Synapse-type-specific plasticity in local circuits

Synapse-type-specific competitive Hebbian learning forms functional recurrent networks

Cortical networks exhibit complex stimulus-response patterns that are based on specific recurrent interactions between neurons. For example, the balance between excitatory and inhibitory currents has been identified as a central component of cortical computations. However, it remains unclear how the required synaptic connectivity can emerge in developing circuits where synapses between excitatory and inhibitory neurons are simultaneously plastic. Using theory and modeling, we propose that a wide range of cortical response properties can arise from a single plasticity paradigm that acts simultaneously at all excitatory and inhibitory connections-Hebbian learning that is stabilized by the synapse-type-specific competition for a limited supply of synaptic resources. In plastic recurrent circuits, this competition enables the formation and decorrelation of inhibition-balanced receptive fields. Networks develop an assembly structure with stronger synaptic connections between similarly tuned excitatory and inhibitory neurons and exhibit response normalization and orientation-specific center-surround suppression, reflecting the stimulus statistics during training. These results demonstrate how neurons can self-organize into functional networks and suggest an essential role for synapse-type-specific competitive learning in the development of cortical circuits.

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.

Creative therapy in health and disease: Inner vision

Can we better understand the unique mechanisms of de novo abilities in light of our current knowledge of the psychological and neuroscientific literature on creativity? This review outlines the state-of-the-art in the neuroscience of creativity and points out crucial aspects that still demand further exploration, such as brain plasticity. The progressive development of current neuroscience research on creativity presents a multitude of prospects and potentials for furnishing efficacious therapy in the context of health and illness. Therefore, we discuss directions for future studies, identifying a focus on pinpointing the neglected beneficial practices for creative therapy. We emphasize the neglected neuroscience perspective of creativity on health and disease and how creative therapy could offer limitless possibilities to improve our well-being and give hope to patients with neurodegenerative diseases to compensate for their brain injuries and cognitive impairments by expressing their hidden creativity.

Synapse-specific burst coding sustained by local axonal translation

Neurotransmission in the brain is unreliable, suggesting that high-frequency spike bursts rather than individual spikes carry the neural code. For instance, cortical pyramidal neurons rely on bursts in memory formation. Protein synthesis is another key factor in long-term synaptic plasticity and learning but is widely considered unnecessary for synaptic transmission. Here, however, we show that burst neurotransmission at synapses between neocortical layer 5 pyramidal cells depends on axonal protein synthesis linked to presynaptic NMDA receptors and mTOR. We localized protein synthesis to axons with laser axotomy and puromycylation live imaging. We whole-cell recorded connected neurons to reveal how translation sustained readily releasable vesicle pool size and replenishment rate. We live imaged axons and found sparsely docked RNA granules, suggesting synapse-specific regulation. In agreement, translation boosted neurotransmission onto excitatory but not inhibitory basket or Martinotti cells. Local axonal mRNA translation is thus a hitherto unappreciated principle for sustaining burst coding at specific synapse types.

Presynaptic spike-driven plasticity based on eligibility trace for on-chip learning system

Introduction

Recurrent spiking neural network (RSNN) performs excellently in spatio-temporal learning with backpropagation through time (BPTT) algorithm. But the requirement of computation and memory in BPTT makes it hard to realize an on-chip learning system based on RSNN. In this paper, we aim to realize a high-efficient RSNN learning system on field programmable gate array (FPGA).

Methods

A presynaptic spike-driven plasticity architecture based on eligibility trace is implemented to reduce the resource consumption. The RSNN with leaky integrate-and-fire (LIF) and adaptive LIF (ALIF) models is implemented on FPGA based on presynaptic spike-driven architecture. In this architecture, the eligibility trace gated by a learning signal is used to optimize synaptic weights without unfolding the network through time. When a presynaptic spike occurs, the eligibility trace is calculated based on its latest timestamp and drives synapses to update their weights. Only the latest timestamps of presynaptic spikes are required to be stored in buffers to calculate eligibility traces.

Results

We show the implementation of this architecture on FPGA and test it with two experiments. With the presynaptic spike-driven architecture, the resource consumptions, including look-up tables (LUTs) and registers, and dynamic power consumption of synaptic modules in the on-chip learning system are greatly reduced. The experiment results and compilation results show that the buffer size of the on-chip learning system is reduced and the RSNNs implemented on FPGA exhibit high efficiency in resources and energy while accurately solving tasks.

Discussion

This study provides a solution to the problem of data congestion in the buffer of large-scale learning systems.

What the hippocampus tells the HPA axis: Hippocampal output attenuates acute stress responses via disynaptic inhibition of CRF+ PVN neurons

The hippocampus exerts inhibitory feedback on the release of glucocorticoids. Because the major hippocampal efferent projections are excitatory, it has been hypothesized that this inhibition is mediated by populations of inhibitory neurons in the hypothalamus or elsewhere. These regions would be excited by hippocampal efferents and project to corticotropin-releasing factor (CRF) cells in the paraventricular nucleus of the hypothalamus (PVN). A direct demonstration of the synaptic responses elicited by hippocampal outputs in PVN cells or upstream GABAergic interneurons has not been provided previously. Here, we used viral vectors to express channelrhodopsin (ChR) and enhanced yellow fluorescent protein (EYFP) in pyramidal cells in the ventral hippocampus (vHip) in mice expressing tdTomato in GABA- or CRF-expressing neurons. We observed dense innervation of the bed nucleus of the stria terminalis (BNST) by labeled vHip axons and sparse labeling within the PVN. Using whole-cell voltage-clamp recording in parasagittal brain slices containing the BNST and PVN, photostimulation of vHip terminals elicited rapid excitatory postsynaptic currents (EPSCs) and longer-latency inhibitory postsynaptic currents (IPSCs) in both CRF+ and GAD + cells. The ratio of synaptic excitation and inhibition was maintained in CRF + cells during 20 Hz stimulus trains. Photostimulation of hippocampal afferents to the BNST and PVN in vivo inhibited the rise in blood glucocorticoid levels produced by acute restraint stress. We thus provide functional evidence suggesting that hippocampal output to the BNST contributes to a net inhibition of the hypothalamic-pituitary axis, providing further mechanistic insights into this process using methods with enhanced spatial and temporal resolution.

