Plasticity of Inhibition

Immature Status Epilepticus Alters the Temporal Relationship between Hippocampal Interictal Epileptiform Discharges and High-frequency Oscillations

The aim was to investigate the long-term effects of a single episode of immature Status Epilepticus (SE) on the excitability of the septal and temporal hippocampus in vitro, by studying the relationship between interictal-like epileptiform discharges (IEDs) and high-frequency oscillations (HFOs; Ripples, Rs and Fast Ripples, FRs). A pentylenetetrazol-induced Status Epilepticus-(SE)-like generalized seizure was induced at postnatal day 20 in 22 male and female juvenile rats, sacrificed >40 days later to prepare hippocampal slices. Spontaneous IEDs induced by Mg2+-free ACSF were recorded from the CA3 area of temporal (T) or septal (S) slices. Recordings were band-pass filtered off-line revealing Rs and FRs and a series of measurements were conducted, with mean values compared with those obtained from age-matched controls (CTRs). In CTR S (vs T) slices, we recorded longer R & FR durations, a longer HFO-IED temporal overlap, higher FR peak power and more frequent FR initiation preceding IEDs (% events). Post-SE, in T slices all types of events duration (IED, R, FR) and the time lag between their onsets (R-IED, FR-IED, R-FR) increased, while FR/R peak power decreased; in S slices, the IED 1st population spike and the FR amplitudes, the R and FR peak power and the (percent) events where Rs or FRs preceded IEDs all decreased. The CA3 IED-HFO relationship offers insights to the septal-to-temporal synchronization patterns; its post-juvenile-SE changes indicate permanent modifications in the septotemporal excitability gradient. Moreover, these findings are in line to region-specific regulation of various currents post-SE, as reported in literature.

Dynamic and selective engrams emerge with memory consolidation

Episodic memories are encoded by experience-activated neuronal ensembles that remain necessary and sufficient for recall. However, the temporal evolution of memory engrams after initial encoding is unclear. In this study, we employed computational and experimental approaches to examine how the neural composition and selectivity of engrams change with memory consolidation. Our spiking neural network model yielded testable predictions: memories transition from unselective to selective as neurons drop out of and drop into engrams; inhibitory activity during recall is essential for memory selectivity; and inhibitory synaptic plasticity during memory consolidation is critical for engrams to become selective. Using activity-dependent labeling, longitudinal calcium imaging and a combination of optogenetic and chemogenetic manipulations in mouse dentate gyrus, we conducted contextual fear conditioning experiments that supported our model's predictions. Our results reveal that memory engrams are dynamic and that changes in engram composition mediated by inhibitory plasticity are crucial for the emergence of memory selectivity.

Internal-state-dependent control of feeding behavior via hippocampal ghrelin signaling

Hunger is an internal state that not only invigorates feeding but also acts as a contextual cue for higher-order control of anticipatory feeding-related behavior. The ventral hippocampus is crucial for differentiating optimal behavior across contexts, but how internal contexts such as hunger influence hippocampal circuitry is unknown. In this study, we investigated the role of the ventral hippocampus during feeding behavior across different states of hunger in mice. We found that activity of a unique subpopulation of neurons that project to the nucleus accumbens (vS-NAc neurons) increased when animals investigated food, and this activity inhibited the transition to begin eating. Increases in the level of the peripheral hunger hormone ghrelin reduced vS-NAc activity during this anticipatory phase of feeding via ghrelin-receptor-dependent increases in postsynaptic inhibition and promoted the initiation of eating. Together, these experiments define a ghrelin-sensitive hippocampal circuit that informs the decision to eat based on internal state.

Silences, spikes and bursts: Three-part knot of the neural code

When a neuron breaks silence, it can emit action potentials in a number of patterns. Some responses are so sudden and intense that electrophysiologists felt the need to single them out, labelling action potentials emitted at a particularly high frequency with a metonym - bursts. Is there more to bursts than a figure of speech? After all, sudden bouts of high-frequency firing are expected to occur whenever inputs surge. The burst coding hypothesis advances that the neural code has three syllables: silences, spikes and bursts. We review evidence supporting this ternary code in terms of devoted mechanisms for burst generation, synaptic transmission and synaptic plasticity. We also review the learning and attention theories for which such a triad is beneficial.

Hippocampal GABAergic interneurons and memory

One of the most captivating questions in neuroscience revolves around the brain's ability to efficiently and durably capture and store information. It must process continuous input from sensory organs while also encoding memories that can persist throughout a lifetime. What are the cellular-, subcellular-, and network-level mechanisms that underlie this remarkable capacity for long-term information storage? Furthermore, what contributions do distinct types of GABAergic interneurons make to this process? As the hippocampus plays a pivotal role in memory, our review focuses on three aspects: (1) delineation of hippocampal interneuron types and their connectivity, (2) interneuron plasticity, and (3) activity patterns of interneurons during memory-related rhythms, including the role of long-range interneurons and disinhibition. We explore how these three elements, together showcasing the remarkable diversity of inhibitory circuits, shape the processing of memories in the hippocampus.

Distinct Features of Interictal Activity Predict Seizure Localization and Burden in a Mouse Model of Childhood Epilepsy

The epileptic brain is distinguished by spontaneous seizures and interictal epileptiform discharges (IEDs). Basic patterns of mesoscale brain activity outside of seizures and IEDs are also frequently disrupted in the epileptic brain and likely influence disease symptoms, but are poorly understood. We aimed to quantify how interictal brain activity differs from that in healthy individuals, and identify what features of interictal activity influence seizure occurrence in a genetic mouse model of childhood epilepsy. Neural activity across the majority of the dorsal cortex was monitored with widefield Ca2+ imaging in mice of both sexes expressing a human Kcnt1 variant (Kcnt1m/m ) and wild-type controls (WT). Ca2+ signals during seizures and interictal periods were classified according to their spatiotemporal features. We identified 52 spontaneous seizures, which emerged and propagated within a consistent set of susceptible cortical areas, and were predicted by a concentration of total cortical activity within the emergence zone. Outside of seizures and IEDs, similar events were detected in Kcnt1m/m and WT mice, suggesting that the spatial structure of interictal activity is similar. However, the rate of events whose spatial profile overlapped with where seizures and IEDs emerged was increased, and the characteristic global intensity of cortical activity in individual Kcnt1m/m mice predicted their epileptic activity burden. This suggests that cortical areas with excessive interictal activity are vulnerable to seizures, but epilepsy is not an inevitable outcome. Global scaling of the intensity of cortical activity below levels found in the healthy brain may provide a natural mechanism of seizure protection.SIGNIFICANCE STATEMENT Defining the scope and structure of an epilepsy-causing gene variant's effects on mesoscale brain activity constitutes a major contribution to our understanding of how epileptic brains differ from healthy brains, and informs the development of precision epilepsy therapies. We provide a clear roadmap for measuring how severely brain activity deviates from normal, not only in pathologically active areas, but across large portions of the brain and outside of epileptic activity. This will indicate where and how activity needs to be modulated to holistically restore normal function. It also has the potential to reveal unintended off-target treatment effects and facilitate therapy optimization to deliver maximal benefit with minimal side-effect potential.

mTORC1-mediated acquisition of reward-related representations by hippocampal somatostatin interneurons

Plasticity of principal cells and inhibitory interneurons underlies hippocampal memory. Bidirectional modulation of somatostatin cell mTORC1 activity, a crucial translational control mechanism in synaptic plasticity, causes parallel changes in hippocampal CA1 somatostatin interneuron (SOM-IN) long-term potentiation and hippocampus-dependent memory, indicating a key role in learning. However, SOM-IN activity changes and behavioral correlates during learning, and the role of mTORC1 in these processes, remain ill-defined. To address these questions, we used two-photon Ca²⁺ imaging from SOM-INs during a virtual reality goal-directed spatial memory task in head-fixed control mice (SOM-IRES-Cre mice) or in mice with conditional knockout of Rptor (SOM-Rptor-KO mice) to block mTORC1 activity in SOM-INs. We found that control mice learn the task, but SOM-Raptor-KO mice exhibit a deficit. Also, SOM-IN Ca²⁺ activity became increasingly related to reward during learning in control mice but not in SOM-Rptor-KO mice. Four types of SOM-IN activity patterns related to reward location were observed, "reward off sustained", "reward off transient", "reward on sustained" and "reward on transient", and these responses showed reorganization after reward relocation in control but not SOM-Rptor-KO mice. Thus, SOM-INs develop mTORC1-dependent reward- related activity during learning. This coding may bi-directionally interact with pyramidal cells and other structures to represent and consolidate reward location.

