Spike-timing-dependent plasticity of neocortical excitatory synapses on inhibitory interneurons depends on target cell type

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.

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.

Sequence anticipation and spike-timing-dependent plasticity emerge from a predictive learning rule

Intelligent behavior depends on the brain's ability to anticipate future events. However, the learning rules that enable neurons to predict and fire ahead of sensory inputs remain largely unknown. We propose a plasticity rule based on predictive processing, where the neuron learns a low-rank model of the synaptic input dynamics in its membrane potential. Neurons thereby amplify those synapses that maximally predict other synaptic inputs based on their temporal relations, which provide a solution to an optimization problem that can be implemented at the single-neuron level using only local information. Consequently, neurons learn sequences over long timescales and shift their spikes towards the first inputs in a sequence. We show that this mechanism can explain the development of anticipatory signalling and recall in a recurrent network. Furthermore, we demonstrate that the learning rule gives rise to several experimentally observed STDP (spike-timing-dependent plasticity) mechanisms. These findings suggest prediction as a guiding principle to orchestrate learning and synaptic plasticity in single neurons.

Controlling neocortical epileptic seizures using forced temporal spike-time stimulation: an in silico computational study

Epileptic seizure is typically characterized by highly synchronized episodes of neural activity. Existing stimulation therapies focus purely on suppressing the pathologically synchronized neuronal firing patterns during the ictal (seizure) period. While these strategies are effective in suppressing seizures when they occur, they fail to prevent the re-emergence of seizures once the stimulation is turned off. Previously, we developed a novel neurostimulation motif, which we refer to as "Forced Temporal Spike-Time Stimulation" (FTSTS) that has shown remarkable promise in long-lasting desynchronization of excessively synchronized neuronal firing patterns by harnessing synaptic plasticity. In this paper, we build upon this prior work by optimizing the parameters of the FTSTS protocol in order to efficiently desynchronize the pathologically synchronous neuronal firing patterns that occur during epileptic seizures using a recently published computational model of neocortical-onset seizures. We show that the FTSTS protocol applied during the ictal period can modify the excitatory-to-inhibitory synaptic weight in order to effectively desynchronize the pathological neuronal firing patterns even after the ictal period. Our investigation opens the door to a possible new neurostimulation therapy for epilepsy.

Spike timing-dependent plasticity and memory

Spike timing-dependent plasticity (STDP) is a bidirectional form of synaptic plasticity discovered about 30 years ago and based on the relative timing of pre- and post-synaptic spiking activity with a millisecond precision. STDP is thought to be involved in the formation of memory but the millisecond-precision spike-timing required for STDP is difficult to reconcile with the much slower timescales of behavioral learning. This review therefore aims to expose and discuss recent findings about i) the multiple STDP learning rules at both excitatory and inhibitory synapses in vitro, ii) the contribution of STDP-like synaptic plasticity in the formation of memory in vivo and iii) the implementation of STDP rules in artificial neural networks and memristive devices.

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.

Plasticity impairment alters community structure but permits successful pattern separation in a hippocampal network model

Patients who suffer from traumatic brain injury (TBI) often complain of learning and memory problems. Their symptoms are principally mediated by the hippocampus and the ability to adapt to stimulus, also known as neural plasticity. Therefore, one plausible injury mechanism is plasticity impairment, which currently lacks comprehensive investigation across TBI research. For these studies, we used a computational network model of the hippocampus that includes the dentate gyrus, CA3, and CA1 with neuron-scale resolution. We simulated mild injury through weakened spike-timing-dependent plasticity (STDP), which modulates synaptic weights according to causal spike timing. In preliminary work, we found functional deficits consisting of decreased firing rate and broadband power in areas CA3 and CA1 after STDP impairment. To address structural changes with these studies, we applied modularity analysis to evaluate how STDP impairment modifies community structure in the hippocampal network. We also studied the emergent function of network-based learning and found that impaired networks could acquire conditioned responses after training, but the magnitude of the response was significantly lower. Furthermore, we examined pattern separation, a prerequisite of learning, by entraining two overlapping patterns. Contrary to our initial hypothesis, impaired networks did not exhibit deficits in pattern separation with either population- or rate-based coding. Collectively, these results demonstrate how a mechanism of injury that operates at the synapse regulates circuit function.

Prefrontal Interneurons: Populations, Pathways, and Plasticity Supporting Typical and Disordered Cognition in Rodent Models

Prefrontal cortex (PFC) inhibitory microcircuits regulate the gain and timing of pyramidal neuron firing, coordinate neural ensemble interactions, and gate local and long-range neural communication to support adaptive cognition and contextually tuned behavior. Accordingly, perturbations of PFC inhibitory microcircuits are thought to underlie dysregulated cognition and behavior in numerous psychiatric diseases and relevant animal models. This review, based on a Mini-Symposium presented at the 2022 Society for Neuroscience Meeting, highlights recent studies providing novel insights into: (1) discrete medial PFC (mPFC) interneuron populations in the mouse brain; (2) mPFC interneuron connections with, and regulation of, long-range mPFC afferents; and (3) circuit-specific plasticity of mPFC interneurons. The contributions of such populations, pathways, and plasticity to rodent cognition are discussed in the context of stress, reward, motivational conflict, and genetic mutations relevant to psychiatric disease.

Role of Group I Metabotropic Glutamate Receptors in Spike Timing-Dependent Plasticity

Metabotropic glutamate receptors (mGluRs) are G-protein-coupled receptors that exhibit enormous diversity in their expression patterns, sequence homology, pharmacology, biophysical properties and signaling pathways in the brain. In general, mGluRs modulate different traits of neuronal physiology, including excitability and plasticity processes. Particularly, group I mGluRs located at the pre- or postsynaptic compartments are involved in spike timing-dependent plasticity (STDP) at hippocampal and neocortical synapses. Their roles of participating in the underlying mechanisms for detection of activity coincidence in STDP induction are debated, and diverse findings support models involving mGluRs in STDP forms in which NMDARs do not operate as classical postsynaptic coincidence detectors. Here, we briefly review the involvement of group I mGluRs in STDP and their possible role as coincidence detectors.

Parvalbumin-Positive Interneurons Regulate Cortical Sensory Plasticity in Adulthood and Development Through Shared Mechanisms

Parvalbumin-positive neurons are the largest class of GABAergic, inhibitory neurons in the central nervous system. In the cortex, these fast-spiking cells provide feedforward and feedback synaptic inhibition onto a diverse set of cell types, including pyramidal cells, other inhibitory interneurons, and themselves. Cortical inhibitory networks broadly, and cortical parvalbumin-expressing interneurons (cPVins) specifically, are crucial for regulating sensory plasticity during both development and adulthood. Here we review the functional properties of cPVins that enable plasticity in the cortex of adult mammals and the influence of cPVins on sensory activity at four spatiotemporal scales. First, cPVins regulate developmental critical periods and adult plasticity through molecular and structural interactions with the extracellular matrix. Second, they activate in precise sequence following feedforward excitation to enforce strict temporal limits in response to the presentation of sensory stimuli. Third, they implement gain control to normalize sensory inputs and compress the dynamic range of output. Fourth, they synchronize broad network activity patterns in response to behavioral events and state changes. Much of the evidence for the contribution of cPVins to plasticity comes from classic models that rely on sensory deprivation methods to probe experience-dependent changes in the brain. We support investigating naturally occurring, adaptive cortical plasticity to study cPVin circuits in an ethologically relevant framework, and discuss recent insights from our work on maternal experience-induced auditory cortical plasticity.

