Membrane potential-dependent modulation of recurrent inhibition in rat neocortex

Dynamic balance of excitation and inhibition is crucial for network stability and cortical processing, but it is unclear how this balance is achieved at different membrane potentials (V(m)) of cortical neurons, as found during persistent activity or slow V(m) oscillation. Here we report that a V(m)-dependent modulation of recurrent inhibition between pyramidal cells (PCs) contributes to the excitation-inhibition balance. Whole-cell recording from paired layer-5 PCs in rat somatosensory cortical slices revealed that both the slow and the fast disynaptic IPSPs, presumably mediated by low-threshold spiking and fast spiking interneurons, respectively, were modulated by changes in presynaptic V(m). Somatic depolarization (>5 mV) of the presynaptic PC substantially increased the amplitude and shortened the onset latency of the slow disynaptic IPSPs in neighboring PCs, leading to a narrowed time window for EPSP integration. A similar increase in the amplitude of the fast disynaptic IPSPs in response to presynaptic depolarization was also observed. Further paired recording from PCs and interneurons revealed that PC depolarization increases EPSP amplitude and thus elevates interneuronal firing and inhibition of neighboring PCs, a reflection of the analog mode of excitatory synaptic transmission between PCs and interneurons. Together, these results revealed an immediate V(m)-dependent modulation of cortical inhibition, a key strategy through which the cortex dynamically maintains the balance of excitation and inhibition at different states of cortical activity.     

The maturation of cortical interneuron diversity: how multiple developmental journeys shape the emergence of proper network function

If the classical functional attribute of cortical GABAergic interneurons is to mediate synaptic inhibition in the adult cortex, it is becoming evident that their major task is instead to shape the spatio-temporal dynamics of the network oscillations that support most brain functions. This complex function involves a division of labour between morpho-physiologically diverse interneuron subtypes. Both the central network function and the bewildering heterogeneity of the interneuron population are especially emphasized during cortical development: at early postnatal stages, a single GABAergic neuron can efficiently pace the activity of hundreds of other cells, whereas some interneuron subtypes are still poorly developed. Given the role of coherent activity in brain development, this confers to GABAergic interneurons a major role in the proper maturation of cortical networks.     

Optimizing interneuron circuits for compartment-specific feedback inhibition

Cortical circuits process information by rich recurrent interactions between excitatory neurons and inhibitory interneurons. One of the prime functions of interneurons is to stabilize the circuit by feedback inhibition, but the level of specificity on which inhibitory feedback operates is not fully resolved. We hypothesized that inhibitory circuits could enable separate feedback control loops for different synaptic input streams, by means of specific feedback inhibition to different neuronal compartments. To investigate this hypothesis, we adopted an optimization approach. Leveraging recent advances in training spiking network models, we optimized the connectivity and short-term plasticity of interneuron circuits for compartment-specific feedback inhibition onto pyramidal neurons. Over the course of the optimization, the interneurons diversified into two classes that resembled parvalbumin (PV) and somatostatin (SST) expressing interneurons. Using simulations and mathematical analyses, we show that the resulting circuit can be understood as a neural decoder that inverts the nonlinear biophysical computations performed within the pyramidal cells. Our model provides a proof of concept for studying structure-function relations in cortical circuits by a combination of gradient-based optimization and biologically plausible phenomenological models.     

Signal processing properties of fast spiking interneurons

Fast spiking interneurons receive excitatory synaptic inputs from pyramidal cells and a relevant problem is to understand how these cells readout this information. Here this topic is investigated theoretically by using a biophysical modeling of a pair of coupled fast spiking interneuron models. The model predicts, in agreement with the experimental findings, that these cells are capable of transmitting pre-synaptic signals with high temporal precision and transferring high frequency inputs while preserving their relative timing. Moreover, it is shown that a pair of fast spiking interneurons, coupled through both inhibitory and electrical synapses, behaves as a coincidence detector. Lastly, to understand the mechanisms underlying these phenomena, a theoretical analysis is carried out by using a simpler modeling approach.     