Pannexin-1 Modulates Inhibitory Transmission and Hippocampal Synaptic Plasticity

Pannexin-1 (Panx1) hemichannel is a non-selective transmembrane channel that may play important roles in intercellular signaling by allowing the permeation of ions and metabolites, such as ATP. Although recent evidence shows that the Panx1 hemichannel is involved in controlling excitatory synaptic transmission, the role of Panx1 in inhibitory transmission remains unknown. Here, we studied the contribution of Panx1 to the GABAergic synaptic efficacy onto CA1 pyramidal neurons (PyNs) by using patch-clamp recordings and pharmacological approaches in wild-type and Panx1 knock-out (Panx1-KO) mice. We reported that blockage of the Panx1 hemichannel with the mimetic peptide ¹⁰Panx1 increases the synaptic level of endocannabinoids (eCB) and the activation of cannabinoid receptors type 1 (CB1Rs), which results in a decrease in hippocampal GABAergic efficacy, shifting excitation/inhibition (E/I) balance toward excitation and facilitating the induction of long-term potentiation. Our finding provides important insight unveiling that Panx1 can strongly influence the overall neuronal excitability and play a key role in shaping synaptic changes affecting the amplitude and direction of plasticity, as well as learning and memory processes.

Distributing task-related neural activity across a cortical network through task-independent connections

Task-related neural activity is widespread across populations of neurons during goal-directed behaviors. However, little is known about the synaptic reorganization and circuit mechanisms that lead to broad activity changes. Here we trained a subset of neurons in a spiking network with strong synaptic interactions to reproduce the activity of neurons in the motor cortex during a decision-making task. Task-related activity, resembling the neural data, emerged across the network, even in the untrained neurons. Analysis of trained networks showed that strong untrained synapses, which were independent of the task and determined the dynamical state of the network, mediated the spread of task-related activity. Optogenetic perturbations suggest that the motor cortex is strongly-coupled, supporting the applicability of the mechanism to cortical networks. Our results reveal a cortical mechanism that facilitates distributed representations of task-variables by spreading the activity from a subset of plastic neurons to the entire network through task-independent strong synapses.

The plasticitome of cortical interneurons

Hebb postulated that, to store information in the brain, assemblies of excitatory neurons coding for a percept are bound together via associative long-term synaptic plasticity. In this view, it is unclear what role, if any, is carried out by inhibitory interneurons. Indeed, some have argued that inhibitory interneurons are not plastic. Yet numerous recent studies have demonstrated that, similar to excitatory neurons, inhibitory interneurons also undergo long-term plasticity. Here, we discuss the many diverse forms of long-term plasticity that are found at inputs to and outputs from several types of cortical inhibitory interneuron, including their plasticity of intrinsic excitability and their homeostatic plasticity. We explain key plasticity terminology, highlight key interneuron plasticity mechanisms, extract overarching principles and point out implications for healthy brain functionality as well as for neuropathology. We introduce the concept of the plasticitome - the synaptic plasticity counterpart to the genome or the connectome - as well as nomenclature and definitions for dealing with this rich diversity of plasticity. We argue that the great diversity of interneuron plasticity rules is best understood at the circuit level, for example as a way of elucidating how the credit-assignment problem is solved in deep biological neural networks.

Object location learning in mice requires hippocampal somatostatin interneuron activity and is facilitated by mTORC1-mediated long-term potentiation of their excitatory synapses

Hippocampus-dependent learning and memory originate from long-term synaptic changes in hippocampal networks. The activity of CA1 somatostatin interneurons (SOM-INs) during aversive stimulation is necessary for contextual fear memory formation. In addition, mTORC1-dependent long-term potentiation (LTP) of SOM-IN excitatory input synapses from local pyramidal cells (PC-SOM synapses) contributes to the consolidation of fear motivated spatial and contextual memories. Although, it remains unknown if SOM-IN activity and LTP are necessary and sufficient for novelty motivated spatial episodic memory such as the object location memory, and if so when it is required. Here we use optogenetics to examine whether dorsal CA1 SOM-IN activity and LTP are sufficient to regulate object location memory. First, we found that silencing SOM-INs during object location learning impaired memory. Second, optogenetic induction of PC-SOM synapse LTP (TBS_opto) given 30 min before object location training, resulted in facilitation of memory. However, in mice with mTORC1 pathway genetically inactivated in SOM-INs, which blocks PC-SOM synapse LTP, TBS_opto failed to facilitate object location memory. Our results indicate that SOM-IN activity is necessary during object location learning and that optogenetic induction of PC-SOM synapse LTP is sufficient to facilitate consolidation of object location memory. Thus, hippocampal somatostatin interneuron activity is required for object location learning, a hippocampus-dependent form of novelty motivated spatial learning that is facilitated by plasticity at PC-SOM synapses.

Theta patterns of stimulation induce synaptic and intrinsic potentiation in O-LM interneurons

Brain oscillations have long-lasting effects on synaptic and cellular properties. For instance, synaptic stimulation at theta (θ) frequency induces persistent depression of both excitatory synaptic transmission and intrinsic excitability in CA1 principal neurons. However, the incidence of θ activity on synaptic transmission and intrinsic excitability in hippocampal GABAergic interneurons is unclear. We report here the induction of both synaptic and intrinsic potentiation in oriens-lacunosum moleculare (O-LM) interneurons following stimulation of afferent glutamatergic inputs in the θ frequency range (∼5 Hz). Long-term synaptic potentiation (LTP) is induced by synaptic activation of calcium-permeable AMPA receptors (CP-AMPAR), whereas long-term potentiation of intrinsic excitability (LTP-IE) results from the mGluR1-dependent down-regulation of Kv7 voltage-dependent potassium channel and hyperpolarization activated and cyclic nucleotide-gated (HCN) channel through the depletion of phosphatidylinositol-4,5-biphosphate (PIP2). LTP and LTP-IE are reversible, demonstrating that both synaptic and intrinsic changes are bidirectional in O-LM cells. We conclude that synaptic activity at θ frequency induces both synaptic and intrinsic potentiation in O-LM interneurons, i.e., the opposite of what is typically seen in glutamatergic neurons.

Recognition Memory Induces Natural LTP-like Hippocampal Synaptic Excitation and Inhibition

Synaptic plasticity is a cellular process involved in learning and memory by which specific patterns of neural activity adapt the synaptic strength and efficacy of the synaptic transmission. Its induction is governed by fine tuning between excitatory/inhibitory synaptic transmission. In experimental conditions, synaptic plasticity can be artificially evoked at hippocampal CA1 pyramidal neurons by repeated stimulation of Schaffer collaterals. However, long-lasting synaptic modifications studies during memory formation in physiological conditions in freely moving animals are very scarce. Here, to study synaptic plasticity phenomena during recognition memory in the dorsal hippocampus, field postsynaptic potentials (fPSPs) evoked at the CA3–CA1 synapse were recorded in freely moving mice during object-recognition task performance. Paired pulse stimuli were applied to Schaffer collaterals at the moment that the animal explored a new or a familiar object along different phases of the test. Stimulation evoked a complex synaptic response composed of an ionotropic excitatory glutamatergic fEPSP, followed by two inhibitory responses, an ionotropic, GABA_A-mediated fIPSP and a metabotropic, G-protein-gated inwardly rectifying potassium (GirK) channel-mediated fIPSP. Our data showed the induction of LTP-like enhancements for both the glutamatergic and GirK-dependent components of the dorsal hippocampal CA3–CA1 synapse during the exploration of novel but not familiar objects. These results support the contention that synaptic plasticity processes that underlie hippocampal-dependent memory are sustained by fine tuning mechanisms that control excitatory and inhibitory neurotransmission balance.

