The dendritic branch is the preferred integrative unit for protein synthesis-dependent LTP

Septin 3 regulates memory and L-LTP-dependent extension of endoplasmic reticulum into spines

Transient memories are converted to persistent memories at the synapse and circuit/systems levels. The synapse-level consolidation parallels electrophysiological transition from early- to late-phase long-term potentiation of synaptic transmission (E-/L-LTP). While glutamate signaling upregulations coupled with dendritic spine enlargement are common underpinnings of E-LTP and L-LTP, synaptic mechanisms conferring persistence on L-LTP remain unclear. Here, we show that L-LTP induced at the perforant path-hippocampal dentate gyrus (DG) synapses accompanies cytoskeletal remodeling that involves actin and the septin subunit SEPT3. L-LTP in DG neurons causes fast spine enlargement, followed by SEPT3-dependent smooth endoplasmic reticulum (sER) extension into enlarged spines. Spines containing sER show greater Ca2+ responses upon synaptic input and local synaptic activity. Consistently, Sept3 knockout in mice (Sept3-/-) impairs memory consolidation and causes a scarcity of sER-containing spines. These findings indicate a concept that sER extension into active spines serves as a synaptic basis of memory consolidation.

Structural synaptic signatures of contextual memory retrieval-reactivated hippocampal engram cells

Learning enhances hippocampal engram cell synaptic connectivity which is crucial for engram reactivation and recall to natural cues. Memory retrieval engages only a subset of the learning-activated ensemble, indicating potential differences in synaptic connectivity signatures of reactivated and non-reactivated cells. We probed these differences in structural synaptic connectivity patterns after recent memory retrieval, 72 h after either neutral Context Exploration (CE) or aversive Contextual Fear Conditioning (CFC). Using a combination of eGRASP (enhanced green fluorescent protein (GFP) reconstitution across synaptic partners) and viral-TRAP (targeted recombination in activated populations) to label CA3 synapses onto CA1 engram cells, we investigated differences in spine density, clusters, and morphology between the reactivated and non-reactivated population of the learning ensemble. In doing so, we developed a pipeline for reconstruction and analysis of dendrites and spines, taking nested data structure into account. Our data demonstrate an interplay between reactivation status, context valence or both factors on the number, distribution, and morphology of CA1 engram cell synapses. Despite a lack of differences in spine density, reactivated engram cells encoding an aversive context were characterised by a higher probability of forming spine clusters and a more dynamic spine type signature compared to their non-reactivated counterparts or engram cells encoding a neutral context. Together, our data indicate that the learning-activated ensemble undergoes different trajectories in structural synaptic connectivity during engram refinement.

Compartmentalized dendritic plasticity in the mouse retrosplenial cortex links contextual memories formed close in time

Events occurring close in time are often linked in memory, and recent studies suggest that such memories are encoded by overlapping neuronal ensembles. However, the role of dendritic plasticity mechanisms in linking memories is unknown. Here we show that memory linking is dependent not only on neuronal ensemble overlap in the mouse retrosplenial cortex, but also on branch-specific dendritic allocation mechanisms. The same dendritic segments are preferentially activated by two linked (but not independent) contextual memories, and spine clusters added after each of two linked (but not independent) contextual memories are allocated to the same dendritic segments. Importantly, we show that the reactivation of dendrites activated during the first context exploration is sufficient to link two contextual memories. Our results demonstrate a critical role for localized dendritic plasticity in memory integration and reveal rules governing how linked and independent memories are allocated to dendritic compartments.