Action Potential Modulation in CA1 Pyramidal Neuron Axons Facilitates OLM Interneuron Activation in Recurrent Inhibitory Microcircuits of Rat Hippocampus

Oriens-lacunosum moleculare (O-LM) interneurons in the CA1 region of the hippocampus play a key role in feedback inhibition and in the control of network activity. However, how these cells are efficiently activated in the network remains unclear. To address this question, I performed recordings from CA1 pyramidal neuron axons, the presynaptic fibers that provide feedback innervation of these interneurons. Two forms of axonal action potential (AP) modulation were identified. First, repetitive stimulation resulted in activity-dependent AP broadening. Broadening showed fast onset, with marked changes in AP shape following a single AP. Second, tonic depolarization in CA1 pyramidal neuron somata induced AP broadening in the axon, and depolarization-induced broadening summated with activity-dependent broadening. Outside-out patch recordings from CA1 pyramidal neuron axons revealed a high density of α-dendrotoxin (α-DTX)-sensitive, inactivating K⁺ channels, suggesting that K⁺ channel inactivation mechanistically contributes to AP broadening. To examine the functional consequences of axonal AP modulation for synaptic transmission, I performed paired recordings between synaptically connected CA1 pyramidal neurons and O-LM interneurons. CA1 pyramidal neuron–O-LM interneuron excitatory postsynaptic currents (EPSCs) showed facilitation during both repetitive stimulation and tonic depolarization of the presynaptic neuron. Both effects were mimicked and occluded by α-DTX, suggesting that they were mediated by K⁺ channel inactivation. Therefore, axonal AP modulation can greatly facilitate the activation of O-LM interneurons. In conclusion, modulation of AP shape in CA1 pyramidal neuron axons substantially enhances the efficacy of principal neuron–interneuron synapses, promoting the activation of O-LM interneurons in recurrent inhibitory microcircuits.     

Impact of gamma-oscillatory inhibition on the signal transmission of a cortical pyramidal neuron

Networks of synchronized fast-spiking interneurons are thought to be key elements in the generation of gamma (γ) oscillations (30–80 Hz) in the brain. We examined how such γ-oscillatory inhibition regulates the output of a cortical pyramidal cell. Specifically, we modeled a situation where a pyramidal cell receives inputs from γ-synchronized fast-spiking inhibitory interneurons. This model successfully reproduced several important aspects of a recent experimental result regarding the γ-inhibitory regulation of pyramidal cellular firing that is presumably associated with the sensation of whisker stimuli. Through an in-depth analysis of this model system, we show that there is an obvious rhythmic gating effect of the γ-oscillated interneuron networks on the pyramidal neuron’s signal transmission. This effect is further illustrated by the interactions of this interneuron network and the pyramidal neuron. Prominent power in the γ frequency range can emerge provided that there are appropriate delays on the excitatory connections and inhibitory synaptic conductance between interneurons. These results indicate that interactions between excitation and inhibition are critical for the modulation of coherence and oscillation frequency of network activities.     

Reduction in cortical parvalbumin expression due to intermittent theta‐burst stimulation correlates with maturation of the perineuronal nets in young rats

