Local dendritic activity sets release probability at hippocampal synapses

Intracellular magnesium optimizes transmission efficiency and plasticity of hippocampal synapses by reconfiguring their connectivity

Synapses at dendritic branches exhibit specific properties for information processing. However, how the synapses are orchestrated to dynamically modify their properties, thus optimizing information processing, remains elusive. Here, we observed at hippocampal dendritic branches diverse configurations of synaptic connectivity, two extremes of which are characterized by low transmission efficiency, high plasticity and coding capacity, or inversely. The former favors information encoding, pertinent to learning, while the latter prefers information storage, relevant to memory. Presynaptic intracellular Mg2+ crucially mediates the dynamic transition continuously between the two extreme configurations. Consequently, varying intracellular Mg2+ levels endow individual branches with diverse synaptic computations, thus modulating their ability to process information. Notably, elevating brain Mg2+ levels in aging animals restores synaptic configuration resembling that of young animals, coincident with improved learning and memory. These findings establish intracellular Mg2+ as a crucial factor reconfiguring synaptic connectivity at dendrites, thus optimizing their branch-specific properties in information processing.

Spinal microcircuits go through multiphasic homeostatic compensations in a mouse model of motoneuron degeneration

In neurological conditions affecting the brain, early-stage neural circuit adaption is key for long-term preservation of normal behaviour. We tested if motoneurons and respective microcircuits also adapt in the initial stages of disease progression in a mouse model of progressive motoneuron degeneration. Using a combination of in vitro and in vivo electrophysiology and super-resolution microscopy, we found that, preceding muscle denervation and motoneuron death, recurrent inhibition mediated by Renshaw cells is reduced in half due to impaired quantal size associated with decreased glycine receptor density. Additionally, higher probability of release from proprioceptive Ia terminals leads to increased monosynaptic excitation to motoneurons. Surprisingly, the initial impairment in recurrent inhibition is not a widespread feature of inhibitory spinal circuits, such as group I inhibitory afferents, and is compensated at later stages of disease progression. We reveal that in disease conditions, spinal microcircuits undergo specific multiphasic homeostatic compensations to preserve force output.

Rapid sequential clustering of NMDARs, CaMKII, and AMPARs upon activation of NMDARs at developing synapses

Rapid, synapse-specific neurotransmission requires the precise alignment of presynaptic neurotransmitter release and postsynaptic receptors. How postsynaptic glutamate receptor accumulation is induced during maturation is not well understood. We find that in cultures of dissociated hippocampal neurons at 11 days in vitro (DIV) numerous synaptic contacts already exhibit pronounced accumulations of the pre- and postsynaptic markers synaptotagmin, synaptophysin, synapsin, bassoon, VGluT1, PSD-95, and Shank. The presence of an initial set of AMPARs and NMDARs is indicated by miniature excitatory postsynaptic currents (mEPSCs). However, AMPAR and NMDAR immunostainings reveal rather smooth distributions throughout dendrites and synaptic enrichment is not obvious. We found that brief periods of Ca2+ influx through NMDARs induced a surprisingly rapid accumulation of NMDARs within 1 min, followed by accumulation of CaMKII and then AMPARs within 2-5 min. Postsynaptic clustering of NMDARs and AMPARs was paralleled by an increase in their mEPSC amplitudes. A peptide that blocked the interaction of NMDAR subunits with PSD-95 prevented the NMDAR clustering. NMDAR clustering persisted for 3 days indicating that brief periods of elevated glutamate fosters permanent accumulation of NMDARs at postsynaptic sites in maturing synapses. These data support the model that strong glutamatergic stimulation of immature glutamatergic synapses results in a fast and substantial increase in postsynaptic NMDAR content that required NMDAR binding to PSD-95 or its homologues and is followed by recruitment of CaMKII and subsequently AMPARs.

Altered exocytosis of inhibitory synaptic vesicles at single presynaptic terminals of cultured striatal neurons in a knock-in mouse model of Huntington's disease

Huntington's disease (HD) is a progressive dominantly inherited neurodegenerative disease caused by the expansion of a cytosine-adenine-guanine (CAG) trinucleotide repeat in the huntingtin gene, which encodes the mutant huntingtin protein containing an expanded polyglutamine tract. One of neuropathologic hallmarks of HD is selective degeneration in the striatum. Mechanisms underlying selective neurodegeneration in the striatum of HD remain elusive. Neurodegeneration is suggested to be preceded by abnormal synaptic transmission at the early stage of HD. However, how mutant huntingtin protein affects synaptic vesicle exocytosis at single presynaptic terminals of HD striatal neurons is poorly understood. Here, we measured synaptic vesicle exocytosis at single presynaptic terminals of cultured striatal neurons (mainly inhibitory neurons) in a knock-in mouse model of HD (zQ175) during electrical field stimulation using real-time imaging of FM 1-43 (a lipophilic dye). We found a significant decrease in bouton density and exocytosis of synaptic vesicles at single presynaptic terminals in cultured striatal neurons. Real-time imaging of VGAT-CypHer5E (a pH sensitive dye conjugated to an antibody against vesicular GABA transporter (VGAT)) for inhibitory synaptic vesicles revealed a reduction in bouton density and exocytosis of inhibitory synaptic vesicles at single presynaptic terminals of HD striatal neurons. Thus, our results suggest that the mutant huntingtin protein decreases bouton density and exocytosis of inhibitory synaptic vesicles at single presynaptic terminals of striatal neurons, causing impaired inhibitory synaptic transmission, eventually leading to the neurodegeneration in the striatum of HD.

Synaptic weights that correlate with presynaptic selectivity increase decoding performance

The activity of neurons in the visual cortex is often characterized by tuning curves, which are thought to be shaped by Hebbian plasticity during development and sensory experience. This leads to the prediction that neural circuits should be organized such that neurons with similar functional preference are connected with stronger weights. In support of this idea, previous experimental and theoretical work have provided evidence for a model of the visual cortex characterized by such functional subnetworks. A recent experimental study, however, have found that the postsynaptic preferred stimulus was defined by the total number of spines activated by a given stimulus and independent of their individual strength. While this result might seem to contradict previous literature, there are many factors that define how a given synaptic input influences postsynaptic selectivity. Here, we designed a computational model in which postsynaptic functional preference is defined by the number of inputs activated by a given stimulus. Using a plasticity rule where synaptic weights tend to correlate with presynaptic selectivity, and is independent of functional-similarity between pre- and postsynaptic activity, we find that this model can be used to decode presented stimuli in a manner that is comparable to maximum likelihood inference.