Plasticity impairment exposes CA3 vulnerability in a hippocampal network model of mild traumatic brain injury

Proper function of the hippocampus is critical for executing cognitive tasks such as learning and memory. Traumatic brain injury (TBI) and other neurological disorders are commonly associated with cognitive deficits and hippocampal dysfunction. Although there are many existing models of individual subregions of the hippocampus, few models attempt to integrate the primary areas into one system. In this work, we developed a computational model of the hippocampus, including the dentate gyrus, CA3, and CA1. The subregions are represented as an interconnected neuronal network, incorporating well-characterized ex vivo slice electrophysiology into the functional neuron models and well-documented anatomical connections into the network structure. In addition, since plasticity is foundational to the role of the hippocampus in learning and memory as well as necessary for studying adaptation to injury, we implemented spike-timing-dependent plasticity among the synaptic connections. Our model mimics key features of hippocampal activity, including signal frequencies in the theta and gamma bands and phase-amplitude coupling in area CA1. We also studied the effects of spike-timing-dependent plasticity impairment, a potential consequence of TBI, in our model and found that impairment decreases broadband power in CA3 and CA1 and reduces phase coherence between these two subregions, yet phase-amplitude coupling in CA1 remains intact. Altogether, our work demonstrates characteristic hippocampal activity with a scaled network model of spiking neurons and reveals the sensitive balance of plasticity mechanisms in the circuit through one manifestation of mild traumatic injury.

Cortical Representation of Touch in Silico

With its six layers and ~ 12,000 neurons, a cortical column is a complex network whose function is plausibly greater than the sum of its constituents'. Functional characterization of its network components will require going beyond the brute-force modulation of the neural activity of a small group of neurons. Here we introduce an open-source, biologically inspired, computationally efficient network model of the somatosensory cortex's granular and supragranular layers after reconstructing the barrel cortex in soma resolution. Comparisons of the network activity to empirical observations showed that the in silico network replicates the known properties of touch representations and whisker deprivation-induced changes in synaptic strength induced in vivo. Simulations show that the history of the membrane potential acts as a spatial filter that determines the presynaptic population of neurons contributing to a post-synaptic action potential; this spatial filtering might be critical for synaptic integration of top-down and bottom-up information.

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).

A dopamine gradient controls access to distributed working memory in the large-scale monkey cortex

Dopamine is required for working memory, but how it modulates the large-scale cortex is unknown. Here, we report that dopamine receptor density per neuron, measured by autoradiography, displays a macroscopic gradient along the macaque cortical hierarchy. This gradient is incorporated in a connectome-based large-scale cortex model endowed with multiple neuron types. The model captures an inverted U-shaped dependence of working memory on dopamine and spatial patterns of persistent activity observed in over 90 experimental studies. Moreover, we show that dopamine is crucial for filtering out irrelevant stimuli by enhancing inhibition from dendrite-targeting interneurons. Our model revealed that an activity-silent memory trace can be realized by facilitation of inter-areal connections and that adjusting cortical dopamine induces a switch from this internal memory state to distributed persistent activity. Our work represents a cross-level understanding from molecules and cell types to recurrent circuit dynamics underlying a core cognitive function distributed across the primate cortex.

Alternation of Neuronal Feature Selectivity Induced by Paired Optogenetic-Mechanical Stimulation in the Barrel Cortex

Paired stimulation has been applied to modulate neuronal functions in the primary somatosensory cortex but its utility in the alternation of tuning function, such as direction tuning for whisker stimuli, remains unclear. In the present study, we attempted to manipulate feature preferences in barrel cortical neurons using repetitive paired whisker deflection combined with optogenetic stimulation and to obtain optimal parameters that can induce neuroplasticity. We found no significant response changes across stimulus parameters, such as onset asynchronies and paired directions. Only when paired stimulation was applied in the nonpreferred direction of the principal whisker of a neuron, were the neuron’s responses enhanced in that direction. Importantly, this effect was only observed when the optogenetic stimulus preceded the mechanical stimulus. Our findings indicate that repetitive paired optogenetic-mechanical stimulation can induce in vivo neuroplasticity of feature selectivity in limited situations.

Imbalance of Excitatory/Inhibitory Neuron Differentiation in Neurodevelopmental Disorders with an NR2F1 Point Mutation

Recent studies have revealed an essential role for embryonic cortical development in the pathophysiology of neurodevelopmental disorders, including autism spectrum disorder (ASD). However, the genetic basis and underlying mechanisms remain unclear. Here, we generate mutant human embryonic stem cell lines (Mut hESCs) carrying an NR2F1-R112K mutation that has been identified in a patient with ASD features and investigate their neurodevelopmental alterations. Mut hESCs overproduce ventral telencephalic neuron progenitors (ventral NPCs) and underproduce dorsal NPCs, causing the imbalance of excitatory/inhibitory neurons. These alterations can be mainly attributed to the aberrantly activated Hedgehog signaling pathway. Moreover, the corresponding Nr2f1 point-mutant mice display a similar excitatory/inhibitory neuron imbalance and abnormal behaviors. Antagonizing the increased inhibitory synaptic transmission partially alleviates their behavioral deficits. Together, our results suggest that the NR2F1-dependent imbalance of excitatory/inhibitory neuron differentiation caused by the activated Hedgehog pathway is one precursor of neurodevelopmental disorders and may enlighten the therapeutic approaches.

Preexisting hippocampal network dynamics constrain optogenetically induced place fields

Memory models often emphasize the need to encode novel patterns of neural activity imposed by sensory drive. Prior learning and innate architecture likely restrict neural plasticity, however. Here, we test how the incorporation of synthetic hippocampal signals is constrained by preexisting circuit dynamics. We optogenetically stimulated small groups of CA1 neurons as mice traversed a chosen segment of a linear track, mimicking the emergence of place fields. Stimulation induced persistent place field remapping in stimulated and non-stimulated neurons. The emergence of place fields could be predicted from sporadic firing in the new place field location and the temporal relationship to peer neurons before the optogenetic perturbation. Circuit modification was reflected by altered spike transmission between connected pyramidal cells and inhibitory interneurons, which persisted during post-experience sleep. We hypothesize that optogenetic perturbation unmasked sub-threshold place fields. Plasticity in recurrent/lateral inhibition may drive learning through the rapid association of existing states.

Molecular Mechanisms Underlying Ascl1-Mediated Astrocyte-to-Neuron Conversion

Direct neuronal reprogramming potentially provides valuable sources for cell-based therapies. Proneural gene Ascl1 converts astrocytes into induced neuronal (iN) cells efficiently both in vitro and in vivo. However, the underlying mechanisms are largely unknown. By combining RNA sequencing and chromatin immunoprecipitation followed by high-throughput sequencing, we found that the expression of 1,501 genes was markedly changed during the early stages of Ascl1-induced astrocyte-to-neuron conversion and that the regulatory regions of 107 differentially expressed genes were directly bound by ASCL1. Among Ascl1's direct targets, Klf10 regulates the neuritogenesis of iN cells at the early stage, Myt1 and Myt1l are critical for the electrophysiological maturation of iN cells, and Neurod4 and Chd7 are required for the efficient conversion of astrocytes into neurons. Together, this study provides more insights into understanding the molecular mechanisms underlying Ascl1-mediated astrocyte-to-neuron conversion and will be of value for the application of direct neuronal reprogramming.

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RNA-seq and ChIP-seq were used to study Ascl1-induced astrocyte-to-neuron conversion

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Early Klf10 regulates neuritogenesis and electrophysiological properties of iN cells

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Myt1 and Myt1l are critical for the electrophysiological maturation of iN cells

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Neurod4 and Chd7 are required for efficient conversion of astrocytes to neurons

Neurodegeneration exposes firing rate dependent effects on oscillation dynamics in computational neural networks

Traumatic brain injury (TBI) can lead to neurodegeneration in the injured circuitry, either through primary structural damage to the neuron or secondary effects that disrupt key cellular processes. Moreover, traumatic injuries can preferentially impact subpopulations of neurons, but the functional network effects of these targeted degeneration profiles remain unclear. Although isolating the consequences of complex injury dynamics and long-term recovery of the circuit can be difficult to control experimentally, computational networks can be a powerful tool to analyze the consequences of injury. Here, we use the Izhikevich spiking neuron model to create networks representative of cortical tissue. After an initial settling period with spike-timing-dependent plasticity (STDP), networks developed rhythmic oscillations similar to those seen in vivo. As neurons were sequentially removed from the network, population activity rate and oscillation dynamics were significantly reduced. In a successive period of network restructuring with STDP, network activity levels returned to baseline for some injury levels and oscillation dynamics significantly improved. We next explored the role that specific neurons have in the creation and termination of oscillation dynamics. We determined that oscillations initiate from activation of low firing rate neurons with limited structural inputs. To terminate oscillations, high activity excitatory neurons with strong input connectivity activate downstream inhibitory circuitry. Finally, we confirm the excitatory neuron population role through targeted neurodegeneration. These results suggest targeted neurodegeneration can play a key role in the oscillation dynamics after injury.