We recently showed that intermittent theta‐burst stimulation (iTBS) using transcranial magnetic stimulation strongly reduces the number of rat neocortical interneurons expressing glutamic acid decarboxylase 67 kDa (GAD67) and parvalbumin (PV), indicating changed activity of fast‐spiking (FS) interneurons. In advance of in vitro studies intended to characterize changes in electrical properties of FS interneurons under these conditions, we tested whether the iTBS effect is age‐dependent. Conscious Sprague‐Dawley rats aged between 28 and 90 days received three blocks of iTBS at 15 min intervals. We found that iTBS‐related reduction in PV+ cells was absent up to an age of 32 days, then gradually increased, and approached a maximum of about 40% reduction at an age of about 40 days. The relative number of cells expressing PV (PV+, 8–9%) did not change with age in sham‐controls and also the increase in cortical c‐Fos expression induced by iTBS was not principally age‐dependent. However, a prominent growth of the perineuronal nets, typically surrounding the PV+ cells, exactly paralleled the increase in the iTBS effect. Based on these findings, we conclude that the functional development of the inhibitory network of PV+ interneurons with regard to intracortical synaptic connectivity is not sufficiently matured in rats younger than 35d to enable activity‐dependent modifications during iTBS. Outgrowth of the perineuronal nets and associated maturation of excitatory cortical inputs, as is characteristic for the critical cortical period, may take place before PV+ interneurons can be sufficiently activated via repetitive transcranial magnetic stimulation, allowing plastic changes of molecular phenotype and likely also synaptic plasticity. © 2014 Wiley Periodicals, Inc. Develop Neurobiol 75: 1–11, 2015     

Modeling the Spontaneous Activity of the Auditory Cortex

We present a rate model of the spontaneous activity in the auditory cortex, based on synaptic depression. A Stochastic integro-differential system of equations is derived and the analysis reveals two main regimes. The first regime corresponds to a normal activity. The second regime corresponds to epileptic spiking. A detailed analysis of each regime is presented and we prove in particular that synaptic depression stabilizes the global cortical dynamics. The transition between the two regimes is induced by a change in synaptic connectivity: when the overall connectivity is strong enough, an epileptic activity is spontaneously generated. Numerical simulations confirm the predictions of the theoretical analysis. In particular, our results explain the transition from normal to epileptic regime which can be induced in rats auditory cortex, following a specific pairing protocol. A change in the cortical maps reorganizes the synaptic connectivity and this transition between regimes is accounted for by our model. We have used data from recording experiments to fit synaptic weight distributions. Simulations with the fitted distributions are qualitatively similar to the real EEG recorded in vivo during the experiments. We conclude that changes in the synaptic weight function in our model, which affects excitatory synapses organization and reproduces the changes in cortical map connectivity can be understood as the main mechanism to explain the transitions of the EEG from the normal to the epileptic regime in the auditory cortex. D.H is incumbent to the Hass Russell Career Chair Development.     

Interneurons unbound

Local-circuit, gamma-aminobutyric acid-releasing inhibitory interneurons of the hippocampus and cortex have traditionally been considered as the regulators of principal neuron activity--the yin to the excitatory yang. Recent evidence indicates that, in addition to that role, their network connectivity and the properties of their intrinsic voltage-gated currents are finely tuned to permit inhibitory interneurons to generate and control the rhythmic output of large populations of both principal cells and other populations of inhibitory interneurons. This review brings together recently described properties and emerging principles of interneuron function that indicate a much more complex role for these cells than just providers of inhibition.     

Spontaneous Local Gamma Oscillation Selectively Enhances Neural Network Responsiveness

Synchronized oscillation is very commonly observed in many neuronal systems and might play an important role in the response properties of the system. We have studied how the spontaneous oscillatory activity affects the responsiveness of a neuronal network, using a neural network model of the visual cortex built from Hodgkin-Huxley type excitatory (E-) and inhibitory (I-) neurons. When the isotropic local E-I and I-E synaptic connections were sufficiently strong, the network commonly generated gamma frequency oscillatory firing patterns in response to random feed-forward (FF) input spikes. This spontaneous oscillatory network activity injects a periodic local current that could amplify a weak synaptic input and enhance the network's responsiveness. When E-E connections were added, we found that the strength of oscillation can be modulated by varying the FF input strength without any changes in single neuron properties or interneuron connectivity. The response modulation is proportional to the oscillation strength, which leads to self-regulation such that the cortical network selectively amplifies various FF inputs according to its strength, without requiring any adaptation mechanism. We show that this selective cortical amplification is controlled by E-E cell interactions. We also found that this response amplification is spatially localized, which suggests that the responsiveness modulation may also be spatially selective. This suggests a generalized mechanism by which neural oscillatory activity can enhance the selectivity of a neural network to FF inputs.     