Experience-driven competition in neural reorganization after stroke

Behavioural experiences interact with regenerative responses to shape patterns of neural reorganization after stroke. This review is focused on the competitive nature of these behavioural experience effects. Interactions between learning-related plasticity and regenerative reactions have been found to underlie the establishment of new compensatory behaviours and the efficacy of motor rehabilitative training in rodent stroke models. Learning in intact brains depends on competitive and cooperative mechanisms of synaptic plasticity. Synapses are added in response to learning and selectively maintained and strengthened via activity-dependent competition. Long-term memories for experiences that occur closely in time can be weakened or enhanced by competitive or cooperative interactions in the time-dependent process of stabilizing synaptic changes. Rodent stroke model findings suggest that compensatory reliance on the non-paretic hand after stroke can shape and stabilize synaptic reorganization patterns in both hemispheres, to compete with the capacity for experiences of the paretic side to do so. However, the competitive edge of the non-paretic side can be countered by overlapping experiences of the paretic hand, and might even be shifted in a cooperative direction with skilfully coordinated bimanual experience. Advances in the basic understanding of learning-related synaptic competition are helping to inform the basis of experience-dependent variations in stroke outcome.

Time-lapse imaging of identified granule cells in the mouse dentate gyrus after entorhinal lesion in vitro reveals heterogeneous cellular responses to denervation

Denervation of neurons is a network consequence of brain injury. The effects of denervation on neurons can be readily studied in vitro using organotypic slice cultures of entorhinal cortex and hippocampus. Following transection of the entorhino-dentate projection, granule cells (GCs) are denervated and show on average a transient loss of spines on their denervated distal dendrites but not on their non-denervated proximal dendrites. In the present study, we addressed the question how single GCs and their denervated and non-denervated segments react to entorhinal denervation. Local adeno-associated virus (AAV)-injections were employed to transduce dentate GCs with tdTomato and entorhinal projection neurons with EGFP. This made it possible to visualize both innervating entorhinal fibers and their target neurons and to identify dendritic segments located in the "entorhinal" and the "hippocampal" zone of the dentate gyrus. Confocal time-lapse imaging was used to image distal and proximal segments of single GCs after entorhinal denervation. Time-matched non-denervated cultures served as controls. In line with previous reports, average dendritic spine loss was ~30% (2-4 days post-lesion) in the denervated zone. However, individual GCs showed considerable variability in their response to denervation in both layers, and both decreases as well as increases in spine density were observed at the single cell level. Based on the standard deviations and the effect sizes observed in this study, a computer simulation yielded recommendations for the minimum number of neurons that should be analyzed in future studies using the entorhinal in vitro denervation model.

Photomarking Relocalization Technique for Correlated Two-Photon and Electron Microscopy Imaging of Single Stimulated Synapses

Synapses learn and remember by persistent modifications of their internal structures and composition but, due to their small size, it is difficult to observe these changes at the ultrastructural level in real time. Two-photon fluorescence microscopy (2PM) allows time-course live imaging of individual synapses but lacks ultrastructural resolution. Electron microscopy (EM) allows the ultrastructural imaging of subcellular components but cannot detect fluorescence and lacks temporal resolution. Here we describe a combination of procedures designed to achieve the correlated imaging of the same individual synapse under both 2PM and EM. This technique permits the selective stimulation and live imaging of a single dendritic spine and the subsequent localization of the same spine in EM ultrathin serial sections. Landmarks created through a photomarking method based on the 2-photon-induced precipitation of an electrodense compound are used to unequivocally localize the stimulated synapse. This technique was developed to image, for the first time, the ultrastructure of the postsynaptic density in which long-term potentiation was selectively induced just seconds or minutes before, but it can be applied for the study of any biological process that requires the precise relocalization of micron-wide structures for their correlated imaging with 2PM and EM.

Clustering of synaptic engram: Functional and structural basis of memory

Studies on memory engram have demonstrated how experience and learning can be allocated at a neuronal level for centuries. Recently emerging evidence narrowed down further to the synaptic connections and their patterned allocation on dendrites. Notably, groups of synapses within a specific range within dendrites known as 'synaptic clusters' have been revealed in association with learning and memory. Previous investigations have shown that a variety of factors mediated by both presynaptic inputs and postsynaptic dendrites contribute to clustering. Here, we review the neural mechanism of synaptic clustering and its correlation with memory. We highlight the recent findings about the clustering of synaptic engrams and memory formation and discuss future directions.

