Short-term plasticity optimizes synaptic information transmission

The synaptic vesicle cluster as a controller of pre- and postsynaptic structure and function

The synaptic vesicle cluster (SVC) is an essential component of chemical synapses, which provides neurotransmitter-loaded vesicles during synaptic activity, at the same time as also controlling the local concentrations of numerous exo- and endocytosis cofactors. In addition, the SVC hosts molecules that participate in other aspects of synaptic function, from cytoskeletal components to adhesion proteins, and affects the location and function of organelles such as mitochondria and the endoplasmic reticulum. We argue here that these features extend the functional involvement of the SVC in synapse formation, signalling and plasticity, as well as synapse stabilization and metabolism. We also propose that changes in the size of the SVC coalesce with changes in the postsynaptic compartment, supporting the interplay between pre- and postsynaptic dynamics. Thereby, the SVC could be seen as an 'all-in-one' regulator of synaptic structure and function, which should be investigated in more detail, to reveal molecular mechanisms that control synaptic function and heterogeneity.

Muscarinic Modulation of Synaptic Transmission and Short-Term Plasticity in the Dorsal and Ventral Hippocampus

Muscarinic neurotransmission is fundamentally involved in supporting several brain functions by modulating flow of information in brain neural circuits including the hippocampus which displays a remarkable functional segregation along its longitudinal axis. However, how muscarinic neuromodulation contributes to the functional segregation along the hippocampus remains unclear. In this study we show that the nonselective muscarinic receptor agonist carbachol similarly suppresses basal synaptic transmission in the dorsal and ventral CA1 hippocampal field, in a concentration-depended manner. Furthermore, using a ten-pulse stimulation train of varying frequency we found that carbachol changes the frequency filtering properties more in ventral than dorsal hippocampus by facilitating synaptic inputs at a wide range of input frequencies in the ventral compared with dorsal hippocampus. Using the M2 receptor antagonist gallamine and the M4 receptor antagonist tropicamide, we found that M2 receptors are involved in controlling basal synaptic transmission and short-term synaptic plasticity (STSP) in the ventral but not the dorsal hippocampus, while M4 receptors participate in modulating basal synaptic transmission and STSP in both segments of the hippocampus. These results were corroborated by the higher protein expression levels of M2 receptors in the ventral compared with dorsal hippocampus. We conclude that muscarinic transmission modulates excitatory synaptic transmission and short-term synaptic plasticity along the entire rat hippocampus by acting through M4 receptors and recruiting M2 receptors only in the ventral hippocampus. Furthermore, M4 receptors appear to exert a permissive role on the actions of M2 receptors on STSP in the ventral hippocampus. This dorsoventral differentiation of muscarinic modulation is expected to have important implications in information processing along the endogenous hippocampal circuitry.

Brain-inspired computing with fluidic iontronic nanochannels

The brain's remarkable and efficient information processing capability is driving research into brain-inspired (neuromorphic) computing paradigms. Artificial aqueous ion channels are emerging as an exciting platform for neuromorphic computing, representing a departure from conventional solid-state devices by directly mimicking the brain's fluidic ion transport. Supported by a quantitative theoretical model, we present easy-to-fabricate tapered microchannels that embed a conducting network of fluidic nanochannels between a colloidal structure. Due to transient salt concentration polarization, our devices are volatile memristors (memory resistors) that are remarkably stable. The voltage-driven net salt flux and accumulation, that underpin the concentration polarization, surprisingly combine into a diffusionlike quadratic dependence of the memory retention time on the channel length, allowing channel design for a specific timescale. We implement our device as a synaptic element for neuromorphic reservoir computing. Individual channels distinguish various time series, that together represent (handwritten) numbers, for subsequent in silico classification with a simple readout function. Our results represent a significant step toward realizing the promise of fluidic ion channels as a platform to emulate the rich aqueous dynamics of the brain.

An unsupervised STDP-based spiking neural network inspired by biologically plausible learning rules and connections

The backpropagation algorithm has promoted the rapid development of deep learning, but it relies on a large amount of labeled data and still has a large gap with how humans learn. The human brain can quickly learn various conceptual knowledge in a self-organized and unsupervised manner, accomplished through coordinating various learning rules and structures in the human brain. Spike-timing-dependent plasticity (STDP) is a general learning rule in the brain, but spiking neural networks (SNNs) trained with STDP alone is inefficient and perform poorly. In this paper, taking inspiration from short-term synaptic plasticity, we design an adaptive synaptic filter and introduce the adaptive spiking threshold as the neuron plasticity to enrich the representation ability of SNNs. We also introduce an adaptive lateral inhibitory connection to adjust the spikes balance dynamically to help the network learn richer features. To speed up and stabilize the training of unsupervised spiking neural networks, we design a samples temporal batch STDP (STB-STDP), which updates weights based on multiple samples and moments. By integrating the above three adaptive mechanisms and STB-STDP, our model greatly accelerates the training of unsupervised spiking neural networks and improves the performance of unsupervised SNNs on complex tasks. Our model achieves the current state-of-the-art performance of unsupervised STDP-based SNNs in the MNIST and FashionMNIST datasets. Further, we tested on the more complex CIFAR10 dataset, and the results fully illustrate the superiority of our algorithm. Our model is also the first work to apply unsupervised STDP-based SNNs to CIFAR10. At the same time, in the small-sample learning scenario, it will far exceed the supervised ANN using the same structure.

A computational view of short-term plasticity and its implications for E-I balance

Short-term plasticity (STP) and excitatory-inhibitory balance (EI balance) are both ubiquitous building blocks of brain circuits across the animal kingdom. The synapses involved in EI are also subject to short-term plasticity, and several experimental studies have shown that their effects overlap. Recent computational and theoretical work has begun to highlight the functional implications of the intersection of these motifs. The findings are nuanced: while there are general computational themes, such as pattern tuning, normalization, and gating, much of the richness of these interactions comes from region- and modality specific tuning of STP properties. Together these findings point towards the STP-EI balance combination as being a versatile and highly efficient neural building block for a wide range of pattern-specific responses.

Short-term synaptic plasticity in emerging devices for neuromorphic computing

Neuromorphic computing is a promising computing paradigm toward building next-generation artificial intelligence machines, in which diverse types of synaptic plasticity play an active role in information processing. Compared to long-term plasticity (LTP) forming the foundation of learning and memory, short-term plasticity (STP) is essential for critical computational functions. So far, the practical applications of LTP have been widely investigated, whereas the implementation of STP in hardware is still elusive. Here, we review the development of STP by bridging the physics in emerging devices and biological behaviors. We explore the computational functions of various STP in biology and review their recent progress. Finally, we discuss the main challenges of introducing STP into synaptic devices and offer the potential approaches to utilize STP to enrich systems' capabilities. This review is expected to provide prospective ideas for implementing STP in emerging devices and may promote the construction of high-level neuromorphic machines.

