Heterosynaptic Plasticity Determines the Set Point for Cortical Excitatory-Inhibitory Balance

Lateralized local circuit tuning in female mouse auditory cortex

Most offspring are born helpless, requiring intense caregiving from parents especially during the first few days of neonatal life. For many species, infant cries are a primary signal used by parents to provide caregiving. Previously we and others documented how maternal left auditory cortex rapidly becomes sensitized to pup calls over hours of parental experience, enabled by oxytocin. The speed and robustness of this maternal plasticity suggests cortical pre-tuning or initial bias for pup call stimulus features. Here we examine the circuit basis of left-lateralized tuning to vocalization features with whole-cell recordings in brain slices. We found that layer 2/3 pyramidal cells of female left auditory cortex show selective suppression of inhibitory inputs with repeated stimulation at the fundamental pup call rate (inter-stimulus interval ∼150 msec) in pup-naïve females and expanded with maternal experience. However, optogenetic stimulation of cortical inhibitory cells showed that inputs from somatostatin-positive and oxytocin-receptor-expressing interneurons were less suppressed at these rates. This suggested that disynaptic inhibition rather than monosynaptic depression was a major mechanism underlying pre-tuning of cortical excitatory neurons, confirmed with simulations. Thus cortical interneuron specializations can augment neuroplasticity mechanisms to ensure fast appropriate caregiving in response to infant cries.

Pleiotropic neurotransmitters: neurotransmitter-receptor crosstalk regulates excitation-inhibition balance in social brain functions and pathologies

Neuronal excitation-inhibition (E/I) balance is essential for maintaining neuronal stability and proper brain functioning. Disruptions in this balance are implicated in various neurological disorders, including autism spectrum disorder, schizophrenia and epilepsy. The E/I balance is thought to be primarily mediated by intrinsic excitability, governed by an array of voltage-gated ion channels, and extrinsic excitability, maintained through a counterbalance between excitatory synaptic transmission primarily mediated by excitatory transmitter glutamate acting on excitatory ion-tropic glutamate receptors and inhibitory synaptic transmissions chiefly mediated by GABA or glycine acting on their respective inhibitory ion-tropic receptors. However, recent studies reveal that neurotransmitters can exhibit interactions that extend beyond their traditional targets, leading to a phenomenon called neurotransmitter-receptor crosstalk. Examples of such crosstalks include earlier discovery of inhibitory glycine functioning as co-transmitter gating on the NMDA subtype of excitatory glutamate receptor, and the most recent demonstration that shows the excitatory glutamate transmitter binds to the inhibitory GABAA receptor, thereby allosterically potentiating its inhibitory function. These studies demonstrate structurally and physiologically important crosstalk between excitatory and inhibitory synaptic transmission, blurring the distinction between the concepts of classic excitatory and inhibitory synaptic transmission. In this article, evidence supporting the forms of excitatory and inhibitory crosstalks will be briefly summarized and their underlying mechanisms will be discussed. Furthermore, this review will discuss the implications of these crosstalks in maintaining the E/I balance, as well as their potential involvement in synaptic plasticity and cognition in the context of social conditions.

Modeling the Emergence of Circuit Organization and Function during Development

Developing neural circuits show unique patterns of spontaneous activity and structured network connectivity shaped by diverse activity-dependent plasticity mechanisms. Based on extensive experimental work characterizing patterns of spontaneous activity in different brain regions over development, theoretical and computational models have played an important role in delineating the generation and function of individual features of spontaneous activity and their role in the plasticity-driven formation of circuit connectivity. Here, we review recent modeling efforts that explore how the developing cortex and hippocampus generate spontaneous activity, focusing on specific connectivity profiles and the gradual strengthening of inhibition as the key drivers behind the observed developmental changes in spontaneous activity. We then discuss computational models that mechanistically explore how different plasticity mechanisms use this spontaneous activity to instruct the formation and refinement of circuit connectivity, from the formation of single neuron receptive fields to sensory feature maps and recurrent architectures. We end by highlighting several open challenges regarding the functional implications of the discussed circuit changes, wherein models could provide the missing step linking immature developmental and mature adult information processing capabilities.

Extracellular matrix integrity regulates GABAergic plasticity in the hippocampus

The brain's extracellular matrix (ECM) is crucial for neural circuit functionality, synaptic plasticity, and learning. While the role of the ECM in excitatory synapses has been extensively studied, its influence on inhibitory synapses, particularly on GABAergic long-term plasticity, remains poorly understood. This study aims to elucidate the effects of ECM components on inhibitory synaptic transmission and plasticity in the hippocampal CA1 region. We focus on the roles of chondroitin sulfate proteoglycans (CSPGs) and hyaluronic acid in modulating inhibitory postsynaptic currents (IPSCs) at two distinct inhibitory synapses formed by somatostatin (SST)-positive and parvalbumin (PV)-positive interneurons onto pyramidal cells (PCs). Using optogenetic stimulation in brain slices, we observed that acute degradation of ECM constituents by hyaluronidase or chondroitinase-ABC did not affect basal inhibitory synaptic transmission. However, short-term plasticity, particularly burst-induced depression, was enhanced at PV→PC synapses following enzymatic treatments. Long-term plasticity experiments demonstrated that CSPGs are essential for NMDA-induced iLTP at SST→PC synapses, whereas the digestion of hyaluronic acid by hyaluronidase impaired iLTP at PV→PC synapses. This indicates a synapse-specific role of CSPGs and hyaluronic acid in regulating GABAergic plasticity. Additionally, we report the presence of cryptic GABAergic plasticity at PV→PC synapses induced by prolonged NMDA application, which became evident after CSPG digestion and was absent under control conditions. Our results underscore the differential impact of ECM degradation on inhibitory synaptic plasticity, highlighting the synapse-specific interplay between ECM components and specific GABAergic synapses. This offers new perspectives in studies on learning and critical period timing.