Pre- and postsynaptically expressed spike-timing-dependent plasticity contribute differentially to neuronal learning

A plethora of experimental studies have shown that long-term synaptic plasticity can be expressed pre- or postsynaptically depending on a range of factors such as developmental stage, synapse type, and activity patterns. The functional consequences of this diversity are not clear, although it is understood that whereas postsynaptic expression of plasticity predominantly affects synaptic response amplitude, presynaptic expression alters both synaptic response amplitude and short-term dynamics. In most models of neuronal learning, long-term synaptic plasticity is implemented as changes in connective weights. The consideration of long-term plasticity as a fixed change in amplitude corresponds more closely to post- than to presynaptic expression, which means theoretical outcomes based on this choice of implementation may have a postsynaptic bias. To explore the functional implications of the diversity of expression of long-term synaptic plasticity, we adapted a model of long-term plasticity, more specifically spike-timing-dependent plasticity (STDP), such that it was expressed either independently pre- or postsynaptically, or in a mixture of both ways. We compared pair-based standard STDP models and a biologically tuned triplet STDP model, and investigated the outcomes in a minimal setting, using two different learning schemes: in the first, inputs were triggered at different latencies, and in the second a subset of inputs were temporally correlated. We found that presynaptic changes adjusted the speed of learning, while postsynaptic expression was more efficient at regulating spike timing and frequency. When combining both expression loci, postsynaptic changes amplified the response range, while presynaptic plasticity allowed control over postsynaptic firing rates, potentially providing a form of activity homeostasis. Our findings highlight how the seemingly innocuous choice of implementing synaptic plasticity by single weight modification may unwittingly introduce a postsynaptic bias in modelling outcomes. We conclude that pre- and postsynaptically expressed plasticity are not interchangeable, but enable complimentary functions.

Differences between functional properties of pre- or postsynaptically expressed long-term plasticity have not yet been explored in much detail. In this paper, we used minimalist models of STDP with different expression loci, in search of fundamental functional consequences. Biologically, presynaptic expression acts mostly on neurotransmitter release, thereby altering short-term synaptic dynamics, whereas postsynaptic expression affects mainly synaptic gain. We compared models where plasticity was expressed only presynaptically or postsynaptically, or in both ways. We found that postsynaptic plasticity had a bigger impact over response times, while both pre- and postsynaptic plasticity were similarly capable of detecting correlated inputs. A model with biologically tuned expression of plasticity achieved the same outcome over a range of frequencies. Also, postsynaptic spiking frequency was not directly affected by presynaptic plasticity of short-term plasticity alone, however in combination with a postsynaptic component, it helped restrain positive feedback, contributing to activity homeostasis. In conclusion, expression locus may determine affinity for distinct coding schemes while also contributing to keep activity within bounds. Our findings highlight the importance of carefully implementing expression of plasticity in biological modelling, since the locus of expression may affect functional outcomes in simulations.

Distinct but overlapping roles of LRRTM1 and LRRTM2 in developing and mature hippocampal circuits

LRRTMs are postsynaptic cell adhesion proteins that have region-restricted expression in the brain. To determine their role in the molecular organization of synapses in vivo, we studied synapse development and plasticity in hippocampal neuronal circuits in mice lacking both Lrrtm1 and Lrrtm2. We found that LRRTM1 and LRRTM2 regulate the density and morphological integrity of excitatory synapses on CA1 pyramidal neurons in the developing brain but are not essential for these roles in the mature circuit. Further, they are required for long-term-potentiation in the CA3-CA1 pathway and the dentate gyrus, and for enduring fear memory in both the developing and mature brain. Our data show that LRRTM1 and LRRTM2 regulate synapse development and function in a cell-type and developmental-stage-specific manner, and thereby contribute to the fine-tuning of hippocampal circuit connectivity and plasticity.

A calcium-based plasticity model for predicting long-term potentiation and depression in the neocortex

Pyramidal cells (PCs) form the backbone of the layered structure of the neocortex, and plasticity of their synapses is thought to underlie learning in the brain. However, such long-term synaptic changes have been experimentally characterized between only a few types of PCs, posing a significant barrier for studying neocortical learning mechanisms. Here we introduce a model of synaptic plasticity based on data-constrained postsynaptic calcium dynamics, and show in a neocortical microcircuit model that a single parameter set is sufficient to unify the available experimental findings on long-term potentiation (LTP) and long-term depression (LTD) of PC connections. In particular, we find that the diverse plasticity outcomes across the different PC types can be explained by cell-type-specific synaptic physiology, cell morphology and innervation patterns, without requiring type-specific plasticity. Generalizing the model to in vivo extracellular calcium concentrations, we predict qualitatively different plasticity dynamics from those observed in vitro. This work provides a first comprehensive null model for LTP/LTD between neocortical PC types in vivo, and an open framework for further developing models of cortical synaptic plasticity.

Local connectivity and synaptic dynamics in mouse and human neocortex

We present a unique, extensive, and open synaptic physiology analysis platform and dataset. Through its application, we reveal principles that relate cell type to synaptic properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Synaptic properties are heterogeneous in most subclass-to-subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, whereas the strength axis accounts for substantial heterogeneity within the subclass. In the human cortex, excitatory-to-excitatory synaptic dynamics are distinct from those in the mouse cortex and vary with depth across layers 2 and 3.