Septotemporal variation in modulation of synaptic transmission, paired-pulse ratio and frequency facilitation/depression by adenosine and GABAB receptors in the rat hippocampus

Short-term synaptic plasticity represents a fundamental mechanism in neural information processing and is regulated by neuromodulators. Here, using field recordings from the CA1 region of adult rat hippocampal slices, we show that excitatory synaptic transmission is suppressed by strong but not moderate activation of adenosine A₁ receptors by 2-Chloro-N⁶-cyclopentyladenosine (CCPA) more in the dorsal than the ventral hippocampus; in contrast, both mild and strong activation of GABA_B receptors by baclofen (1 μM, 10 μM) suppress synaptic transmission more in the ventral than the dorsal hippocampus. Using a 10-pulse stimulation train of variable frequency, we found that CCPA modulates short-term synaptic plasticity independently of the suppression of synaptic transmission in both segments of the hippocampus and at stimulation frequencies greater than 10 Hz. However, specifically regarding the paired-pulse ratio (PPR) and frequency facilitation/depression (FF/D) we found significant drug action before but not after adjusting conditioning responses to control levels. Activation of GABA_BRs by baclofen suppressed synaptic transmission more in the ventral than the dorsal hippocampus. Furthermore, relatively high (10 μM) but not low (1 μM) baclofen concentration enhanced both PPR and FF in both hippocampal segments at stimulation frequencies greater than 1 Hz, independently of the suppression of synaptic transmission by baclofen. These results show that A₁Rs and GABA_BRs control synaptic transmission more effectively in the dorsal and the ventral hippocampus, respectively, and suggest that these receptors modulate PPR and FF/D at different frequency bands of afferent input, in both segments of the hippocampus.

Multiscale modeling of presynaptic dynamics from molecular to mesoscale

Chemical synapses exhibit a diverse array of internal mechanisms that affect the dynamics of transmission efficacy. Many of these processes, such as release of neurotransmitter and vesicle recycling, depend strongly on activity-dependent influx and accumulation of Ca²⁺. To model how each of these processes may affect the processing of information in neural circuits, and how their dysfunction may lead to disease states, requires a computationally efficient modelling framework, capable of generating accurate phenomenology without incurring a heavy computational cost per synapse. Constructing a phenomenologically realistic model requires the precise characterization of the timing and probability of neurotransmitter release. Difficulties arise in that functional forms of instantaneous release rate can be difficult to extract from noisy data without running many thousands of trials, and in biophysical synapses, facilitation of per-vesicle release probability is confounded by depletion. To overcome this, we obtained traces of free Ca²⁺ concentration in response to various action potential stimulus trains from a molecular MCell model of a hippocampal Schaffer collateral axon. Ca²⁺ sensors were placed at varying distance from a voltage-dependent calcium channel (VDCC) cluster, and Ca²⁺ was buffered by calbindin. Then, using the calcium traces to drive deterministic state vector models of synaptotagmin 1 and 7 (Syt-1/7), which respectively mediate synchronous and asynchronous release in excitatory hippocampal synapses, we obtained high-resolution profiles of instantaneous release rate, to which we applied functional fits. Synchronous vesicle release occurred predominantly within half a micron of the source of spike-evoked Ca²⁺ influx, while asynchronous release occurred more consistently at all distances. Both fast and slow mechanisms exhibited multi-exponential release rate curves, whose magnitudes decayed exponentially with distance from the Ca²⁺ source. Profile parameters facilitate on different time scales according to a single, general facilitation function. These functional descriptions lay the groundwork for efficient mesoscale modelling of vesicular release dynamics.

Most information transmission between neurons in the brain occurs via release of neurotransmitter from synaptic vesicles. In response to a presynaptic spike, calcium influx at the active zone of a synapse can trigger the release of neurotransmitter with a certain probability. These stochastic release events may occur immediately after a spike or with some delay. As calcium accumulates from one spike to the next, the probability of release may increase (facilitate) for subsequent spikes. This process, known as short-term plasticity, transforms the spiking code to a release code, underlying much of the brain’s information processing. In this paper, we use an accurate, detailed model of presynaptic molecular physiology to characterize these processes at high precision in response to various spike trains. We then apply model reduction to the results to obtain a phenomenological model of release timing, probability, and facilitation, which can perform as accurately as the molecular model but with far less computational cost. This mesoscale model of spike-evoked release and facilitation helps to bridge the gap between microscale molecular dynamics and macroscale information processing in neural circuits. It can thus benefit large scale modelling of neural circuits, biologically inspired machine learning models, and the design of neuromorphic chips.

Endogenous neurosteroids pregnanolone and pregnanolone sulfate potentiate presynaptic glutamate release through distinct mechanisms

BACKGROUND AND PURPOSE

Neurosteroids influence neuronal function and have multiple promising clinical applications. Direct modulation of postsynaptic neurotransmitter receptors by neurosteroids is well characterized, but presynaptic effects remain poorly understood. Here, we report presynaptic glutamate release potentiation by neurosteroids pregnanolone and pregnanolone sulfate and compare their mechanisms of action to phorbol 12,13-dibutyrate (PDBu), a mimic of the second messenger DAG.

EXPERIMENTAL APPROACH

We use whole-cell patch-clamp electrophysiology and pharmacology in rat hippocampal microisland cultures and total internal reflection fluorescence (TIRF) microscopy in HEK293 cells expressing GFP-tagged vesicle priming protein Munc13-1, to explore the mechanisms of neurosteroid presynaptic modulation.

KEY RESULTS

Pregnanolone sulfate and pregnanolone potentiate glutamate release downstream of presynaptic Ca2+ influx, resembling the action of a phorbol ester PDBu. PDBu partially occludes the effect of pregnanolone, but not of pregnanolone sulfate. Calphostin C, an inhibitor that disrupts DAG binding to its targets, reduces the effect PDBu and pregnanolone, but not of pregnanolone sulfate, suggesting that pregnanolone might interact with a well-known DAG/phorbol ester target Munc13-1. However, TIRF microscopy experiments found no evidence of pregnanolone-induced membrane translocation of GFP-tagged Munc13-1, suggesting that pregnanolone may regulate Munc13-1 indirectly or interact with other DAG targets.

CONCLUSION AND IMPLICATIONS

We describe a novel presynaptic effect of neurosteroids pregnanolone and pregnanolone sulfate to potentiate glutamate release downstream of presynaptic Ca2+ influx. The mechanism of action of pregnanolone, but not of pregnanolone sulfate, partly overlaps with that of PDBu. Presynaptic effects of neurosteroids may contribute to their therapeutic potential in the treatment of disorders of the glutamate system.