Maintenance of synaptic plasticity by negative-feedback of synaptic protein elimination: Dynamic modeling of KIBRA- PKM ζ interactions in LTP and memory

Activity-dependent modifications of synaptic efficacies are a cellular substrate of learning and memory. Current theories propose that the long-term maintenance of synaptic efficacies and memory is accomplished via a positive-feedback loop at the level of production of a protein species or a protein state. Here we propose a qualitatively different theoretical framework based on negative-feedback at the level of protein elimination. This theory is motivated by recent experimental findings regarding the binding of P K M ζ and KIBRA, two synaptic proteins involved in maintenance of memory, and on how this binding affects the proteins' degradation. We demonstrate this theoretical framework with two different models, a simple abstract model to explore generic features of such a process, and an experimentally motivated phenomenological model. The results of these models are qualitatively consistent with existing data, and generate novel predictions that could be experimentally tested to further validate or reject the negative-feedback theory.

Branch-specific clustered parallel fiber input controls dendritic computation in Purkinje cells

Most central neurons have intricately branched dendritic trees that integrate massive numbers of synaptic inputs. Intrinsic active mechanisms in dendrites can be heterogeneous and be modulated in a branch-specific way. However, it remains poorly understood how heterogeneous intrinsic properties contribute to processing of synaptic input. We propose the first computational model of the cerebellar Purkinje cell with dendritic heterogeneity, in which each branch is an individual unit and is characterized by its own set of ion channel conductance densities. When simultaneously activating a cluster of parallel fiber synapses, we measure the peak amplitude of a response and observe how changes in P-type calcium channel conductance density shift the dendritic responses from a linear one to a bimodal one including dendritic calcium spikes and vice-versa. These changes relate to the morphology of each branch. We show how dendritic calcium spikes propagate and how Kv4.3 channels block spreading depolarization to nearby branches.

Ion-channel degeneracy and heterogeneities in the emergence of signature physiological characteristics of dentate gyrus granule cells

Complex systems are neither fully determined nor completely random. Biological complex systems, including single neurons, manifest intermediate regimes of randomness that recruit integration of specific combinations of functionally specialized subsystems. Such emergence of biological function provides the substrate for the expression of degeneracy, the ability of disparate combinations of subsystems to yield similar function. Here, we present evidence for the expression of degeneracy in morphologically realistic models of dentate gyrus granule cells (GCs) through functional integration of disparate ion-channel combinations. We performed a 45-parameter randomized search spanning 16 active and passive ion channels, each biophysically constrained by their gating kinetics and localization profiles, to search for valid GC models. Valid models were those that satisfied 17 sub- and suprathreshold cellular-scale electrophysiological measurements from rat GCs. A vast majority (>99%) of the 15,000 random models were not electrophysiologically valid, demonstrating that arbitrarily random ion-channel combinations would not yield GC functions. The 141 valid models (0.94% of 15,000) manifested heterogeneities in and cross-dependencies across local and propagating electrophysiological measurements, which matched with their respective biological counterparts. Importantly, these valid models were widespread throughout the parametric space and manifested weak cross-dependencies across different parameters. These observations together showed that GC physiology could neither be obtained by entirely random ion-channel combinations nor is there an entirely determined single parametric combination that satisfied all constraints. The complexity, the heterogeneities in measurement and parametric spaces, and degeneracy associated with GC physiology should be rigorously accounted for while assessing GCs and their robustness under physiological and pathological conditions.NEW & NOTEWORTHY A recent study from our laboratory had demonstrated pronounced heterogeneities in a set of 17 electrophysiological measurements obtained from a large population of rat hippocampal granule cells. Here, we demonstrate the manifestation of ion-channel degeneracy in a heterogeneous population of morphologically realistic conductance-based granule cell models that were validated against these measurements and their cross-dependencies. Our analyses show that single neurons are complex entities whose functions emerge through intricate interactions among several functionally specialized subsystems.