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).

Synaptic Dynamics Convey Differential Sensitivity to Input Pattern Changes in Two Muscles Innervated by the Same Motor Neurons

Postsynaptic responses depend on input patterns as well as short-term synaptic plasticity, summation, and postsynaptic membrane properties, but the interactions of those dynamics with realistic input patterns are not well understood. We recorded the responses of the two pyloric dilator (PD) muscles, cpv2a and cpv2b, that are innervated by and receive identical periodic bursting input from the same two motor neurons in the lobster Homarus americanus. Cpv2a and cpv2b showed quantitative differences in membrane nonlinearities and synaptic summation. At a short timescale, responses in both muscles were dominated by facilitation, albeit with different frequency and time dependence. Realistic burst stimulations revealed more substantial differences. Across bursts, cpv2a showed transient depression, whereas cpv2b showed transient facilitation. Steady-state responses to bursting input also differed substantially. Neither muscle had a monotonic dependence on frequency, but cpv2b showed particularly pronounced bandpass filtering. Cpv2a was sensitive to changes in both burst frequency and intra-burst spike frequency, whereas, despite its much slower responses, cpv2b was largely insensitive to changes in burst frequency. Cpv2a was sensitive to both burst duration and number of spikes per burst, whereas cpv2b was sensitive only to the former parameter. Neither muscle showed consistent sensitivity to changes in the overall spike interval structure, but cpv2b was surprisingly sensitive to changes in the first intervals in each burst, a parameter known to be regulated by dopamine (DA) modulation of spike propagation of the presynaptic axon. These findings highlight how seemingly minor circuit output changes mediated by neuromodulation could be read out differentially at the two synapses.

Mechanisms Underlying Target Selectivity for Cell Types and Subcellular Domains in Developing Neocortical Circuits

The cerebral cortex contains numerous neuronal cell types, distinguished by their molecular identity as well as their electrophysiological and morphological properties. Cortical function is reliant on stereotyped patterns of synaptic connectivity and synaptic function among these neuron types, but how these patterns are established during development remains poorly understood. Selective targeting not only of different cell types but also of distinct postsynaptic neuronal domains occurs in many brain circuits and is directed by multiple mechanisms. These mechanisms include the regulation of axonal and dendritic guidance and fine-scale morphogenesis of pre- and postsynaptic processes, lineage relationships, activity dependent mechanisms and intercellular molecular determinants such as transmembrane and secreted molecules, many of which have also been implicated in neurodevelopmental disorders. However, many studies of synaptic targeting have focused on circuits in which neuronal processes target different lamina, such that cell-type-biased connectivity may be confounded with mechanisms of laminar specificity. In the cerebral cortex, each cortical layer contains cell bodies and processes from intermingled neuronal cell types, an arrangement that presents a challenge for the development of target-selective synapse formation. Here, we address progress and future directions in the study of cell-type-biased synaptic targeting in the cerebral cortex. We highlight challenges to identifying developmental mechanisms generating stereotyped patterns of intracortical connectivity, recent developments in uncovering the determinants of synaptic target selection during cortical synapse formation, and current gaps in the understanding of cortical synapse specificity.

Direction selectivity in retinal bipolar cell axon terminals

The ability to encode the direction of image motion is fundamental to our sense of vision. Direction selectivity along the four cardinal directions is thought to originate in direction-selective ganglion cells (DSGCs) because of directionally tuned GABAergic suppression by starburst cells. Here, by utilizing two-photon glutamate imaging to measure synaptic release, we reveal that direction selectivity along all four directions arises earlier than expected at bipolar cell outputs. Individual bipolar cells contained four distinct populations of axon terminal boutons with different preferred directions. We further show that this bouton-specific tuning relies on cholinergic excitation from starburst cells and GABAergic inhibition from wide-field amacrine cells. DSGCs received both tuned directionally aligned inputs and untuned inputs from among heterogeneously tuned glutamatergic bouton populations. Thus, directional tuning in the excitatory visual pathway is incrementally refined at the bipolar cell axon terminals and their recipient DSGC dendrites by two different neurotransmitters co-released from starburst cells.

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Cardinal direction selectivity emerges at types 7 and 2 bipolar cell axon terminals

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Starburst amacrine cells are necessary for direction selectivity in bipolar cells

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Cholinergic excitation and GABAergic inhibition are integrated at axon terminals

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Direction-selective ganglion cells receive directionally aligned glutamate inputs

Presynaptic NMDA receptors facilitate short-term plasticity and BDNF release at hippocampal mossy fiber synapses

Neurotransmitter release is a highly controlled process by which synapses can critically regulate information transfer within neural circuits. While presynaptic receptors - typically activated by neurotransmitters and modulated by neuromodulators - provide a powerful way of fine-tuning synaptic function, their contribution to activity-dependent changes in transmitter release remains poorly understood. Here, we report that presynaptic NMDA receptors (preNMDARs) at mossy fiber boutons in the rodent hippocampus can be activated by physiologically relevant patterns of activity and selectively enhance short-term synaptic plasticity at mossy fiber inputs onto CA3 pyramidal cells and mossy cells, but not onto inhibitory interneurons. Moreover, preNMDARs facilitate brain-derived neurotrophic factor release and contribute to presynaptic calcium rise. Taken together, our results indicate that by increasing presynaptic calcium, preNMDARs fine-tune mossy fiber neurotransmission and can control information transfer during dentate granule cell burst activity that normally occur in vivo.