Bio-Plausible Multimodal Learning with Emerging Neuromorphic Devices

Multimodal machine learning, as a prospective advancement in artificial intelligence, endeavors to emulate the brain's multimodal learning abilities with the objective to enhance interactions with humans. However, this approach requires simultaneous processing of diverse types of data, leading to increased model complexity, longer training times, and higher energy consumption. Multimodal neuromorphic devices have the capability to preprocess spatio-temporal information from various physical signals into unified electrical signals with high information density, thereby enabling more biologically plausible multimodal learning with low complexity and high energy-efficiency. Here, this work conducts a comparison between the expression of multimodal machine learning and multimodal neuromorphic computing, followed by an overview of the key characteristics associated with multimodal neuromorphic devices. The bio-plausible operational principles and the multimodal learning abilities of emerging devices are examined, which are classified into heterogeneous and homogeneous multimodal neuromorphic devices. Subsequently, this work provides a detailed description of the multimodal learning capabilities demonstrated by neuromorphic circuits and their respective applications. Finally, this work highlights the limitations and challenges of multimodal neuromorphic computing in order to hopefully provide insight into potential future research directions.

Input specificity of NMDA-dependent GABAergic plasticity in the hippocampus

Sensory experiences and learning induce long-lasting changes in both excitatory and inhibitory synapses, thereby providing a crucial substrate for memory. However, the co-tuning of excitatory long-term potentiation (eLTP) or depression (eLTD) with the simultaneous changes at inhibitory synapses (iLTP/iLTD) remains unclear. Herein, we investigated the co-expression of NMDA-induced synaptic plasticity at excitatory and inhibitory synapses in hippocampal CA1 pyramidal cells (PCs) using a combination of electrophysiological, optogenetic, and pharmacological approaches. We found that inhibitory inputs from somatostatin (SST) and parvalbumin (PV)-positive interneurons onto CA1 PCs display input-specific long-term plastic changes following transient NMDA receptor activation. Notably, synapses from SST-positive interneurons consistently exhibited iLTP, irrespective of the direction of excitatory plasticity, whereas synapses from PV-positive interneurons predominantly showed iLTP concurrent with eLTP, rather than eLTD. As neuroplasticity is known to depend on the extracellular matrix, we tested the impact of metalloproteinases (MMP) inhibition. MMP3 blockade interfered with GABAergic plasticity for all inhibitory inputs, whereas MMP9 inhibition selectively blocked eLTP and iLTP in SST-CA1PC synapses co-occurring with eLTP but not eLTD. These findings demonstrate the dissociation of excitatory and inhibitory plasticity co-expression. We propose that these mechanisms of plasticity co-expression may be involved in maintaining excitation-inhibition balance and modulating neuronal integration modes.

Contributions of cortical neuron firing patterns, synaptic connectivity, and plasticity to task performance

Neuronal responses during behavior are diverse, ranging from highly reliable 'classical' responses to irregular 'non-classically responsive' firing. While a continuum of response properties is observed across neural systems, little is known about the synaptic origins and contributions of diverse responses to network function, perception, and behavior. To capture the heterogeneous responses measured from auditory cortex of rodents performing a frequency recognition task, we use a novel task-performing spiking recurrent neural network incorporating spike-timing-dependent plasticity. Reliable and irregular units contribute differentially to task performance via output and recurrent connections, respectively. Excitatory plasticity shifts the response distribution while inhibition constrains its diversity. Together both improve task performance with full network engagement. The same local patterns of synaptic inputs predict spiking response properties of network units and auditory cortical neurons from in vivo whole-cell recordings during behavior. Thus, diverse neural responses contribute to network function and emerge from synaptic plasticity rules.

Dissociated Representation of Binaural Cues in Single-Sided Deafness: Implications for Cochlear Implantation

Congenital single-sided deafness (SSD) leads to an aural preference syndrome that is characterized by overrepresentation of the hearing ear in the auditory system. Cochlear implantation (CI) of the deaf ear is an effective treatment for SSD. However, the newly introduced auditory input in congenital SSD often does not reach expectations in late-implanted CI recipients with respect to binaural hearing and speech perception. In a previous study, a reduction of the interaural time difference (ITD) sensitivity has been shown in unilaterally congenitally deaf cats (uCDCs). In the present study, we focused on the interaural level difference (ILD) processing in the primary auditory cortex. The uCDC group was compared with hearing cats (HCs) and bilaterally congenitally deaf cats (CDCs). The ILD representation was reorganized, replacing the preference for the contralateral ear with a preference for the hearing ear, regardless of the cortical hemisphere. In accordance with the previous study, uCDCs were less sensitive to interaural time differences than HCs, resulting in unmodulated ITD responses, thus lacking directional information. Such incongruent ITDs and ILDs cannot be integrated for binaural sound source localization. In normal hearing, the predominant effect of each ear is excitation of the auditory cortex in the contralateral cortical hemisphere and inhibition in the ipsilateral hemisphere. In SSD, however, auditory pathways reorganized such that the hearing ear produced greater excitation in both cortical hemispheres and the deaf ear produced weaker excitation and preserved inhibition in both cortical hemispheres.

Contributions of dysfunctional plasticity mechanisms to the development of atypical perceptual processing

Experimental studies of sensory plasticity during development in birds and mammals have highlighted the importance of sensory experiences for the construction and refinement of functional neural circuits. We discuss how dysregulation of experience-dependent brain plasticity can lead to abnormal perceptual representations that may contribute to heterogeneous deficits symptomatic of several neurodevelopmental disorders. We focus on alterations of somatosensory processing and the dynamic reorganization of cortical synaptic networks that occurs during early perceptual development. We also discuss the idea that the heterogeneity of strengths and weaknesses observed in children with neurodevelopmental disorders may be a direct consequence of altered plasticity mechanisms during early development. Treating the heterogeneity of perceptual developmental trajectories as a phenomenon worthy of study rather than as an experimental confound that should be overcome may be key to developing interventions that better account for the complex developmental trajectories experienced by modern humans.