Chronic Neuronal Inactivity Utilizes the mTOR-TFEB Pathway to Drive Transcription-Dependent Autophagy for Homeostatic Up-Scaling

Activity-dependent changes in protein expression are critical for neuronal plasticity, a fundamental process for the processing and storage of information in the brain. Among the various forms of plasticity, homeostatic synaptic up-scaling is unique in that it is induced primarily by neuronal inactivity. However, precisely how the turnover of synaptic proteins occurs in this homeostatic process remains unclear. Here, we report that chronically inhibiting neuronal activity in primary cortical neurons prepared from embryonic day (E)18 Sprague Dawley rats (both sexes) induces autophagy, thereby regulating key synaptic proteins for up-scaling. Mechanistically, chronic neuronal inactivity causes dephosphorylation of ERK and mTOR, which induces transcription factor EB (TFEB)-mediated cytonuclear signaling and drives transcription-dependent autophagy to regulate αCaMKII and PSD95 during synaptic up-scaling. Together, these findings suggest that mTOR-dependent autophagy, which is often triggered by metabolic stressors such as starvation, is recruited and sustained during neuronal inactivity to maintain synaptic homeostasis, a process that ensures proper brain function and if impaired can cause neuropsychiatric disorders such as autism.SIGNIFICANCE STATEMENT In the mammalian brain, protein turnover is tightly controlled by neuronal activation to ensure key neuronal functions during long-lasting synaptic plasticity. However, a long-standing question is how this process occurs during synaptic up-scaling, a process that requires protein turnover but is induced by neuronal inactivation. Here, we report that mTOR-dependent signaling, which is often triggered by metabolic stressors such as starvation, is "hijacked" by chronic neuronal inactivation, which then serves as a nucleation point for transcription factor EB (TFEB) cytonuclear signaling that drives transcription-dependent autophagy for up-scaling. These results provide the first evidence of a physiological role of mTOR-dependent autophagy in enduing neuronal plasticity, thereby connecting major themes in cell biology and neuroscience via a servo loop that mediates autoregulation in the brain.

Elevated amyloid beta disrupts the nanoscale organization and function of synaptic vesicle pools in hippocampal neurons

Alzheimer's disease is linked to increased levels of amyloid beta (Aβ) in the brain, but the mechanisms underlying neuronal dysfunction and neurodegeneration remain enigmatic. Here, we investigate whether organizational characteristics of functional presynaptic vesicle pools, key determinants of information transmission in the central nervous system, are targets for elevated Aβ. Using an optical readout method in cultured hippocampal neurons, we show that acute Aβ42 treatment significantly enlarges the fraction of functional vesicles at individual terminals. We observe the same effect in a chronically elevated Aβ transgenic model (APPSw,Ind) using an ultrastructure-function approach that provides detailed information on nanoscale vesicle pool positioning. Strikingly, elevated Aβ is correlated with excessive accumulation of recycled vesicles near putative endocytic sites, which is consistent with deficits in vesicle retrieval pathways. Using the glutamate reporter, iGluSnFR, we show that there are parallel functional consequences, where ongoing information signaling capacity is constrained. Treatment with levetiracetam, an antiepileptic that dampens synaptic hyperactivity, partially rescues these transmission defects. Our findings implicate organizational and dynamic features of functional vesicle pools as targets in Aβ-driven synaptic impairment, suggesting that interventions to relieve the overloading of vesicle retrieval pathways might have promising therapeutic value.

Probing the segregation of evoked and spontaneous neurotransmission via photobleaching and recovery of a fluorescent glutamate sensor

Synapses maintain both action potential-evoked and spontaneous neurotransmitter release; however, organization of these two forms of release within an individual synapse remains unclear. Here, we used photobleaching properties of iGluSnFR, a fluorescent probe that detects glutamate, to investigate the subsynaptic organization of evoked and spontaneous release in primary hippocampal cultures. In nonneuronal cells and neuronal dendrites, iGluSnFR fluorescence is intensely photobleached and recovers via diffusion of nonphotobleached probes with a time constant of ~10 s. After photobleaching, while evoked iGluSnFR events could be rapidly suppressed, their recovery required several hours. In contrast, iGluSnFR responses to spontaneous release were comparatively resilient to photobleaching, unless the complete pool of iGluSnFR was activated by glutamate perfusion. This differential effect of photobleaching on different modes of neurotransmission is consistent with a subsynaptic organization where sites of evoked glutamate release are clustered and corresponding iGluSnFR probes are diffusion restricted, while spontaneous release sites are broadly spread across a synapse with readily diffusible iGluSnFR probes.

Heterogeneous CaMKII-Dependent Synaptic Compensations in CA1 Pyramidal Neurons From Acute Hippocampal Slices

Prolonged changes in neural activity trigger homeostatic synaptic plasticity (HSP) allowing neuronal networks to operate within functional ranges. Cell-wide or input-specific adaptations can be induced by pharmacological or genetic manipulations of activity, and by sensory deprivation. Reactive functional changes caused by deafferentation may partially share mechanisms with HSP. Acute hippocampal slices are a suitable model to investigate relatively rapid (hours) modifications occurring after denervation and explore the underlying mechanisms. As during slicing many afferents are cut, we conducted whole-cell recordings of miniature excitatory postsynaptic currents (mEPSCs) in CA1 pyramidal neurons to evaluate changes over the following 12 h. As Schaffer collaterals constitute a major glutamatergic input to these neurons, we also dissected CA3. We observed an average increment in mEPSCs amplitude and a decrease in decay time, suggesting synaptic AMPA receptor upregulation and subunit content modifications. Sorting mEPSC by rise time, a correlate of synapse location along dendrites, revealed amplitude raises at two separate domains. A specific frequency increase was observed in the same domains and was accompanied by a global, unspecific raise. Amplitude and frequency increments were lower at sites initially more active, consistent with local compensatory processes. Transient preincubation with a specific Ca2+/calmodulin-dependent kinase II (CaMKII) inhibitor either blocked or occluded amplitude and frequency upregulation in different synapse populations. Results are consistent with the concurrent development of different known CaMKII-dependent HSP processes. Our observations support that deafferentation causes rapid and diverse compensations resembling classical slow forms of adaptation to inactivity. These results may contribute to understand fast-developing homeostatic or pathological events after brain injury.

Molecular Mechanisms of Memory Consolidation That Operate During Sleep

The role of sleep for brain function has been in the focus of interest for many years. It is now firmly established that sleep and the corresponding brain activity is of central importance for memory consolidation. Less clear are the underlying molecular mechanisms and their specific contribution to the formation of long-term memory. In this review, we summarize the current knowledge of such mechanisms and we discuss the several unknowns that hinder a deeper appreciation of how molecular mechanisms of memory consolidation during sleep impact synaptic function and engram formation.