Short-Term Synaptic Plasticity Makes Neurons Sensitive to the Distribution of Presynaptic Population Firing Rates

The ability to discriminate spikes that encode a particular stimulus from spikes produced by background activity is essential for reliable information processing in the brain. We describe how synaptic short-term plasticity (STP) modulates the output of presynaptic populations as a function of the distribution of the spiking activity and find a strong relationship between STP features and sparseness of the population code, which could solve this problem. Furthermore, we show that feedforward excitation followed by inhibition (FF-EI), combined with target-dependent STP, promote substantial increase in the signal gain even for considerable deviations from the optimal conditions, granting robustness to this mechanism. A simulated neuron driven by a spiking FF-EI network is reliably modulated as predicted by a rate analysis and inherits the ability to differentiate sparse signals from dense background activity changes of the same magnitude, even at very low signal-to-noise conditions. We propose that the STP-based distribution discrimination is likely a latent function in several regions such as the cerebellum and the hippocampus.

Short-term high-fat feeding induces a reversible net decrease in synaptic AMPA receptors in the hypothalamus

Dietary obesity compromises brain function, but the effects of high-fat food on synaptic transmission in hypothalamic networks, as well as their potential reversibility, are yet to be fully characterized. We investigated the impact of high-fat feeding on a hallmark of synaptic plasticity, i.e., the expression of glutamatergic α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors (AMPARs) that contain the subunits GluA1 and GluA2, in hypothalamic and cortical synaptoneurosomes of male rats. In the main experiment (experiment 1), three days, but not one day of high-fat diet (HFD) decreased the levels of AMPAR GluA1 and GluA2 subunits, as well as GluA1 phosphorylation at Ser845, in hypothalamus but not cortex. In experiment 2, we compared the effects of the three-day HFD with those a three-day HFD followed by four recovery days of normal chow. This experiment corroborated the suppressive effect of high-fat feeding on hypothalamic but not cortical AMPAR GluA1, GluA2, and GluA1 phosphorylation at Ser845, and indicated that the effects are reversed by normal-chow feeding. High-fat feeding generally increased energy intake, body weight, and serum concentrations of insulin, leptin, free fatty acids, and corticosterone; only the three-day HFD increased wakefulness assessed via video analysis. Results indicate a reversible down-regulation of hypothalamic glutamatergic synaptic strength in response to short-term high-fat feeding. Preceding the manifestation of obesity, this rapid change in glutamatergic neurotransmission may underlie counter-regulatory efforts to prevent excess body weight gain, and therefore, represent a new target of interventions to improve metabolic control.

NMDA receptors in axons: there's no coincidence

In the textbook view, N-methyl-d-aspartate (NMDA) receptors are postsynaptically located detectors of coincident activity in Hebbian learning. However, controversial presynaptically located NMDA receptors (preNMDARs) have for decades been repeatedly reported in the literature. These preNMDARs have typically been implicated in the regulation of short-term and long-term plasticity, but precisely how they signal and what their functional roles are have been poorly understood. The functional roles of preNMDARs across several brain regions and different forms of plasticity can differ vastly, with recent discoveries showing key involvement of unusual subunit composition. Increasing evidence shows preNMDAR can signal through both ionotropic action by fluxing calcium and in metabotropic mode even in the presence of magnesium blockade. We argue that these unusual properties may explain why controversy has surrounded this receptor type. In addition, the expression of preNMDARs at some synapse types but not others can underlie synapse-type-specific plasticity. Last but not least, preNMDARs are emerging therapeutic targets in disease states such as neuropathic pain. We conclude that axonally located preNMDARs are required for specific purposes and do not end up there by accident.

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

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

Circuit-Specific Plasticity of Callosal Inputs Underlies Cortical Takeover

Injury induces synaptic, circuit, and systems reorganization. After unilateral amputation or stroke, this functional loss disrupts the interhemispheric interaction between intact and deprived somatomotor cortices to recruit deprived cortex in response to intact limb stimulation. This recruitment has been implicated in enhanced intact sensory function. In other patients, maladaptive consequences such as phantom limb pain can occur. We used unilateral whisker denervation in male and female mice to detect circuitry alterations underlying interhemispheric cortical reorganization. Enhanced synaptic strength from the intact cortex via the corpus callosum (CC) onto deep neurons in deprived primary somatosensory barrel cortex (S1BC) has previously been detected. It was hypothesized that specificity in this plasticity may depend on to which area these neurons projected. Increased connectivity to somatomotor areas such as contralateral S1BC, primary motor cortex (M1) and secondary somatosensory cortex (S2) may underlie beneficial adaptations, while increased connectivity to pain areas like anterior cingulate cortex (ACC) might underlie maladaptive pain phenotypes. Neurons from the deprived S1BC that project to intact S1BC were hyperexcitable, had stronger responses and reduced inhibitory input to CC stimulation. M1-projecting neurons also showed increases in excitability and CC input strength that was offset with enhanced inhibition. S2 and ACC-projecting neurons showed no changes in excitability or CC input. These results demonstrate that subgroups of output neurons undergo dramatic and specific plasticity after peripheral injury. The changes in S1BC-projecting neurons likely underlie enhanced reciprocal connectivity of S1BC after unilateral deprivation consistent with the model that interhemispheric takeover supports intact whisker processing.SIGNIFICANCE STATEMENT Amputation, peripheral injury, and stroke patients experience widespread alterations in neural activity after sensory loss. A hallmark of this reorganization is the recruitment of deprived cortical space which likely aids processing and thus enhances performance on intact sensory systems. Conversely, this recruitment of deprived cortical space has been hypothesized to underlie phenotypes like phantom limb pain and hinder recovery. A mouse model of unilateral denervation detected remarkable specificity in alterations in the somatomotor circuit. These changes underlie increased reciprocal connectivity between intact and deprived cortical hemispheres. This increased connectivity may help explain the enhanced intact sensory processing detected in humans.