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

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

Engram mechanisms of memory linking and identity

Memories are thought to be stored in neuronal ensembles referred to as engrams. Studies have suggested that when two memories occur in quick succession, a proportion of their engrams overlap and the memories become linked (in a process known as prospective linking) while maintaining their individual identities. In this Review, we summarize the key principles of memory linking through engram overlap, as revealed by experimental and modelling studies. We describe evidence of the involvement of synaptic memory substrates, spine clustering and non-linear neuronal capacities in prospective linking, and suggest a dynamic somato-synaptic model, in which memories are shared between neurons yet remain separable through distinct dendritic and synaptic allocation patterns. We also bring into focus retrospective linking, in which memories become associated after encoding via offline reactivation, and discuss key temporal and mechanistic differences between prospective and retrospective linking, as well as the potential differences in their cognitive outcomes.

Focal clusters of peri-synaptic matrix contribute to activity-dependent plasticity and memory in mice

Recent findings show that effective integration of novel information in the brain requires coordinated processes of homo- and heterosynaptic plasticity. In this work, we hypothesize that activity-dependent remodeling of the peri-synaptic extracellular matrix (ECM) contributes to these processes. We show that clusters of the peri-synaptic ECM, recognized by CS56 antibody, emerge in response to sensory stimuli, showing temporal and spatial coincidence with dendritic spine plasticity. Using CS56 co-immunoprecipitation of synaptosomal proteins, we identify several molecules involved in Ca2+ signaling, vesicle cycling, and AMPA-receptor exocytosis, thus suggesting a role in long-term potentiation (LTP). Finally, we show that, in the CA1 hippocampal region, the attenuation of CS56 glycoepitopes, through the depletion of versican as one of its main carriers, impairs LTP and object location memory in mice. These findings show that activity-dependent remodeling of the peri-synaptic ECM regulates the induction and consolidation of LTP, contributing to hippocampal-dependent memory.

Altered projection-specific synaptic remodeling and its modification by oxytocin in an idiopathic autism marmoset model

Alterations in the experience-dependent and autonomous elaboration of neural circuits are assumed to underlie autism spectrum disorder (ASD), though it is unclear what synaptic traits are responsible. Here, utilizing a valproic acid-induced ASD marmoset model, which shares common molecular features with idiopathic ASD, we investigate changes in the structural dynamics of tuft dendrites of upper-layer pyramidal neurons and adjacent axons in the dorsomedial prefrontal cortex through two-photon microscopy. In model marmosets, dendritic spine turnover is upregulated, and spines are generated in clusters and survived more often than in control marmosets. Presynaptic boutons in local axons, but not in commissural long-range axons, demonstrate hyperdynamic turnover in model marmosets, suggesting alterations in projection-specific plasticity. Intriguingly, nasal oxytocin administration attenuates clustered spine emergence in model marmosets. Enhanced clustered spine generation, possibly unique to certain presynaptic partners, may be associated with ASD and be a potential therapeutic target.

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.

Local and global predictors of synapse elimination during motor learning

During learning, synaptic connections between excitatory neurons in the brain display considerable dynamism, with new connections being added and old connections eliminated. Synapse elimination offers an opportunity to understand the features of synapses that the brain deems dispensable. However, with limited observations of synaptic activity and plasticity in vivo, the features of synapses subjected to elimination remain poorly understood. Here, we examined the functional basis of synapse elimination in the apical dendrites of L2/3 neurons in the primary motor cortex throughout motor learning. We found no evidence that synapse elimination is facilitated by a lack of activity or other local forms of plasticity. Instead, eliminated synapses display asynchronous activity with nearby synapses, suggesting that functional synaptic clustering is a critical component of synapse survival. In addition, eliminated synapses show delayed activity timing with respect to postsynaptic output. Thus, synaptic inputs that fail to be co-active with their neighboring synapses or are mistimed with neuronal output are targeted for elimination.