Facial Nerve Axotomy Induces Changes on Hippocampal CA3-to-CA1 Long-term Synaptic Plasticity

Peripheral facial axotomy induces functional and structural central nervous system changes beyond facial motoneurons, causing, among others, changes in sensorimotor cortex and impairment in hippocampal-dependent memory tasks. Here, we explored facial nerve axotomy effects on basal transmission and long-term plasticity of commissural CA3-to-CA1 synapses. Adult, male rats were submitted to unilateral axotomy of the buccal and mandibular branches of facial nerve and allowed 1, 3, 7, or 21 days of recovery before performing electrophysiological recordings of contralateral CA3 (cCA3) stimulation-evoked CA1 field postsynaptic potential in basal conditions and after high frequency stimulation (HFS) (six, one-second length, 100 Hz stimuli trains). Facial nerve axotomy induced transient release probability enhancement during the first week after surgery, without significant changes in basal synaptic strength. In addition, peripheral axotomy caused persistent long-term potentiation (LTP) induction impairment, affecting mainly its presynaptic component. Such synaptic changes may underlie previously reported impairments in hippocampal-dependent memory tasks and suggest a direct hippocampal implication in sensorimotor integration in whisking behavior.

Astrocyte GluN2C NMDA receptors control basal synaptic strengths of hippocampal CA1 pyramidal neurons in the stratum radiatum

Experience-dependent plasticity is a key feature of brain synapses for which neuronal N-Methyl-D-Aspartate receptors (NMDARs) play a major role, from developmental circuit refinement to learning and memory. Astrocytes also express NMDARs, although their exact function has remained controversial. Here, we identify in mouse hippocampus, a circuit function for GluN2C NMDAR, a subtype highly expressed in astrocytes, in layer-specific tuning of synaptic strengths in CA1 pyramidal neurons. Interfering with astrocyte NMDAR or GluN2C NMDAR activity reduces the range of presynaptic strength distribution specifically in the stratum radiatum inputs without an appreciable change in the mean presynaptic strength. Mathematical modeling shows that narrowing of the width of presynaptic release probability distribution compromises the expression of long-term synaptic plasticity. Our findings suggest a novel feedback signaling system that uses astrocyte GluN2C NMDARs to adjust basal synaptic weight distribution of Schaffer collateral inputs, which in turn impacts computations performed by the CA1 pyramidal neuron.

Presynaptic stochasticity improves energy efficiency and helps alleviate the stability-plasticity dilemma

When an action potential arrives at a synapse there is a large probability that no neurotransmitter is released. Surprisingly, simple computational models suggest that these synaptic failures enable information processing at lower metabolic costs. However, these models only consider information transmission at single synapses ignoring the remainder of the neural network as well as its overall computational goal. Here, we investigate how synaptic failures affect the energy efficiency of models of entire neural networks that solve a goal-driven task. We find that presynaptic stochasticity and plasticity improve energy efficiency and show that the network allocates most energy to a sparse subset of important synapses. We demonstrate that stabilising these synapses helps to alleviate the stability-plasticity dilemma, thus connecting a presynaptic notion of importance to a computational role in lifelong learning. Overall, our findings present a set of hypotheses for how presynaptic plasticity and stochasticity contribute to sparsity, energy efficiency and improved trade-offs in the stability-plasticity dilemma.

The glutamatergic synapse: a complex machinery for information processing

Being the most abundant synaptic type, the glutamatergic synapse is responsible for the larger part of the brain's information processing. Despite the conceptual simplicity of the basic mechanism of synaptic transmission, the glutamatergic synapse shows a large variation in the response to the presynaptic release of the neurotransmitter. This variability is observed not only among different synapses but also in the same single synapse. The synaptic response variability is due to several mechanisms of control of the information transferred among the neurons and suggests that the glutamatergic synapse is not a simple bridge for the transfer of information but plays an important role in its elaboration and management. The control of the synaptic information is operated at pre, post, and extrasynaptic sites in a sort of cooperation between the pre and postsynaptic neurons which also involves the activity of other neurons. The interaction between the different mechanisms of control is extremely complicated and its complete functionality is far from being fully understood. The present review, although not exhaustively, is intended to outline the most important of these mechanisms and their complexity, the understanding of which will be among the most intriguing challenges of future neuroscience.

Quantum propensities in the brain cortex and free will

Capacity of conscious agents to perform genuine choices among future alternatives is a prerequisite for moral responsibility. Determinism that pervades classical physics, however, forbids free will, undermines the foundations of ethics, and precludes meaningful quantification of personal biases. To resolve that impasse, we utilize the characteristic indeterminism of quantum physics and derive a quantitative measure for the amount of free will manifested by the brain cortical network. The interaction between the central nervous system and the surrounding environment is shown to perform a quantum measurement upon the neural constituents, which actualize a single measurement outcome selected from the resulting quantum probability distribution. Inherent biases in the quantum propensities for alternative physical outcomes provide varying amounts of free will, which can be quantified with the expected information gain from learning the actual course of action chosen by the nervous system. For example, neuronal electric spikes evoke deterministic synaptic vesicle release in the synapses of sensory or somatomotor pathways, with no free will manifested. In cortical synapses, however, vesicle release is triggered indeterministically with probability of 0.35 per spike. This grants the brain cortex, with its over 100 trillion synapses, an amount of free will exceeding 96 terabytes per second. Although reliable deterministic transmission of sensory or somatomotor information ensures robust adaptation of animals to their physical environment, unpredictability of behavioral responses initiated by decisions made by the brain cortex is evolutionary advantageous for avoiding predators. Thus, free will may have a survival value and could be optimized through natural selection.

Mitochondria: new players in homeostatic regulation of firing rate set points

Neural circuit functions are stabilized by homeostatic processes at long timescales in response to changes in behavioral states, experience, and learning. However, it remains unclear which specific physiological variables are being stabilized and which cellular or neural network components compose the homeostatic machinery. At this point, most evidence suggests that the distribution of firing rates among neurons in a neuronal circuit is the key variable that is maintained around a set-point value in a process called 'firing rate homeostasis.' Here, we review recent findings that implicate mitochondria as central players in mediating firing rate homeostasis. While mitochondria are known to regulate neuronal variables such as synaptic vesicle release or intracellular calcium concentration, the mitochondrial signaling pathways that are essential for firing rate homeostasis remain largely unknown. We used basic concepts of control theory to build a framework for classifying possible components of the homeostatic machinery that stabilizes firing rate, and we particularly emphasize the potential role of sleep and wakefulness in this homeostatic process. This framework may facilitate the identification of new homeostatic pathways whose malfunctions drive instability of neural circuits in distinct brain disorders.