Structure predicts synaptic function of two classes of interneurons in the thoracic ganglia of Locusta migratoria

Summary The relationship between synaptic function and structure was examined for 32 spiking interneurons (13 inhibitory and 19 excitatory) in the meso- and metathoracic ganglia of the locust, Locusta migratoria. In no instance was the structure of an excitatory interneuron similar to that of an inhibitory interneuron. However, 12 of the 13 inhibitory interneurons shared a number of structural features, namely a ventromedially located soma, axon(s) projecting into contralateral connective(s), and a laterally bowed primary neurite. Structurally the excitatory interneurons formed a more heterogeneous group. Even so, 12 of the 19 had a combination of structural features in common, namely laterally located somata and axon(s) projecting into contralateral connective(s). The clear differences in structure of the two main groups of inhibitory and excitatory interneurons suggest that other neurons with structures similar to members of these two groups can be classified as inhibitory and excitatory, respectively. Thus we propose that structure predicts synaptic function for two distinct groups of interneurons in the thoracic ganglia of locusts. Present address: Department of Biology, McGill University, Montreal, Qubeck, Canada     

Glutamate-Bound NMDARs Arising from In Vivo-like Network Activity Extend Spatio-temporal Integration in a L5 Cortical Pyramidal Cell Model

In vivo, cortical pyramidal cells are bombarded by asynchronous synaptic input arising from ongoing network activity. However, little is known about how such ‘background’ synaptic input interacts with nonlinear dendritic mechanisms. We have modified an existing model of a layer 5 (L5) pyramidal cell to explore how dendritic integration in the apical dendritic tuft could be altered by the levels of network activity observed in vivo. Here we show that asynchronous background excitatory input increases neuronal gain and extends both temporal and spatial integration of stimulus-evoked synaptic input onto the dendritic tuft. Addition of fast and slow inhibitory synaptic conductances, with properties similar to those from dendritic targeting interneurons, that provided a ‘balanced’ background configuration, partially counteracted these effects, suggesting that inhibition can tune spatio-temporal integration in the tuft. Excitatory background input lowered the threshold for NMDA receptor-mediated dendritic spikes, extended their duration and increased the probability of additional regenerative events occurring in neighbouring branches. These effects were also observed in a passive model where all the non-synaptic voltage-gated conductances were removed. Our results show that glutamate-bound NMDA receptors arising from ongoing network activity can provide a powerful spatially distributed nonlinear dendritic conductance. This may enable L5 pyramidal cells to change their integrative properties as a function of local network activity, potentially allowing both clustered and spatially distributed synaptic inputs to be integrated over extended timescales.     

The dynamical stability of reverberatory neural circuits

The concept of reverberation proposed by Lorente de Nó and Hebb is key to understanding strongly recurrent cortical networks. In particular, synaptic reverberation is now viewed as a likely mechanism for the active maintenance of working memory in the prefrontal cortex. Theoretically, this has spurred a debate as to how such a potentially explosive mechanism can provide stable working-memory function given the synaptic and cellular mechanisms at play in the cerebral cortex. We present here new evidence for the participation of NMDA receptors in the stabilization of persistent delay activity in a biophysical network model of conductance-based neurons. We show that the stability of working-memory function, and the required NMDA/AMPA ratio at recurrent excitatory synapses, depend on physiological properties of neurons and synaptic interactions, such as the time constants of excitation and inhibition, mutual inhibition between interneurons, differential NMDA receptor participation at excitatory projections to pyramidal neurons and interneurons, or the presence of slow intrinsic ion currents in pyramidal neurons. We review other mechanisms proposed to enhance the dynamical stability of synaptically generated attractor states of a reverberatory circuit. This recent work represents a necessary and significant step towards testing attractor network models by cortical electrophysiology.     