Unifying Long-Term Plasticity Rules for Excitatory Synapses by Modeling Dendrites of Cortical Pyramidal Neurons

A large number of experiments have indicated that precise spike times, firing rates, and synapse locations crucially determine the dynamics of long-term plasticity induction in excitatory synapses. However, it remains unknown how plasticity mechanisms of synapses distributed along dendritic trees cooperate to produce the wide spectrum of outcomes for various plasticity protocols. Here, we propose a four-pathway plasticity framework that is well grounded in experimental evidence and apply it to a biophysically realistic cortical pyramidal neuron model. We show in computer simulations that several seemingly contradictory experimental landmark studies are consistent with one unifying set of mechanisms when considering the effects of signal propagation in dendritic trees with respect to synapse location. Our model identifies specific spatiotemporal contributions of dendritic and axo-somatic spikes as well as of subthreshold activation of synaptic clusters, providing a unified parsimonious explanation not only for rate and timing dependence but also for location dependence of synaptic changes.

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A phenomenological synaptic plasticity rule is applied to a pyramidal neuron model

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Model reproduces rate-, timing-, and location-dependent plasticity results

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Active dendrites allow plasticity via dendritic spikes and subthreshold events

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Cooperative plasticity exists across the dendritic tree and within single branches

A Practical Guide to Using CV Analysis for Determining the Locus of Synaptic Plasticity

Long-term synaptic plasticity is widely believed to underlie learning and memory in the brain. Whether plasticity is primarily expressed pre- or postsynaptically has been the subject of considerable debate for many decades. More recently, it is generally agreed that the locus of plasticity depends on a number of factors, such as developmental stage, induction protocol, and synapse type. Since presynaptic expression alters not just the gain but also the short-term dynamics of a synapse, whereas postsynaptic expression only modifies the gain, the locus has fundamental implications for circuits dynamics and computations in the brain. It therefore remains crucial for our understanding of neuronal circuits to know the locus of expression of long-term plasticity. One classical method for elucidating whether plasticity is pre- or postsynaptically expressed is based on analysis of the coefficient of variation (CV), which serves as a measure of noise levels of synaptic neurotransmission. Here, we provide a practical guide to using CV analysis for the purposes of exploring the locus of expression of long-term plasticity, primarily aimed at beginners in the field. We provide relatively simple intuitive background to an otherwise theoretically complex approach as well as simple mathematical derivations for key parametric relationships. We list important pitfalls of the method, accompanied by accessible computer simulations to better illustrate the problems (downloadable from GitHub), and we provide straightforward solutions for these issues.

Chronic adolescent exposure to ∆9-tetrahydrocannabinol decreases NMDA current and extrasynaptic plasmalemmal density of NMDA GluN1 subunits in the prelimbic cortex of adult male mice

Adolescence is a vulnerable period of development when limbic connection of the prefrontal cortex (PFC) involved in emotional processing may be rendered dysfunctional by chronic exposure to delta-9-tetrahydrocannabinol (∆9-THC), the major psychoactive compound in marijuana. Cannabinoid-1 receptors (CB1Rs) largely mediate the central neural effects of ∆9-THC and endocannabinoids that regulate NMDA receptor-dependent synaptic plasticity of glutamatergic synapses in the prelimbic prefrontal cortex (PL-PFC). Thus, chronic occupancy of CB1Rs by ∆9-THC during adolescence may competitively decrease the functional expression and activity of NMDA receptors in the mature PL-PFC. We used a multidisciplinary approach to test this hypothesis in adult C57BL/6J male mice that received vehicle or ∆9-THC in escalating doses (2.5-10 mg/kg/ip) through adolescence (postnatal day 29-43). In comparison with vehicle, the mice receiving ∆9-THC showed a hyperpolarized resting membrane potential, decreased spontaneous firing rate, increased current-induced firing threshold, and decreased depolarizing response to NMDA in deep-layer PL-PFC neurons analyzed by current-clamp recordings. Electron microscopic immunolabeling in the PL-PFC of adult mice that had received Δ9-THC only during adolescence showed a significant (1) decrease in the extrasynaptic plasmalemmal density of obligatory GluN1-NMDA subunits in dendrites of all sizes and (2) a shift from cytoplasmic to plasmalemmal distribution of GluN1 in large dendrites receiving mainly inhibitory-type synapses from CB1R-labeled terminals. From these results and concomitant behavioral studies, we conclude that social dysfunctions resulting from excessive intake of ∆9-THC in the increasingly available marijuana products used by male teens may largely reflect circuit defects in PL-PFC networks communicating through endocannabinoid-regulated NMDA receptors.

Enhanced Thalamocortical Synaptic Transmission and Dysregulation of the Excitatory-Inhibitory Balance at the Thalamocortical Feedforward Inhibitory Microcircuit in a Genetic Mouse Model of Migraine