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.

Presynaptic endoplasmic reticulum regulates short-term plasticity in hippocampal synapses

Short-term plasticity preserves a brief history of synaptic activity that is communicated to the postsynaptic neuron. This is primarily regulated by a calcium signal initiated by voltage dependent calcium channels in the presynaptic terminal. Imaging studies of CA3-CA1 synapses reveal the presence of another source of calcium, the endoplasmic reticulum (ER) in all presynaptic terminals. However, the precise role of the ER in modifying STP remains unexplored. We performed in-silico experiments in synaptic geometries based on reconstructions of the rat CA3-CA1 synapses to investigate the contribution of ER. Our model predicts that presynaptic ER is critical in generating the observed short-term plasticity profile of CA3-CA1 synapses and allows synapses with low release probability to operate more reliably. Blocking the ER lowers facilitation in a manner similar to what has been previously characterized in animal models of Alzheimer's disease and underscores the important role played by presynaptic stores in normal function.

Local Design Principles at Hippocampal Synapses Revealed by an Energy-Information Trade-Off

Synapses across different brain regions display distinct structure-function relationships. We investigated the interplay of fundamental design constraints that shape the transmission properties of the excitatory CA3-CA1 pyramidal cell connection, a prototypic synapse for studying the mechanisms of learning in the mammalian hippocampus. This small synapse is characterized by probabilistic release of transmitter, which is markedly facilitated in response to naturally occurring trains of action potentials. Based on a physiologically motivated computational model of the rat CA3 presynaptic terminal, we show how unreliability and short-term dynamics of vesicular release work together to regulate the trade-off of information transfer versus energy use. We propose that individual CA3-CA1 synapses are designed to operate near the maximum possible capacity of information transmission in an efficient manner. Experimental measurements reveal a wide range of vesicular release probabilities at hippocampal synapses, which may be a necessary consequence of long-term plasticity and homeostatic mechanisms that manifest as presynaptic modifications of the release probability. We show that the timescales and magnitude of short-term plasticity (STP) render synaptic information transfer nearly independent of differences in release probability. Thus, individual synapses transmit optimally while maintaining a heterogeneous distribution of presynaptic strengths indicative of synaptically-encoded memory representations. Our results support the view that organizing principles that are evident on higher scales of neural organization percolate down to the design of an individual synapse.

A two-compartment model of synaptic computation and plasticity

The synapse is typically viewed as a single compartment, which acts as a linear gain controller on incoming input. Traditional plasticity rules enable this gain control to be dynamically optimized by Hebbian activity. Whilst this view nicely captures postsynaptic function, it neglects the non-linear dynamics of presynaptic function. Here we present a two-compartment model of the synapse in which the presynaptic terminal first acts to filter presynaptic input before the postsynaptic terminal, acting as a gain controller, amplifies or depresses transmission. We argue that both compartments are equipped with distinct plasticity rules to enable them to optimally adapt synaptic transmission to the statistics of pre- and postsynaptic activity. Specifically, we focus on how presynaptic plasticity enables presynaptic filtering to be optimally tuned to only transmit information relevant for postsynaptic firing. We end by discussing the advantages of having a presynaptic filter and propose future work to explore presynaptic function and plasticity in vivo.

Spatiotemporal dynamics of multi-vesicular release is determined by heterogeneity of release sites within central synapses

A synaptic active zone (AZ) can release multiple vesicles in response to an action potential. This multi-vesicular release (MVR) occurs at most synapses, but its spatiotemporal properties are unknown. Nanoscale-resolution detection of individual release events in hippocampal synapses revealed unprecedented heterogeneity among vesicle release sites within a single AZ, with a gradient of release probability decreasing from AZ center to periphery. Parallel to this organization, MVR events preferentially overlap with uni-vesicular release (UVR) events at sites closer to an AZ center. Pairs of fusion events comprising MVR are also not perfectly synchronized, and the earlier event tends to occur closer to AZ center. The spatial features of release sites and MVR events are similarly tightened by buffering intracellular calcium. These observations revealed a marked heterogeneity of release site properties within individual AZs, which determines the spatiotemporal features of MVR events and is controlled, in part, by non-uniform calcium elevation across the AZ.

Recent Progress in Three-Terminal Artificial Synapses: From Device to System

Synapses are essential to the transmission of nervous signals. Synaptic plasticity allows changes in synaptic strength that make a brain capable of learning from experience. During development of neuromorphic electronics, great efforts have been made to design and fabricate electronic devices that emulate synapses. Three-terminal artificial synapses have the merits of concurrently transmitting signals and learning. Inorganic and organic electronic synapses have mimicked plasticity and learning. Optoelectronic synapses and photonic synapses have the prospective benefits of low electrical energy loss, high bandwidth, and mechanical robustness. These artificial synapses provide new opportunities for the development of neuromorphic systems that can use parallel processing to manipulate datasets in real time. Synaptic devices have also been used to build artificial sensory systems. Here, recent progress in the development and application of three-terminal artificial synapses and artificial sensory systems is reviewed.

Short-term dynamics of input and output of CA1 network greatly differ between the dorsal and ventral rat hippocampus

Background

The functional heterogeneity of the hippocampus along its longitudinal axis at the level of behavior is an established concept; however, the neurobiological mechanisms are still unknown. Diversifications in the functioning of intrinsic hippocampal circuitry including short-term dynamics of synaptic inputs and neuronal output, that are important determinants of information processing in the brain, may profoundly contribute to functional specializations along the hippocampus. The objectives of the present study were the examination of the role of the GABA_A receptor-mediated inhibition, the μ-opioid receptors and the effect of stimulation intensity on the dynamics of both synaptic input and neuronal output of CA1 region in the dorsal and ventral hippocampus. We used recordings of field potentials from adult rat hippocampal slices evoked by brief repetitive activation of Schaffer collaterals.

Results

We find that the local CA1 circuit of the dorsal hippocampus presents a remarkably increased dynamic range of frequency-dependent short-term changes in both input and output, ranging from strong facilitation to intense depression at low and high stimulation frequencies respectively. Furthermore, the input–output relationship in the dorsal CA1 circuit is profoundly influenced by frequency and time of presynaptic activation. Strikingly, the ventral hippocampus responds mostly with depression, displaying a rather monotonous input–output relationship over frequency and time. Partial blockade of GABA_A receptor-mediated transmission (by 5 μM picrotoxin) profoundly influences input and output dynamics in the dorsal hippocampus but affected only the neuronal output in the ventral hippocampus. M-opioid receptors control short-term dynamics of input and output in the dorsal hippocampus but they play no role in the ventral hippocampus.