Synaptic Plasticity in Cortical Inhibitory Neurons: What Mechanisms May Help to Balance Synaptic Weight Changes?

Inhibitory neurons play a fundamental role in the normal operation of neuronal networks. Diverse types of inhibitory neurons serve vital functions in cortical networks, such as balancing excitation and taming excessive activity, organizing neuronal activity in spatial and temporal patterns, and shaping response selectivity. Serving these, and a multitude of other functions effectively requires fine-tuning of inhibition, mediated by synaptic plasticity. Plasticity of inhibitory systems can be mediated by changes at inhibitory synapses and/or by changes at excitatory synapses at inhibitory neurons. In this review, we consider that latter locus: plasticity at excitatory synapses to inhibitory neurons. Despite the fact that plasticity of excitatory synaptic transmission to interneurons has been studied in much less detail than in pyramids and other excitatory cells, an abundance of forms and mechanisms of plasticity have been observed in interneurons. Specific requirements and rules for induction, while exhibiting a broad diversity, could correlate with distinct sources of excitatory inputs and distinct types of inhibitory neurons. One common requirement for the induction of plasticity is the rise of intracellular calcium, which could be mediated by a variety of ligand-gated, voltage-dependent, and intrinsic mechanisms. The majority of the investigated forms of plasticity can be classified as Hebbian-type associative plasticity. Hebbian-type learning rules mediate adaptive changes of synaptic transmission. However, these rules also introduce intrinsic positive feedback on synaptic weight changes, making plastic synapses and learning networks prone to runaway dynamics. Because real inhibitory neurons do not express runaway dynamics, additional plasticity mechanisms that counteract imbalances introduced by Hebbian-type rules must exist. We argue that weight-dependent heterosynaptic plasticity has a number of characteristics that make it an ideal candidate mechanism to achieve homeostatic regulation of synaptic weight changes at excitatory synapses to inhibitory neurons.

Contrasting sex-dependent adaptations to synaptic physiology and membrane properties of prefrontal cortex interneuron subtypes in a mouse model of binge drinking

Alcohol use disorder (AUD) affects all sexes, however women who develop AUD may be particularly susceptible to cravings and other components of the disease. While many brain regions are involved in AUD etiology, proper prefrontal cortex (PFC) function is particularly important for top-down craving management and the moderation of drinking behaviors. Essential regulation of PFC output is provided by local inhibitory interneurons, yet how drinking affects interneuron physiology remains poorly understood, particularly in female individuals. To address this gap, we generated fluorescent reporter transgenic mice to label the two major classes of interneuron in deep layer prelimbic PFC, based on expression of parvalbumin (PV-IN) or somatostatin (SST-IN). We then interrogated PV-IN and SST-IN membrane and synaptic physiology in a rodent model of binge drinking. Beginning in late adolescence, mice received 3-4 weeks of intermittent access (IA) ethanol. We prepared acute brain slices one day after the last drinking session. PV-INs but not SST-INs from IA ethanol mice displayed increased excitability relative to controls, regardless of sex. On the contrary, synaptic adaptations to PV-INs differed based on sex. While drinking decreased excitatory synaptic strength onto PV-INs from female mice, PV-INs from IA ethanol male mice exhibited potentiated excitatory transmission relative to controls. In contrast, decreased synaptic strength onto SST-INs was observed following IA ethanol in all groups of mice. Together, these findings illustrate novel sex differences in drinking-related PFC pathophysiology. Discovering means to restore PV-IN and SST-IN dysfunction following extended drinking provides opportunities for developing new treatments for all AUD patients.

Somatodendritic consistency check for temporal feature segmentation

The brain identifies potentially salient features within continuous information streams to process hierarchical temporal events. This requires the compression of information streams, for which effective computational principles are yet to be explored. Backpropagating action potentials can induce synaptic plasticity in the dendrites of cortical pyramidal neurons. By analogy with this effect, we model a self-supervising process that increases the similarity between dendritic and somatic activities where the somatic activity is normalized by a running average. We further show that a family of networks composed of the two-compartment neurons performs a surprisingly wide variety of complex unsupervised learning tasks, including chunking of temporal sequences and the source separation of mixed correlated signals. Common methods applicable to these temporal feature analyses were previously unknown. Our results suggest the powerful ability of neural networks with dendrites to analyze temporal features. This simple neuron model may also be potentially useful in neural engineering applications.

The authors propose a learning rule for a neuron model with dendrite. In their model, somatodendritic interaction implements self-supervised learning applicable to a wide range of sequence learning tasks, including spike pattern detection, chunking temporal input and blind source separation.

Spatial Asymmetry and Short-Term Suppression Underlie Direction Selectivity of Synaptic Excitation in the Mouse Visual Cortex

Direction selectivity (DS) of neuronal responses is fundamental for motion detection. With in vivo whole-cell voltage-clamp recordings from layer (L)4 neurons in the mouse visual cortex, we observed a strong correlation between DS and spatial asymmetry in the distribution of excitatory input strengths. This raises an interesting possibility that the latter may contribute to DS. The preferred direction of excitatory input was found from the stronger to weaker side of its spatial receptive field. A simple linear summation of asymmetrically distributed excitatory responses to stationary flash stimuli however failed to predict the correct directionality: it at best resulted in weak DS with preferred direction opposite to what was observed experimentally. Further studies with sequential 2 flash-bar stimulation revealed a short-term suppression of excitatory input evoked by the late bar. More importantly, the level of the suppression positively correlated with the relative amplitude of the early-bar response. Implementing this amplitude-dependent suppressive interaction can successfully predict DS of excitatory input. Our results suggest that via nonlinear temporal interactions, the spatial asymmetry can be transformed into differential temporal integration of inputs under opposite directional movements. This mechanism may contribute to the DS of excitatory inputs to L4 neurons.

Distinct Heterosynaptic Plasticity in Fast Spiking and Non-Fast-Spiking Inhibitory Neurons in Rat Visual Cortex

Inhibition in neuronal networks of the neocortex serves a multitude of functions, such as balancing excitation and structuring neuronal activity in space and time. Plasticity of inhibition is mediated by changes at both inhibitory synapses, as well as excitatory synapses on inhibitory neurons. Using slices from visual cortex of young male rats, we describe a novel form of plasticity of excitatory synapses on inhibitory neurons, weight-dependent heterosynaptic plasticity. Recordings from connected pyramid-to-interneuron pairs confirm that postsynaptic activity alone can induce long-term changes at synapses that were not presynaptically active during the induction, i.e., heterosynaptic plasticity. Moreover, heterosynaptic changes can accompany homosynaptic plasticity induced in inhibitory neurons by conventional spike-timing-dependent plasticity protocols. In both fast-spiking (FS) and non-FS neurons, heterosynaptic changes were weight-dependent, because they correlated with initial paired-pulse ratio (PPR), indicative of initial strength of a synapse. Synapses with initially high PPR, indicative of low release probability ("weak" synapses), had the tendency to be potentiated, while synapses with low initial PPR ("strong" synapses) tended to depress or did not change. Interestingly, the net outcome of heterosynaptic changes was different in FS and non-FS neurons. FS neurons expressed balanced changes, with gross average (n = 142) not different from control. Non-FS neurons (n = 66) exhibited net potentiation. This difference could be because of higher initial PPR in the non-FS neurons. We propose that weight-dependent heterosynaptic plasticity may counteract runaway dynamics of excitatory inputs imposed by Hebbian-type learning rules and contribute to fine-tuning of distinct aspects of inhibitory function mediated by FS and non-FS neurons in neocortical networks.SIGNIFICANCE STATEMENT Dynamic balance of excitation and inhibition is fundamental for operation of neuronal networks. Fine-tuning of such balance requires synaptic plasticity. Knowledge about diverse forms of plasticity operating in excitatory and inhibitory neurons is necessary for understanding normal function and causes of dysfunction of the nervous system. Here we show that excitatory inputs to major archetypal classes of neocortical inhibitory neurons, fast-spiking (FS) and non-fast-spiking (non-FS), express a novel type of plasticity, weight-dependent heterosynaptic plasticity, which accompanies the induction of Hebbian-type changes. This novel form of plasticity may counteract runaway dynamics at excitatory synapses to inhibitory neurons imposed by Hebbian-type learning rules and contribute to fine-tuning of diverse aspects of inhibitory function mediated by FS and non-FS neurons in neocortical networks.