Cdc42 activation is necessary for heterosynaptic cooperation and competition

Synapses change their weights in response to neuronal activity and in turn, neuronal networks alter their response properties and ultimately allow the brain to store information as memories. As for memories, not all events are maintained over time. Maintenance of synaptic plasticity depends on the interplay between functional changes at synapses and the synthesis of plasticity-related proteins that are involved in stabilizing the initial functional changes. Different forms of synaptic plasticity coexist in time and across the neuronal dendritic area. Thus, homosynaptic plasticity refers to activity-dependent synaptic modifications that are input-specific, whereas heterosynaptic plasticity relates to changes in non-activated synapses. Heterosynaptic forms of plasticity, such as synaptic cooperation and competition allow neurons to integrate events that occur separated by relatively large time windows, up to one hour. Here, we show that activation of Cdc42, a Rho GTPase that regulates actin cytoskeleton dynamics, is necessary for the maintenance of long-term potentiation (LTP) in a time-dependent manner. Inhibiting Cdc42 activation does not alter the time-course of LTP induction and its initial expression but blocks its late maintenance. We show that Cdc42 activation is involved in the phosphorylation of cofilin, a protein involved in modulating actin filaments and that weak and strong synaptic activation leads to similar levels on cofilin phosphorylation, despite different levels of LTP expression. We show that Cdc42 activation is required for synapses to interact by cooperation or competition, supporting the hypothesis that modulation of the actin cytoskeleton provides an activity-dependent and time-restricted permissive state of synapses allowing synaptic plasticity to occur. We found that under competition, the sequence in which synapses are activated determines the degree of LTP destabilization, demonstrating that competition is an active destabilization process. Taken together, we show that modulation of actin cytoskeleton by Cdc42 activation is necessary for the expression of homosynaptic and heterosynaptic forms of plasticity. Determining the temporal and spatial rules that determine whether synapses cooperate or compete will allow us to understand how memories are associated.

The spike-timing-dependent plasticity of VIP interneurons in motor cortex

The plasticity of inhibitory interneurons (INs) plays an important role in the organization and maintenance of cortical microcircuits. Given the many different IN types, there is an even greater diversity in synapse-type-specific plasticity learning rules at excitatory to excitatory (E→I), I→E, and I→I synapses. I→I synapses play a key disinhibitory role in cortical circuits. Because they typically target other INs, vasoactive intestinal peptide (VIP) INs are often featured in I→I→E disinhibition, which upregulates activity in nearby excitatory neurons. VIP IN dysregulation may thus lead to neuropathologies such as epilepsy. In spite of the important activity regulatory role of VIP INs, their long-term plasticity has not been described. Therefore, we characterized the phenomenology of spike-timing-dependent plasticity (STDP) at inputs and outputs of genetically defined VIP INs. Using a combination of whole-cell recording, 2-photon microscopy, and optogenetics, we explored I→I STDP at layer 2/3 (L2/3) VIP IN outputs onto L5 Martinotti cells (MCs) and basket cells (BCs). We found that VIP IN→MC synapses underwent causal long-term depression (LTD) that was presynaptically expressed. VIP IN→BC connections, however, did not undergo any detectable plasticity. Conversely, using extracellular stimulation, we explored E→I STDP at inputs to VIP INs which revealed long-term potentiation (LTP) for both causal and acausal timings. Taken together, our results demonstrate that VIP INs possess synapse-type-specific learning rules at their inputs and outputs. This suggests the possibility of harnessing VIP IN long-term plasticity to control activity-related neuropathologies such as epilepsy.

The selfish network: how the brain preserves behavioral function through shifts in neuronal network state

Neuronal networks possess the ability to regulate their activity states in response to disruptions. How and when neuronal networks turn from physiological into pathological states, leading to the manifestation of neuropsychiatric disorders, remains largely unknown. Here, we propose that neuronal networks intrinsically maintain network stability even at the cost of neuronal loss. Despite the new stable state being potentially maladaptive, neural networks may not reverse back to states associated with better long-term outcomes. These maladaptive states are often associated with hyperactive neurons, marking the starting point for activity-dependent neurodegeneration. Transitions between network states may occur rapidly, and in discrete steps rather than continuously, particularly in neurodegenerative disorders. The self-stabilizing, metastable, and noncontinuous characteristics of these network states can be mathematically described as attractors. Maladaptive attractors may represent a distinct pathophysiological entity that could serve as a target for new therapies and for fostering resilience.

Interleukin-15 alters hippocampal synaptic transmission and impairs episodic memory formation in mice

Cytokines are potent immunomodulators exerting pleiotropic effects in the central nervous system (CNS). They influence neuronal functions and circuit activities with effects on memory processes and behaviors. Here, we unravel a neuromodulatory activity of interleukin-15 (IL-15) in mouse brain. Acute exposure of hippocampal slices to IL-15 enhances gamma-aminobutyricacid (GABA) release and reduces glutamatergic currents, while chronic treatment with IL-15 increases the frequency of hippocampal miniature inhibitory synaptic transmission and impairs memory formation in the novel object recognition (NOR) test. Moreover, we describe that serotonin is involved in mediating the hippocampal effects of IL-15, because a selective 5-HT3A receptor antagonist prevents the effects on inhibitory neurotransmission and ameliorates mice performance in the NOR test. These findings provide new insights into the modulatory activities of cytokines in the CNS, with implications on behavior.

Heterosynaptic plasticity-induced modulation of synapses

Plasticity is a common feature of synapses that is stated in different ways and occurs through several mechanisms. The regular action of the brain needs to be balanced in several neuronal and synaptic features, one of which is synaptic plasticity. The different homeostatic processes, including the balance between excitation/inhibition or homeostasis of synaptic weights at the single-neuron level, may obtain this. Homosynaptic Hebbian-type plasticity causes associative alterations of synapses. Both homosynaptic and heterosynaptic plasticity characterize the corresponding aspects of adjustable synapses, and both are essential for the regular action of neural systems and their plastic synapses.In this review, we will compare homo- and heterosynaptic plasticity and the main factors affecting the direction of plastic changes. This review paper will also discuss the diverse functions of the different kinds of heterosynaptic plasticity and their properties. We argue that a complementary system of heterosynaptic plasticity demonstrates an essential cellular constituent for homeostatic modulation of synaptic weights and neuronal activity.

The effect of ketamine on synaptic mistuning induced by impaired glutamate reuptake

Mistuning of synaptic transmission has been proposed to underlie many psychiatric disorders, with decreased reuptake of the excitatory neurotransmitter glutamate as one contributing factor. Synaptic tuning occurs through several diverging and converging forms of plasticity. By recording evoked field postsynaptic potentials in the CA1 area in hippocampal slices, we found that inhibiting glutamate transporters using DL-TBOA causes retuning of synaptic transmission, resulting in a new steady state with reduced synaptic strength and a lower threshold for inducing long-term synaptic potentiation (LTP). Moreover, a similar reduced threshold for LTP was observed in a rat model of depression with decreased levels of glutamate transporters. Most importantly, we found that the antidepressant ketamine counteracts the effects of increased glutamate on the various steps involved in synaptic retuning. We, therefore, propose that ketamine's mechanism of action as an antidepressant is to restore adequate synaptic tuning.