Conclusion

The results demonstrate that information processing by CA1 local network is highly diversified between the dorsal and ventral hippocampus. Transient detection of incoming patterns of activity and frequency-dependent sustained signaling of amplified neuronal information may be assigned to the ventral and dorsal hippocampal circuitry respectively. This disparity should have profound implications for the functional roles ascribed to distinct segments along the long axis of the hippocampus.

Electronic supplementary material

The online version of this article (10.1186/s12868-019-0517-5) contains supplementary material, which is available to authorized users.

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.

Short-term synaptic depression can increase the rate of information transfer at a release site

The release of neurotransmitters from synapses obeys complex and stochastic dynamics. Depending on the recent history of synaptic activation, many synapses depress the probability of releasing more neurotransmitter, which is known as synaptic depression. Our understanding of how synaptic depression affects the information efficacy, however, is limited. Here we propose a mathematically tractable model of both synchronous spike-evoked release and asynchronous release that permits us to quantify the information conveyed by a synapse. The model transits between discrete states of a communication channel, with the present state depending on many past time steps, emulating the gradual depression and exponential recovery of the synapse. Asynchronous and spontaneous releases play a critical role in shaping the information efficacy of the synapse. We prove that depression can enhance both the information rate and the information rate per unit energy expended, provided that synchronous spike-evoked release depresses less (or recovers faster) than asynchronous release. Furthermore, we explore the theoretical implications of short-term synaptic depression adapting on longer time scales, as part of the phenomenon of metaplasticity. In particular, we show that a synapse can adjust its energy expenditure by changing the dynamics of short-term synaptic depression without affecting the net information conveyed by each successful release. Moreover, the optimal input spike rate is independent of the amplitude or time constant of synaptic depression. We analyze the information efficacy of three types of synapses for which the short-term dynamics of both synchronous and asynchronous release have been experimentally measured. In hippocampal autaptic synapses, the persistence of asynchronous release during depression cannot compensate for the reduction of synchronous release, so that the rate of information transmission declines with synaptic depression. In the calyx of Held, the information rate per release remains constant despite large variations in the measured asynchronous release rate. Lastly, we show that dopamine, by controlling asynchronous release in corticostriatal synapses, increases the synaptic information efficacy in nucleus accumbens.

Fatigue is an intrinsic property of living systems and synapses are no exception. Synaptic depression reduces the ability of synapses to release vesicles in response to an incoming action potential. Whether synaptic depression simply reflects the exhaustion of neuronal resources or whether it serves some additional function is still an open question. We ask how synaptic depression modulates the information transfer between neurons by keeping the synapse in an appropriate operating range. Using a tractable mathematical model for synaptic depression of both synchronous spike-evoked and asynchronous release of neurotransmitter, we derive a closed-form expression for the mutual information rate. Depression, it turns out, can both enhance or impair information transfer, depending on the relative level of depression for synchronous spike-evoked and asynchronous releases. We also study the compromise a synapse makes between its energy consumption and the rate of information transmission. Interestingly, we show that synaptic depression can regulate energy use without affecting the information (measured in bits) per synaptic release. By applying our mathematical framework to experimentally measured synapses, we show that some synapses can compensate for intrinsic variability in asynchronous release rates; moreover, we show how neuromodulators such as dopamine act to improve the information transmission rate.

Short-Term Synaptic Plasticity as a Mechanism for Sensory Timing

The ability to detect time intervals and temporal patterns is critical to some of the most fundamental computations the brain performs, including the ability to communicate and appraise a dynamically changing environment. Many of these computations take place on the scale of tens to hundreds of milliseconds. Electrophysiological evidence shows that some neurons respond selectively to duration, interval, rate, or order. Because the time constants of many time-varying neural and synaptic properties, including short-term synaptic plasticity (STP), are also in the range of tens to hundreds of milliseconds, they are strong candidates to underlie the formation of temporally selective neurons. Neurophysiological studies indicate that STP is indeed one of the mechanisms that contributes to temporal selectivity, and computational models demonstrate that neurons embedded in local microcircuits exhibit temporal selectivity if their synapses undergo STP. Converging evidence suggests that some forms of temporal selectivity emerge from the dynamic changes in the balance of excitation and inhibition imposed by STP.

Target-cell-specific Short-term Plasticity Reduces the Excitatory Drive onto CA1 Interneurons Relative to Pyramidal Cells During Physiologically-derived Spike Trains

Short-term plasticity enables synaptic strength to be dynamically regulated by input timing. Excitatory synapses arising from the same axon can have profoundly different presynaptic forms of short-term plasticity onto inhibitory and excitatory neurons. We previously showed that Schaffer collateral synapses onto most hippocampal CA1 stratum radiatum interneurons have less paired-pulse facilitation than synapses onto CA1 pyramidal cells, but little difference in steady-state short-term depression. However, less is known about how synapses onto interneurons respond to temporally complex patterns that occur in vivo. Here we compared Schaffer collateral synapses onto stratum radiatum interneurons and pyramidal cells in acute hippocampal slices in response to physiologically-derived spike trains. We find that synapses onto interneurons have less short-term facilitation than synapses onto pyramidal cells, and a subset expresses only short-term depression. Mathematical modeling predicts this target cell-specific short-term plasticity occurs through differences in initial release probability. All three groups have more short-term facilitation during physiologically-derived train stimulation than during constant-frequency stimulation at the same frequency, indicating that variability in stimulus timing is important. These target-cell specific differences in short-term plasticity reduce the strength of excitatory input onto interneurons relative to pyramidal cells, and of depression interneurons relative to facilitation interneurons, during high frequency portions of the train. This occurs to a similar extent at 25 °C and at 33 °C, and is even greater at physiological extracellular calcium. Target-cell specific differences in short-term plasticity enable synapses to have different temporal filtering characteristics, which may help to dynamically regulate the balance of inhibition and excitation in CA1.

Regulation of synaptic release-site Ca2+ channel coupling as a mechanism to control release probability and short-term plasticity

Synaptic transmission relies on the rapid fusion of neurotransmitter-containing synaptic vesicles (SVs), which happens in response to action potential (AP)-induced Ca²⁺ influx at active zones (AZs). A highly conserved molecular machinery cooperates at SV-release sites to mediate SV plasma membrane attachment and maturation, Ca²⁺ sensing, and membrane fusion. Despite this high degree of conservation, synapses - even within the same organism, organ or neuron - are highly diverse regarding the probability of APs to trigger SV fusion. Additionally, repetitive activation can lead to either strengthening or weakening of transmission. In this review, we discuss mechanisms controlling release probability and this short-term plasticity. We argue that an important layer of control is exerted by evolutionarily conserved AZ scaffolding proteins, which determine the coupling distance between SV fusion sites and voltage-gated Ca²⁺ channels (VGCC) and, thereby, shape synapse-specific input/output behaviors. We propose that AZ-scaffold modifications may occur to adapt the coupling distance during synapse maturation and plastic regulation of synapse strength.