Nanoscale Remodeling of Functional Synaptic Vesicle Pools in Hebbian Plasticity

Vesicle pool properties are known determinants of synaptic efficacy, but their potential role as modifiable substrates in forms of Hebbian plasticity is still unclear. Here, we investigate this using a nanoscale readout of functionally recycled vesicles in natively wired hippocampal CA3→CA1 circuits undergoing long-term potentiation (LTP). We show that the total recycled vesicle pool is larger after plasticity induction, with the smallest terminals exhibiting the greatest relative expansion. Changes in the spatial organization of vesicles accompany potentiation including a specific increase in the number of recycled vesicles at the active zone, consistent with an ultrastructural remodeling component of synaptic strengthening. The cAMP-PKA pathway activator, forskolin, selectively mimics some features of LTP-driven changes, suggesting that distinct and independent modules of regulation accompany plasticity expression. Our findings provide evidence for a presynaptic locus of LTP encoded in the number and arrangement of functionally recycled vesicles, with relevance for models of long-term plasticity storage.

Spike bursting in a dragonfly target-detecting neuron

Dragonflies visually detect prey and conspecifics, rapidly pursuing these targets via acrobatic flights. Over many decades, studies have investigated the elaborate neuronal circuits proposed to underlie this rapid behaviour. A subset of dragonfly visual neurons exhibit exquisite tuning to small, moving targets even when presented in cluttered backgrounds. In prior work, these neuronal responses were quantified by computing the rate of spikes fired during an analysis window of interest. However, neuronal systems can utilize a variety of neuronal coding principles to signal information, so a spike train’s information content is not necessarily encapsulated by spike rate alone. One example of this is burst coding, where neurons fire rapid bursts of spikes, followed by a period of inactivity. Here we show that the most studied target-detecting neuron in dragonflies, CSTMD1, responds to moving targets with a series of spike bursts. This spiking activity differs from those in other identified visual neurons in the dragonfly, indicative of different physiological mechanisms underlying CSTMD1’s spike generation. Burst codes present several advantages and disadvantages compared to other coding approaches. We propose functional implications of CSTMD1’s burst coding activity and show that spike bursts enhance the robustness of target-evoked responses.

Release probability increases towards distal dendrites boosting high-frequency signal transfer in the rodent hippocampus

Dendritic integration of synaptic inputs involves their increased electrotonic attenuation at distal dendrites, which can be counterbalanced by the increased synaptic receptor density. However, during network activity, the influence of individual synapses depends on their release fidelity, the dendritic distribution of which remains poorly understood. Here, we employed classical optical quantal analyses and a genetically encoded optical glutamate sensor in acute hippocampal slices of rats and mice to monitor glutamate release at CA3-CA1 synapses. We find that their release probability increases with greater distances from the soma. Similar-fidelity synapses tend to group together, whereas release probability shows no trends regarding the branch ends. Simulations with a realistic CA1 pyramidal cell hosting stochastic synapses suggest that the observed trends boost signal transfer fidelity, particularly at higher input frequencies. Because high-frequency bursting has been associated with learning, the release probability pattern we have found may play a key role in memory trace formation.

Heterosynaptic cross-talk of pre- and postsynaptic strengths along segments of dendrites

Dendrites are crucial for integrating incoming synaptic information. Individual dendritic branches are thought to constitute a signal processing unit, yet how neighboring synapses shape the boundaries of functional dendritic units is not well understood. Here, we address the cellular basis underlying the organization of the strengths of neighboring Schaffer collateral-CA1 synapses by optical quantal analysis and spine size measurements. Inducing potentiation at clusters of spines produces NMDA-receptor-dependent heterosynaptic plasticity. The direction of postsynaptic strength change shows distance dependency to the stimulated synapses where proximal synapses predominantly depress, whereas distal synapses potentiate; potentiation and depression are regulated by CaMKII and calcineurin, respectively. In contrast, heterosynaptic presynaptic plasticity is confined to weakening of presynaptic strength of nearby synapses, which requires CaMKII and the retrograde messenger nitric oxide. Our findings highlight the parallel engagement of multiple signaling pathways, each with characteristic spatial dynamics in shaping the local pattern of synaptic strengths.

Single synapse glutamate imaging reveals multiple levels of release mode regulation in mammalian synapses

Mammalian central synapses exhibit vast heterogeneity in signaling strength. To understand the extent of this diversity, how it is achieved, and its functional implications, characterization of a large number of individual synapses is required. Using glutamate imaging, we characterized the evoked release probability and spontaneous release frequency of over 24,000 individual synapses. We found striking variability and no correlation between action potential-evoked and spontaneous synaptic release strength, suggesting distinct regulatory mechanisms. Subpixel localization of individual evoked and spontaneous release events reveals tight spatial regulation of evoked release and enhanced spontaneous release outside of evoked release region. Using on-stage post hoc immune-labeling of vesicle-associated proteins, Ca²⁺-sensing proteins, and soluble presynaptic proteins we were able to show that distinct molecular ensembles are associated with evoked and spontaneous modes of synaptic release.

A Novel Optical Quantal Analysis of Miniature Events Reveals Enhanced Frequency Following Amyloid β Exposure

Non-evoked miniature release of neurotransmitters is increasingly recognized as playing an important role in neural function and is implicated in synaptic plasticity, metaplasticity, and homeostasis. Spontaneous miniature release events (minis) are usually measured electrophysiologically by recording the miniature postsynaptic currents (mEPSCs) that they evoke. However, this indirect technique can be confounded by changes within the postsynaptic neuron. Here, using the fluorescent probe SynaptopHluorin 2×, we have developed an optical method for the measurement of minis that enables direct assessment of release events. We use the technique to reveal that the frequency of minis following incubation of hippocampal neurons with Amyloid β oligomers (Aβo) is increased. Electrophysiological mEPSC recordings obtained under the same conditions report a decrease in frequency, with the discrepancy likely due to Aβo-induced changes in quantal size. Optical quantal analysis of minis may therefore have a role in the study of minis in both normal physiology and disease, as it can circumvent potential confounds caused by postsynaptic changes.

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.

Presynaptic inhibition rapidly stabilises recurrent excitation in the face of plasticity

Hebbian plasticity, a mechanism believed to be the substrate of learning and memory, detects and further enhances correlated neural activity. Because this constitutes an unstable positive feedback loop, it requires additional homeostatic control. Computational work suggests that in recurrent networks, the homeostatic mechanisms observed in experiments are too slow to compensate instabilities arising from Hebbian plasticity and need to be complemented by rapid compensatory processes. We suggest presynaptic inhibition as a candidate that rapidly provides stability by compensating recurrent excitation induced by Hebbian changes. Presynaptic inhibition is mediated by presynaptic GABA receptors that effectively and reversibly attenuate transmitter release. Activation of these receptors can be triggered by excess network activity, hence providing a stabilising negative feedback loop that weakens recurrent interactions on sub-second timescales. We study the stabilising effect of presynaptic inhibition in recurrent networks, in which presynaptic inhibition is implemented as a multiplicative reduction of recurrent synaptic weights in response to increasing inhibitory activity. We show that networks with presynaptic inhibition display a gradual increase of firing rates with growing excitatory weights, in contrast to traditional excitatory-inhibitory networks. This alleviates the positive feedback loop between Hebbian plasticity and network activity and thereby allows homeostasis to act on timescales similar to those observed in experiments. Our results generalise to spiking networks with a biophysically more detailed implementation of the presynaptic inhibition mechanism. In conclusion, presynaptic inhibition provides a powerful compensatory mechanism that rapidly reduces effective recurrent interactions and thereby stabilises Hebbian learning.