Size-Dependent Axonal Bouton Dynamics following Visual Deprivation In Vivo

Persistent synapses are thought to underpin the storage of sensory experience, yet little is known about their structural plasticity in vivo. We investigated how persistent presynaptic structures respond to the loss of primary sensory input. Using in vivo two-photon (2P) imaging, we measured fluctuations in the size of excitatory axonal boutons in L2/3 of adult mouse visual cortex after monocular enucleation. The average size of boutons did not change after deprivation, but the range of bouton sizes was reduced. Large boutons decreased, and small boutons increased. Reduced bouton variance was accompanied by a reduced range of correlated calcium-mediated neural activity in L2/3 of awake animals. Network simulations predicted that size-dependent plasticity may promote conditions of greater bidirectional plasticity. These predictions were supported by electrophysiological measures of short- and long-term plasticity. We propose size-dependent dynamics facilitate cortical reorganization by maximizing the potential for bidirectional plasticity.

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The range of persistent axonal bouton sizes is reduced following visual deprivation

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Bouton sizes move toward the mean in a size-dependent manner

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Bouton plasticity is accompanied by a reduced range of correlated network activity

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Deprived cortex exhibits greater bidirectional functional presynaptic plasticity

Leveraging heterogeneity for neural computation with fading memory in layer 2/3 cortical microcircuits

Complexity and heterogeneity are intrinsic to neurobiological systems, manifest in every process, at every scale, and are inextricably linked to the systems’ emergent collective behaviours and function. However, the majority of studies addressing the dynamics and computational properties of biologically inspired cortical microcircuits tend to assume (often for the sake of analytical tractability) a great degree of homogeneity in both neuronal and synaptic/connectivity parameters. While simplification and reductionism are necessary to understand the brain’s functional principles, disregarding the existence of the multiple heterogeneities in the cortical composition, which may be at the core of its computational proficiency, will inevitably fail to account for important phenomena and limit the scope and generalizability of cortical models. We address these issues by studying the individual and composite functional roles of heterogeneities in neuronal, synaptic and structural properties in a biophysically plausible layer 2/3 microcircuit model, built and constrained by multiple sources of empirical data. This approach was made possible by the emergence of large-scale, well curated databases, as well as the substantial improvements in experimental methodologies achieved over the last few years. Our results show that variability in single neuron parameters is the dominant source of functional specialization, leading to highly proficient microcircuits with much higher computational power than their homogeneous counterparts. We further show that fully heterogeneous circuits, which are closest to the biophysical reality, owe their response properties to the differential contribution of different sources of heterogeneity.

Cortical microcircuits are highly inhomogeneous dynamical systems whose information processing capacity is determined by the characteristics of its heterogeneous components and their complex interactions. The high degree of variability that characterizes macroscopic population dynamics, both during ongoing, spontaneous activity and active processing states reflects the underlying complexity and heterogeneity which has the potential to dramatically constrain the space of functions that any given circuit can compute, leading to richer and more expressive information processing systems. In this study, we identify different tentative sources of heterogeneity and assess their differential and cumulative contribution to the microcircuit’s dynamics and information processing capacity. We study these properties in a generic Layer 2/3 cortical microcircuit model, built and constrained by multiple sources of experimental data, and demonstrate that heterogeneity in neuronal properties and microconnectivity structure are important sources of functional specialization, greatly improving the circuit’s processing capacity, while capturing various important features of cortical physiology.

A Hypothetical Model Concerning How Spike-Timing-Dependent Plasticity Contributes to Neural Circuit Formation and Initiation of the Critical Period in Barrel Cortex

Spike timing is an important factor in the modification of synaptic strength. Various forms of spike timing-dependent plasticity (STDP) occur in the brains of diverse species, from insects to humans. In unimodal STDP, only LTP or LTD occurs at the synapse, regardless of which neuron spikes first; the magnitude of potentiation or depression increases as the time between presynaptic and postsynaptic spikes decreases. This from of STDP may promote developmental strengthening or weakening of early projections. In bidirectional Hebbian STDP, the magnitude and the sign (potentiation or depression) of plasticity depend, respectively, on the timing and the order of presynaptic and postsynaptic spikes. In the rodent barrel cortex, multiple forms of STDP appear sequentially during development, and they contribute to network formation, retraction, or fine-scale functional reorganization. Hebbian STDP appears at L4-L2/3 synapses starting at postnatal day (P) 15; the synapses exhibit unimodal "all-LTP STDP" before that age. The appearance of Hebbian STDP at L4-L2/3 synapses coincides with the maturation of parvalbumin-containing GABA interneurons in L4, which contributes to the generation of L4-before-L2/3 spiking in response to thalamic input by producing fast feedforward suppression of both L4 and L2/3 cells. After P15, L4-L2/3 STDP mediates fine-scale circuit refinement, essential for the critical period in the barrel cortex. In this review, we first briefly describe the relevance of STDP to map plasticity in the barrel cortex, then look over roles of distinct forms of STDP during development. Finally, we propose a hypothesis that explains the transition from network formation to the initiation of the critical period in the barrel cortex.

Sensory experience inversely regulates feedforward and feedback excitation-inhibition ratio in rodent visual cortex

Brief (2-3d) monocular deprivation (MD) during the critical period induces a profound loss of responsiveness within binocular (V1b) and monocular (V1m) regions of rodent primary visual cortex. This has largely been ascribed to long-term depression (LTD) at thalamocortical synapses, while a contribution from intracortical inhibition has been controversial. Here we used optogenetics to isolate and measure feedforward thalamocortical and feedback intracortical excitation-inhibition (E-I) ratios following brief MD. Despite depression at thalamocortical synapses, thalamocortical E-I ratio was unaffected in V1b and shifted toward excitation in V1m, indicating that thalamocortical excitation was not effectively reduced. In contrast, feedback intracortical E-I ratio was shifted toward inhibition in V1m, and a computational model demonstrated that these opposing shifts produced an overall suppression of layer 4 excitability. Thus, feedforward and feedback E-I ratios can be independently tuned by visual experience, and enhanced feedback inhibition is the primary driving force behind loss of visual responsiveness.

Input-specific maturation of NMDAR-mediated transmission onto parvalbumin-expressing interneurons in layers 2/3 of the visual cortex

Parvalbumin-expressing (PV) GABAergic interneurons regulate local circuit dynamics. In terms of the excitation driving PV interneuron activity, the N-methyl-d-aspartate receptor (NMDAR)-mediated component onto PV interneurons tends to be smaller than that onto pyramidal neurons but makes a significant contribution to their physiology and development. In the visual cortex, PV interneurons mature during the critical period. We hypothesize that during the critical period, the NMDAR-mediated signaling and functional properties of glutamatergic synapses onto PV interneurons are developmentally regulated. We therefore compared the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)- and NMDAR-mediated synaptic responses before (postnatal days 15-20, P15-P20), during (P25-P40), and after (P50-P60) the visual critical period. AMPAR miniature excitatory postsynaptic currents (mEPSCs) showed a developmental decrease in frequency, whereas NMDAR mEPSCs were absent or showed extremely low frequencies throughout development. For evoked responses, we consistently saw a NMDAR-mediated component, suggesting pre- or postsynaptic differences between evoked and spontaneous neurotransmission. Evoked responses showed input-specific developmental changes. For intralaminar inputs, the NMDAR-mediated component significantly decreased with development. This resulted in adult intralaminar inputs almost exclusively mediated by AMPARs, suited for the computation of synaptic inputs with precise timing, and likely having NMDAR-independent forms of plasticity. In contrast, interlaminar inputs maintained a stable NMDAR-mediated component throughout development but had a shift in the AMPAR paired-pulse ratio from depression to facilitation. Adult interlaminar inputs with facilitating AMPAR responses and a substantial NMDAR component would favor temporal integration of synaptic responses and could be modulated by NMDAR-dependent forms of plasticity. NEW & NOTEWORTHY We show for the first time input-specific developmental changes in the N-methyl-d-aspartate receptor component and short-term plasticity of the excitatory drive onto layers 2/3 parvalbumin-expressing (PV) interneurons in the visual cortex during the critical period. These developmental changes would lead to functionally distinct adult intralaminar and interlaminar glutamatergic inputs that would engage PV interneuron-mediated inhibition differently.