Metaplasticity at CA1 Synapses by Homeostatic Control of Presynaptic Release Dynamics

Hebbian and homeostatic forms of plasticity operate on different timescales to regulate synaptic strength. The degree of mechanistic overlap between these processes and their mutual influence are still incompletely understood. Here, we report that homeostatic synaptic strengthening induced by prolonged network inactivity compromised the ability of CA1 synapses to exhibit LTP. This effect could not be accounted for by an obvious deficit in the postsynaptic capacity for LTP expression, since neither the fraction of silent synapses nor the ability to induce LTP by two-photon glutamate uncaging were reduced by the homeostatic process. Rather, optical quantal analysis reveals that homeostatically strengthened synapses display a reduced capacity to maintain glutamate release fidelity during repetitive stimulation, ultimately impeding the induction, and thus expression, of LTP. By regulating the short-term dynamics of glutamate release, the homeostatic process thus influences key aspects of dynamic network function and exhibits features of metaplasticity.

Effect of Neuromodulation of Short-term Plasticity on Information Processing in Hippocampal Interneuron Synapses

Neurons in a micro-circuit connected by chemical synapses can have their connectivity affected by the prior activity of the cells. The number of synapses available for releasing neurotransmitter can be decreased by repetitive activation through depletion of readily releasable neurotransmitter (NT), or increased through facilitation, where the probability of release of NT is increased by prior activation. These competing effects can create a complicated and subtle range of time-dependent connectivity. Here we investigate the probabilistic properties of facilitation and depression (FD) for a presynaptic neuron that is receiving a Poisson spike train of input. We use a model of FD that is parameterized with experimental data from a hippocampal basket cell and pyramidal cell connection, for fixed frequency input spikes at frequencies in the range of theta (3-8 Hz) and gamma (20-100 Hz) oscillations. Hence our results will apply to micro-circuits in the hippocampus that are responsible for the interaction of theta and gamma rhythms associated with learning and memory. A control situation is compared with one in which a pharmaceutical neuromodulator (muscarine) is employed. We apply standard information-theoretic measures such as entropy and mutual information, and find a closed form approximate expression for the probability distribution of release probability. We also use techniques that measure the dependence of the response on the exact history of stimulation the synapse has received, which uncovers some unexpected differences between control and muscarine-added cases.

Comparison of the Upper Marginal Neurons of Cortical Layer 2 with Layer 2/3 Pyramidal Neurons in Mouse Temporal Cortex

Layer 2/3 (L2/3) excitatory neurons in the neocortex make major contributions to corticocortical connections and therefore function to integrate information across cortical areas and hemispheres. Recent evidence suggests that excitatory neurons in L2/3 can have different properties. Sparse evidence from previous studies suggests that L2 neurons located at the border between L1 and L2 (referred to as L2 marginal neurons, L2MNs), have a morphology distinct from a typical pyramidal neuron. However, whether the membrane properties and input/output properties of L2MNs are different from those of typical pyramidal neurons in L2/3 is unknown. Here we addressed these questions in a slice preparation of mouse temporal cortex. We found that L2MNs were homogeneous in intrinsic membrane properties but appeared diverse in morphology. In agreement with previous studies, L2MNs either had oblique apical dendrites or had no obvious apical dendrites. The tufts of both apical and basal dendrites of these neurons invaded L1 extensively. All L2MNs showed a regular firing pattern with moderate adaptation. Compared with typical L2/3 pyramidal neurons that showed regular spiking (RS) activity (neurons), L2MNs showed a higher firing rate, larger sag ratio, and higher input resistance. No difference in the amplitude of excitatory and inhibitory postsynaptic potentials (EPSPs and IPSPs, respectively), evoked by stimulation of L1, was found between the two types of neurons, but the IPSPs in L2MNs had a slower time course than those in L2/3 RS cells. In paired recordings, unitary EPSPs showed no significant differences between synapses formed by L2MNs and those formed by L2/3 RS neurons. However, short-term synaptic depression (STSD) examined with a L2MN as the presynaptic neuron was greater when another L2MN was the postsynaptic neuron than when a L2/3 RS neuron was the postsynaptic neuron. The distinct morphological features of L2MNs found here have developmental implications, and the differences in electrophysiological properties between L2MNs and other L2/3 pyramidal neurons suggest that they play different functional roles in cortical networks.

The effects of dynamical synapses on firing rate activity: a spiking neural network model

Accumulating evidence relates the fine-tuning of synaptic maturation and regulation of neural network activity to several key factors, including GABA_A signaling and a lateral spread length between neighboring neurons (i.e., local connectivity). Furthermore, a number of studies consider short-term synaptic plasticity (STP) as an essential element in the instant modification of synaptic efficacy in the neuronal network and in modulating responses to sustained ranges of external Poisson input frequency (IF). Nevertheless, evaluating the firing activity in response to the dynamical interaction between STP (triggered by ranges of IF) and these key parameters in vitro remains elusive. Therefore, we designed a spiking neural network (SNN) model in which we incorporated the following parameters: local density of arbor essences and a lateral spread length between neighboring neurons. We also created several network scenarios based on these key parameters. Then, we implemented two classes of STP: (1) short-term synaptic depression (STD) and (2) short-term synaptic facilitation (STF). Each class has two differential forms based on the parametric value of its synaptic time constant (either for depressing or facilitating synapses). Lastly, we compared the neural firing responses before and after the treatment with STP. We found that dynamical synapses (STP) have a critical differential role on evaluating and modulating the firing rate activity in each network scenario. Moreover, we investigated the impact of changing the balance between excitation (E) and inhibition (I) on stabilizing this firing activity.

Haploinsufficiency of the 22q11.2 microdeletion gene Mrpl40 disrupts short-term synaptic plasticity and working memory through dysregulation of mitochondrial calcium

Hemizygous deletion of a 1.5- to 3-megabase region on chromosome 22 causes 22q11.2 deletion syndrome (22q11DS), which constitutes one of the strongest genetic risks for schizophrenia. Mouse models of 22q11DS have abnormal short-term synaptic plasticity that contributes to working-memory deficiencies similar to those in schizophrenia. We screened mutant mice carrying hemizygous deletions of 22q11DS genes and identified haploinsufficiency of Mrpl40 (mitochondrial large ribosomal subunit protein 40) as a contributor to abnormal short-term potentiation (STP), a major form of short-term synaptic plasticity. Two-photon imaging of the genetically encoded fluorescent calcium indicator GCaMP6, expressed in presynaptic cytosol or mitochondria, showed that Mrpl40 haploinsufficiency deregulates STP via impaired calcium extrusion from the mitochondrial matrix through the mitochondrial permeability transition pore. This led to abnormally high cytosolic calcium transients in presynaptic terminals and deficient working memory but did not affect long-term spatial memory. Thus, we propose that mitochondrial calcium deregulation is a novel pathogenic mechanism of cognitive deficiencies in schizophrenia.