Inhibitory conductance controls place field dynamics in the hippocampus

Hippocampal place cells receive a disparate collection of excitatory and inhibitory currents that endow them with spatially selective discharges and rhythmic activity. Using a combination of in vivo intracellular and extracellular recordings with opto/chemogenetic manipulations and computational modeling, we investigate the influence of inhibitory and excitatory inputs on CA1 pyramidal cell responses. At the cell bodies, inhibition leads and is stronger than excitation across the entire theta cycle. Pyramidal neurons fire on the ascending phase of theta when released from inhibition. Computational models equipped with the observed conductances reproduce these dynamics. In these models, place field properties are favored when the increased excitation is coupled with a reduction of inhibition within the field. As predicted by our simulations, firing rate within place fields and phase locking to theta are impaired by DREADDs activation of interneurons. Our results indicate that decreased inhibitory conductance is critical for place field expression.

Valero et al. examine the influence of inhibition on place fields. They show that hippocampal neurons are dominated by inhibitory conductances during theta oscillations. A transient increase of excitation and drop of inhibition mediates place field emergence in simulations. Consistently, chemogenetic activation of interneurons deteriorates place cell properties in vivo.

Modulation of GABAergic Synaptic Transmission by NMDA Receptors in the Dorsal Horn of the Spinal Cord

The dorsal horn (DH) of the spinal cord is an important structure involved in the integration of nociceptive messages. Plastic changes in the properties of neuronal networks in the DH underlie the development of analgesia as well as of hyperalgesia and allodynia in acute and chronic pain states. Two key mechanisms are involved in these chronic pain states: increased electrical activities and glutamate release leading to the recruitment of NMDAr and plastic changes in the synaptic inhibition. Although: (1) the balance between excitation and inhibition is known to play a critical role in the spinal network; and (2) plastic changes in spinal excitation and inhibition have been studied separately, the relationship between these two mechanisms has not been investigated in detail. In the present work, we addressed the role of NMDA receptors in the modulation of GABAergic synaptic transmission in the DH network. Using tight-seal whole-cell recordings on adult mice DH neurons, we characterized the effect of NMDAr activation on inhibitory synaptic transmission and more especially on the GABAergic one. Our results show that, in a subset of neurons recorded in lamina II, NMDAr activation facilitates spontaneous and miniature GABAergic synaptic transmission with a target specificity on GABAergic interneurons. In contrast, NMDA reduced the mean amplitude of evoked GABAergic IPSCs. These results show that NMDAr modulate GABAergic transmission by a presynaptic mechanism of action. Using a pharmacological approach, we investigated the composition of NMDAr involved in this modulation of GABAergic synaptic transmission. We found that the NMDA-induced facilitation was mediated by the activation of NMDAr containing GluN2C/D subunits. Altogether, our results bring new insights on nociceptive information processing in the spinal cord network and plastic changes in synaptic inhibition that could underlie the development and maintenance of chronic pain.

Long-term potentiation at pyramidal cell to somatostatin interneuron synapses controls hippocampal network plasticity and memory

Hippocampal somatostatin (SOM) cells are dendrite-projecting inhibitory interneurons. CA1 SOM cells receive major excitatory inputs from pyramidal cells (PC-SOM synapses) which show mGluR1a- and mTORC1-mediated long-term potentiation (LTP). PC-SOM synapse LTP contributes to CA1 network metaplasticity and memory consolidation, but whether it is sufficient to regulate these processes remains unknown. Here we used optogenetic stimulation of CA1 pyramidal cells and whole-cell recordings in slices to show that optogenetic theta-burst stimulation (TBS_opto) produces LTP at PC-SOM synapses. At the network level, we found that TBS_opto differentially regulates metaplasticity of pyramidal cell inputs: enhancing LTP at Schaffer collateral synapses and depressing LTP at temporo-ammonic synapses. At the behavioral level, we uncovered that in vivo TBS_opto regulates learning-induced LTP at PC-SOM synapses, as well as contextual fear memory. Thus, LTP of PC-SOM synapses is a long-term feedback mechanism controlling pyramidal cell synaptic plasticity, sufficient to regulate memory consolidation.

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Optogenetic theta-burst (TBS_opto) induces LTP at PC-SOM synapses

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TBS_opto differentially regulates metaplasticity of pyramidal cell inputs

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In vivo TBS_opto regulates PC-SOM plasticity and contextual fear memory

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PC-SOM synapse LTP grants durable feedback control of network plasticity and memory

Rational designing of oscillatory rhythmicity for memory rescue in plasticity-impaired learning networks

In the brain, oscillatory strength embedded in network rhythmicity is important for processing experiences, and this process is disrupted in certain psychiatric disorders. The use of rhythmic network stimuli can change these oscillations and has shown promise in terms of improving cognitive function, although the underlying mechanisms are poorly understood. Here, we combine a two-layer learning model, with experiments involving genetically modified mice, that provides precise control of experience-driven oscillations by manipulating long-term potentiation of excitatory synapses onto inhibitory interneurons (LTP_E→I). We find that, in the absence of LTP_E→I, impaired network dynamics and memory are rescued by activating inhibitory neurons to augment the power in theta and gamma frequencies, which prevents network overexcitation with less inhibitory rebound. In contrast, increasing either theta or gamma power alone was less effective. Thus, inducing network changes at dual frequencies is involved in memory encoding, indicating a potentially feasible strategy for optimizing network-stimulating therapies.

A Critical Role for γCaMKII in Decoding NMDA Signaling to Regulate AMPA Receptors in Putative Inhibitory Interneurons

CaMKII is essential for long-term potentiation (LTP), a process in which synaptic strength is increased following the acquisition of information. Among the four CaMKII isoforms, γCaMKII is the one that mediates the LTP of excitatory synapses onto inhibitory interneurons (LTP_E→I). However, the molecular mechanism underlying how γCaMKII mediates LTP_E→I remains unclear. Here, we show that γCaMKII is highly enriched in cultured hippocampal inhibitory interneurons and opts to be activated by higher stimulating frequencies in the 10-30 Hz range. Following stimulation, γCaMKII is translocated to the synapse and becomes co-localized with the postsynaptic protein PSD-95. Knocking down γCaMKII prevents the chemical LTP-induced phosphorylation and trafficking of AMPA receptors (AMPARs) in putative inhibitory interneurons, which are restored by overexpression of γCaMKII but not its kinase-dead form. Taken together, these data suggest that γCaMKII decodes NMDAR-mediated signaling and in turn regulates AMPARs for expressing LTP in inhibitory interneurons.