Self-Organization of Microcircuits in Networks of Spiking Neurons with Plastic Synapses

The synaptic connectivity of cortical networks features an overrepresentation of certain wiring motifs compared to simple random-network models. This structure is shaped, in part, by synaptic plasticity that promotes or suppresses connections between neurons depending on their joint spiking activity. Frequently, theoretical studies focus on how feedforward inputs drive plasticity to create this network structure. We study the complementary scenario of self-organized structure in a recurrent network, with spike timing-dependent plasticity driven by spontaneous dynamics. We develop a self-consistent theory for the evolution of network structure by combining fast spiking covariance with a slow evolution of synaptic weights. Through a finite-size expansion of network dynamics we obtain a low-dimensional set of nonlinear differential equations for the evolution of two-synapse connectivity motifs. With this theory in hand, we explore how the form of the plasticity rule drives the evolution of microcircuits in cortical networks. When potentiation and depression are in approximate balance, synaptic dynamics depend on weighted divergent, convergent, and chain motifs. For additive, Hebbian STDP these motif interactions create instabilities in synaptic dynamics that either promote or suppress the initial network structure. Our work provides a consistent theoretical framework for studying how spiking activity in recurrent networks interacts with synaptic plasticity to determine network structure.     

Coexistence of lateral and co-tuned inhibitory configurations in cortical networks

The responses of neurons in sensory cortex depend on the summation of excitatory and inhibitory synaptic inputs. How the excitatory and inhibitory inputs scale with stimulus depends on the network architecture, which ranges from the lateral inhibitory configuration where excitatory inputs are more narrowly tuned than inhibitory inputs, to the co-tuned configuration where both are tuned equally. The underlying circuitry that gives rise to lateral inhibition and co-tuning is yet unclear. Using large-scale network simulations with experimentally determined connectivity patterns and simulations with rate models, we show that the spatial extent of the input determined the configuration: there was a smooth transition from lateral inhibition with narrow input to co-tuning with broad input. The transition from lateral inhibition to co-tuning was accompanied by shifts in overall gain (reduced), output firing pattern (from tonic to phasic) and rate-level functions (from non-monotonic to monotonically increasing). The results suggest that a single cortical network architecture could account for the extended range of experimentally observed response types between the extremes of lateral inhibitory versus co-tuned configurations.     

Local interneurons and information processing in the olfactory glomeruli of the moth Manduca sexta

Intracellular recordings were made from the major neurites of local interneurons in the moth antennal lobe. Antennal nerve stimulation evoked 3 patterns of postsynaptic activity: (i) a short-latency compound excitatory postsynaptic potential that, based on electrical stimulation of the antennal nerve and stimulation of the antenna with odors, represents a monosynaptic input from olfactory afferent axons (71 out of 86 neurons), (ii) a delayed activation of firing in response to both electrical- and odor-driven input (11 neurons), and (iii) a delayed membrane hyperpolarization in response to antennal nerve input (4 neurons).Simultaneous intracellular recordings from a local interneuron with short-latency responses and a projection (output) neuron revealed unidirectional synaptic interactions between these two cell types. In 20% of the 30 pairs studied, spontaneous and current-induced spiking activity in a local interneuron correlated with hyperpolarization and suppression of firing in a projection neuron. No evidence for recurrent or feedback inhibition of projection neurons was found. Furthermore, suppression of firing in an inhibitory local interneuron led to an increase in firing in the normally quiescent projection neuron, suggesting that a disinhibitory pathway may mediate excitation in projection neurons. This is the first direct evidence of an inhibitory role for local interneurons in olfactory information processing in insects. Through different types of multisynaptic interactions with projection neurons, local interneurons help to generate and shape the output from olfactory glomeruli in the antennal lobe.Abbreviations AL antennal lobe - EPSP excitatory postsynaptic potential - GABA -aminobutyric acid - IPSP inhibitory postsynaptic potential - LN local interneuron - MGC macroglomerular complex - OB olfactory bulb - PN projection neuron - TES N-tris[hydroxymethyl]methyl-2-aminoethane-sulfonic acid     