Attractor dynamics of a Boolean model of a brain circuit controlled by multiple parameters

Studies of Boolean recurrent neural networks are briefly introduced with an emphasis on the attractor dynamics determined by the sequence of distinct attractors observed in the limit cycles. We apply this framework to a simplified model of the basal ganglia-thalamocortical circuit where each brain area is represented by a "neuronal" node in a directed graph. Control parameters ranging from neuronal excitability that affects all cells to targeted local connections modified by a new adaptive plasticity rule, and the regulation of the interactive feedback affecting the external input stream of information, allow the network dynamics to switch between stable domains delimited by highly discontinuous boundaries and reach very high levels of complexity with specific configurations. The significance of this approach with regard to brain circuit studies is briefly discussed.

Opposite Roles in Short-Term Plasticity for N-Type and P/Q-Type Voltage-Dependent Calcium Channels in GABAergic Neuronal Connections in the Rat Cerebral Cortex

Neurotransmitter release is triggered by Ca²⁺ influx through voltage-dependent Ca²⁺ channels (VDCCs). Distinct expression patterns of VDCC subtypes localized on the synaptic terminal affect intracellular Ca²⁺ dynamics induced by action potential-triggered Ca²⁺ influx. However, it has been unknown whether the expression pattern of VDCC subtypes depends on each axon terminal or neuronal subtype. Furthermore, little information is available on how these VDCC subtypes regulate the release probability of neurotransmitters. To address these questions, we performed multiple whole-cell patch-clamp recordings from GABAergic neurons in the insular cortex of either the male or the female rat. The paired-pulse ratio (PPR; 50 ms interstimulus interval) varied widely among inhibitory connections between GABAergic neurons. The PPR of unitary IPSCs was enhanced by ω-conotoxin GVIA (CgTx; 3 μm), an N-type VDCC blocker, whereas blockade of P/Q-type VDCCs by ω-agatoxin IVA (AgTx, 200 nm) decreased the PPR. In the presence of CgTx, application of 4 mm [Ca²⁺]_o or of roscovitine, a P/Q-type activator, increased the PPR. These results suggest that the recruitment of P/Q-type VDCCs increases the PPR, whereas N-type VDCCs suppress the PPR. Furthermore, we found that charybdotoxin or apamin, blockers of Ca²⁺-dependent K⁺ channels, with AgTx increased the PPR, suggesting that Ca²⁺-dependent K⁺ channels are coupled to N-type VDCCs and suppress the PPR in GABAergic neuronal terminals. Variance-mean analysis with changing [Ca²⁺]_o showed a negative correlation between the PPR and release probability in GABAergic synapses. These results suggest that GABAergic neurons differentially express N-type and/or P/Q-type VDCCs and that these VDCCs regulate the GABA release probability in distinct manners.SIGNIFICANCE STATEMENT GABAergic neuronal axons target multiple neurons and release GABA triggered by Ca²⁺ influx via voltage-dependent Ca²⁺ channels (VDCCs), including N-type and P/Q-type channels. Little is known about VDCC expression patterns in GABAergic synaptic terminals and their role in short-term plasticity. We focused on inhibitory synaptic connections between GABAergic neurons in the cerebral cortex using multiple whole-cell patch-clamp recordings and found different expression patterns of VDCCs in the synaptic terminals branched from a single presynaptic neuron. Furthermore, we observed facilitative and depressive short-term plasticity of IPSCs mediated by P/Q-type and N-type VDCCs, respectively. These results suggest that VDCC expression patterns regulate distinctive types of synaptic transmission in each GABAergic axon terminal even though they are branched from a common presynaptic neuron.

Presynaptic Effects of N-Methyl-D-Aspartate Receptors Enhance Parvalbumin Cell-Mediated Inhibition of Pyramidal Cells in Mouse Prefrontal Cortex

BACKGROUND

Testing hypotheses regarding the role of N-methyl-D-aspartate receptor (NMDAR) hypofunction in schizophrenia requires understanding the mechanisms of NMDAR regulation of prefrontal cortex (PFC) circuit function. NMDAR antagonists are thought to produce pyramidal cell (PC) disinhibition. However, inhibitory parvalbumin-positive basket cells (PVBCs) have modest NMDAR-mediated excitatory drive and thus are unlikely to participate in NMDAR antagonist-mediated disinhibition. Interestingly, recent studies demonstrated that presynaptic NMDARs enhance transmitter release at central synapses. Thus, if presynaptic NMDARs enhance gamma-aminobutyric acid release at PVBC-to-PC synapses, they could participate in NMDAR-dependent PC disinhibition. Here, we examined whether presynaptic NMDAR effects could modulate gamma-aminobutyric acid release at PVBC-to-PC synapses in mouse PFC.

METHODS

Using whole-cell recordings from synaptically connected pairs in mouse PFC, we determined whether NMDA or NMDAR antagonist application affects PVBC-to-PC inhibition in a manner consistent with a presynaptic mechanism.

RESULTS

NMDAR activation enhanced by ∼40% the synaptic current at PVBC-to-PC pairs. This effect was consistent with a presynaptic mechanism given that it was 1) observed with postsynaptic NMDARs blocked by intracellular MK801, 2) associated with a lower rate of transmission failures and a higher transmitter release probability, and 3) blocked by intracellular MK801 in the PVBC. NMDAR antagonist application did not affect the synaptic currents in PVBC-to-PC pairs, but it reduced the inhibitory currents elicited in PCs with simultaneous glutamate release by extracellular stimulation.

CONCLUSIONS

We demonstrate that NMDAR activation enhances PVBC-to-PC inhibition in a manner consistent with presynaptic mechanisms, and we suggest that the functional impact of this presynaptic effect depends on the activity state of the PFC network.

Interplay of multiple pathways and activity-dependent rules in STDP

Hebbian plasticity describes a basic mechanism for synaptic plasticity whereby synaptic weights evolve depending on the relative timing of paired activity of the pre- and postsynaptic neurons. Spike-timing-dependent plasticity (STDP) constitutes a central experimental and theoretical synaptic Hebbian learning rule. Various mechanisms, mostly calcium-based, account for the induction and maintenance of STDP. Classically STDP is assumed to gradually emerge in a monotonic way as the number of pairings increases. However, non-monotonic STDP accounting for fast associative learning led us to challenge this monotonicity hypothesis and explore how the existence of multiple plasticity pathways affects the dynamical establishment of plasticity. To account for distinct forms of STDP emerging from increasing numbers of pairings and the variety of signaling pathways involved, we developed a general class of simple mathematical models of plasticity based on calcium transients and accommodating various calcium-based plasticity mechanisms. These mechanisms can either compete or cooperate for the establishment of long-term potentiation (LTP) and depression (LTD), that emerge depending on past calcium activity. Our model reproduces accurately the striatal STDP that involves endocannabinoid and NMDAR signaling pathways. Moreover, we predict how stimulus frequency alters plasticity, and how triplet rules are affected by the number of pairings. We further investigate the general model with an arbitrary number of pathways and show that depending on those pathways and their properties, a variety of plasticities may emerge upon variation of the number and/or the frequency of pairings, even when the outcome after large numbers of pairings is identical. These findings, built upon a biologically realistic example and generalized to other applications, argue that in order to fully describe synaptic plasticity it is not sufficient to record STDP curves at fixed pairing numbers and frequencies. In fact, considering the whole spectrum of activity-dependent parameters could have a great impact on the description of plasticity, and a better understanding of the engram.