Synchronization and oscillation behaviors of excitatory and inhibitory populations with spike-timing-dependent plasticity

The effect of synaptic plasticity on the synchronization mechanism of the cerebral cortex has been a hot research topic over the past two decades. There are a great deal of literatures on excitatory pyramidal neurons, but the mechanism of interaction between the inhibitory interneurons is still under exploration. In this study, we consider a complex network consisting of excitatory (E) pyramidal neurons and inhibitory (I) interneurons interacting with chemical synapses through spike-timing-dependent plasticity (STDP). To study the effects of eSTDP and iSTDP on synchronization and oscillation behaviors emerged in an excitatory-inhibitory balanced network, we analyzed three different cases, a small-world network of purely excitatory neurons with eSTDP, a small-world network of purely inhibitory neurons with iSTDP and a small-world network with excitatory-inhibitory balanced neurons. By varying the number of inhibitory interneurons, and that of connected edges in a small-world network, and the coupling strength, these networks exhibit different synchronization and oscillation behaviors. We found that the eSTDP facilitates synchronization effectively, while iSTDP has no significant impact on it. In addition, eSTDP and iSTDP restrict the balance of the excitatory-inhibitory balanced neuronal network together and play a fundamental role in maintaining network stability and synchronization. They also can be used to guide the treatment and further research of neurodegenerative diseases.

Synaptic logistics: Competing over shared resources

High turnover rates of synaptic proteins imply that synapses constantly need to replace their constituent building blocks. This requires sophisticated supply chains and potentially exposes synapses to shortages as they compete for limited resources. Interestingly, competition in neurons has been observed at different scales. Whether it is competition of receptors for binding sites inside a single synapse or synapses fighting for resources to grow. Here we review the implications of such competition for synaptic function and plasticity. We identify multiple mechanisms that synapses use to safeguard themselves against supply shortages and identify a fundamental neurologistic trade-off governing the sizes of reserve pools of essential synaptic building blocks.

Computational insights into mRNA and protein dynamics underlying synaptic plasticity rules

Recent advances in experimental techniques provide an unprecedented peek into the intricate molecular dynamics inside synapses and dendrites. The experimental insights into the molecular turnover revealed that such processes as diffusion, active transport, spine uptake, and local protein synthesis could dynamically modulate the copy numbers of plasticity-related molecules in synapses. Subsequently, theoretical models were designed to understand the interaction of these processes better and to explain how local synaptic plasticity cues can up or down-regulate the molecular copy numbers across synapses. In this review, we discuss the recent advances in experimental techniques and computational models to highlight how these complementary approaches can provide insight into molecular cross-talk across synapses, ultimately allowing us to develop biologically-inspired neural network models to understand brain function.

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.

Where is the error? Hierarchical predictive coding through dendritic error computation

Top-down feedback in cortex is critical for guiding sensory processing, which has prominently been formalized in the theory of hierarchical predictive coding (hPC). However, experimental evidence for error units, which are central to the theory, is inconclusive and it remains unclear how hPC can be implemented with spiking neurons. To address this, we connect hPC to existing work on efficient coding in balanced networks with lateral inhibition and predictive computation at apical dendrites. Together, this work points to an efficient implementation of hPC with spiking neurons, where prediction errors are computed not in separate units, but locally in dendritic compartments. We then discuss the correspondence of this model to experimentally observed connectivity patterns, plasticity, and dynamics in cortex.

Stability and learning in excitatory synapses by nonlinear inhibitory plasticity

Synaptic changes are hypothesized to underlie learning and memory formation in the brain. But Hebbian synaptic plasticity of excitatory synapses on its own is unstable, leading to either unlimited growth of synaptic strengths or silencing of neuronal activity without additional homeostatic mechanisms. To control excitatory synaptic strengths, we propose a novel form of synaptic plasticity at inhibitory synapses. Using computational modeling, we suggest two key features of inhibitory plasticity, dominance of inhibition over excitation and a nonlinear dependence on the firing rate of postsynaptic excitatory neurons whereby inhibitory synaptic strengths change with the same sign (potentiate or depress) as excitatory synaptic strengths. We demonstrate that the stable synaptic strengths realized by this novel inhibitory plasticity model affects excitatory/inhibitory weight ratios in agreement with experimental results. Applying a disinhibitory signal can gate plasticity and lead to the generation of receptive fields and strong bidirectional connectivity in a recurrent network. Hence, a novel form of nonlinear inhibitory plasticity can simultaneously stabilize excitatory synaptic strengths and enable learning upon disinhibition.

Regulation of circuit organization and function through inhibitory synaptic plasticity

Diverse inhibitory neurons in the mammalian brain shape circuit connectivity and dynamics through mechanisms of synaptic plasticity. Inhibitory plasticity can establish excitation/inhibition (E/I) balance, control neuronal firing, and affect local calcium concentration, hence regulating neuronal activity at the network, single neuron, and dendritic level. Computational models can synthesize multiple experimental results and provide insight into how inhibitory plasticity controls circuit dynamics and sculpts connectivity by identifying phenomenological learning rules amenable to mathematical analysis. We highlight recent studies on the role of inhibitory plasticity in modulating excitatory plasticity, forming structured networks underlying memory formation and recall, and implementing adaptive phenomena and novelty detection. We conclude with experimental and modeling progress on the role of interneuron-specific plasticity in circuit computation and context-dependent learning.

Formation and computational implications of assemblies in neural circuits

In the brain, patterns of neural activity represent sensory information and store it in non-random synaptic connectivity. A prominent theoretical hypothesis states that assemblies, groups of neurons that are strongly connected to each other, are the key computational units underlying perception and memory formation. Compatible with these hypothesised assemblies, experiments have revealed groups of neurons that display synchronous activity, either spontaneously or upon stimulus presentation, and exhibit behavioural relevance. While it remains unclear how assemblies form in the brain, theoretical work has vastly contributed to the understanding of various interacting mechanisms in this process. Here, we review the recent theoretical literature on assembly formation by categorising the involved mechanisms into four components: synaptic plasticity, symmetry breaking, competition and stability. We highlight different approaches and assumptions behind assembly formation and discuss recent ideas of assemblies as the key computational unit in the brain. Abstract figure legend Assembly Formation. Assemblies are groups of strongly connected neurons formed by the interaction of multiple mechanisms and with vast computational implications. Four interacting components are thought to drive assembly formation: synaptic plasticity, symmetry breaking, competition and stability. This article is protected by copyright. All rights reserved.