The synchronization properties of a network of inhibitory interneurons depend on the biophysical model

The synchronization properties of a pair of coupled fast spiking interneurons are studied by using the theory of weakly coupled oscillators. Four different biophysical models of the single fast spiking interneuron are used and the corresponding results are compared. It is shown that for a pair of identical coupled cells, the synchronization properties are model-dependent. In particular, the firing coherence of the network is strongly affected by the reversal potential, the kinetics of the inhibitory postsynaptic current and the electrical coupling; the activation properties of the sodium and potassium currents play a significant role too.     

Stuttering Interneurons Generate Fast and Robust Inhibition onto Projection Neurons with Low Capacity of Short Term Modulation in Mouse Lateral Amygdala

The stuttering interneurons (STi) represent one minor subset of interneuron population and exhibit characteristic stuttering firing upon depolarization current injection. While it has been long held that the GABAergic inhibitory transmission largely varies with the subtype identity of presynaptic interneurons, whether such a rule also applies to STi is largely unknown. Here, by paired recording of interneuron and their neighboring projection neuron in lateral amygdala, we found that relative to the fast spiking and late spiking interneurons, the STi-evoked unitary postsynaptic currents onto the projection neurons had markedly larger amplitude, shorter onset latency and faster rising and decay kinetics. The quantal content and the number of vesicles in the readily releasable pool were also larger in synapses made by STi versus other interneurons. Moreover, the short-term plasticity, as reflected by the paired pulse depression and depolarization-induced suppression of inhibition, was the least prominent in the output synapses of STi. Thus, the fast and robust inhibition together with its low capacity of short term modulation may suggest an important role for STi in preventing the overexcitation of the projection neurons and thus gating the information traffic in amygdala.     

Differing afferent connections of spiking and nonspiking wind-sensitive local interneurons in the terminal abdominal ganglion of the cricket Gryllus bimaculatus

Fifteen local spiking interneurons (LSIs) and twentyone local non-spiking interneurons (LNIs) were identified in the terminal abdominal ganglion (TAG) of the cricket Gryllus bimaculatus on the basis of intracellular recording and staining (Figs. 1, 5, 6). Although the majority of LNIs showed sharp directionalities (Fig. 7) the LSIs did not (Fig. 3). The directionality of LNIs varied with the recording sites within a single cell (Fig. 8). Electrical stimulations of the cereal sensory nerve suggested that the LNIs are connected monosynaptically with the sensory afferents of both the cerci, and that LSIs may possess a variety of bilateral combinations of polysynaptic connections with the sensory afferents. We found that the spiking and the non-spiking local interneurons in the cereal sensory system differ not only in their membrane properties, but also in their afferent connections, and concluded that their differing connectivity to the sensory afferents will associate them with different roles in signal processing.Abbreviations TAG terminal abdominal ganglion - LSI local spiking interneuron - LNI local non-spiking interneurons - CNS central nervous system - PSP post synaptic potential - GI giant interneuron     

Oscillations in Large-Scale Cortical Networks: Map-Based Model

We develop a new computationally efficient approach for the analysis of complex large-scale neurobiological networks. Its key element is the use of a new phenomenological model of a neuron capable of replicating important spike pattern characteristics and designed in the form of a system of difference equations (a map). We developed a set of map-based models that replicate spiking activity of cortical fast spiking, regular spiking and intrinsically bursting neurons. Interconnected with synaptic currents these model neurons demonstrated responses very similar to those found with Hodgkin-Huxley models and in experiments. We illustrate the efficacy of this approach in simulations of one- and two-dimensional cortical network models consisting of regular spiking neurons and fast spiking interneurons to model sleep and activated states of the thalamocortical system. Our study suggests that map-based models can be widely used for large-scale simulations and that such models are especially useful for tasks where the modeling of specific firing patterns of different cell classes is important.