Migraine is a complex brain disorder, characterized by attacks of unilateral headache and global dysfunction in multisensory information processing, whose underlying cellular and circuit mechanisms remain unknown. The finding of enhanced excitatory, but unaltered inhibitory, neurotransmission at intracortical synapses in mouse models of familial hemiplegic migraine (FHM) suggested the hypothesis that dysregulation of the excitatory-inhibitory balance in specific circuits is a key pathogenic mechanism. Here, we investigated the thalamocortical (TC) feedforward inhibitory microcircuit in FHM1 mice of both sexes carrying a gain-of-function mutation in Ca_V2.1. We show that TC synaptic transmission in somatosensory cortex is enhanced in FHM1 mice. Due to similar gain of function of TC excitation of layer 4 excitatory and fast-spiking inhibitory neurons elicited by single thalamic stimulations, neither the excitatory-inhibitory balance nor the integration time window set by the TC feedforward inhibitory microcircuit was altered in FHM1 mice. However, during repetitive thalamic stimulation, the typical shift of the excitatory-inhibitory balance toward excitation and the widening of the integration time window were both smaller in FHM1 compared with WT mice, revealing a dysregulation of the excitatory-inhibitory balance, whereby the balance is relatively skewed toward inhibition. This is due to an unexpected differential effect of the FHM1 mutation on short-term synaptic plasticity at TC synapses on cortical excitatory and fast-spiking inhibitory neurons. Our findings point to enhanced transmission of sensory, including trigeminovascular nociceptive, signals from thalamic nuclei to cortex and TC excitatory-inhibitory imbalance as mechanisms that may contribute to headache, increased sensory gain, and sensory processing dysfunctions in migraine.SIGNIFICANCE STATEMENT Migraine is a complex brain disorder, characterized by attacks of unilateral headache and by global dysfunction in multisensory information processing, whose underlying cellular and circuit mechanisms remain unknown. Here we provide insights into these mechanisms by investigating thalamocortical (TC) synaptic transmission and the function of the TC feedforward inhibitory microcircuit in a mouse model of a rare monogenic migraine. This microcircuit is critical for gating information flow to cortex and for sensory processing. We reveal increased TC transmission and dysregulation of the cortical excitatory-inhibitory balance set by the TC feedforward inhibitory microcircuit, whereby the balance is relatively skewed toward inhibition during repetitive thalamic activity. These alterations may contribute to headache, increased sensory gain, and sensory processing dysfunctions in migraine.

Degeneracy in hippocampal physiology and plasticity

Degeneracy, defined as the ability of structurally disparate elements to perform analogous function, has largely been assessed from the perspective of maintaining robustness of physiology or plasticity. How does the framework of degeneracy assimilate into an encoding system where the ability to change is an essential ingredient for storing new incoming information? Could degeneracy maintain the balance between the apparently contradictory goals of the need to change for encoding and the need to resist change towards maintaining homeostasis? In this review, we explore these fundamental questions with the mammalian hippocampus as an example encoding system. We systematically catalog lines of evidence, spanning multiple scales of analysis that point to the expression of degeneracy in hippocampal physiology and plasticity. We assess the potential of degeneracy as a framework to achieve the conjoint goals of encoding and homeostasis without cross-interferences. We postulate that biological complexity, involving interactions among the numerous parameters spanning different scales of analysis, could establish disparate routes towards accomplishing these conjoint goals. These disparate routes then provide several degrees of freedom to the encoding-homeostasis system in accomplishing its tasks in an input- and state-dependent manner. Finally, the expression of degeneracy spanning multiple scales offers an ideal reconciliation to several outstanding controversies, through the recognition that the seemingly contradictory disparate observations are merely alternate routes that the system might recruit towards accomplishment of its goals.

Novel Optogenetic Approaches in Epilepsy Research

Epilepsy is a major neurological disorder characterized by repeated seizures afflicting 1% of the global population. The emergence of seizures is associated with several comorbidities and severely decreases the quality of life of patients. Unfortunately, around 30% of patients do not respond to first-line treatment using anti-seizure drugs (ASDs). Furthermore, it is still unclear how seizures arise in the healthy brain. Therefore, it is critical to have well developed models where a causal understanding of epilepsy can be investigated. While the development of seizures has been studied in several animal models, using chemical or electrical induction, deciphering the results of such studies has been difficult due to the uncertainty of the cell population being targeted as well as potential confounds such as brain damage from the procedure itself. Here we describe novel approaches using combinations of optical and genetic methods for studying epileptogenesis. These approaches can circumvent some shortcomings associated with the classical animal models and may thus increase the likelihood of developing new treatment options.

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.

Discrimination of Motion Direction in a Robot Using a Phenomenological Model of Synaptic Plasticity

Recognizing and tracking the direction of moving stimuli is crucial to the control of much animal behaviour. In this study, we examine whether a bio-inspired model of synaptic plasticity implemented in a robotic agent may allow the discrimination of motion direction of real-world stimuli. Starting with a well-established model of short-term synaptic plasticity (STP), we develop a microcircuit motif of spiking neurons capable of exhibiting preferential and nonpreferential responses to changes in the direction of an orientation stimulus in motion. While the robotic agent processes sensory inputs, the STP mechanism introduces direction-dependent changes in the synaptic connections of the microcircuit, resulting in a population of units that exhibit a typical cortical response property observed in primary visual cortex (V1), namely, direction selectivity. Visually evoked responses from the model are then compared to those observed in multielectrode recordings from V1 in anesthetized macaque monkeys, while sinusoidal gratings are displayed on a screen. Overall, the model highlights the role of STP as a complementary mechanism in explaining the direction selectivity and applies these insights in a physical robot as a method for validating important response characteristics observed in experimental data from V1, namely, direction selectivity.

An Optogenetic Kindling Model of Neocortical Epilepsy

Epileptogenesis is the gradual process by which the healthy brain develops epilepsy. However, the neuronal circuit changes that underlie epileptogenesis are not well understood. Unfortunately, current chemically or electrically induced epilepsy models suffer from lack of cell specificity, so it is seldom known which cells were activated during epileptogenesis. We therefore sought to develop an optogenetic variant of the classical kindling model of epilepsy in which activatable cells are both genetically defined and fluorescently tagged. We briefly optogenetically activated pyramidal cells (PCs) in awake behaving mice every two days and conducted a series of experiments to validate the effectiveness of the model. Although initially inert, brief optogenetic stimuli eventually elicited seizures that increased in number and severity with additional stimulation sessions. Seizures were associated with long-lasting plasticity, but not with tissue damage or astrocyte reactivity. Once optokindled, mice retained an elevated seizure susceptibility for several weeks in the absence of additional stimulation, indicating a form of long-term sensitization. We conclude that optokindling shares many features with classical kindling, with the added benefit that the role of specific neuronal populations in epileptogenesis can be studied. Links between long-term plasticity and epilepsy can thus be elucidated.