A circuit mechanism for independent modulation of excitatory and inhibitory firing rates after sensory deprivation

The cortex is particularly vulnerable to perturbations during sensitive periods, such as the critical period when manipulating sensory experience can induce long-lasting changes in brain structure. Depriving rodents of vision in one eye (known as monocular deprivation [MD]) reduces network activity over two days, whereby inhibitory neurons decrease their firing rates one day after MD, while excitatory neurons are delayed by an additional day. We use spiking networks to mechanistically dissect the requirements for this independent firing-rate regulation after sensory deprivation. We find that in networks stabilized by recurrent inhibition, at least two interneuron subtypes (parvalbumin-expressing and somatostatin-expressing interneurons) are necessary to dynamically alter the circuit response after deprivation and generalize the result across sensory cortices.

Diverse interneuron subtypes shape sensory processing in mature cortical circuits. During development, sensory deprivation evokes powerful synaptic plasticity that alters circuitry, but how different inhibitory subtypes modulate circuit dynamics in response to this plasticity remains unclear. We investigate how deprivation-induced synaptic changes affect excitatory and inhibitory firing rates in a microcircuit model of the sensory cortex with multiple interneuron subtypes. We find that with a single interneuron subtype (parvalbumin-expressing [PV]), excitatory and inhibitory firing rates can only be comodulated—increased or decreased together. To explain the experimentally observed independent modulation, whereby one firing rate increases and the other decreases, requires strong feedback from a second interneuron subtype (somatostatin-expressing [SST]). Our model applies to the visual and somatosensory cortex, suggesting a general mechanism across sensory cortices. Therefore, we provide a mechanistic explanation for the differential role of interneuron subtypes in regulating firing rates, contributing to the already diverse roles they serve in the cortex.

Multiplicative Shot-Noise: A New Route to Stability of Plastic Networks

Fluctuations of synaptic weights, among many other physical, biological, and ecological quantities, are driven by coincident events of two "parent" processes. We propose a multiplicative shot-noise model that can capture the behaviors of a broad range of such natural phenomena, and analytically derive an approximation that accurately predicts its statistics. We apply our results to study the effects of a multiplicative synaptic plasticity rule that was recently extracted from measurements in physiological conditions. Using mean-field theory analysis and network simulations, we investigate how this rule shapes the connectivity and dynamics of recurrent spiking neural networks. The multiplicative plasticity rule is shown to support efficient learning of input stimuli, and it gives a stable, unimodal synaptic-weight distribution with a large fraction of strong synapses. The strong synapses remain stable over long times but do not "run away." Our results suggest that the multiplicative shot-noise offers a new route to understand the tradeoff between flexibility and stability in neural circuits and other dynamic networks.

Integrins Bidirectionally Regulate the Efficacy of Inhibitory Synaptic Transmission and Control GABAergic Plasticity

For many decades, synaptic plasticity was believed to be restricted to excitatory transmission. However, in recent years, this view started to change, and now it is recognized that GABAergic synapses show distinct forms of activity-dependent long-term plasticity, but the underlying mechanisms remain obscure. Herein, we asked whether signaling mediated by β1 or β3 subunit-containing integrins might be involved in regulating the efficacy of GABAergic synapses, including the NMDA receptor-dependent inhibitory long-term potentiation (iLTP) in the hippocampus. We found that activation of β3 integrin with fibrinogen induced a stable depression, whereas inhibition of β1 integrin potentiated GABAergic synapses at CA1 pyramidal neurons in male mice. Additionally, compounds that interfere with the interaction of β1 or β3 integrins with extracellular matrix blocked the induction of NMDA-iLTP. In conclusion, we provide the first evidence that integrins are key players in regulating the endogenous modulatory mechanisms of GABAergic inhibition and plasticity in the hippocampus.SIGNIFICANCE STATEMENT Epilepsy, schizophrenia, and anxiety are just a few medical conditions associated with dysfunctional inhibitory synaptic transmission. GABAergic synapses are known for their extraordinary susceptibility to modulation by endogenous factors and exogenous pharmacological agents. We describe here that integrins, adhesion proteins, play a key role in the modulation of inhibitory synaptic transmission. Specifically, we show that interference with integrin-dependent adhesion results in a variety of effects on the amplitude and frequency of GABAergic mIPSCs. Activation of β3 subunit-containing integrins induces inhibitory long-term depression, whereas the inhibition of β1 subunit-containing integrins induces iLTP. Our results unveil an important mechanism controlling synaptic inhibition, which opens new avenues into the usage of integrin-aimed pharmaceuticals as modulators of GABAergic synapses.

Role of Lateral Inhibition on Visual Number Sense

Newborn animals, such as 4-month-old infants, 4-day-old chicks, and 1-day-old guppies, exhibit sensitivity to an approximate number of items in the visual array. These findings are often interpreted as evidence for an innate "number sense." However, number sense is typically investigated using explicit behavioral tasks, which require a form of calibration (e.g., habituation or reward-based training) in experimental studies. Therefore, the generation of number sense may be the result of calibration. We built a number-sense neural network model on the basis of lateral inhibition to explore whether animals demonstrate an innate "number sense" and determine important factors affecting this competence. The proposed model can reproduce size and distance effects of output responses of number-selective neurons when network connection weights are set randomly without an adjustment. Results showed that number sense can be produced under the influence of lateral inhibition, which is one of the fundamental mechanisms of the nervous system, and independent of learning.

Differential Hebbian learning with time-continuous signals for active noise reduction

Spike timing-dependent plasticity, related to differential Hebb-rules, has become a leading paradigm in neuronal learning, because weights can grow or shrink depending on the timing of pre- and post-synaptic signals. Here we use this paradigm to reduce unwanted (acoustic) noise. Our system relies on heterosynaptic differential Hebbian learning and we show that it can efficiently eliminate noise by up to -140 dB in multi-microphone setups under various conditions. The system quickly learns, most often within a few seconds, and it is robust with respect to different geometrical microphone configurations, too. Hence, this theoretical study demonstrates that it is possible to successfully transfer differential Hebbian learning, derived from the neurosciences, into a technical domain.