A Simplified Plasticity Model Based on Synaptic Tagging and Capture Theory: Simplified STC

The formation and consolidation of memory play a vital role for survival in an ever-changing environment. In the brain, the change and stabilization of potentiated and depressed synapses are the neural basis of memory formation and maintenance. These changes can be induced by rather short stimuli (only a few seconds or even less) but should then be stable for months or years. Recently, the neural mechanism of conversion from rapid change during the early phase of synaptic plasticity into a stable memory trace in the late phase of synaptic plasticity is more and more clear at the protein and molecular levels, among which synaptic tagging and capture (STC) theory is one of the most popular theories. According to the STC theory, the change and stabilization of synaptic efficiency mainly depend on three processes related to calcium concentration, including synaptic tagging, synthesis of plasticity-related product (PRP), and the capture of PRP by tagged synapse. Based on the STC theory, several computational models are proposed. However, these models hardly take simplicity and biological interpretability into account simultaneously. Here, we propose a simplified STC (SM-STC) model to address this issue. In the SM-STC model, the concentration of calcium ion in each neuronal compartment and synapse is first calculated, and then the tag state of synapse and PRP are updated, and the coupling effect of tagged synapse and PRP is further considered to determine the plasticity state of the synapse, either potentiation or depression. We simulated the Schaffer collaterals pathway of the hippocampus targeting a multicompartment CA1 neuron for several hours of biological time. The results show that the SM-STC model can produce a broad range of experimental phenomena known in the physiological experiments, including long-term potentiation induced by high-frequency stimuli, long-term depression induced by low-frequency stimuli, and cross-capture with two stimuli separated by a delay. Thus, the SM-STC model proposed in this study provides an effective learning rule for brain-like computation on the premise of ensuring biological plausibility and computational efficiency.

Excitatory-Inhibitory Homeostasis and Diaschisis: Tying the Local and Global Scales in the Post-stroke Cortex

Maintaining a balance between excitatory and inhibitory activity is an essential feature of neural networks of the neocortex. In the face of perturbations in the levels of excitation to cortical neurons, synapses adjust to maintain excitatory-inhibitory (EI) balance. In this review, we summarize research on this EI homeostasis in the neocortex, using stroke as our case study, and in particular the loss of excitation to distant cortical regions after focal lesions. Widespread changes following a localized lesion, a phenomenon known as diaschisis, are not only related to excitability, but also observed with respect to functional connectivity. Here, we highlight the main findings regarding the evolution of excitability and functional cortical networks during the process of post-stroke recovery, and how both are related to functional recovery. We show that cortical reorganization at a global scale can be explained from the perspective of EI homeostasis. Indeed, recovery of functional networks is paralleled by increases in excitability across the cortex. These adaptive changes likely result from plasticity mechanisms such as synaptic scaling and are linked to EI homeostasis, providing a possible target for future therapeutic strategies in the process of rehabilitation. In addition, we address the difficulty of simultaneously studying these multiscale processes by presenting recent advances in large-scale modeling of the human cortex in the contexts of stroke and EI homeostasis, suggesting computational modeling as a powerful tool to tie the meso- and macro-scale processes of recovery in stroke patients.

Sensory coding and contrast invariance emerge from the control of plastic inhibition over emergent selectivity

Visual stimuli are represented by a highly efficient code in the primary visual cortex, but the development of this code is still unclear. Two distinct factors control coding efficiency: Representational efficiency, which is determined by neuronal tuning diversity, and metabolic efficiency, which is influenced by neuronal gain. How these determinants of coding efficiency are shaped during development, supported by excitatory and inhibitory plasticity, is only partially understood. We investigate a fully plastic spiking network of the primary visual cortex, building on phenomenological plasticity rules. Our results suggest that inhibitory plasticity is key to the emergence of tuning diversity and accurate input encoding. We show that inhibitory feedback (random and specific) increases the metabolic efficiency by implementing a gain control mechanism. Interestingly, this led to the spontaneous emergence of contrast-invariant tuning curves. Our findings highlight that (1) interneuron plasticity is key to the development of tuning diversity and (2) that efficient sensory representations are an emergent property of the resulting network.

Synaptic plasticity is crucial for the development of efficient input representation in the different sensory cortices, such as the primary visual cortex. Efficient visual representation is determined by two factors: representational efficiency, i.e. how many different input features can be represented, and metabolic efficiency, i.e. how many spikes are required to represent a specific feature. Previous research has pointed out the importance of plasticity at excitatory synapses to achieve high representational efficiency and feedback inhibition as a gain control mechanism for controlling metabolic efficiency. However, it is only partially understood how the influence of inhibitory plasticity on excitatory plasticity can lead to an efficient representation. Using a spiking neural network, we show that plasticity at feed-forward and feedback inhibitory synapses is necessary for the emergence of well-distributed neuronal selectivity to improve representational efficiency. Further, the emergent balance between excitatory and inhibitory currents improves the metabolic efficiency, and leads to contrast-invariant tuning as an inherent network property. Extending previous work, our simulation results highlight the importance of plasticity at inhibitory synapses.

Endocannabinoids Tune Intrinsic Excitability in O-LM Interneurons by Direct Modulation of Postsynaptic Kv7 Channels

KCNQ-Kv7 channels are found at the axon initial segment of pyramidal neurons, where they control cell firing and membrane potential. In oriens lacunosum moleculare (O-LM) interneurons, these channels are mainly expressed in the dendrites, suggesting a peculiar function of Kv7 channels in these neurons. Here, we show that Kv7 channel activity is upregulated following induction of presynaptic long-term synaptic depression (LTD) in O-LM interneurons from rats of both sex, thus resulting in a synergistic long-term depression of intrinsic excitability (LTD-IE). Both LTD and LTD-IE involve endocannabinoid (eCB) biosynthesis for induction. However, although LTD is dependent on cannabinoid type 1 receptors, LTD-IE is not. Molecular modeling shows a strong interaction of eCBs with Kv7.2/3 channel, suggesting a persistent action of these lipids on Kv7 channel activity. Our data thus unveil a major role for eCB synthesis in triggering both synaptic and intrinsic depression in O-LM interneurons.SIGNIFICANCE STATEMENT In principal cells, Kv7 channels are essentially located at the axon initial segment. In contrast, in O-LM interneurons, Kv7 channels are highly expressed in the dendrites, suggesting a singular role of these channels in O-LM cell function. Here, we show that LTD of excitatory inputs in O-LM interneurons is associated with an upregulation of Kv7 channels, thus resulting in a synergistic LTD of LTD-IE. Both forms of plasticity are mediated by the biosynthesis of eCBs. Stimulation of CB1 receptors induces LTD, whereas the direct interaction of eCBs with Kv7 channels induces LTD-IE. Our results thus provide a previously unexpected involvement of eCBs in long-lasting plasticity of intrinsic excitability in GABAergic interneurons.

GABAergic microcircuitry of fear memory encoding

The paradigm of fear conditioning is largely responsible for our current understanding of how memories are encoded at the cellular level. Its most fundamental underlying mechanism is considered to be plasticity of synaptic connections between excitatory projection neurons (PNs). However, recent studies suggest that while PNs execute critical memory functions, their activity at key stages of learning and recall is extensively orchestrated by a diverse array of GABAergic interneurons (INs). Here we review the contributions of genetically-defined INs to processing of threat-related stimuli in fear conditioning, with a particular focus on how synaptic interactions within interconnected networks of INs modulates PN activity through both inhibition and disinhibition. Furthermore, we discuss accumulating evidence that GABAergic microcircuits are an important locus for synaptic plasticity during fear learning and therefore a viable substrate for long-term memory. These findings suggest that further investigation of INs could unlock unique conceptual insights into the organization and function of fear memory networks.

Spike frequency adaptation supports network computations on temporally dispersed information

For solving tasks such as recognizing a song, answering a question, or inverting a sequence of symbols, cortical microcircuits need to integrate and manipulate information that was dispersed over time during the preceding seconds. Creating biologically realistic models for the underlying computations, especially with spiking neurons and for behaviorally relevant integration time spans, is notoriously difficult. We examine the role of spike frequency adaptation in such computations and find that it has a surprisingly large impact. The inclusion of this well-known property of a substantial fraction of neurons in the neocortex - especially in higher areas of the human neocortex - moves the performance of spiking neural network models for computations on network inputs that are temporally dispersed from a fairly low level up to the performance level of the human brain.