Synapses between neurons change during learning and memory formation, a process termed synaptic plasticity. Established models of plasticity rely on strengthening synapses of co-active neurons. In recurrent networks, mutually connected neurons tend to be co-active. The emerging positive feedback loop is believed to be counteracted by homeostatic mechanisms that aim to keep neural activity at a given set point. However, theoretical work indicates that experimentally observed forms of homeostasis are too slow to maintain stable network activity. In this article, we suggest that presynaptic inhibition can alleviate this problem. Presynaptic inhibition is an inhibitory mechanism that weakens synapses rather than suppressing neural activity. Using mathematical analyses and computer simulations, we show that presynaptic inhibition can compensate the strengthening of recurrent connections and thus stabilises neural networks subject to synaptic plasticity, even if homeostasis acts on biologically plausible timescales.

Mechanisms and Functional Consequences of Presynaptic Homeostatic Plasticity at Auditory Nerve Synapses

Multiple forms of homeostasis influence synaptic function under diverse activity conditions. Both presynaptic and postsynaptic forms of homeostasis are important, but their relative impact on fidelity is unknown. To address this issue, we studied auditory nerve synapses onto bushy cells in the cochlear nucleus of mice of both sexes. These synapses undergo bidirectional presynaptic and postsynaptic homeostatic changes with increased and decreased acoustic stimulation. We found that both young and mature synapses exhibit similar activity-dependent changes in short-term depression. Experiments using chelators and imaging both indicated that presynaptic Ca²⁺ influx decreased after noise exposure, and increased after ligating the ear canal. By contrast, Ca²⁺ cooperativity was unaffected. Experiments using specific antagonists suggest that occlusion leads to changes in the Ca²⁺ channel subtypes driving neurotransmitter release. Furthermore, dynamic-clamp experiments revealed that spike fidelity primarily depended on changes in presynaptic depression, with some contribution from changes in postsynaptic intrinsic properties. These experiments indicate that presynaptic Ca²⁺ influx is homeostatically regulated in vivo to enhance synaptic fidelity.SIGNIFICANCE STATEMENT Homeostatic mechanisms in synapses maintain stable function in the face of different levels of activity. Both juvenile and mature auditory nerve synapses onto bushy cells modify short-term depression in different acoustic environments, which raises the question of what the underlying presynaptic mechanisms are and the relative importance of presynaptic and postsynaptic contributions to the faithful transfer of information. Changes in short-term depression under different acoustic conditions were a result of changes in presynaptic Ca²⁺ influx. Spike fidelity was affected by both presynaptic and postsynaptic changes after ear occlusion and was only affected by presynaptic changes after noise-rearing. These findings are important for understanding regulation of auditory synapses under normal conditions and also in disorders following noise exposure or conductive hearing loss.

Firing rate homeostasis counteracts changes in stability of recurrent neural networks caused by synapse loss in Alzheimer's disease

The impairment of cognitive function in Alzheimer's disease is clearly correlated to synapse loss. However, the mechanisms underlying this correlation are only poorly understood. Here, we investigate how the loss of excitatory synapses in sparsely connected random networks of spiking excitatory and inhibitory neurons alters their dynamical characteristics. Beyond the effects on the activity statistics, we find that the loss of excitatory synapses on excitatory neurons reduces the network's sensitivity to small perturbations. This decrease in sensitivity can be considered as an indication of a reduction of computational capacity. A full recovery of the network's dynamical characteristics and sensitivity can be achieved by firing rate homeostasis, here implemented by an up-scaling of the remaining excitatory-excitatory synapses. Mean-field analysis reveals that the stability of the linearised network dynamics is, in good approximation, uniquely determined by the firing rate, and thereby explains why firing rate homeostasis preserves not only the firing rate but also the network's sensitivity to small perturbations.

A Synthetic Likelihood Solution to the Silent Synapse Estimation Problem

Functional features of synaptic populations are typically inferred from random electrophysiological sampling of small subsets of synapses. Are these samples unbiased? Here, we develop a biophysically constrained statistical framework to address this question and apply it to assess the performance of a widely used method based on a failure-rate analysis to quantify the occurrence of silent (AMPAR-lacking) synapses. We simulate this method in silico and find that it is characterized by strong and systematic biases, poor reliability, and weak statistical power. Key conclusions are validated by whole-cell recordings from hippocampal neurons. To address these shortcomings, we develop a simulator of the experimental protocol and use it to compute a synthetic likelihood. By maximizing the likelihood, we infer silent synapse fraction with no bias, low variance, and superior statistical power over alternatives. Together, this generalizable approach highlights how a simulator of experimental methodologies can substantially improve the estimation of physiological properties.

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.

Illuminating Relationships Between the Pre- and Post-synapse

Excitatory synapses in the mammalian cortex are highly diverse, both in terms of their structure and function. However, relationships between synaptic features indicate they are highly coordinated entities. Imaging techniques, that enable physiology at the resolution of individual synapses to be investigated, have allowed the presynaptic activity level of the synapse to be related to postsynaptic function. This approach has revealed that neuronal activity induces the pre- and post-synapse to be functionally correlated and that subsets of synapses are more susceptible to certain forms of synaptic plasticity. As presynaptic function is often examined in isolation from postsynaptic properties, the effect it has on the post-synapse is not fully understood. However, since postsynaptic receptors at excitatory synapses respond to release of glutamate, it follows that they may be differentially regulated depending on the frequency of its release. Therefore, examining postsynaptic properties in the context of presynaptic function may be a useful way to approach a broad range of questions on synaptic physiology. In this review, we focus on how optophysiology tools have been utilized to study relationships between the pre- and the post-synapse. Multiple imaging techniques have revealed correlations in synaptic properties from the submicron to the dendritic level. Optical tools together with advanced imaging techniques are ideally suited to illuminate this area further, due to the spatial resolution and control they allow.

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.