The Mechanisms and Functions of Synaptic Facilitation

The ability of the brain to store and process information relies on changing the strength of connections between neurons. Synaptic facilitation is a form of short-term plasticity that enhances synaptic transmission for less than a second. Facilitation is a ubiquitous phenomenon thought to play critical roles in information transfer and neural processing. Yet our understanding of the function of facilitation remains largely theoretical. Here we review proposed roles for facilitation and discuss how recent progress in uncovering the underlying molecular mechanisms could enable experiments that elucidate how facilitation, and short-term plasticity in general, contributes to circuit function and animal behavior.

Dopaminergic Modulation of Synaptic Integration and Firing Patterns in the Rat Entopeduncular Nucleus

Dopamine is known to differentially modulate the impact of cortical input to the striatum between the direct and indirect pathways of the basal ganglia (BG). However, the role of extrastriatal dopamine receptors (DRs) in BG information processing is less clear. To investigate the role of extrastriatal DRs, we studied their distribution and function in one of the output nuclei of the BG of the rodent, the entopeduncular nucleus (EP). qRT-PCR indicated that all DR subtypes were expressed by EP neurons, suggesting that both D₁-like receptors (D1LRs) and D₂-like receptors (D2LRs) were likely to affect information processing in the EP. Whole-cell recordings revealed that striatal inputs to the EP were potentiated by D1LRs whereas pallidal inputs to the EP were depressed by D2LRs. Changes to the paired-pulse ratio of inputs to the EP suggested that dopaminergic modulation of striatal inputs is mediated by postsynaptic receptors, and that of globus pallidus-evoked inputs is mediated by presynaptic receptors. We show that these changes in synaptic efficacy changed the information content of EP neuron firing. Overall, the findings suggest that the dopaminergic system affects the passage of feedforward information through the BG by modulating input divergence in the striatum and output convergence in the EP.SIGNIFICANCE STATEMENT The entopeduncular nucleus (EP), one of the basal ganglia (BG) output nuclei, is an important station in information processing in BG. However, it remains unclear how EP neurons encode information and how dopamine affects this process. This contrasts with the well established role of dopamine in the striatum, which is known to redistribute cortical input between the direct and indirect pathways. Here we show that, in symmetry with the striatum, dopamine controls the rebalancing of information flow between the two pathways in the EP. Specifically, we demonstrate that dopamine regulates EP activity by differentially modulating striatal and pallidal GABAergic inputs. These results call for a reassessment of current perspectives on BG information processing by highlighting the functional role of extrastriatal dopamine receptors.

Functional roles of short-term synaptic plasticity with an emphasis on inhibition

Almost all synapses show activity-dependent dynamic changes in efficacy. Numerous studies have explored the mechanisms underlying different forms of short-term synaptic plasticity (STP), but the functional role of STP for circuit output and animal behavior is less understood. This is particularly true for inhibitory synapses that can play widely varied roles in circuit activity. We review recent findings on the role of synaptic STP in sensory, pattern generating, thalamocortical, and hippocampal networks, with a focus on synaptic inhibition. These studies show a variety of functions including sensory adaptation and gating, dynamic gain control and rhythm generation. Because experimental manipulations of STP are difficult and nonspecific, a clear demonstration of STP function often requires a combination of experimental and computational techniques.

Dynamic balance of excitation and inhibition rapidly modulates spike probability and precision in feed-forward hippocampal circuits

Feed-forward inhibitory (FFI) circuits are important for many information-processing functions. FFI circuit operations critically depend on the balance and timing between the excitatory and inhibitory components, which undergo rapid dynamic changes during neural activity due to short-term plasticity (STP) of both components. How dynamic changes in excitation/inhibition (E/I) balance during spike trains influence FFI circuit operations remains poorly understood. In the current study we examined the role of STP in the FFI circuit functions in the mouse hippocampus. Using a coincidence detection paradigm with simultaneous activation of two Schaffer collateral inputs, we found that the spiking probability in the target CA1 neuron was increased while spike precision concomitantly decreased during high-frequency bursts compared with a single spike. Blocking inhibitory synaptic transmission revealed that dynamics of inhibition predominately modulates the spike precision but not the changes in spiking probability, whereas the latter is modulated by the dynamics of excitation. Further analyses combining whole cell recordings and simulations of the FFI circuit suggested that dynamics of the inhibitory circuit component may influence spiking behavior during bursts by broadening the width of excitatory postsynaptic responses and that the strength of this modulation depends on the basal E/I ratio. We verified these predictions using a mouse model of fragile X syndrome, which has an elevated E/I ratio, and found a strongly reduced modulation of postsynaptic response width during bursts. Our results suggest that changes in the dynamics of excitatory and inhibitory circuit components due to STP play important yet distinct roles in modulating the properties of FFI circuits.

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.

Synaptic Plasticity, a Prominent Contributor to the Anxiety in Fragile X Syndrome

Fragile X syndrome (FXS) is an inheritable neuropsychological disease caused by expansion of the CGG trinucleotide repeat affecting the fmr1 gene on X chromosome, resulting in silence of the fmr1 gene and failed expression of FMRP. Patients with FXS suffer from cognitive impairment, sensory integration deficits, learning disability, anxiety, autistic traits, and so forth. Specifically, the morbidity of anxiety in FXS individuals remains high from childhood to adulthood. By and large, it is common that the change of brain plasticity plays a key role in the progression of disease. But for now, most studies excessively emphasized the one-sided factor on the change of synaptic plasticity participating in the generation of anxiety during the development of FXS. Here we proposed an integrated concept to acquire better recognition about the details of this process.

ADAR-mediated RNA editing suppresses sleep by acting as a brake on glutamatergic synaptic plasticity

It has been postulated that synaptic potentiation during waking is offset by a homoeostatic reduction in net synaptic strength during sleep. However, molecular mechanisms to support such a process are lacking. Here we demonstrate that deficiencies in the RNA-editing gene Adar increase sleep due to synaptic dysfunction in glutamatergic neurons in Drosophila. Specifically, the vesicular glutamate transporter is upregulated, leading to over-activation of NMDA receptors, and the reserve pool of glutamatergic synaptic vesicles is selectively expanded in Adar mutants. Collectively these changes lead to sustained neurotransmitter release under conditions that would otherwise result in synaptic depression. We propose that a shift in the balance from synaptic depression towards synaptic potentiation in sleep-promoting neurons underlies the increased sleep pressure of Adar-deficient animals. Our findings provide a plausible molecular mechanism linking sleep and synaptic plasticity.