Balanced networks under spike-time dependent plasticity

The dynamics of local cortical networks are irregular, but correlated. Dynamic excitatory–inhibitory balance is a plausible mechanism that generates such irregular activity, but it remains unclear how balance is achieved and maintained in plastic neural networks. In particular, it is not fully understood how plasticity induced changes in the network affect balance, and in turn, how correlated, balanced activity impacts learning. How do the dynamics of balanced networks change under different plasticity rules? How does correlated spiking activity in recurrent networks change the evolution of weights, their eventual magnitude, and structure across the network? To address these questions, we develop a theory of spike–timing dependent plasticity in balanced networks. We show that balance can be attained and maintained under plasticity–induced weight changes. We find that correlations in the input mildly affect the evolution of synaptic weights. Under certain plasticity rules, we find an emergence of correlations between firing rates and synaptic weights. Under these rules, synaptic weights converge to a stable manifold in weight space with their final configuration dependent on the initial state of the network. Lastly, we show that our framework can also describe the dynamics of plastic balanced networks when subsets of neurons receive targeted optogenetic input.

Animals are able to learn complex tasks through changes in individual synapses between cells. Such changes lead to the coevolution of neural activity patterns and the structure of neural connectivity, but the consequences of these interactions are not fully understood. We consider plasticity in model neural networks which achieve an average balance between the excitatory and inhibitory synaptic inputs to different cells, and display cortical–like, irregular activity. We extend the theory of balanced networks to account for synaptic plasticity and show which rules can maintain balance, and which will drive the network into a different state. This theory of plasticity can provide insights into the relationship between stimuli, network dynamics, and synaptic circuitry.

Probing the Brain-Body Connection Using Transcranial Magnetic Stimulation (TMS): Validating a Promising Tool to Provide Biomarkers of Neuroplasticity and Central Nervous System Function

Transcranial magnetic stimulation (TMS) is a non-invasive method used to investigate neurophysiological integrity of the human neuromotor system. We describe in detail, the methodology of a single pulse TMS protocol that was performed in a large cohort of people (n = 110) with multiple sclerosis (MS). The aim was to establish and validate a core-set of TMS variables that predicted typical MS clinical outcomes: walking speed, hand dexterity, fatigue, and cognitive processing speed. We provide a brief and simple methodological pipeline to examine excitatory and inhibitory corticospinal mechanisms in MS that map to clinical status. Delayed and longer ipsilateral silent period (a measure of transcallosal inhibition; the influence of one brain hemisphere's activity over the other), longer cortical silent period (suggestive of greater corticospinal inhibition via GABA) and higher resting motor threshold (lower corticospinal excitability) most strongly related to clinical outcomes, especially when measured in the hemisphere corresponding to the weaker hand. Greater interhemispheric asymmetry (imbalance between hemispheres) correlated with poorer performance in the greatest number of clinical outcomes. We also show, not surprisingly, that TMS variables related more strongly to motor outcomes than non-motor outcomes. As it was validated in a large sample of patients with varying severities of central nervous system dysfunction, the protocol described herein can be used by investigators and clinicians alike to investigate the role of TMS as a biomarker in MS and other central nervous system disorders.

Brief Sensory Deprivation Triggers Cell Type-Specific Structural and Functional Plasticity in Olfactory Bulb Neurons

Can alterations in experience trigger different plastic modifications in neuronal structure and function, and if so, how do they integrate at the cellular level? To address this question, we interrogated circuitry in the mouse olfactory bulb responsible for the earliest steps in odor processing. We induced experience-dependent plasticity in mice of either sex by blocking one nostril for one day, a minimally invasive manipulation that leaves the sensory organ undamaged and is akin to the natural transient blockage suffered during common mild rhinal infections. We found that such brief sensory deprivation produced structural and functional plasticity in one highly specialized bulbar cell type: axon-bearing dopaminergic neurons in the glomerular layer. After 24 h naris occlusion, the axon initial segment (AIS) in bulbar dopaminergic neurons became significantly shorter, a structural modification that was also associated with a decrease in intrinsic excitability. These effects were specific to the AIS-positive dopaminergic subpopulation because no experience-dependent alterations in intrinsic excitability were observed in AIS-negative dopaminergic cells. Moreover, 24 h naris occlusion produced no structural changes at the AIS of bulbar excitatory neurons, mitral/tufted and external tufted cells, nor did it alter their intrinsic excitability. By targeting excitability in one specialized dopaminergic subpopulation, experience-dependent plasticity in early olfactory networks might act to fine-tune sensory processing in the face of continually fluctuating inputs.SIGNIFICANCE STATEMENT Sensory networks need to be plastic so they can adapt to changes in incoming stimuli. To see how cells in mouse olfactory circuits can change in response to sensory challenges, we blocked a nostril for just one day, a naturally relevant manipulation akin to the deprivation that occurs with a mild cold. We found that this brief deprivation induces forms of axonal and intrinsic functional plasticity in one specific olfactory bulb cell subtype: axon-bearing dopaminergic interneurons. In contrast, intrinsic properties of axon-lacking bulbar dopaminergic neurons and neighboring excitatory neurons remained unchanged. Within the same sensory circuits, specific cell types can therefore make distinct plastic changes in response to an ever-changing external landscape.

Gating of hippocampal rhythms and memory by synaptic plasticity in inhibitory interneurons

Mental experiences can become long-term memories if the hippocampal activity patterns that encode them are broadcast during network oscillations. The activity of inhibitory neurons is essential for generating these neural oscillations, but molecular control of this dynamic process during learning remains unknown. Here, we show that hippocampal oscillatory strength positively correlates with excitatory monosynaptic drive onto inhibitory neurons (E→I) in freely behaving mice. To establish a causal relationship between them, we identified γCaMKII as the long-sought mediator of long-term potentiation for E→I synapses (LTP_E→I), which enabled the genetic manipulation of experience-dependent E→I synaptic input/plasticity. Deleting γCaMKII in parvalbumin interneurons selectively eliminated LTP_E→I and disrupted experience-driven strengthening in theta and gamma rhythmicity. Behaviorally, this manipulation impaired long-term memory, for which the kinase activity of γCaMKII was required. Taken together, our data suggest that E→I synaptic plasticity, exemplified by LTP_E→I, plays a gatekeeping role in tuning experience-dependent brain rhythms and mnemonic function.

Nucleus accumbens fast-spiking interneurons in motivational and addictive behaviors

The development of drug addiction is associated with functional adaptations within the reward circuitry, within which the nucleus accumbens (NAc) is anatomically positioned as an interface between motivational salience and behavioral output. The functional output of NAc is profoundly altered after exposure to drugs of abuse, and some of the functional changes continue to evolve during drug abstinence, contributing to numerous emotional and motivational alterations related drug taking, seeking, and relapse. As in most brain regions, the functional output of NAc is critically dependent on the dynamic interaction between excitation and inhibition. One of the most prominent sources of inhibition within the NAc arises from fast-spiking interneurons (FSIs). Each NAc FSI innervates hundreds of principal neurons, and orchestrates population activity through its powerful and sustained feedforward inhibition. While the role of NAc FSIs in the context of drug addiction remains poorly understood, emerging evidence suggests that FSIs and FSI-mediated local circuits are key targets for drugs of abuse to tilt the functional output of NAc toward a motivational state favoring drug seeking and relapse. In this review, we discuss recent findings and our conceptualization about NAc FSI-mediated regulation of motivated and cocaine-induced behaviors. We hope that the conceptual framework proposed in this review may provide a useful guidance for ongoing and future studies to determine how FSIs influence the function of NAc and related reward circuits, ultimately leading to addictive behaviors.