Sensory Processing at Ribbon Synapses in the Retina and the Cochlea

In recent years, sensory neuroscientists have made major efforts to dissect the structure and function of ribbon synapses which process sensory information in the eye and ear. This review aims to summarize our current understanding of two key aspects of ribbon synapses: 1) their mechanisms of exocytosis and endocytosis and 2) their molecular anatomy and physiology. Our comparison of ribbon synapses in the cochlea and the retina reveals convergent signaling mechanisms, as well as divergent strategies in different sensory systems.

miRNA-Dependent Control of Homeostatic Plasticity in Neurons

Homeostatic plasticity is a form of plasticity in which neurons compensate for changes in neuronal activity through the control of key physiological parameters such as the number and the strength of their synaptic inputs and intrinsic excitability. Recent studies revealed that miRNAs, which are small non-coding RNAs repressing mRNA translation, participate in this process by controlling the translation of multiple effectors such as glutamate transporters, receptors, signaling molecules and voltage-gated ion channels. In this review, we present and discuss the role of miRNAs in both cell-wide and compartmentalized forms of homeostatic plasticity as well as their implication in pathological processes associated with homeostatic failure.

Homeostatic control of Drosophila neuromuscular junction function

The ability to adapt to changing internal and external conditions is a key feature of biological systems. Homeostasis refers to a regulatory process that stabilizes dynamic systems to counteract perturbations. In the nervous system, homeostatic mechanisms control neuronal excitability, neurotransmitter release, neurotransmitter receptors, and neural circuit function. The neuromuscular junction (NMJ) of Drosophila melanogaster has provided a wealth of molecular information about how synapses implement homeostatic forms of synaptic plasticity, with a focus on the transsynaptic, homeostatic modulation of neurotransmitter release. This review examines some of the recent findings from the Drosophila NMJ and highlights questions the field will ponder in coming years.

Global and Multiplexed Dendritic Computations under In Vivo-like Conditions

Dendrites integrate inputs nonlinearly, but it is unclear how these nonlinearities contribute to the overall input-output transformation of single neurons. We developed statistically principled methods using a hierarchical cascade of linear-nonlinear subunits (hLN) to model the dynamically evolving somatic response of neurons receiving complex, in vivo-like spatiotemporal synaptic input patterns. We used the hLN to predict the somatic membrane potential of an in vivo-validated detailed biophysical model of a L2/3 pyramidal cell. Linear input integration with a single global dendritic nonlinearity achieved above 90% prediction accuracy. A novel hLN motif, input multiplexing into parallel processing channels, could improve predictions as much as conventionally used additional layers of local nonlinearities. We obtained similar results in two other cell types. This approach provides a data-driven characterization of a key component of cortical circuit computations: the input-output transformation of neurons during in vivo-like conditions.

Alzheimer's Disease: From Firing Instability to Homeostasis Network Collapse

Alzheimer's disease (AD) starts from pure cognitive impairments and gradually progresses into degeneration of specific brain circuits. Although numerous factors initiating AD have been extensively studied, the common principles underlying the transition from cognitive deficits to neuronal loss remain unknown. Here we describe an evolutionarily conserved, integrated homeostatic network (IHN) that enables functional stability of central neural circuits and safeguards from neurodegeneration. We identify the critical modules comprising the IHN and propose a central role of neural firing in controlling the complex homeostatic network at different spatial scales. We hypothesize that firing instability and impaired synaptic plasticity at early AD stages trigger a vicious cycle, leading to dysregulation of the whole IHN. According to this hypothesis, the IHN collapse represents the major driving force of the transition from early memory impairments to neurodegeneration. Understanding the core elements of homeostatic control machinery, the reciprocal connections between distinct IHN modules, and the role of firing homeostasis in this hierarchy has important implications for physiology and should offer novel conceptual approaches for AD and other neurodegenerative disorders.

Dendritic spines: Revisiting the physiological role

Dendritic spines are small, thin, specialized protrusions from neuronal dendrites, primarily localized in the excitatory synapses. Sophisticated imaging techniques revealed that dendritic spines are complex structures consisting of a dense network of cytoskeletal, transmembrane and scaffolding molecules, and numerous surface receptors. Molecular signaling pathways, mainly Rho and Ras family small GTPases pathways that converge on actin cytoskeleton, regulate the spine morphology and dynamics bi-directionally during synaptic activity. During synaptic plasticity the number and shapes of dendritic spines undergo radical reorganizations. Long-term potentiation (LTP) induction promote spine head enlargement and the formation and stabilization of new spines. Long-term depression (LTD) results in their shrinkage and retraction. Reports indicate increased spine density in the pyramidal neurons of autism and Fragile X syndrome patients and reduced density in the temporal gyrus loci of schizophrenic patients. Post-mortem reports of Alzheimer's brains showed reduced spine number in the hippocampus and cortex. This review highlights the spine morphogenesis process, the activity-dependent structural plasticity and mechanisms by which synaptic activity sculpts the dendritic spines, the structural and functional changes in spines during learning and memory using LTP and LTD processes. It also discusses on spine status in neurodegenerative diseases and the impact of nootropics and neuroprotective agents on the functional restoration of dendritic spines.

Differential role of pre- and postsynaptic neurons in the activity-dependent control of synaptic strengths across dendrites

Neurons receive a large number of active synaptic inputs from their many presynaptic partners across their dendritic tree. However, little is known about how the strengths of individual synapses are controlled in balance with other synapses to effectively encode information while maintaining network homeostasis. This is in part due to the difficulty in assessing the activity of individual synapses with identified afferent and efferent connections for a synapse population in the brain. Here, to gain insights into the basic cellular rules that drive the activity-dependent spatial distribution of pre- and postsynaptic strengths across incoming axons and dendrites, we combine patch-clamp recordings with live-cell imaging of hippocampal pyramidal neurons in dissociated cultures and organotypic slices. Under basal conditions, both pre- and postsynaptic strengths cluster on single dendritic branches according to the identity of the presynaptic neurons, thus highlighting the ability of single dendritic branches to exhibit input specificity. Stimulating a single presynaptic neuron induces input-specific and dendritic branchwise spatial clustering of presynaptic strengths, which accompanies a widespread multiplicative scaling of postsynaptic strengths in dissociated cultures and heterosynaptic plasticity at distant synapses in organotypic slices. Our study provides evidence for a potential homeostatic mechanism by which the rapid changes in global or distant postsynaptic strengths compensate for input-specific presynaptic plasticity.

Multiplex imaging relates quantal glutamate release to presynaptic Ca2+ homeostasis at multiple synapses in situ

Information processing by brain circuits depends on Ca2+-dependent, stochastic release of the excitatory neurotransmitter glutamate. Whilst optical glutamate sensors have enabled detection of synaptic discharges, understanding presynaptic machinery requires simultaneous readout of glutamate release and nanomolar presynaptic Ca2+ in situ. Here, we find that the fluorescence lifetime of the red-shifted Ca2+ indicator Cal-590 is Ca2+-sensitive in the nanomolar range, and employ it in combination with green glutamate sensors to relate quantal neurotransmission to presynaptic Ca2+ kinetics. Multiplexed imaging of individual and multiple synapses in identified axonal circuits reveals that glutamate release efficacy, but not its short-term plasticity, varies with time-dependent fluctuations in presynaptic resting Ca2+ or spike-evoked Ca2+ entry. Within individual presynaptic boutons, we find no nanoscopic co-localisation of evoked presynaptic Ca2+ entry with the prevalent glutamate release site, suggesting loose coupling between the two. The approach enables a better understanding of release machinery at central synapses.