Dynamic Communications Between GABAA Switch, Local Connectivity, and Synapses During Cortical Development: A Computational Study

Several factors regulate cortical development, such as changes in local connectivity and the influences of dynamical synapses. In this study, we simulated various factors affecting the regulation of neural network activity during cortical development. Previous studies have shown that during early cortical development, the reversal potential of GABA_A shifts from depolarizing to hyperpolarizing. Here we provide the first integrative computational model to simulate the combined effects of these factors in a unified framework (building on our prior work: Khalil et al., 2017a,b). In the current study, we extend our model to monitor firing activity in response to the excitatory action of GABA_A. Precisely, we created a Spiking Neural Network model that included certain biophysical parameters for lateral connectivity (distance between adjacent neurons) and nearby local connectivity (complex connections involving those between neuronal groups). We simulated different network scenarios (for immature and mature conditions) based on these biophysical parameters. Then, we implemented two forms of Short-term synaptic plasticity (depression and facilitation). Each form has two distinct kinds according to its synaptic time constant value. Finally, in both sets of networks, we compared firing rate activity responses before and after simulating dynamical synapses. Based on simulation results, we found that the modulation effect of dynamical synapses for evaluating and shaping the firing activity of the neural network is strongly dependent on the physiological state of GABA_A. Moreover, the STP mechanism acts differently in every network scenario, mirroring the crucial modulating roles of these critical parameters during cortical development. Clinical implications for pathological alterations of GABAergic signaling in neurological and psychiatric disorders are discussed.

Synapse molecular complexity and the plasticity behaviour problem

Synapses are the hallmark of brain complexity and have long been thought of as simple connectors between neurons. We are now in an era in which we know the full complement of synapse proteins and this has created an existential crisis because the molecular complexity far exceeds the requirements of most simple models of synaptic function. Studies of the organisation of proteome complexity and its evolution provide surprising new insights that challenge existing dogma and promote the development of new theories about the origins and role of synapses in behaviour. The postsynaptic proteome of excitatory synapses is a structure with high molecular complexity and sophisticated computational properties that is disrupted in over 130 brain diseases. A key goal of 21st-century neuroscience is to develop comprehensive molecular datasets on the brain and develop theories that explain the molecular basis of behaviour.

Synapse Type-Dependent Expression of Calcium-Permeable AMPA Receptors

Calcium-permeable (CP) AMPA-type glutamate receptors (AMPARs) are known to mediate synaptic plasticity in several different interneuron (IN) types. Recent evidence suggests that CP-AMPARs are synapse-specifically expressed at excitatory connections onto a subset of IN types in hippocampus and neocortex. For example, CP-AMPARs are found at connections from pyramidal cells (PCs) to basket cells (BCs), but not to Martinotti cells (MCs). This synapse type-specific expression of CP-AMPARs suggests that synaptic dynamics as well as learning rules are differentially implemented in local circuits and has important implications not just in health but also in disease states such as epilepsy.

Sparse recurrent excitatory connectivity in the microcircuit of the adult mouse and human cortex

Generating a comprehensive description of cortical networks requires a large-scale, systematic approach. To that end, we have begun a pipeline project using multipatch electrophysiology, supplemented with two-photon optogenetics, to characterize connectivity and synaptic signaling between classes of neurons in adult mouse primary visual cortex (V1) and human cortex. We focus on producing results detailed enough for the generation of computational models and enabling comparison with future studies. Here, we report our examination of intralaminar connectivity within each of several classes of excitatory neurons. We find that connections are sparse but present among all excitatory cell classes and layers we sampled, and that most mouse synapses exhibited short-term depression with similar dynamics. Synaptic signaling between a subset of layer 2/3 neurons, however, exhibited facilitation. These results contribute to a body of evidence describing recurrent excitatory connectivity as a conserved feature of cortical microcircuits.

Long-Term Plasticity of Neurotransmitter Release: Emerging Mechanisms and Contributions to Brain Function and Disease

Long-lasting changes of brain function in response to experience rely on diverse forms of activity-dependent synaptic plasticity. Chief among them are long-term potentiation and long-term depression of neurotransmitter release, which are widely expressed by excitatory and inhibitory synapses throughout the central nervous system and can dynamically regulate information flow in neural circuits. This review article explores recent advances in presynaptic long-term plasticity mechanisms and contributions to circuit function. Growing evidence indicates that presynaptic plasticity may involve structural changes, presynaptic protein synthesis, and transsynaptic signaling. Presynaptic long-term plasticity can alter the short-term dynamics of neurotransmitter release, thereby contributing to circuit computations such as novelty detection, modifications of the excitatory/inhibitory balance, and sensory adaptation. In addition, presynaptic long-term plasticity underlies forms of learning and its dysregulation participates in several neuropsychiatric conditions, including schizophrenia, autism, intellectual disabilities, neurodegenerative diseases, and drug abuse.

How neuroscience can inform the study of individual differences in cognitive abilities

Theories of human mental abilities should be consistent with what is known in neuroscience. Currently, tests of human mental abilities are modeled by cognitive constructs such as attention, working memory, and speed of information processing. These constructs are in turn related to a single general ability. However, brains are very complex systems and whether most of the variability between the operations of different brains can be ascribed to a single factor is questionable. Research in neuroscience suggests that psychological processes such as perception, attention, decision, and executive control are emergent properties of interacting distributed networks. The modules that make up these networks use similar computational processes that involve multiple forms of neural plasticity, each having different time constants. Accordingly, these networks might best be characterized in terms of the information they process rather than in terms of abstract psychological processes such as working memory and executive control.