Mechanisms and plasticity of chemogenically induced interneuronal suppression of principal cells

How do firing patterns in a cortical circuit change when inhibitory neurons are excited? We virally expressed an excitatory designer receptor exclusively activated by a designer drug (Gq-DREADD) in all inhibitory interneuron types of the CA1 region of the hippocampus in the rat. While clozapine N-oxide (CNO) activation of interneurons suppressed firing of pyramidal cells, unexpectedly the majority of interneurons also decreased their activity. CNO-induced inhibition decreased over repeated sessions, which we attribute to long-term synaptic plasticity between interneurons and pyramidal cells. Individual interneurons did not display sustained firing but instead transiently enhanced their activity, interleaved with suppression of others. The power of the local fields in the theta band was unaffected, while power at higher frequencies was attenuated, likely reflecting reduced pyramidal neuron spiking. The incidence of sharp wave ripples decreased but the surviving ripples were associated with stronger population firing compared with the control condition. These findings demonstrate that DREADD activation of interneurons brings about both short-term and long-term circuit reorganization, which should be taken into account in the interpretation of chemogenic effects on behavior.

Experience-regulated molecular mechanisms in cortical GABAergic interneurons: from cellular functions to control over circuit plasticity

Experience-induced changes in GABAergic interneurons (INs) are thought to control the plasticity of neural circuits in the developing and adult cortex. However, it remains poorly understood how experience and the ensuing neuronal activity alter the properties and connectivity of specific IN subtypes and how these cellular changes, in turn, control the plasticity of cortical circuits. Here, I discuss recent experimental and theoretical studies that point to specific experience-induced changes in select IN subtypes as central regulators of plasticity in the cortex. In particular, I focus on the recent identification of several experience-regulated secreted molecules that modulate specific sets of synapses in IN subtypes. I argue that elucidating these molecular mechanisms will allow us to test experimentally the predictions made by theoretical models about the plasticity functions of specific IN subtypes.

Inhibitory interneurons in a brainstem circuit adjust their inhibitory motifs to process multimodal input

KEY POINTS

Inhibitory-interneuron networks, consisting of multiple forms of circuit motifs including reciprocal (inhibitory interneurons inhibiting other interneurons) and feedforward (inhibitory interneurons inhibiting principal neurons) connections, are crucial in processing sensory information. The present study applies a statistical method to in vivo multichannel spike trains of dorsal cochlear nucleus neurons to disentangle reciprocal and feedforward-inhibitory motifs. After inducing input-specific plasticity, reciprocal and feedforward inhibition are found to be differentially regulated, and the combined effect synergistically modulates circuit output. The findings highlight the interplay among different circuit motifs as a key element in neural computation.

ABSTRACT

Inhibitory interneurons play an essential role in neural computations by utilizing a combination of reciprocal (interneurons inhibiting each other) and feedforward (interneuron inhibiting the principal neuron) inhibition to process information. To disentangle the interplay between the two inhibitory-circuit motifs and understand their effects on the circuit output, in vivo recordings were made from the guinea pig dorsal cochlear nucleus, a cerebellar-like brainstem circuit. Spikes from inhibitory interneurons (cartwheel cell) and principal output neurons (fusiform cell) were compared before and after manipulating their common multimodal input. Using a statistical model based on the Cox method of modulated renewal process of spike train influence, reciprocal- and feedforward-inhibition motifs were quantified. In response to altered multimodal input, reciprocal inhibition was strengthened while feedforward inhibition was weakened, and the two motifs combined to modulate fusiform cell output and acoustic-driven responses. These findings reveal the cartwheel cell's role in auditory and multimodal processing, as well as illustrated the balance between different inhibitory-circuit motifs as a key element in neural computation.

Long-term potentiation of glycinergic synapses by semi-natural stimulation patterns during tonotopic map refinement

Before the onset of hearing, cochlea-generated patterns of spontaneous spike activity drive the maturation of central auditory circuits. In the glycinergic sound localization pathway from the medial nucleus of the trapezoid body (MNTB) to the lateral superior olive (LSO) this spontaneous activity guides the strengthening and silencing of synapses which underlies tonotopic map refinement. However, the mechanisms by which patterned activity regulates synaptic refinement in the MNTB-LSO pathway are still poorly understood. To address this question, we recorded from LSO neurons in slices from prehearing mice while stimulating MNTB afferents with stimulation patterns that mimicked those present in vivo. We found that these semi-natural stimulation patterns reliably elicited a novel form of long-term potentiation (LTP) of MNTB-LSO synapses. Stimulation patterns that lacked the characteristic high-frequency (200 Hz) component of prehearing spike activity failed to elicit potentiation. LTP was calcium dependent, required the activation of both g-protein coupled GABA_B and metabotropic glutamate receptors and involved an increase in postsynaptic glycine receptor-mediated currents. Our results provide a possible mechanism linking spontaneous spike bursts to tonotopic map refinement and further highlight the importance of the co-release of GABA and glutamate from immature glycinergic MNTB terminals.

Interneuron-specific plasticity at parvalbumin and somatostatin inhibitory synapses onto CA1 pyramidal neurons shapes hippocampal output

The formation and maintenance of spatial representations within hippocampal cell assemblies is strongly dictated by patterns of inhibition from diverse interneuron populations. Although it is known that inhibitory synaptic strength is malleable, induction of long-term plasticity at distinct inhibitory synapses and its regulation of hippocampal network activity is not well understood. Here, we show that inhibitory synapses from parvalbumin and somatostatin expressing interneurons undergo long-term depression and potentiation respectively (PV-iLTD and SST-iLTP) during physiological activity patterns. Both forms of plasticity rely on T-type calcium channel activation to confer synapse specificity but otherwise employ distinct mechanisms. Since parvalbumin and somatostatin interneurons preferentially target perisomatic and distal dendritic regions respectively of CA1 pyramidal cells, PV-iLTD and SST-iLTP coordinate a reprioritisation of excitatory inputs from entorhinal cortex and CA3. Furthermore, circuit-level modelling reveals that PV-iLTD and SST-iLTP cooperate to stabilise place cells while facilitating representation of multiple unique environments within the hippocampal network.

Inhibitory interneuron subtypes differentially control place cell representations in CA1. Here, the authors show that parvalbumin and somatostatin interneuron synapses onto CA1 pyramidal neurons exhibit distinct plasticity mechanisms and incorporating this insight into circuit-level modeling leads to stable place cell representations.

Network control through coordinated inhibition

Coordinated excitatory and inhibitory activity is required for proper brain functioning. Recent computational and experimental studies have demonstrated that activity patterns in recurrent cortical networks are dominated by inhibition. Whereas previous studies have suggested that inhibitory plasticity is important for homeostatic control, this new framework puts inhibition in the driver's seat. Complex neuronal networks in the brain comprise many configurations in parallel, controlled by external and internal 'switches'. Context-dependent modulation and plasticity of inhibitory connections play a key role in memory and learning. It is therefore important to realize that synaptic plasticity is often multisynaptic and that a proper balance between excitation and inhibition is not fixed, but depends on context and activity level.

The ins and outs of inhibitory synaptic plasticity: Neuron types, molecular mechanisms and functional roles

GABAergic interneurons are highly diverse, and their synaptic outputs express various forms of plasticity. Compelling evidence indicates that activity-dependent changes of inhibitory synaptic transmission play a significant role in regulating neural circuits critically involved in learning and memory and circuit refinement. Here, we provide an updated overview of inhibitory synaptic plasticity with a focus on the hippocampus and neocortex. To illustrate the diversity of inhibitory interneurons, we discuss the case of two highly divergent interneuron types, parvalbumin-expressing basket cells and neurogliaform cells, which support unique roles on circuit dynamics. We also present recent progress on the molecular mechanisms underlying long-term, activity-dependent plasticity of fast inhibitory transmission. Lastly, we discuss the role of inhibitory synaptic plasticity in neuronal circuits' function. The emerging picture is that inhibitory synaptic transmission in the CNS is extremely diverse, undergoes various mechanistically distinct forms of plasticity and contributes to a much more refined computational role than initially thought. Both the remarkable diversity of inhibitory interneurons and the various forms of plasticity expressed by GABAergic synapses provide an amazingly rich inhibitory repertoire that is central to a variety of complex neural circuit functions, including memory.