Homeostatic scaling of active zone scaffolds maintains global synaptic strength

Synaptic terminals grow and retract throughout life, yet synaptic strength is maintained within stable physiological ranges. To study this process, we investigated Drosophila endophilin (endo) mutants. Although active zone (AZ) number is doubled in endo mutants, a compensatory reduction in their size homeostatically adjusts global neurotransmitter output to maintain synaptic strength. We find an inverse adaptation in rab3 mutants. Additional analyses using confocal, STED, and electron microscopy reveal a stoichiometric tuning of AZ scaffolds and nanoarchitecture. Axonal transport of synaptic cargo via the lysosomal kinesin adapter Arl8 regulates AZ abundance to modulate global synaptic output and sustain the homeostatic potentiation of neurotransmission. Finally, we find that this AZ scaling can interface with two independent homeostats, depression and potentiation, to remodel AZ structure and function, demonstrating a robust balancing of separate homeostatic adaptations. Thus, AZs are pliable substrates with elastic and modular nanostructures that can be dynamically sculpted to stabilize and tune both local and global synaptic strength.

Homeostatic synaptic plasticity as a metaplasticity mechanism - a molecular and cellular perspective

The molecular mechanisms underlying various types of synaptic plasticity are historically regarded as separate processes involved in independent cellular events. However, recent progress in our molecular understanding of Hebbian and homeostatic synaptic plasticity supports the observation that these two types of plasticity share common cellular events, and are often altered together in neurological diseases. Here, we discuss the emerging concept of homeostatic synaptic plasticity as a metaplasticity mechanism with a focus on cellular signaling processes that enable a direct interaction between Hebbian and homeostatic plasticity. We also identify distinct and shared molecular players involved in these cellular processes that may be explored experimentally in future studies to test the hypothesis that homeostatic synaptic plasticity serves as a metaplasticity mechanism to integrate changes in neuronal activity and support optimal Hebbian learning.

Through synapses to spatial memory maps via a topological model

Various neurophysiological and cognitive functions are based on transferring information between spiking neurons via a complex system of synaptic connections. In particular, the capacity of presynaptic inputs to influence the postsynaptic outputs–the efficacy of the synapses–plays a principal role in all aspects of hippocampal neurophysiology. However, a direct link between the information processed at the level of individual synapses and the animal’s ability to form memories at the organismal level has not yet been fully understood. Here, we investigate the effect of synaptic transmission probabilities on the ability of the hippocampal place cell ensembles to produce a cognitive map of the environment. Using methods from algebraic topology, we find that weakening synaptic connections increase spatial learning times, produce topological defects in the large-scale representation of the ambient space and restrict the range of parameters for which place cell ensembles are capable of producing a map with correct topological structure. On the other hand, the results indicate a possibility of compensatory phenomena, namely that spatial learning deficiencies may be mitigated through enhancement of neuronal activity.

Altered Synaptic Vesicle Release and Ca2+ Influx at Single Presynaptic Terminals of Cortical Neurons in a Knock-in Mouse Model of Huntington's Disease

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by the abnormal expansion of CAG repeats in the huntingtin (HTT) gene, which leads to progressive loss of neurons starting in the striatum and cortex. One possible mechanism for this selective loss of neurons in the early stage of HD is altered neurotransmission at synapses. Despite the recent finding that presynaptic terminals play an important role in HD, neurotransmitter release at synapses in HD remains poorly understood. Here, we measured synaptic vesicle release in real time at single presynaptic terminals during electrical field stimulation. We found the increase in synaptic vesicle release at presynaptic terminals in primary cortical neurons in a knock-in mouse model of HD (zQ175). We also found the increase in Ca²⁺ influx at presynaptic terminals in HD neurons during the electrical stimulation. Consistent with increased Ca²⁺-dependent neurotransmission in HD neurons, the increase in vesicle release and Ca²⁺ influx was rescued with Ca²⁺ chelators or by blocking N-type voltage-gated Ca²⁺ channels, suggesting N-type voltage-gated Ca²⁺ channels play an important role in HD. Taken together, our results suggest that the increased synaptic vesicles release due to increased Ca²⁺ influx at presynaptic terminals in cortical neurons contributes to the selective neurodegeneration of these neurons in early HD and provide a possible therapeutic target.

Computational roles of plastic probabilistic synapses

The probabilistic nature of synaptic transmission has remained enigmatic. However, recent developments have started to shed light on why the brain may rely on probabilistic synapses. Here, we start out by reviewing experimental evidence on the specificity and plasticity of synaptic response statistics. Next, we overview different computational perspectives on the function of plastic probabilistic synapses for constrained, statistical and deep learning. We highlight that all of these views require some form of optimisation of probabilistic synapses, which has recently gained support from theoretical analysis of long-term synaptic plasticity experiments. Finally, we contrast these different computational views and propose avenues for future research. Overall, we argue that the time is ripe for a better understanding of the computational functions of probabilistic synapses.

Homeostatic Plasticity Scales Dendritic Spine Volumes and Changes the Threshold and Specificity of Hebbian Plasticity

Information is encoded in neural networks through changes in synaptic weights. Synaptic learning rules involve a combination of rapid Hebbian plasticity and slower homeostatic synaptic plasticity that regulates neuronal activity through global synaptic scaling. Hebbian and homeostatic plasticity have been extensively investigated, whereas much less is known about their interaction. Here we investigated structural and functional consequences of homeostatic plasticity at dendritic spines of mouse hippocampal neurons. We found that prolonged activity blockade induced spine growth, paralleling synaptic strength increases. Following activity blockade, glutamate uncaging-mediated stimulation at single spines led to size-dependent structural potentiation: smaller spines underwent robust growth, whereas larger spines remained unchanged. Moreover, spines near the stimulated spine exhibited volume changes following homeostatic plasticity, indicating that there was a breakdown of input specificity following homeostatic plasticity. Overall, these findings demonstrate that Hebbian and homeostatic plasticity interact to shape neural connectivity through non-uniform structural plasticity at inputs.

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Chronic activity blockade leads to enlarged hippocampal spines and structural scaling

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Homeostatic plasticity affects subsequent Hebbian plasticity according to size of spines

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Neighbors also grow after potentiation of single spines, compromising input specificity

A Distance-Dependent Distribution of Presynaptic Boutons Tunes Frequency-Dependent Dendritic Integration

How presynaptic inputs and neurotransmitter release dynamics are distributed along a dendritic tree is not well established. Here, we show that presynaptic boutons that form onto basal dendrites of CA1 pyramidal neurons display a decrease in active zone (AZ) size with distance from the soma, resulting in a distance-dependent increase in short-term facilitation. Our findings suggest that the spatial distribution of short-term facilitation serves to compensate for the electrotonic attenuation of subthreshold distal inputs during repeated stimulation and fine-tunes the preferred input frequency of dendritic domains.