The Yin and Yang of GABAergic and Glutamatergic Synaptic Plasticity: Opposites in Balance by Crosstalking Mechanisms

Synaptic plasticity is a critical process that regulates neuronal activity by allowing neurons to adjust their synaptic strength in response to changes in activity. Despite the high proximity of excitatory glutamatergic and inhibitory GABAergic postsynaptic zones and their functional integration within dendritic regions, concurrent plasticity has historically been underassessed. Growing evidence for pathological disruptions in the excitation and inhibition (E/I) balance in neurological and neurodevelopmental disorders indicates the need for an improved, more "holistic" understanding of synaptic interplay. There continues to be a long-standing focus on the persistent strengthening of excitation (excitatory long-term potentiation; eLTP) and its role in learning and memory, although the importance of inhibitory long-term potentiation (iLTP) and depression (iLTD) has become increasingly apparent. Emerging evidence further points to a dynamic dialogue between excitatory and inhibitory synapses, but much remains to be understood regarding the mechanisms and extent of this exchange. In this mini-review, we explore the role calcium signaling and synaptic crosstalk play in regulating postsynaptic plasticity and neuronal excitability. We examine current knowledge on GABAergic and glutamatergic synapse responses to perturbances in activity, with a focus on postsynaptic plasticity induced by short-term pharmacological treatments which act to either enhance or reduce neuronal excitability via ionotropic receptor regulation in neuronal culture. To delve deeper into potential mechanisms of synaptic crosstalk, we discuss the influence of synaptic activity on key regulatory proteins, including kinases, phosphatases, and synaptic structural/scaffolding proteins. Finally, we briefly suggest avenues for future research to better understand the crosstalk between glutamatergic and GABAergic synapses.

Assessing Local and Branch-specific Activity in Dendrites

Dendrites are elaborate neural processes which integrate inputs from various sources in space and time. While decades of work have suggested an independent role for dendrites in driving nonlinear computations for the cell, only recently have technological advances enabled us to capture the variety of activity in dendrites and their coupling dynamics with the soma. Under certain circumstances, activity generated in a given dendritic branch remains isolated, such that the soma or even sister dendrites are not privy to these localized signals. Such branch-specific activity could radically increase the capacity and flexibility of coding for the cell as a whole. Here, we discuss these forms of localized and branch-specific activity, their functional relevance in plasticity and behavior, and their supporting biophysical and circuit-level mechanisms. We conclude by showcasing electrical and optical approaches in hippocampal area CA3, using original experimental data to discuss experimental and analytical methodology and key considerations to take when investigating the functional relevance of independent dendritic activity.

Spatial regulation of coordinated excitatory and inhibitory synaptic plasticity at dendritic synapses

The induction of synaptic plasticity at an individual dendritic glutamatergic spine can affect neighboring spines. This local modulation generates dendritic plasticity microdomains believed to expand the neuronal computational capacity. Here, we investigate whether local modulation of plasticity can also occur between glutamatergic synapses and adjacent GABAergic synapses. We find that the induction of long-term potentiation at an individual glutamatergic spine causes the depression of nearby GABAergic inhibitory synapses (within 3 μm), whereas more distant ones are potentiated. Notably, L-type calcium channels and calpain are required for this plasticity spreading. Overall, our data support a model whereby input-specific glutamatergic postsynaptic potentiation induces a spatially regulated rearrangement of inhibitory synaptic strength in the surrounding area through short-range heterosynaptic interactions. Such local coordination of excitatory and inhibitory synaptic plasticity is expected to influence dendritic information processing and integration.

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LTP of individual dendritic spines causes iLTD at neighboring GABAergic synapses

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Interaction between single-spine LTP and iLTD occurs in the spatial range of ±3 μm

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This iLTD depends on the local dendritic calcium increase and calpain activation

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iLTD is associated with reduced gephyrin clustering and increased GABAAR mobility

Gabaergic Interneurons in Early Brain Development: Conducting and Orchestrated by Cortical Network Activity

Throughout early phases of brain development, the two main neural signaling mechanisms—excitation and inhibition—are dynamically sculpted in the neocortex to establish primary functions. Despite its relatively late formation and persistent developmental changes, the GABAergic system promotes the ordered shaping of neuronal circuits at the structural and functional levels. Within this frame, interneurons participate first in spontaneous and later in sensory-evoked activity patterns that precede cortical functions of the mature brain. Upon their subcortical generation, interneurons in the embryonic brain must first orderly migrate to and settle in respective target layers before they can actively engage in cortical network activity. During this process, changes at the molecular and synaptic level of interneurons allow not only their coordinated formation but also the pruning of connections as well as excitatory and inhibitory synapses. At the postsynaptic site, the shift of GABAergic signaling from an excitatory towards an inhibitory response is required to enable synchronization within cortical networks. Concomitantly, the progressive specification of different interneuron subtypes endows the neocortex with distinct local cortical circuits and region-specific modulation of neuronal firing. Finally, the apoptotic process further refines neuronal populations by constantly maintaining a controlled ratio of inhibitory and excitatory neurons. Interestingly, many of these fundamental and complex processes are influenced—if not directly controlled—by electrical activity. Interneurons on the subcellular, cellular, and network level are affected by high frequency patterns, such as spindle burst and gamma oscillations in rodents and delta brushes in humans. Conversely, the maturation of interneuron structure and function on each of these scales feeds back and contributes to the generation of cortical activity patterns that are essential for the proper peri- and postnatal development. Overall, a more precise description of the conducting role of interneurons in terms of how they contribute to specific activity patterns—as well as how specific activity patterns impinge on their maturation as orchestra members—will lead to a better understanding of the physiological and pathophysiological development and function of the nervous system.

Heterosynaptic Plasticity and the Experience-Dependent Refinement of Developing Neuronal Circuits

Neurons remodel the structure and strength of their synapses during critical periods of development in order to optimize both perception and cognition. Many of these developmental synaptic changes are thought to occur through synapse-specific homosynaptic forms of experience-dependent plasticity. However, homosynaptic plasticity can also induce or contribute to the plasticity of neighboring synapses through heterosynaptic interactions. Decades of research in vitro have uncovered many of the molecular mechanisms of heterosynaptic plasticity that mediate local compensation for homosynaptic plasticity, facilitation of further bouts of plasticity in nearby synapses, and cooperative induction of plasticity by neighboring synapses acting in concert. These discoveries greatly benefited from new tools and technologies that permitted single synapse imaging and manipulation of structure, function, and protein dynamics in living neurons. With the recent advent and application of similar tools for in vivo research, it is now feasible to explore how heterosynaptic plasticity contribute to critical periods and the development of neuronal circuits. In this review, we will first define the forms heterosynaptic plasticity can take and describe our current understanding of their molecular mechanisms. Then, we will outline how heterosynaptic plasticity may lead to meaningful refinement of neuronal responses and observations that suggest such mechanisms are indeed at work in vivo. Finally, we will use a well-studied model of cortical plasticity—ocular dominance plasticity during a critical period of visual cortex development—to highlight the molecular overlap between heterosynaptic and developmental forms of plasticity, and suggest potential avenues of future research.