Activity-dependent tuning of intrinsic excitability in mouse and human neurogliaform cells

The ability to modulate the efficacy of synaptic communication between neurons constitutes an essential property critical for normal brain function. Animal models have proved invaluable in revealing a wealth of diverse cellular mechanisms underlying varied plasticity modes. However, to what extent these processes are mirrored in humans is largely uncharted thus questioning their relevance in human circuit function. In this study, we focus on neurogliaform cells, that possess specialized physiological features enabling them to impart a widespread inhibitory influence on neural activity. We demonstrate that this prominent neuronal subtype, embedded in both mouse and human neural circuits, undergo remarkably similar activity-dependent modulation manifesting as epochs of enhanced intrinsic excitability. In principle, these evolutionary conserved plasticity routes likely tune the extent of neurogliaform cell mediated inhibition thus constituting canonical circuit mechanisms underlying human cognitive processing and behavior.

A Model for Structured Information Representation in Neural Networks of the Brain

Humans can reason at an abstract level and structure information into abstract categories, but the underlying neural processes have remained unknown. Recent experimental data provide the hint that this is likely to involve specific subareas of the brain from which structural information can be decoded. Based on this data, we introduce the concept of assembly projections, a general principle for attaching structural information to content in generic networks of spiking neurons. According to the assembly projections principle, structure-encoding assemblies emerge and are dynamically attached to content representations through Hebbian plasticity mechanisms. This model provides the basis for explaining a number of experimental data and provides a basis for modeling abstract computational operations of the brain.

Perceptron Learning and Classification in a Modeled Cortical Pyramidal Cell

The perceptron learning algorithm and its multiple-layer extension, the backpropagation algorithm, are the foundations of the present-day machine learning revolution. However, these algorithms utilize a highly simplified mathematical abstraction of a neuron; it is not clear to what extent real biophysical neurons with morphologically-extended non-linear dendritic trees and conductance-based synapses can realize perceptron-like learning. Here we implemented the perceptron learning algorithm in a realistic biophysical model of a layer 5 cortical pyramidal cell with a full complement of non-linear dendritic channels. We tested this biophysical perceptron (BP) on a classification task, where it needed to correctly binarily classify 100, 1,000, or 2,000 patterns, and a generalization task, where it was required to discriminate between two "noisy" patterns. We show that the BP performs these tasks with an accuracy comparable to that of the original perceptron, though the classification capacity of the apical tuft is somewhat limited. We concluded that cortical pyramidal neurons can act as powerful classification devices.

Nitric Oxide Signaling Strengthens Inhibitory Synapses of Cerebellar Molecular Layer Interneurons through a GABARAP-Dependent Mechanism

Nitric oxide (NO) is an important signaling molecule that fulfills diverse functional roles as a neurotransmitter or diffusible second messenger in the developing and adult CNS. Although the impact of NO on different behaviors such as movement, sleep, learning, and memory has been well documented, the identity of its molecular and cellular targets is still an area of ongoing investigation. Here, we identify a novel role for NO in strengthening inhibitory GABA_A receptor-mediated transmission in molecular layer interneurons of the mouse cerebellum. NO levels are elevated by the activity of neuronal NO synthase (nNOS) following Ca²⁺ entry through extrasynaptic NMDA-type ionotropic glutamate receptors (NMDARs). NO activates protein kinase G with the subsequent production of cGMP, which prompts the stimulation of NADPH oxidase and protein kinase C (PKC). The activation of PKC promotes the selective strengthening of α3-containing GABA_ARs synapses through a GΑΒΑ receptor-associated protein-dependent mechanism. Given the widespread but cell type-specific expression of the NMDAR/nNOS complex in the mammalian brain, our data suggest that NMDARs may uniquely strengthen inhibitory GABAergic transmission in these cells through a novel NO-mediated pathway.SIGNIFICANCE STATEMENT Long-term changes in the efficacy of GABAergic transmission is mediated by multiple presynaptic and postsynaptic mechanisms. A prominent pathway involves crosstalk between excitatory and inhibitory synapses whereby Ca²⁺-entering through postsynaptic NMDARs promotes the recruitment and strengthening of GABA_A receptor synapses via Ca²⁺/calmodulin-dependent protein kinase II. Although Ca²⁺ transport by NMDARs is also tightly coupled to nNOS activity and NO production, it has yet to be determined whether this pathway affects inhibitory synapses. Here, we show that activation of NMDARs trigger a NO-dependent pathway that strengthens inhibitory GABAergic synapses of cerebellar molecular layer interneurons. Given the widespread expression of NMDARs and nNOS in the mammalian brain, we speculate that NO control of GABAergic synapse efficacy may be more widespread than has been appreciated.

Effect of interpopulation spike-timing-dependent plasticity on synchronized rhythms in neuronal networks with inhibitory and excitatory populations

We consider a two-population network consisting of both inhibitory (I) interneurons and excitatory (E) pyramidal cells. This I-E neuronal network has adaptive dynamic I to E and E to I interpopulation synaptic strengths, governed by interpopulation spike-timing-dependent plasticity (STDP). In previous works without STDPs, fast sparsely synchronized rhythms, related to diverse cognitive functions, were found to appear in a range of noise intensity D for static synaptic strengths. Here, by varying D, we investigate the effect of interpopulation STDPs on fast sparsely synchronized rhythms that emerge in both the I- and the E-populations. Depending on values of D, long-term potentiation (LTP) and long-term depression (LTD) for population-averaged values of saturated interpopulation synaptic strengths are found to occur. Then, the degree of fast sparse synchronization varies due to effects of LTP and LTD. In a broad region of intermediate D, the degree of good synchronization (with higher synchronization degree) becomes decreased, while in a region of large D, the degree of bad synchronization (with lower synchronization degree) gets increased. Consequently, in each I- or E-population, the synchronization degree becomes nearly the same in a wide range of D (including both the intermediate and the large D regions). This kind of "equalization effect" is found to occur via cooperative interplay between the average occupation and pacing degrees of spikes (i.e., the average fraction of firing neurons and the average degree of phase coherence between spikes in each synchronized stripe of spikes in the raster plot of spikes) in fast sparsely synchronized rhythms. Finally, emergences of LTP and LTD of interpopulation synaptic strengths (leading to occurrence of equalization effect) are intensively investigated via a microscopic method based on the distributions of time delays between the pre- and the post-synaptic spike times.

Neural Correlates of Learning Pure Tones or Natural Sounds in the Auditory Cortex

Associative learning of pure tones is known to cause tonotopic map expansion in the auditory cortex (ACx), but the function this plasticity sub-serves is unclear. We developed an automated training platform called the “Educage,” which was used to train mice on a go/no-go auditory discrimination task to their perceptual limits, for difficult discriminations among pure tones or natural sounds. Spiking responses of excitatory and inhibitory parvalbumin (PV⁺) L2/3 neurons in mouse ACx revealed learning-induced overrepresentation of the learned frequencies, as expected from previous literature. The coordinated plasticity of excitatory and inhibitory neurons supports a role for PV⁺ neurons in homeostatic maintenance of excitation–inhibition balance within the circuit. Using a novel computational model to study auditory tuning curves, we show that overrepresentation of the learned tones does not necessarily improve discrimination performance of the network to these tones. In a separate set of experiments, we trained mice to discriminate among natural sounds. Perceptual learning of natural sounds induced “sparsening” and decorrelation of the neural response, consequently improving discrimination of these complex sounds. This signature of plasticity in A1 highlights its role in coding natural sounds.