The brain’s capacity to treat information, learn and store memory relies on synaptic connectivity patterns, which are altered through synaptic plasticity mechanisms. Experimentally, such plasticities were evidenced through protocols involving numerous repetitive stimulations of a given synapse, and were shown to be supported by multiple pathways. Using a simple biologically grounded mathematical model, we show how activation timescales and inactivation levels of each pathway interact and alter plasticity in an intricate manner as stimuli are presented. Building upon data from the synapse between cortex and striatum, we show that synaptic changes may revert or re-emerge as stimuli are presented, and predict specific responses to changes in stimulus frequency or to distinct simulation patterns. Our general model shows that a given plasticity profile emerging in response to a repetitive stimulation protocol can unfold into various scenarii upon variations of the number of stimulus presentations or patterns, which tightly depends on the underlying activated pathways. Altogether, these results argue that in order to better understand learning and memory, single plasticity responses obtained through intensive stimulations do not reveal the complexity of the responses for smaller number of presentations, which may have a strong impact in fast learning of stimuli with low numbers of presentations.

Cell type-specific plasticity at parallel fiber synapses onto Purkinje cells in the posterior caudal lobe of the mormyrid fish cerebellum

It has been demonstrated that there are two morphological subtypes of Purkinje cells (PCs)-fan-shaped Purkinje cells (fPCs) and multipolar Purkinje cells (mPCs)-in the posterior caudal lobe of the mormyrid fish cerebellum, but whether these cell types are also functionally distinct is unknown. Here, we have used electrophysiological and pharmacological tools in a slice preparation to demonstrate that pairing parallel fiber (PF) and climbing fiber (CF) inputs at a low frequency induces long-term depression (LTD) in fPCs but long-term potentiation (LTP) in mPCs. The induction of plasticity in both cell types required postsynaptic Ca²⁺ and type 1α metabotropic glutamate receptors. However, the LTD in fPCs was inducted via a calcium/calmodulin-dependent protein kinase II cascade, whereas LTP induction in mPCs required calcineurin. Moreover, the LTD in fPCs and LTP in mPCs were accompanied by changes to the corresponding paired-pulse ratios and their coefficients of variation, suggesting presynaptic modes of expression for the plasticity at PF terminals for both cell types. Hence, the synaptic plasticity at PF synapses onto PCs in the posterior caudal lobe of the mormyrid cerebellum is cell type specific, with both pre- and postsynaptic mechanisms contributing to its induction and expression. NEW & NOTEWORTHY Much has been learnt about the cerebellar long-term depression (LTD) in the cortex. More recent work has shown that long-term potentiation (LTP) is equally important for cerebellar motor learning. Here we report for the first time that plasticity in the mormyrid cerebellum is cell type specific, e.g., following the conventional pairing of parallel and climbing fiber inputs in an in vitro preparation leads to LTD in one Purkinje cell subtype and LTP in another.

Modulation of Spike-Timing Dependent Plasticity: Towards the Inclusion of a Third Factor in Computational Models

In spike-timing dependent plasticity (STDP) change in synaptic strength depends on the timing of pre- vs. postsynaptic spiking activity. Since STDP is in compliance with Hebb's postulate, it is considered one of the major mechanisms of memory storage and recall. STDP comprises a system of two coincidence detectors with N-methyl-D-aspartate receptor (NMDAR) activation often posited as one of the main components. Numerous studies have unveiled a third component of this coincidence detection system, namely neuromodulation and glia activity shaping STDP. Even though dopaminergic control of STDP has most often been reported, acetylcholine, noradrenaline, nitric oxide (NO), brain-derived neurotrophic factor (BDNF) or gamma-aminobutyric acid (GABA) also has been shown to effectively modulate STDP. Furthermore, it has been demonstrated that astrocytes, via the release or uptake of glutamate, gate STDP expression. At the most fundamental level, the timing properties of STDP are expected to depend on the spatiotemporal dynamics of the underlying signaling pathways. However in most cases, due to technical limitations experiments grant only indirect access to these pathways. Computational models carefully constrained by experiments, allow for a better qualitative understanding of the molecular basis of STDP and its regulation by neuromodulators. Recently, computational models of calcium dynamics and signaling pathway molecules have started to explore STDP emergence in ex and in vivo-like conditions. These models are expected to reproduce better at least part of the complex modulation of STDP as an emergent property of the underlying molecular pathways. Elucidation of the mechanisms underlying STDP modulation and its consequences on network dynamics is of critical importance and will allow better understanding of the major mechanisms of memory storage and recall both in health and disease.

Adenosine A2A Receptors Control Glutamatergic Synaptic Plasticity in Fast Spiking Interneurons of the Prefrontal Cortex

Adenosine A_2A receptors (A_2AR) are activated upon increased synaptic activity to assist in the implementation of long-term plastic changes at synapses. While it is reported that A_2AR are involved in the control of prefrontal cortex (PFC)-dependent behavior such as working memory, reversal learning and effort-based decision making, it is not known whether A_2AR control glutamatergic synapse plasticity within the medial PFC (mPFC). To elucidate that, we tested whether A_2AR blockade affects long-term plasticity (LTP) of excitatory post-synaptic potentials in pyramidal neurons and fast spiking (FS) interneurons in layer 5 of the mPFC and of population spikes. Our results show that A_2AR are enriched at mPFC synapses, where their blockade reversed the direction of plasticity at excitatory synapses onto layer 5 FS interneurons from LTP to long-term depression, while their blockade had no effect on the induction of LTP at excitatory synapses onto layer 5 pyramidal neurons. At the network level, extracellularly induced LTP of population spikes was reduced by A_2AR blockade. The interneuron-specificity of A_2AR in controlling glutamatergic synapse LTP may ensure that during periods of high synaptic activity, a proper excitation/inhibition balance is maintained within the mPFC.

Brain-Computer Interface with Inhibitory Neurons Reveals Subtype-Specific Strategies

Brain-computer interfaces have seen an increase in popularity due to their potential for direct neuroprosthetic applications for amputees and disabled individuals. Supporting this promise, animals-including humans-can learn even arbitrary mapping between the activity of cortical neurons and movement of prosthetic devices [1-4]. However, the performance of neuroprosthetic device control has been nowhere near that of limb control in healthy individuals, presenting a dire need to improve the performance. One potential limitation is the fact that previous work has not distinguished diverse cell types in the neocortex, even though different cell types possess distinct functions in cortical computations [5-7] and likely distinct capacities to control brain-computer interfaces. Here, we made a first step in addressing this issue by tracking the plastic changes of three major types of cortical inhibitory neurons (INs) during a neuron-pair operant conditioning task using two-photon imaging of IN subtypes expressing GCaMP6f. Mice were rewarded when the activity of the positive target neuron (N+) exceeded that of the negative target neuron (N-) beyond a set threshold. Mice improved performance with all subtypes, but the strategies were subtype specific. When parvalbumin (PV)-expressing INs were targeted, the activity of N- decreased. However, targeting of somatostatin (SOM)- and vasoactive intestinal peptide (VIP)-expressing INs led to an increase of the N+ activity. These results demonstrate that INs can be individually modulated in a subtype-specific manner and highlight the versatility of neural circuits in adapting to new demands by using cell-type-specific strategies.

Balanced excitation and inhibition are required for high-capacity, noise-robust neuronal selectivity

Neurons and networks in the cerebral cortex must operate reliably despite multiple sources of noise. To evaluate the impact of both input and output noise, we determine the robustness of single-neuron stimulus selective responses, as well as the robustness of attractor states of networks of neurons performing memory tasks. We find that robustness to output noise requires synaptic connections to be in a balanced regime in which excitation and inhibition are strong and largely cancel each other. We evaluate the conditions required for this regime to exist and determine the properties of networks operating within it. A plausible synaptic plasticity rule for learning that balances weight configurations is presented. Our theory predicts an optimal ratio of the number of excitatory and inhibitory synapses for maximizing the encoding capacity of balanced networks for given statistics of afferent activations. Previous work has shown that balanced networks amplify spatiotemporal variability and account for observed asynchronous irregular states. Here we present a distinct type of balanced network that amplifies small changes in the impinging signals and emerges automatically from learning to perform neuronal and network functions robustly.