Brain is modulated by neuronal plasticity during postnatal development

Neuroplasticity is referred to the ability of the nervous system to change its structure or functions as a result of former stimuli. It is a plausible mechanism underlying a dynamic brain through adaptation processes of neural structure and activity patterns. Nevertheless, it is still unclear how the plastic neural systems achieve and maintain their equilibrium. Additionally, the alterations of balanced brain dynamics under different plasticity rules have not been explored either. Therefore, the present article primarily aims to review recent research studies regarding homosynaptic and heterosynaptic neuroplasticity characterized by the manipulation of excitatory and inhibitory synaptic inputs. Moreover, it attempts to understand different mechanisms related to the main forms of synaptic plasticity at the excitatory and inhibitory synapses during the brain development processes. Hence, this study comprised surveying those articles published since 1988 and available through PubMed, Google Scholar and science direct databases on a keyword-based search paradigm. All in all, the study results presented extensive and corroborative pieces of evidence for the main types of plasticity, including the long-term potentiation (LTP) and long-term depression (LTD) of the excitatory and inhibitory postsynaptic potentials (EPSPs and IPSPs).

What is the dynamical regime of cerebral cortex?

Many studies have shown that the excitation and inhibition received by cortical neurons remain roughly balanced across many conditions. A key question for understanding the dynamical regime of cortex is the nature of this balancing. Theorists have shown that network dynamics can yield systematic cancellation of most of a neuron's excitatory input by inhibition. We review a wide range of evidence pointing to this cancellation occurring in a regime in which the balance is loose, meaning that the net input remaining after cancellation of excitation and inhibition is comparable in size with the factors that cancel, rather than tight, meaning that the net input is very small relative to the canceling factors. This choice of regime has important implications for cortical functional responses, as we describe: loose balance, but not tight balance, can yield many nonlinear population behaviors seen in sensory cortical neurons, allow the presence of correlated variability, and yield decrease of that variability with increasing external stimulus drive as observed across multiple cortical areas.

The generation of cortical novelty responses through inhibitory plasticity

Animals depend on fast and reliable detection of novel stimuli in their environment. Neurons in multiple sensory areas respond more strongly to novel in comparison to familiar stimuli. Yet, it remains unclear which circuit, cellular, and synaptic mechanisms underlie those responses. Here, we show that spike-timing-dependent plasticity of inhibitory-to-excitatory synapses generates novelty responses in a recurrent spiking network model. Inhibitory plasticity increases the inhibition onto excitatory neurons tuned to familiar stimuli, while inhibition for novel stimuli remains low, leading to a network novelty response. The generation of novelty responses does not depend on the periodicity but rather on the distribution of presented stimuli. By including tuning of inhibitory neurons, the network further captures stimulus-specific adaptation. Finally, we suggest that disinhibition can control the amplification of novelty responses. Therefore, inhibitory plasticity provides a flexible, biologically plausible mechanism to detect the novelty of bottom-up stimuli, enabling us to make experimentally testable predictions.

Memory recall involves a transient break in excitatory-inhibitory balance

The brain has a remarkable capacity to acquire and store memories that can later be selectively recalled. These processes are supported by the hippocampus which is thought to index memory recall by reinstating information stored across distributed neocortical circuits. However, the mechanism that supports this interaction remains unclear. Here, in humans, we show that recall of a visual cue from a paired associate is accompanied by a transient increase in the ratio between glutamate and GABA in visual cortex. Moreover, these excitatory-inhibitory fluctuations are predicted by activity in the hippocampus. These data suggest the hippocampus gates memory recall by indexing information stored across neocortical circuits using a disinhibitory mechanism.

Modulation of the dynamical state in cortical network models

Cortical neural responses can be modulated by various factors, such as stimulus inputs and the behavior state of the animal. Understanding the circuit mechanisms underlying modulations of network dynamics is important to understand the flexibility of circuit computations. Identifying the dynamical state of a network is an important first step to predict network responses to external stimulus and top-down modulatory inputs. Models in stable or unstable dynamical regimes require different analytic tools to estimate the network responses to inputs and the structure of neural variability. In this article, I review recent cortical models of state-dependent responses and their predictions about the underlying modulatory mechanisms.

Cellular, synaptic, and network effects of chemokines in the central nervous system and their implications to behavior

Accumulating evidence highlights chemokines as key mediators of the bidirectional crosstalk between neurons and glial cells aimed at preserving brain functioning. The multifaceted role of these immune proteins in the CNS is mirrored by the complexity of the mechanisms underlying its biological function, including biased signaling. Neurons, only in concert with glial cells, are essential players in the modulation of brain homeostatic functions. Yet, attempts to dissect these complex multilevel mechanisms underlying coordination are still lacking. Therefore, the purpose of this review is to summarize the current knowledge about mechanisms underlying chemokine regulation of neuron-glia crosstalk linking molecular, cellular, network, and behavioral levels. Following a brief description of molecular mechanisms by which chemokines interact with their receptors and then summarizing cellular patterns of chemokine expression in the CNS, we next delve into the sequence and mechanisms of chemokine-regulated neuron-glia communication in the context of neuroprotection. We then define the interactions with other neurotransmitters, neuromodulators, and gliotransmitters. Finally, we describe their fine-tuning on the network level and the behavioral relevance of their modulation. We believe that a better understanding of the sequence and nature of events that drive neuro-glial communication holds promise for the development of new treatment strategies that could, in a context- and time-dependent manner, modulate the action of specific chemokines to promote brain repair and reduce the neurological impairment.

Activity-Dependent Gene Expression in Neurons

The function of the nervous system in conveying and processing information necessary to interact with the environment confers unique aspects on how the expression of genes in neurons is regulated. Three salient factors are that (1) neurons are the largest and among the most morphologically complex of all cells, with strict polarity, subcellular compartmentation, and long-distant transport of gene products, signaling molecules, and other materials; (2) information is coded in the temporal firing pattern of membrane depolarization; and (3) neurons must maintain a stable homeostatic level of activation to function so stimuli do not normally drive intracellular signaling to steady state. Each of these factors can require special methods of analysis differing from approaches used in non-neuronal cells. This review considers these three aspects of neuronal gene expression and the current approaches being used to analyze these special features of how the neuronal transcriptome is modulated by action potential firing.