Preserving the balance: diverse forms of long-term GABAergic synaptic plasticity

Cellular mechanisms that regulate the interplay of synaptic excitation and inhibition are thought to be central to the functional stability of healthy neuronal circuits. A growing body of literature demonstrates the capacity for inhibitory GABAergic synapses to exhibit long-term plasticity in response to changes in neuronal activity. Here, we review this expanding field of research, focusing on the diversity of mechanisms that link glutamatergic signalling, postsynaptic action potentials and inhibitory synaptic strength. Several lines of evidence indicate that multiple, parallel forms of plasticity serve to regulate activity at both the input and output domains of individual neurons. Overall, these varied phenomena serve to promote both stability and flexibility over the life of the organism.

The regulation of glutamic acid decarboxylases in GABA neurotransmission in the brain

Gamma-aminobutyric acid (GABA) is the main inhibitory neurotransmitter that is required for the control of synaptic excitation/inhibition and neural oscillation. GABA is synthesized by glutamic acid decarboxylases (GADs) that are widely distributed and localized to axon terminals of inhibitory neurons as well as to the soma and, to a lesser extent, dendrites. The expression and activity of GADs is highly correlated with GABA levels and subsequent GABAergic neurotransmission at the inhibitory synapse. Dysregulation of GADs has been implicated in various neurological disorders including epilepsy and schizophrenia. Two isoforms of GADs, GAD67 and GAD65, are expressed from separate genes and have different regulatory processes and molecular properties. This review focuses on the recent advances in understanding the structure of GAD, its transcriptional regulation and post-transcriptional modifications in the central nervous system. This may provide insights into the pathological mechanisms underlying neurological diseases that are associated with GAD dysfunction.

Progressive Circuit Changes during Learning and Disease

A critical step toward understanding cognition, learning, and brain dysfunction will be identification of the underlying cellular computations that occur in and across discrete brain areas, as well as how they are progressively altered by experience or disease. These computations will be revealed by targeted analyses of the neurons that perform these calculations, defined not only by their firing properties but also by their molecular identity and how they are wired within the local and broad-scale network of the brain. New studies that take advantage of sophisticated genetic tools for cell-type-specific identification and control are revealing how learning and neurological disorders initiate and successively change the properties of defined neural circuits. Understanding the temporal sequence of adaptive or pathological synaptic changes across multiple synapses within a network will shed light into how small-scale neural circuits contribute to higher cognitive functions during learning and disease.

Structural and Functional Remodeling of Amygdala GABAergic Synapses in Associative Fear Learning

Associative learning is thought to involve different forms of activity-dependent synaptic plasticity. Although previous studies have mostly focused on learning-related changes occurring at excitatory glutamatergic synapses, we found that associative learning, such as fear conditioning, also entails long-lasting functional and structural plasticity of GABAergic synapses onto pyramidal neurons of the murine basal amygdala. Fear conditioning-mediated structural remodeling of GABAergic synapses was associated with a change in mIPSC kinetics and an increase in the fraction of synaptic benzodiazepine-sensitive (BZD) GABA_A receptors containing the α2 subunit without altering the intrasynaptic distribution and overall amount of BZD-GABA_A receptors. These structural and functional synaptic changes were partly reversed by extinction training. These findings provide evidence that associative learning, such as Pavlovian fear conditioning and extinction, sculpts inhibitory synapses to regulate inhibition of active neuronal networks, a process that may tune amygdala circuit responses to threats.

Regulation of Hippocampal Memory by mTORC1 in Somatostatin Interneurons

Translational control of long-term synaptic plasticity via Mechanistic Target Of Rapamycin Complex 1 (mTORC1) is crucial for hippocampal learning and memory. The role of mTORC1 is well characterized in excitatory principal cells but remains largely unaddressed in inhibitory interneurons. Here, we used cell-type-specific conditional knock-out strategies to alter mTORC1 function selectively in somatostatin (SOM) inhibitory interneurons (SOM-INs). We found that, in male mice, upregulation and downregulation of SOM-IN mTORC1 activity bidirectionally regulates contextual fear and spatial memory consolidation. Moreover, contextual fear learning induced a metabotropic glutamate receptor type 1 (mGluR1)-mediated late long-term potentiation (LTP) of excitatory input synapses onto hippocampal SOM-INs that was dependent on mTORC1. Finally, the induction protocol for mTORC1-mediated late-LTP in SOM-INs regulated Schaffer collateral pathway LTP in pyramidal neurons. Therefore, mTORC1 activity in somatostatin interneurons contributes to learning-induced persistent plasticity of their excitatory synaptic inputs and hippocampal memory consolidation, uncovering a role of mTORC1 in inhibitory circuits for memory.SIGNIFICANCE STATEMENT Memory consolidation necessitates synthesis of new proteins. Mechanistic Target Of Rapamycin Complex 1 (mTORC1) signaling is crucial for translational control involved in long-term memory and in late long-term potentiation (LTP). This is well described in principal glutamatergic pyramidal cells but poorly understood in GABAergic inhibitory interneurons. Here, we show that mTORC1 activity in somatostatin interneurons, a major subclass of GABAergic cells, is important to modulate long-term memory strength and precision. Furthermore, mTORC1 was necessary for learning-induced persistent LTP at excitatory inputs of somatostatin interneurons that depends on type I metabotropic glutamatergic receptors in the hippocampus. This effect was consistent with a newly described role of these interneurons in the modulation of LTP at Schaffer collateral synapses onto pyramidal cells.

A Critical Role of Inhibition in Temporal Processing Maturation in the Primary Auditory Cortex

Faithful representation of sound envelopes in primary auditory cortex (A1) is vital for temporal processing and perception of natural sounds. However, the emergence of cortical temporal processing mechanisms during development remains poorly understood. Although cortical inhibition has been proposed to play an important role in this process, direct in-vivo evidence has been lacking. Using loose-patch recordings in rat A1 immediately after hearing onset, we found that stimulus-following ability in fast-spiking neurons was significantly better than in regular-spiking (RS) neurons. In-vivo whole-cell recordings of RS neurons revealed that inhibition in the developing A1 demonstrated much weaker adaptation to repetitive stimuli than in adult A1. Furthermore, inhibitory synaptic inputs were of longer duration than observed in vitro and in adults. Early in development, overlap of the prolonged inhibition evoked by 2 closely following stimuli disrupted the classical temporal sequence between excitation and inhibition, resulting in slower following capacity. During maturation, inhibitory duration gradually shortened accompanied by an improving temporal following ability of RS neurons. Both inhibitory duration and stimulus-following ability demonstrated exposure-based plasticity. These results demonstrate the role of inhibition in setting the pace for experience-dependent maturation of temporal processing in the auditory cortex.

Input-Specific NMDAR-Dependent Potentiation of Dendritic GABAergic Inhibition

Preservation of a balance between synaptic excitation and inhibition is critical for normal brain function. A number of homeostatic cellular mechanisms have been suggested to play a role in maintaining this balance, including long-term plasticity of GABAergic inhibitory synapses. Many previous studies have demonstrated a coupling of postsynaptic spiking with modification of perisomatic inhibition. Here, we demonstrate that activation of NMDA-type glutamate receptors leads to input-specific long-term potentiation of dendritic inhibition mediated by somatostatin-expressing interneurons. This form of plasticity is expressed postsynaptically and requires both CaMKIIα and the β2 subunit of the GABA-A receptor. Importantly, this process may function to preserve dendritic inhibition, as genetic deletion of NMDAR signaling results in a selective weakening of dendritic inhibition. Overall, our results reveal a new mechanism for linking excitatory and inhibitory input in neuronal dendrites and provide novel insight into the homeostatic regulation of synaptic transmission in cortical circuits.