Functional consequences of pre- and postsynaptic expression of synaptic plasticity

Growing experimental evidence shows that both homeostatic and Hebbian synaptic plasticity can be expressed presynaptically as well as postsynaptically. In this review, we start by discussing this evidence and methods used to determine expression loci. Next, we discuss the functional consequences of this diversity in pre- and postsynaptic expression of both homeostatic and Hebbian synaptic plasticity. In particular, we explore the functional consequences of a biologically tuned model of pre- and postsynaptically expressed spike-timing-dependent plasticity complemented with postsynaptic homeostatic control. The pre- and postsynaptic expression in this model predicts (i) more reliable receptive fields and sensory perception, (ii) rapid recovery of forgotten information (memory savings), and (iii) reduced response latencies, compared with a model with postsynaptic expression only. Finally, we discuss open questions that will require a considerable research effort to better elucidate how the specific locus of expression of homeostatic and Hebbian plasticity alters synaptic and network computations.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity'.

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.

Long-lasting increase in axonal excitability after epidurally applied DC

Effects of direct current (DC) on nerve fibers have primarily been investigated during or just after DC application. However, locally applied cathodal DC was recently demonstrated to increase the excitability of intraspinal preterminal axonal branches for >1 h. The aim of this study was therefore to investigate whether DC evokes a similarly long-lasting increase in the excitability of myelinated axons within the dorsal columns. The excitability of dorsal column fibers stimulated epidurally was monitored by recording compound action potentials in peripheral nerves in acute experiments in deeply anesthetized rats. The results show that 1) cathodal polarization (0.8-1.0 µA) results in a severalfold increase in the number of epidurally activated fibers and 2) the increase in the excitability appears within seconds, 3) lasts for >1 h, and 4) is activity independent, as it does not require fiber stimulation during the polarization. These features demonstrate an unexplored form of plasticity of myelinated fibers and indicate the conditions under which it develops. They also suggest that therapeutic effects of epidural stimulation may be significantly enhanced if it is combined with DC polarization. In particular, by using DC to increase the number of fibers activated by low-intensity epidural stimuli, the low clinical tolerance to higher stimulus intensities might be overcome. The activity independence of long-lasting DC effects would also allow the use of only brief periods of DC polarization preceding epidural stimulation to increase the effect.NEW & NOTEWORTHY The study indicates a new form of plasticity of myelinated fibers. The differences in time course of DC-evoked increases in the excitability of myelinated nerve fibers in the dorsal columns and in preterminal axonal branches suggest that distinct mechanisms are involved in them. The results show that combining epidural stimulation and transspinal DC polarization may dramatically improve their outcome and result in more effective pain control and the return of impaired motor functions.

Mechanisms of input and output synaptic specificity: finding partners, building synapses, and fine-tuning communication

For most neurons to function properly, they need to develop synaptic specificity. This requires finding specific partner neurons, building the correct types of synapses, and fine-tuning these synapses in response to neural activity. Synaptic specificity is common at both a neuron's input and output synapses, whereby unique synapses are built depending on the partnering neuron. Neuroscientists have long appreciated the remarkable specificity of neural circuits but identifying molecular mechanisms mediating synaptic specificity has only recently accelerated. Here, we focus on recent progress in understanding input and output synaptic specificity in the mammalian brain. We review newly identified circuit examples for both and the latest research identifying molecular mediators including Kirrel3, FGFs, and DGLα. Lastly, we expect the pace of research on input and output specificity to continue to accelerate with the advent of new technologies in genomics, microscopy, and proteomics.

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.

Ionotropic glutamate receptors: Which ones, when, and where in the mammalian neocortex

A multitude of 18 iGluR receptor subunits, many of which are diversified by splicing and RNA editing, localize to >20 excitatory and inhibitory neocortical neuron types defined by physiology, morphology, and transcriptome in addition to various types of glial, endothelial, and blood cells. Here we have compiled the published expression of iGluR subunits in the areas and cell types of developing and adult cortex of rat, mouse, carnivore, bovine, monkey, and human as determined with antibody- and mRNA-based techniques. iGluRs are differentially expressed in the cortical areas and in the species, and all have a unique developmental pattern. Differences are quantitative rather than a mere absence/presence of expression. iGluR are too ubiquitously expressed and of limited use as markers for areas or layers. A focus has been the iGluR profile of cortical interneuron types. For instance, GluK1 and GluN3A are enriched in, but not specific for, interneurons; moreover, the interneurons expressing these subunits belong to different types. Adressing the types is still a major hurdle because type-specific markers are lacking, and the frequently used neuropeptide/CaBP signatures are subject to regulation by age and activity and vary as well between species and areas. RNA-seq reveals almost all subunits in the two morphofunctionally characterized interneuron types of adult cortical layer I, suggesting a fairly broad expression at the RNA level. It remains to be determined whether all proteins are synthesized, to which pre- or postsynaptic subdomains in a given neuron type they localize, and whether all are involved in synaptic transmission. J. Comp. Neurol. 525:976-1033, 2017. © 2016 Wiley Periodicals, Inc.

In Vitro Investigation of Synaptic Plasticity

A classical in vitro model for investigation of information storage in the brain is based on the acute hippocampal slice. Here, repeated high-frequency stimulation of excitatory Schaeffer collaterals making synapses onto pyramidal cells in the hippocampal CA1 region leads to strengthening of evoked field-recording responses-long-term potentiation (LTP)-in keeping with Hebb's postulate. This model remains tremendously influential for its reliability, specificity, and relative ease of use. More recent plasticity studies have explored various other brain regions including the neocortex, which often requires more laborious whole-cell recordings of synaptically connected pairs of neurons, to ensure that the identities of recorded cells are known. In addition, with this experimental approach, the spiking activity can be controlled with millisecond precision, which is necessary for the study of spike-timing-dependent plasticity (STDP). Here, we provide protocols for in vitro study of hippocampal CA1 LTP using field recordings, and of STDP in synaptically connected pairs of layer-5 pyramidal cells in acute slices of rodent neocortex.