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Presynaptic inputs decrease in size with distance along CA1 basal dendrites

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Release probability decreases with distance along basal dendrites

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Short-term facilitation increases with distance along basal dendrites

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Increased synaptic facilitation offsets passive decay and boosts supralinear events

Synaptic Vesicle Endocytosis in Different Model Systems

Neurotransmission in complex animals depends on a choir of functionally distinct synapses releasing neurotransmitters in a highly coordinated manner. During synaptic signaling, vesicles fuse with the plasma membrane to release their contents. The rate of vesicle fusion is high and can exceed the rate at which synaptic vesicles can be re-supplied by distant sources. Thus, local compensatory endocytosis is needed to replenish the synaptic vesicle pools. Over the last four decades, various experimental methods and model systems have been used to study the cellular and molecular mechanisms underlying synaptic vesicle cycle. Clathrin-mediated endocytosis is thought to be the predominant mechanism for synaptic vesicle recycling. However, recent studies suggest significant contribution from other modes of endocytosis, including fast compensatory endocytosis, activity-dependent bulk endocytosis, ultrafast endocytosis, as well as kiss-and-run. Currently, it is not clear whether a universal model of vesicle recycling exist for all types of synapses. It is possible that each synapse type employs a particular mode of endocytosis. Alternatively, multiple modes of endocytosis operate at the same synapse, and the synapse toggles between different modes depending on its activity level. Here we compile review and research articles based on well-characterized model systems: frog neuromuscular junctions, C. elegans neuromuscular junctions, Drosophila neuromuscular junctions, lamprey reticulospinal giant axons, goldfish retinal ribbon synapses, the calyx of Held, and rodent hippocampal synapses. We will compare these systems in terms of their known modes and kinetics of synaptic vesicle endocytosis, as well as the underlying molecular machineries. We will also provide the future development of this field.

Synapse-specific and compartmentalized expression of presynaptic homeostatic potentiation

Postsynaptic compartments can be specifically modulated during various forms of synaptic plasticity, but it is unclear whether this precision is shared at presynaptic terminals. Presynaptic homeostatic plasticity (PHP) stabilizes neurotransmission at the Drosophila neuromuscular junction, where a retrograde enhancement of presynaptic neurotransmitter release compensates for diminished postsynaptic receptor functionality. To test the specificity of PHP induction and expression, we have developed a genetic manipulation to reduce postsynaptic receptor expression at one of the two muscles innervated by a single motor neuron. We find that PHP can be induced and expressed at a subset of synapses, over both acute and chronic time scales, without influencing transmission at adjacent release sites. Further, homeostatic modulations to CaMKII, vesicle pools, and functional release sites are compartmentalized and do not spread to neighboring pre- or post-synaptic structures. Thus, both PHP induction and expression mechanisms are locally transmitted and restricted to specific synaptic compartments.

Everything we think and do is the result of communication between neurons. This communication takes place at junctions called synapses. When two nerve cells or neurons communicate at a synapse, the output terminal of the first cell releases a chemical called a neurotransmitter. This binds to receiver proteins, or receptors, on the second cell. When this communication is interrupted, synapses can adapt to maintain a stable dialogue between them. This can occur in two ways. Either the first neuron starts to release more neurotransmitter from its output terminal, or the second neuron produces extra receptors with which to detect the neurotransmitter.

But how specific are these changes? The brain contains far more synapses than neurons because each neuron can form synapses with many other cells. Can a neuron adjust how much of the neurotransmitter it releases at some of its synapses while leaving the others unchanged?

Li et al. have now addressed this question by studying a special type of synapse that forms between neurons and muscles, known as a neuromuscular junction. At one particular neuromuscular junction in fruit flies, a single neuron splits into two output terminals, each of which forms a synapse with a different muscle. Li et al. show that when the number of neurotransmitter receptors in one of the muscles is artificially reduced, the associated output terminal compensates by increasing its neurotransmitter release. By contrast, the other output terminal remains unaffected.

This suggests that a neuron can induce remarkably specific changes in a subset of its synapses. This discovery paves the way towards identifying the smallest possible unit of change that can occur in the neurons’ ability to communicate. This unit may in turn be the smallest change that can support learning. Such knowledge will help us understand how the nervous system processes and stabilizes information transfer, both in health and after injury or disease.

NeuroMatic: An Integrated Open-Source Software Toolkit for Acquisition, Analysis and Simulation of Electrophysiological Data

Acquisition, analysis and simulation of electrophysiological properties of the nervous system require multiple software packages. This makes it difficult to conserve experimental metadata and track the analysis performed. It also complicates certain experimental approaches such as online analysis. To address this, we developed NeuroMatic, an open-source software toolkit that performs data acquisition (episodic, continuous and triggered recordings), data analysis (spike rasters, spontaneous event detection, curve fitting, stationarity) and simulations (stochastic synaptic transmission, synaptic short-term plasticity, integrate-and-fire and Hodgkin-Huxley-like single-compartment models). The merging of a wide range of tools into a single package facilitates a more integrated style of research, from the development of online analysis functions during data acquisition, to the simulation of synaptic conductance trains during dynamic-clamp experiments. Moreover, NeuroMatic has the advantage of working within Igor Pro, a platform-independent environment that includes an extensive library of built-in functions, a history window for reviewing the user's workflow and the ability to produce publication-quality graphics. Since its original release, NeuroMatic has been used in a wide range of scientific studies and its user base has grown considerably. NeuroMatic version 3.0 can be found at http://www.neuromatic.thinkrandom.com and https://github.com/SilverLabUCL/NeuroMatic.

Long-term potentiation expands information content of hippocampal dentate gyrus synapses

An approach combining signal detection theory and precise 3D reconstructions from serial section electron microscopy (3DEM) was used to investigate synaptic plasticity and information storage capacity at medial perforant path synapses in adult hippocampal dentate gyrus in vivo. Induction of long-term potentiation (LTP) markedly increased the frequencies of both small and large spines measured 30 minutes later. This bidirectional expansion resulted in heterosynaptic counterbalancing of total synaptic area per unit length of granule cell dendrite. Control hemispheres exhibited 6.5 distinct spine sizes for 2.7 bits of storage capacity while LTP resulted in 12.9 distinct spine sizes (3.7 bits). In contrast, control hippocampal CA1 synapses exhibited 4.7 bits with much greater synaptic precision than either control or potentiated dentate gyrus synapses. Thus, synaptic plasticity altered total capacity, yet hippocampal subregions differed dramatically in their synaptic information storage capacity, reflecting their diverse functions and activation histories.