Hippocampal GABAergic Inhibitory Interneurons

In the hippocampus GABAergic local circuit inhibitory interneurons represent only ~10-15% of the total neuronal population; however, their remarkable anatomical and physiological diversity allows them to regulate virtually all aspects of cellular and circuit function. Here we provide an overview of the current state of the field of interneuron research, focusing largely on the hippocampus. We discuss recent advances related to the various cell types, including their development and maturation, expression of subtype-specific voltage- and ligand-gated channels, and their roles in network oscillations. We also discuss recent technological advances and approaches that have permitted high-resolution, subtype-specific examination of their roles in numerous neural circuit disorders and the emerging therapeutic strategies to ameliorate such pathophysiological conditions. The ultimate goal of this review is not only to provide a touchstone for the current state of the field, but to help pave the way for future research by highlighting where gaps in our knowledge exist and how a complete appreciation of their roles will aid in future therapeutic strategies.

Impaired Cerebellum to Primary Motor Cortex Associative Plasticity in Parkinson's Disease and Spinocerebellar Ataxia Type 3

Background

Functional perturbation of the cerebellum (CB)–motor cortex (M1) interactions may underlie pathophysiology of movement disorders, such as Parkinson’s disease (PD) and spinocerebellar ataxia type 3 (SCA3). Recently, M1 motor excitability can be bidirectionally modulated in young subjects by corticocortical paired associative stimulation (PAS) on CB and contralateral M1 with transcranial magnetic stimulation (TMS), probably through the cerebello–dentato–thalamo–cortical (CDTC) circuit. In this study, we investigated the CB to M1-associative plasticity in healthy elderly PD and SCA3.

Methods

Ten right-handed PD patients, nine gene-confirmed SCA3 patients, and 10 age-matched healthy controls (HC) were studied. One hundred and twenty pairs of TMS of the left M1 preceded by right lateral CB TMS at an interstimulus interval of 2 (CB → M1 PAS_2ms) and 6 ms (CB → M1 PAS_6ms) were, respectively, applied with at least 1-week interval. M1 excitability was assessed by motor-evoked potential (MEP) amplitude, short-interval intracortical inhibition (SICI), intracortical facilitation (ICF), and cerebellar inhibition (CBI) at the first dorsal interosseous muscle of the right hand before and after the CB → M1 PAS.

Results

The M1 excitability represented by MEP amplitude was significantly facilitated and suppressed in the HC group by CB → M1 PAS_2ms and CB → M1 PAS_6ms, respectively. The bidirectional modulation on MEP amplitude was absent in the PD and SCA3 groups. SICI and the baseline CBI were significantly reduced in the SCA3 group compared to those of the HC group irrespective of the CB → M1 PAS protocols. There was a significant reduction of CBI immediately and 60 min after the CB → M1 PAS protocols in the HC group but not in the patient groups. No significant change of ICF was found.

Conclusion

Corticocortical CB → M1 PAS can induce bidirectional motor cortical plasticity in M1 for healthy aged subjects. The modulation may be independent of the inhibitory neurocircuits, such as SICI and CBI, and the facilitatory mechanism like ICF. Both patients with PD and SCA3 showed impairment of such plasticity, suggesting significant functional perturbation of the CDTC circuit.

Differential excitatory control of 2 parallel basket cell networks in amygdala microcircuits

Information processing in neural networks depends on the connectivity among excitatory and inhibitory neurons. The presence of parallel, distinctly controlled local circuits within a cortical network may ensure an effective and dynamic regulation of microcircuit function. By applying a combination of optogenetics, electrophysiological recordings, and high resolution microscopic techniques, we uncovered the organizing principles of synaptic communication between principal neurons and basket cells in the basal nucleus of the amygdala. In this cortical structure, known to be critical for emotional memory formation, we revealed the presence of 2 parallel basket cell networks expressing either parvalbumin or cholecystokinin. While the 2 basket cell types are mutually interconnected within their own category via synapses and gap junctions, they avoid innervating each other, but form synaptic contacts with axo-axonic cells. Importantly, both basket cell types have the similar potency to control principal neuron spiking, but they receive excitatory input from principal neurons with entirely diverse features. This distinct feedback synaptic excitation enables a markedly different recruitment of the 2 basket cell types upon the activation of local principal neurons. Our data suggest fundamentally different functions for the 2 parallel basket cell networks in circuit operations in the amygdala.

The perisomatic region of neurons refers collectively to the membrane surface of the cell body or soma, proximal dendrites, and axon initial segment. This is a unique functional domain in which the activity of a neuron can be controlled in the most effective manner. In the cerebral cortex, the perisomatic region of excitatory principal cells is solely innervated by inhibitory interneurons, which can be divided into 3 functional groups: axo-axonic cells and 2 types of basket cells. The reason why 3 distinct types of inhibitory cells are specialized to control principal cell firing is still unknown. To reveal the possible differences in the role of the 3 interneuron types played in cortical operation, we have investigated the organizing principles of synaptic communication between principal cells and inhibitory cell types in the basal nucleus of the amygdala. In this cortical structure, known to be critical for affective behavior, we revealed that the 2 basket cell types avoid innervating each other but contact axo-axonic cells. Both basket cell types have a similar potency to control principal cell firing, but they receive excitatory input from principal cells with entirely distinct features. Our data suggest fundamentally different functions for the 2 parallel basket cell networks in amygdala operation.

Impaired Tuning of Neural Ensembles and the Pathophysiology of Schizophrenia: A Translational and Computational Neuroscience Perspective

The functional optimization of neural ensembles is central to human higher cognitive functions. When the functions through which neural activity is tuned fail to develop or break down, symptoms and cognitive impairments arise. This review considers ways in which disturbances in the balance of excitation and inhibition might develop and be expressed in cortical networks in association with schizophrenia. This presentation is framed within a developmental perspective that begins with disturbances in glutamate synaptic development in utero. It considers developmental correlates and consequences, including compensatory mechanisms that increase intrinsic excitability or reduce inhibitory tone. It also considers the possibility that these homeostatic increases in excitability have potential negative functional and structural consequences. These negative functional consequences of disinhibition may include reduced working memory-related cortical activity associated with the downslope of the "inverted-U" input-output curve, impaired spatial tuning of neural activity and impaired sparse coding of information, and deficits in the temporal tuning of neural activity and its implication for neural codes. The review concludes by considering the functional significance of noisy activity for neural network function. The presentation draws on computational neuroscience and pharmacologic and genetic studies in animals and humans, particularly those involving N-methyl-D-aspartate glutamate receptor antagonists, to illustrate principles of network regulation that give rise to features of neural dysfunction associated with schizophrenia. While this presentation focuses on schizophrenia, the general principles outlined in the review may have broad implications for considering disturbances in the regulation of neural ensembles in psychiatric disorders.