Sleep is postulated to offset buildup in net synaptic strength that occurs during waking experience. Here, the authors identify a role for the RNA editing gene Adar in regulating glutamatergic synaptic plasticity and show that disruption in Adar expression impairs normal waking in flies.

Frequency-dependent learning achieved using semiconducting polymer/electrolyte composite cells

Frequency-dependent learning has been achieved using semiconducting polymer/electrolyte composite cells. The cells composed of polymer/electrolyte double layers realized the conventional spike-rate-dependent plasticity (SRDP) learning model. These cells responded to depression upon low-frequency stimulation and to potentiation upon high-frequency stimulation and presented long-term memory. The transition threshold θm from depression to potentiation varied depending on the previous stimulations. A nanostructure resembling a bio-synapse in its transport passages was demonstrated and a random channel model was proposed to describe the ionic kinetics at the polymer/electrolyte interface during and after stimulations with various frequencies, accounting for the observed SRDP.

GABAB receptor-mediated feed-forward circuit dysfunction in the mouse model of fragile X syndrome

KEY POINTS

Cortico-hippocampal feed-forward circuits formed by the temporoammonic (TA) pathway exhibit a marked increase in excitation/inhibition ratio and abnormal spike modulation functions in Fmr1 knock-out (KO) mice. Inhibitory, but not excitatory, synapse dysfunction underlies cortico-hippocampal feed-forward circuit abnormalities in Fmr1 KO mice. GABA release is reduced in TA-associated inhibitory synapses of Fmr1 KO mice in a GABAB receptor-dependent manner. Inhibitory synapse and feed-forward circuit defects are mediated predominately by presynaptic GABAB receptor signalling in the TA pathway of Fmr1 KO mice. GABAB receptor-mediated inhibitory synapse defects are circuit-specific and are not observed in the Schaffer collateral pathway-associated inhibitory synapses in stratum radiatum.

ABSTRACT

Circuit hyperexcitability has been implicated in neuropathology of fragile X syndrome, the most common inheritable cause of intellectual disability. Yet, how canonical unitary circuits are affected in this disorder remains poorly understood. Here, we examined this question in the context of the canonical feed-forward inhibitory circuit formed by the temporoammonic (TA) branch of the perforant path, the major cortical input to the hippocampus. TA feed-forward circuits exhibited a marked increase in excitation/inhibition ratio and major functional defects in spike modulation tasks in Fmr1 knock-out (KO) mice, a fragile X mouse model. Changes in feed-forward circuits were caused specifically by inhibitory, but not excitatory, synapse defects. TA-associated inhibitory synapses exhibited increase in paired-pulse ratio and in the coefficient of variation of IPSPs, consistent with decreased GABA release probability. TA-associated inhibitory synaptic transmission in Fmr1 KO mice was also more sensitive to inhibition of GABAB receptors, suggesting an increase in presynaptic GABAB receptor (GABAB R) signalling. Indeed, the differences in inhibitory synaptic transmission between Fmr1 KO and wild-type (WT) mice were eliminated by a GABAB R antagonist. Inhibition of GABAB Rs or selective activation of presynaptic GABAB Rs also abolished the differences in the TA feed-forward circuit properties between Fmr1 KO and WT mice. These GABAB R-mediated defects were circuit-specific and were not observed in the Schaffer collateral pathway-associated inhibitory synapses. Our results suggest that the inhibitory synapse dysfunction in the cortico-hippocampal pathway of Fmr1 KO mice causes hyperexcitability and feed-forward circuit defects, which are mediated in part by a presynaptic GABAB R-dependent reduction in GABA release.

Shaping Neuronal Network Activity by Presynaptic Mechanisms

Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level.

The activity of neuronal networks underlies basic neural functions such as sleep, learning and sensorimotor gating. Computational models of neuronal networks have been developed to capture the complexity of the network activity and predict how neuronal networks generate spontaneous activity. However, most computational models do not simulate the intricate synaptic release process that governs the interaction between neurons and has been shown to significantly impact neuronal network activity and animal behavior, learning and memory. Our paper demonstrates the importance of simulating the elaborate synaptic release process to understand how neuronal networks generate spontaneous activity and respond to manipulations of the release process. The model provides mechanistic explanations and predictions for experimental pharmacological and genetic manipulations. Thus, the model presents a novel computational platform to understand how mechanistic changes in the synaptic release process modulate network oscillatory activity that might impact basic neural functions.

Effect of heavy-ion on frequency selectivity of semiconducting polymer/electrolyte heterojunction

Long-term bidirectional frequency selectivity has been achieved in MEH-PPV/PEO–Nd³⁺cells, which suggests spike-rate-dependent plasticity learning protocol. It depends on pulse shape due to variation of ionic type.

Controlling Ion Conductance and Channels to Achieve Synaptic-like Frequency Selectivity

Enhancing ion conductance and controlling transport pathway in organic electrolyte could be used to modulate ionic kinetics to handle signals. In a Pt/Poly(3-hexylthiophene-2,5-diyl)/Polyethylene+LiCF₃SO₃/Pt hetero-junction, the electrolyte layer handled at high temperature showed nano-fiber microstructures accompanied with greatly improved salt solubility. Ions with high mobility were confined in the nano-fibrous channels leading to the semiconducting polymer layer, which is favorable for modulating dynamic doping at the semiconducting polymer/electrolyte interface by pulse frequency. Such a device realized synaptic-like frequency selectivity, i.e., depression at low frequency stimulation but potentiation at high-frequency stimulation.

Synaptic plasticity, neural circuits, and the emerging role of altered short-term information processing in schizophrenia

Synaptic plasticity alters the strength of information flow between presynaptic and postsynaptic neurons and thus modifies the likelihood that action potentials in a presynaptic neuron will lead to an action potential in a postsynaptic neuron. As such, synaptic plasticity and pathological changes in synaptic plasticity impact the synaptic computation which controls the information flow through the neural microcircuits responsible for the complex information processing necessary to drive adaptive behaviors. As current theories of neuropsychiatric disease suggest that distinct dysfunctions in neural circuit performance may critically underlie the unique symptoms of these diseases, pathological alterations in synaptic plasticity mechanisms may be fundamental to the disease process. Here we consider mechanisms of both short-term and long-term plasticity of synaptic transmission and their possible roles in information processing by neural microcircuits in both health and disease. As paradigms of neuropsychiatric diseases with strongly implicated risk genes, we discuss the findings in schizophrenia and autism and consider the alterations in synaptic plasticity and network function observed in both human studies and genetic mouse models of these diseases. Together these studies have begun to point toward a likely dominant role of short-term synaptic plasticity alterations in schizophrenia while dysfunction in autism spectrum disorders (ASDs) may be due to a combination of both short-term and long-term synaptic plasticity alterations.

