→ES synapse was ~2-fold greater than that of the LS→LS or ES→ES synapse. When tested at 20 Hz, synapses between different neurons, but not within the same class, were markedly depressing and were more powerful to sculpt activity of postsynaptic neurons. Moreover, neurons of different classes also form synapses with higher degree of connectivity. We demonstrate that ES and LS neurons represent two functionally distinct cell classes in the CeL and interactions between presynaptic and postsynaptic neurons dictate synaptic properties between neurons.

SIGNIFICANCE STATEMENT

The central lateral amygdala (CeL) is a key node in fear circuits, but the functional organization of local circuits in this region is largely unknown. The CeL consists of mostly GABAergic inhibitory neurons with different functional and molecular features. Here, we report that the presynaptic cell class determines functional properties of autapses and cannabinoid-mediated modulation of synaptic transmission between neurons, whereas presynaptic versus postsynaptic cell classes dictate the connectivity, efficacy, and dynamics of GABAergic synapses between any two neurons. The wiring specificity and synaptic diversity have a great impact on neuronal output in amygdala inhibitory networks. Such synaptic organizing principles advance our understanding of the significance of physiologically defined neuronal phenotypes in amygdala inhibitory networks.

Effects of self-coupling and asymmetric output on metastable dynamical transient firing patterns in arrays of neurons with bidirectional inhibitory coupling

Metastable dynamical transient patterns in arrays of bidirectionally coupled neurons with self-coupling and asymmetric output were studied. First, an array of asymmetric sigmoidal neurons with symmetric inhibitory bidirectional coupling and self-coupling was considered and the bifurcations of its steady solutions were shown. Metastable dynamical transient spatially nonuniform states existed in the presence of a pair of spatially symmetric stable solutions as well as unstable spatially nonuniform solutions in a restricted range of the output gain of a neuron. The duration of the transients increased exponentially with the number of neurons up to the maximum number at which the spatially nonuniform steady solutions were stabilized. The range of the output gain for which they existed reduced as asymmetry in a sigmoidal output function of a neuron increased, while the existence range expanded as the strength of inhibitory self-coupling increased. Next, arrays of spiking neuron models with slow synaptic inhibitory bidirectional coupling and self-coupling were considered with computer simulation. In an array of Class 1 Hindmarsh-Rose type models, in which each neuron showed a graded firing rate, metastable dynamical transient firing patterns were observed in the presence of inhibitory self-coupling. This agreed with the condition for the existence of metastable dynamical transients in an array of sigmoidal neurons. In an array of Class 2 Bonhoeffer-van der Pol models, in which each neuron had a clear threshold between firing and resting, long-lasting transient firing patterns with bursting and irregular motion were observed.

Unaltered Network Activity and Interneuronal Firing During Spontaneous Cortical Dynamics In Vivo in a Mouse Model of Severe Myoclonic Epilepsy of Infancy

Severe myoclonic epilepsy of infancy (SMEI) is associated with loss of function of the SCN1A gene encoding the Na_V1.1 sodium channel isoform. Previous studies in Scn1a^−/+ mice during the pre-epileptic period reported selective reduction in interneuron excitability and proposed this as the main pathological mechanism underlying SMEI. Yet, the functional consequences of this interneuronal dysfunction at the circuit level in vivo are unknown. Here, we investigated whether Scn1a^−/+ mice showed alterations in cortical network function. We found that various forms of spontaneous network activity were similar in Scn1a^−/+ during the pre-epileptic period compared with wild-type (WT) in vivo. Importantly, in brain slices from Scn1a^−/+ mice, the excitability of parvalbumin (PV) and somatostatin (SST) interneurons was reduced, epileptiform activity propagated more rapidly, and complex synaptic changes were observed. However, in vivo, optogenetic reduction of firing in PV or SST cells in WT mice modified ongoing network activities, and juxtasomal recordings from identified PV and SST interneurons showed unaffected interneuronal firing during spontaneous cortical dynamics in Scn1a^−/+ compared with WT. These results demonstrate that interneuronal hypoexcitability is not observed in Scn1a^−/+ mice during spontaneous activities in vivo and suggest that additional mechanisms may contribute to homeostatic rearrangements and the pathogenesis of SMEI.

Two types of local interneurons are distinguished by morphology, intrinsic membrane properties, and functional connectivity in the moth antennal lobe

Neurons in the silkmoth antennal lobe (AL) are well characterized in terms of their morphology and odor-evoked firing activity. However, their intrinsic electrical properties including voltage-gated ionic currents and synaptic connectivity remain unclear. To address this, whole cell current- and voltage-clamp recordings were made from second-order projection neurons (PNs) and two morphological types of local interneurons (LNs) in the silkmoth AL. The two morphological types of LNs exhibited distinct physiological properties. One morphological type of LN showed a spiking response with a voltage-gated sodium channel gene expression, whereas the other type of LN was nonspiking without a voltage-gated sodium channel gene expression. Voltage-clamp experiments also revealed that both of two types of LNs as well as PNs possessed two types of voltage-gated potassium channels and calcium channels. In dual whole cell recordings of spiking LNs and PNs, activation of the PN elicited depolarization responses in the paired spiking LN, whereas activation of the spiking LN induced no substantial responses in the paired PN. However, simultaneous recording of a nonspiking LN and a PN showed that activation of the nonspiking LN induced hyperpolarization responses in the PN. We also observed bidirectional synaptic transmission via both chemical and electrical coupling in the pairs of spiking LNs. Thus our results indicate that there were two distinct types of LNs in the silkmoth AL, and their functional connectivity to PNs was substantially different. We propose distinct functional roles for these two different types of LNs in shaping odor-evoked firing activity in PNs.

Colored noise and memory effects on formal spiking neuron models

Simplified neuronal models capture the essence of the electrical activity of a generic neuron, besides being more interesting from the computational point of view when compared to higher-dimensional models such as the Hodgkin-Huxley one. In this work, we propose a generalized resonate-and-fire model described by a generalized Langevin equation that takes into account memory effects and colored noise. We perform a comprehensive numerical analysis to study the dynamics and the point process statistics of the proposed model, highlighting interesting new features such as (i) nonmonotonic behavior (emergence of peak structures, enhanced by the choice of colored noise characteristic time scale) of the coefficient of variation (CV) as a function of memory characteristic time scale, (ii) colored noise-induced shift in the CV, and (iii) emergence and suppression of multimodality in the interspike interval (ISI) distribution due to memory-induced subthreshold oscillations. Moreover, in the noise-induced spike regime, we study how memory and colored noise affect the coherence resonance (CR) phenomenon. We found that for sufficiently long memory, not only is CR suppressed but also the minimum of the CV-versus-noise intensity curve that characterizes the presence of CR may be replaced by a maximum. The aforementioned features allow to interpret the interplay between memory and colored noise as an effective control mechanism to neuronal variability. Since both variability and nontrivial temporal patterns in the ISI distribution are ubiquitous in biological cells, we hope the present model can be useful in modeling real aspects of neurons.