Paired Stimulation for Spike-Timing-Dependent Plasticity in Primate Sensorimotor Cortex

Classic in vitro studies have described spike-timing-dependent plasticity (STDP) at a synapse: the connection from neuron A to neuron B is strengthened (or weakened) when A fires before (or after) B within an optimal time window. Accordingly, more recent in vivo works have demonstrated behavioral effects consistent with an STDP mechanism; however, many relied on single-unit recordings. The ability to modify cortical connections becomes useful in the context of injury, when connectivity and associated behavior are compromised. To avoid the need for long-term, stable isolation of single units, one could control timed activation of two cortical sites with paired electrical stimulation. We tested the hypothesis that STDP could be induced via prolonged paired stimulation as quantified by cortical evoked potentials (EPs) in the sensorimotor cortex of awake, behaving monkeys. Paired simulation between two interconnected sites produced robust effects in EPs consistent with STDP, but only at 2/15 tested pairs. The stimulation protocol often produced increases in global network excitability or depression of the conditioned pair. Together, these results suggest that paired stimulation in vivo is a viable method to induce STDP between cortical populations, but that factors beyond activation timing must be considered to produce conditioning effects.SIGNIFICANCE STATEMENT Plasticity of neural connections is important for development, learning, memory, and recovery from injury. Cellular mechanisms underlying spike-timing-dependent plasticity have been studied extensively in vitro Recent in vivo work has demonstrated results consistent with the previously defined cellular mechanisms; however, the output measure in these studies was typically an indirect assessment of plasticity at the neural level. Here, we show direct plasticity in recordings of neuronal populations in awake, behaving nonhuman primates induced by paired electrical stimulation. In contrast to in vitro studies, we found that plastic effects were only produced between specific cortical areas. These findings suggest that similar mechanisms drive plasticity in vitro and in vivo, but that cortical architecture may contribute significantly to site-dependent effects.

Plasticity in Single Axon Glutamatergic Connection to GABAergic Interneurons Regulates Complex Events in the Human Neocortex

In the human neocortex, single excitatory pyramidal cells can elicit very large glutamatergic EPSPs (VLEs) in inhibitory GABAergic interneurons capable of triggering their firing with short (3–5 ms) delay. Similar strong excitatory connections between two individual neurons have not been found in nonhuman cortices, suggesting that these synapses are specific to human interneurons. The VLEs are crucial for generating neocortical complex events, observed as single pyramidal cell spike-evoked discharge of cell assemblies in the frontal and temporal cortices. However, long-term plasticity of the VLE connections and how the plasticity modulates neocortical complex events has not been studied. Using triple and dual whole-cell recordings from synaptically connected human neocortical layers 2–3 neurons, we show that VLEs in fast-spiking GABAergic interneurons exhibit robust activity-induced long-term depression (LTD). The LTD by single pyramidal cell 40 Hz spike bursts is specific to connections with VLEs, requires group I metabotropic glutamate receptors, and has a presynaptic mechanism. The LTD of VLE connections alters suprathreshold activation of interneurons in the complex events suppressing the discharge of fast-spiking GABAergic cells. The VLEs triggering the complex events may contribute to cognitive processes in the human neocortex, and their long-term plasticity can alter the discharging cortical cell assemblies by learning.

Many microscale features in the human neocortex—a part of the brain involved in higher functions such as sensory perception, generation of motor commands, spatial reasoning, and language—are closely similar to those reported in experimental animals commonly used in neuroscience, like mice. However, the human neocortical neurons also exhibit specializations only reported in our species. One such feature is the capacity of excitatory principal cells to elicit firing in local inhibitory interneurons with a single action potential via very strong excitatory synapses. It has been suggested that this feature has specifically evolved to enhance coordinated firing of neuronal ensembles in higher brain functions. However, it is unknown how these circuits are modified by learning. Therefore, we investigated how these very strong excitatory synapses are changed, and if their impact on the firing of local inhibitory neurons is altered by repetitive action potentials mimicking learning-related activity. By recording in human neocortical slices, we report that the strong excitatory synapses on interneurons exhibit robust activity-dependent long-term plasticity. The plasticity also regulates the discharge of local interneurons driven by these synapses. Although these specialized synapses have only been reported in the human neocortex, their plasticity mechanism is evolutionarily conserved. We suggest that the strong synapses with robust plasticity have evolved to enhance complex brain functions and learning.

Spike Timing-Dependent Plasticity in the Mouse Barrel Cortex Is Strongly Modulated by Sensory Learning and Depends on Activity of Matrix Metalloproteinase 9

Experience and learning in adult primary somatosensory cortex are known to affect neuronal circuits by modifying both excitatory and inhibitory transmission. Synaptic plasticity phenomena provide a key substrate for cognitive processes, but precise description of the cellular and molecular correlates of learning is hampered by multiplicity of these mechanisms in various projections and in different types of neurons. Herein, we investigated the impact of associative learning on neuronal plasticity in distinct types of postsynaptic neurons by checking the impact of classical conditioning (pairing whisker stroking with tail shock) on the spike timing-dependent plasticity (t-LTP and t-LTD) in the layer IV to II/III vertical pathway of the mouse barrel cortex. Learning in this paradigm practically prevented t-LTP measured in pyramidal neurons but had no effect on t-LTD. Since classical conditioning is known to affect inhibition in the barrel cortex, we examined its effect on tonic GABAergic currents and found a strong downregulation of these currents in the layer II/III interneurons but not in pyramidal cells. Matrix metalloproteinases emerged as crucial players in synaptic plasticity and learning. We report that the blockade of MMP-9 (but not MMP-3) abolished t-LTP having no effect on t-LTD. Moreover, associative learning resulted in an upregulation of gelatinolytic activity within the "trained" barrel. We conclude that LTP induced by spike timing-dependent plasticity (STDP) paradigm is strongly correlated with associative learning and critically depends on the activity of MMP-9.

A dendritic disinhibitory circuit mechanism for pathway-specific gating

While reading a book in a noisy café, how does your brain ‘gate in' visual information while filtering out auditory stimuli? Here we propose a mechanism for such flexible routing of information flow in a complex brain network (pathway-specific gating), tested using a network model of pyramidal neurons and three classes of interneurons with connection probabilities constrained by data. We find that if inputs from different pathways cluster on a pyramidal neuron dendrite, a pathway can be gated-on by a disinhibitory circuit motif. The branch-specific disinhibition can be achieved despite dense interneuronal connectivity, even with random connections. Moreover, clustering of input pathways on dendrites can naturally emerge through synaptic plasticity regulated by dendritic inhibition. This gating mechanism in a neural circuit is further demonstrated by performing a context-dependent decision-making task. The model suggests that cognitive flexibility engages top-down signalling of behavioural rule or context that targets specific classes of inhibitory neurons.

Cortical circuits receive simultaneous inputs from multiple pathways and are able to flexibly select the appropriate inputs for processing. Here the authors propose a network model in which dendritic branch-specific disinhibition established through synaptic plasticity achieves pathway-specific gating.

Selective Maturation of Temporal Dynamics of Intracortical Excitatory Transmission at the Critical Period Onset

Although the developmental maturation of cortical inhibitory synapses is known to be a critical factor in gating the onset of critical period (CP) for experience-dependent cortical plasticity, how synaptic transmission dynamics of other cortical synapses are regulated during the transition to CP remains unknown. Here, by systematically examining various intracortical synapses within layer 4 of the mouse visual cortex, we demonstrate that synaptic temporal dynamics of intracortical excitatory synapses on principal cells (PCs) and inhibitory parvalbumin- or somatostatin-expressing cells are selectively regulated before the CP onset, whereas those of intracortical inhibitory synapses and long-range thalamocortical excitatory synapses remain unchanged. This selective maturation of synaptic dynamics results from a ubiquitous reduction of presynaptic release and is dependent on visual experience. These findings provide an additional essential circuit mechanism for regulating CP timing in the developing visual cortex.

Experience-Dependent Bimodal Plasticity of Inhibitory Neurons in Early Development

Inhibitory neurons are heterogeneous in the mature brain. It is unclear when and how inhibitory neurons express distinct structural and functional profiles. Using in vivo time-lapse imaging of tectal neuron structure and visually evoked Ca(2+) responses in tadpoles, we found that inhibitory neurons cluster into two groups with opposite valence of plasticity after 4 hr of dark and visual stimulation. Half decreased dendritic arbor size and Ca(2+) responses after dark and increased them after visual stimulation, matching plasticity in excitatory neurons. Half increased dendrite arbor size and Ca(2+) responses following dark and decreased them after stimulation. At the circuit level, visually evoked excitatory and inhibitory synaptic inputs were potentiated by visual experience and E/I remained constant. Our results indicate that developing inhibitory neurons fall into distinct functional groups with opposite experience-dependent plasticity and as such, are well positioned to foster experience-dependent synaptic plasticity and maintain circuit stability during labile periods of circuit development.