High bandwidth synaptic communication and frequency tracking in human neocortex

Neuronal firing, synaptic transmission, and its plasticity form the building blocks for processing and storage of information in the brain. It is unknown whether adult human synapses are more efficient in transferring information between neurons than rodent synapses. To test this, we recorded from connected pairs of pyramidal neurons in acute brain slices of adult human and mouse temporal cortex and probed the dynamical properties of use-dependent plasticity. We found that human synaptic connections were purely depressing and that they recovered three to four times more swiftly from depression than synapses in rodent neocortex. Thereby, during realistic spike trains, the temporal resolution of synaptic information exchange in human synapses substantially surpasses that in mice. Using information theory, we calculate that information transfer between human pyramidal neurons exceeds that of mouse pyramidal neurons by four to nine times, well into the beta and gamma frequency range. In addition, we found that human principal cells tracked fine temporal features, conveyed in received synaptic inputs, at a wider bandwidth than for rodents. Action potential firing probability was reliably phase-locked to input transients up to 1,000 cycles/s because of a steep onset of action potentials in human pyramidal neurons during spike trains, unlike in rodent neurons. Our data show that, in contrast to the widely held views of limited information transfer in rodent depressing synapses, fast recovering synapses of human neurons can actually transfer substantial amounts of information during spike trains. In addition, human pyramidal neurons are equipped to encode high synaptic information content. Thus, adult human cortical microcircuits relay information at a wider bandwidth than rodent microcircuits.

Activity-dependent regulation of release probability at excitatory hippocampal synapses: a crucial role of fragile X mental retardation protein in neurotransmission

Transcriptional silencing of the Fmr1 gene encoding fragile X mental retardation protein (FMRP) causes fragile X syndrome (FXS), the most common form of inherited intellectual disability and the leading genetic cause of autism. FMRP has been suggested to play important roles in regulating neurotransmission and short-term synaptic plasticity at excitatory hippocampal and cortical synapses. However, the origins and mechanisms of these FMRP actions remain incompletely understood, and the role of FMRP in regulating synaptic release probability and presynaptic function remains debated. Here we used variance-mean analysis and peak-scaled nonstationary variance analysis to examine changes in both presynaptic and postsynaptic parameters during repetitive activity at excitatory CA3-CA1 hippocampal synapses in a mouse model of FXS. Our analyses revealed that loss of FMRP did not affect the basal release probability or basal synaptic transmission, but caused an abnormally elevated release probability specifically during repetitive activity. These abnormalities were not accompanied by changes in excitatory postsynaptic current kinetics, quantal size or postsynaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor conductance. Our results thus indicate that FMRP regulates neurotransmission at excitatory hippocampal synapses specifically during repetitive activity via modulation of release probability in a presynaptic manner. Our study suggests that FMRP function in regulating neurotransmitter release is an activity-dependent phenomenon that may contribute to the pathophysiology of FXS.

Stabilization of memory States by stochastic facilitating synapses

Bistability within a small neural circuit can arise through an appropriate strength of excitatory recurrent feedback. The stability of a state of neural activity, measured by the mean dwelling time before a noise-induced transition to another state, depends on the neural firing-rate curves, the net strength of excitatory feedback, the statistics of spike times, and increases exponentially with the number of equivalent neurons in the circuit. Here, we show that such stability is greatly enhanced by synaptic facilitation and reduced by synaptic depression. We take into account the alteration in times of synaptic vesicle release, by calculating distributions of inter-release intervals of a synapse, which differ from the distribution of its incoming interspike intervals when the synapse is dynamic. In particular, release intervals produced by a Poisson spike train have a coefficient of variation greater than one when synapses are probabilistic and facilitating, whereas the coefficient of variation is less than one when synapses are depressing. However, in spite of the increased variability in postsynaptic input produced by facilitating synapses, their dominant effect is reduced synaptic efficacy at low input rates compared to high rates, which increases the curvature of neural input-output functions, leading to wider regions of bistability in parameter space and enhanced lifetimes of memory states. Our results are based on analytic methods with approximate formulae and bolstered by simulations of both Poisson processes and of circuits of noisy spiking model neurons.

Focal epileptiform activity in the prefrontal cortex is associated with long-term attention and sociability deficits

There is a well-described association between childhood epilepsy and pervasive cognitive and behavioral deficits. Often these children not only have ictal EEG events, but also frequent interictal abnormalities. The precise role of these interictal discharges in cognition remains unclear. In order to understand the relationship between frequent epileptiform discharges during neurodevelopment and cognition later in life, we developed a model of frequent focal interictal spikes (IIS). Postnatal day (p) 21 rats received injections of bicuculline methiodine into the prefrontal cortex (PFC). Injections were repeated in order to achieve 5 consecutive days of transient inhibitory/excitatory imbalance resulting in IIS. Short-term plasticity (STP) and behavioral outcomes were studied in adulthood. IIS is associated with a significant increase in STP bilaterally in the PFC. IIS rats did not show working memory deficits, but rather showed marked inattentiveness without significant alterations in motivation, anxiety or hyperactivity. Rats also demonstrated significant deficits in social behavior. We conclude that GABAergic blockade during early-life and resultant focal IIS in the PFC disrupt neural networks and are associated with long-term consequences for behavior at a time when IIS are no longer present, and thus may have important implications for ADHD and autism spectrum disorder associated with childhood epilepsy.

Role of synaptic dynamics and heterogeneity in neuronal learning of temporal code

Temporal codes are believed to play important roles in neuronal representation of information. Neuronal ability to classify and learn temporal spiking patterns is thus essential for successful extraction and processing of information. Understanding neuronal learning of temporal code has been complicated, however, by the intrinsic stochasticity of synaptic transmission. Using a computational model of a learning neuron, the tempotron, we studied the effects of synaptic unreliability and short-term dynamics on the neuron's ability to learn spike timing rules. Our results suggest that such a model neuron can learn to classify spike timing patterns even with unreliable synapses, albeit with a significantly reduced success rate. We explored strategies to improve correct spike timing classification and found that firing clustered spike bursts significantly improves learning performance. Furthermore, rapid activity-dependent modulation of synaptic unreliability, implemented with realistic models of dynamic synapses, further improved classification of different burst properties and spike timing modalities. Neuronal models with only facilitating or only depressing inputs exhibited preference for specific types of spike timing rules, but a mixture of facilitating and depressing synapses permitted much improved learning of multiple rules. We tested applicability of these findings to real neurons by considering neuronal learning models with the naturally distributed input release probabilities found in excitatory hippocampal synapses. Our results suggest that spike bursts comprise several encoding modalities that can be learned effectively with stochastic dynamic synapses, and that distributed release probabilities significantly improve learning performance. Synaptic unreliability and dynamics may thus play important roles in the neuron's ability to learn spike timing rules during decoding.