The Emergence of Network Activity Patterns in the Somatosensory Cortex - An Early Window to Autism Spectrum Disorders

Across mammalian species, patterned activity in neural populations is a prominent feature of developing sensory cortices. Numerous studies have long appreciated the diversity of these patterns, characterizing their differences in spatial and temporal dynamics. In the murine somatosensory cortex, neuronal co-activation is thought to guide the formation of sensory maps and prepare the cortex for sensory processing after birth. While pioneering studies deftly utilized slice electrophysiology and unit recordings to characterize correlated activity, a detailed understanding of the underlying circuits remains poorly understood. More recently, advances in in vivo calcium imaging in awake mouse pups and increasing genetic tractability of neuronal types have allowed unprecedented manipulation of circuit components at select developmental timepoints. These novel approaches have proven fundamental in uncovering the identity of neurons engaged in correlated activity during development. In particular, recent studies have highlighted interneurons as key in refining the spatial extent and temporal progression of patterned activity. Here, we discuss how emergent synchronous activity across the first postnatal weeks is shaped by underlying gamma aminobutyric acid (GABA)ergic contributors in the somatosensory cortex. Further, the importance of participation in specific activity patterns per se for neuronal maturation and perdurance will be of particular highlight in this survey of recent literature. Finally, we underscore how aberrant neuronal synchrony and disrupted inhibitory interneuron activity underlie sensory perturbations in neurodevelopmental disorders, particularly Autism Spectrum Disorders (ASDs), emphasizing the importance of future investigative approaches that incorporate the spatiotemporal features of patterned activity alongside the cellular components to probe disordered circuit assembly.

Oxytocin, Neural Plasticity, and Social Behavior

Oxytocin regulates parturition, lactation, parental nurturing, and many other social behaviors in both sexes. The circuit mechanisms by which oxytocin modulates social behavior are receiving increasing attention. Here, we review recent studies on oxytocin modulation of neural circuit function and social behavior, largely enabled by new methods of monitoring and manipulating oxytocin or oxytocin receptor neurons in vivo. These studies indicate that oxytocin can enhance the salience of social stimuli and increase signal-to-noise ratios by modulating spiking and synaptic plasticity in the context of circuits and networks. We highlight oxytocin effects on social behavior in nontraditional organisms such as prairie voles and discuss opportunities to enhance the utility of these organisms for studying circuit-level modulation of social behaviors. We then discuss recent insights into oxytocin neuron activity during social interactions. We conclude by discussing some of the major questions and opportunities in the field ahead.

Optimal learning with excitatory and inhibitory synapses

Characterizing the relation between weight structure and input/output statistics is fundamental for understanding the computational capabilities of neural circuits. In this work, I study the problem of storing associations between analog signals in the presence of correlations, using methods from statistical mechanics. I characterize the typical learning performance in terms of the power spectrum of random input and output processes. I show that optimal synaptic weight configurations reach a capacity of 0.5 for any fraction of excitatory to inhibitory weights and have a peculiar synaptic distribution with a finite fraction of silent synapses. I further provide a link between typical learning performance and principal components analysis in single cases. These results may shed light on the synaptic profile of brain circuits, such as cerebellar structures, that are thought to engage in processing time-dependent signals and performing on-line prediction.

My Neighbour Hetero-deconstructing the mechanisms underlying heterosynaptic plasticity

Synapses change in strength following patterns of activity, but in many cases seemingly inactive neighbouring synapses also undergo changes in strength. These heterosynaptic changes occur across developmental time-points in various brain circuits in different species, but their precise molecular mechanisms are not well understood. Additionally, heterosynaptic changes can mirror homosynaptic plasticity or occur in opposition to homosynaptic changes. In this review we consider what useful functionality heterosynaptic dynamics could potentially endow the circuit with, and the underlying signalling events that implement heterosynaptic changes. We discuss what unanswered questions remain, and what the future looks like for understanding the logic of synaptic plasticity.

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.

Autonomous emergence of connectivity assemblies via spike triplet interactions

Non-random connectivity can emerge without structured external input driven by activity-dependent mechanisms of synaptic plasticity based on precise spiking patterns. Here we analyze the emergence of global structures in recurrent networks based on a triplet model of spike timing dependent plasticity (STDP), which depends on the interactions of three precisely-timed spikes, and can describe plasticity experiments with varying spike frequency better than the classical pair-based STDP rule. We derive synaptic changes arising from correlations up to third-order and describe them as the sum of structural motifs, which determine how any spike in the network influences a given synaptic connection through possible connectivity paths. This motif expansion framework reveals novel structural motifs under the triplet STDP rule, which support the formation of bidirectional connections and ultimately the spontaneous emergence of global network structure in the form of self-connected groups of neurons, or assemblies. We propose that under triplet STDP assembly structure can emerge without the need for externally patterned inputs or assuming a symmetric pair-based STDP rule common in previous studies. The emergence of non-random network structure under triplet STDP occurs through internally-generated higher-order correlations, which are ubiquitous in natural stimuli and neuronal spiking activity, and important for coding. We further demonstrate how neuromodulatory mechanisms that modulate the shape of the triplet STDP rule or the synaptic transmission function differentially promote structural motifs underlying the emergence of assemblies, and quantify the differences using graph theoretic measures.

Emergent non-random connectivity structures in different brain regions are tightly related to specific patterns of neural activity and support diverse brain functions. For instance, self-connected groups of neurons, known as assemblies, have been proposed to represent functional units in brain circuits and can emerge even without patterned external instruction. Here we investigate the emergence of non-random connectivity in recurrent networks using a particular plasticity rule, triplet STDP, which relies on the interaction of spike triplets and can capture higher-order statistical dependencies in neural activity. We derive the evolution of the synaptic strengths in the network and explore the conditions for the self-organization of connectivity into assemblies. We demonstrate key differences of the triplet STDP rule compared to the classical pair-based rule in terms of how assemblies are formed, including the realistic asymmetric shape and influence of novel connectivity motifs on network plasticity driven by higher-order correlations. Assembly formation depends on the specific shape of the STDP window and synaptic transmission function, pointing towards an important role of neuromodulatory signals on formation of intrinsically generated assemblies.