VAP spatially stabilizes dendritic mitochondria to locally support synaptic plasticity

Synapses are pivotal sites of plasticity and memory formation. Consequently, synapses are energy consumption hotspots susceptible to dysfunction when their energy supplies are perturbed. Mitochondria are stabilized near synapses via the cytoskeleton and provide the local energy required for synaptic plasticity. However, the mechanisms that tether and stabilize mitochondria to support synaptic plasticity are unknown. We identified proteins exclusively tethering mitochondria to actin near postsynaptic spines. We find that VAP, the vesicle-associated membrane protein-associated protein implicated in amyotrophic lateral sclerosis, stabilizes mitochondria via actin near the spines. To test if the VAP-dependent stable mitochondrial compartments can locally support synaptic plasticity, we used two-photon glutamate uncaging for spine plasticity induction and investigated the induced and adjacent uninduced spines. We find VAP functions as a spatial stabilizer of mitochondrial compartments for up to ~60 min and as a spatial ruler determining the ~30 μm dendritic segment supported during synaptic plasticity.

Control of hippocampal synaptic plasticity by microglia-dendrite interactions depends on genetic context in mouse models of Alzheimer's disease

INTRODUCTION

Human data suggest susceptibility and resilience to features of Alzheimer's disease (AD) such as microglia activation and synaptic dysfunction are under genetic control. However, causal relationships between these processes, and how genomic diversity modulates them remain systemically underexplored in mouse models.

METHODS

AD-vulnerable hippocampal neurons were virally labeled in inbred (C57BL/6J) and wild-derived (PWK/PhJ) APP/PS1 and wild-type mice, and brain microglia depleted from 4 to 8 months of age. Dendrites were assessed for synapse plasticity changes by evaluating spine densities and morphologies.

RESULTS

In C57BL/6J, microglia depletion blocked amyloid-induced synaptic density and morphology changes. At a finer scale, synaptic morphology on individual branches was dependent on microglia-dendrite physical interactions. Conversely, synapses from PWK/PhJ mice showed remarkable stability in response to amyloid, and no evidence of microglia contact-dependent changes on dendrites.

DISCUSSION

These results demonstrate that microglia-dependent synaptic alterations in specific AD-vulnerable projection pathways are differentially controlled by genetic context.

Mapping memories: pulse-chase labeling reveals AMPA receptor dynamics during memory formation

A tool to map changes in synaptic strength during a defined time window could provide powerful insights into the mechanisms governing learning and memory. We developed a technique, Extracellular Protein Surface Labeling in Neurons (EPSILON), to map α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) insertion in vivo by pulse-chase labeling of surface AMPARs with membrane-impermeable dyes. This approach allows for single-synapse resolution maps of plasticity in genetically targeted neurons during memory formation. We investigated the relationship between synapse-level and cell-level memory encodings by mapping synaptic plasticity and cFos expression in hippocampal CA1 pyramidal cells upon contextual fear conditioning (CFC). We observed a strong correlation between synaptic plasticity and cFos expression, suggesting a synaptic mechanism for the association of cFos expression with memory engrams. The EPSILON technique is a useful tool for mapping synaptic plasticity and may be extended to investigate trafficking of other transmembrane proteins.

Making time and space for calcium control of neuron activity

Calcium directly controls or indirectly regulates numerous functions that are critical for neuronal network activity. Intracellular calcium concentration is tightly regulated by numerous molecular mechanisms because spatial domains and temporal dynamics (not just peak amplitude) are critical for calcium control of synaptic plasticity and ion channel activation, which in turn determine neuron spiking activity. The computational models investigating calcium control are valuable because experiments achieving high spatial and temporal resolution simultaneously are technically unfeasible. Simulations of calcium nanodomains reveal that specific calcium sources can couple to specific calcium targets, providing a mechanism to determine the direction of synaptic plasticity. Cooperativity of calcium domains opposes specificity, suggesting that the dendritic branch might be the preferred computational unit of the neuron.

Cell-type-specific optogenetic stimulation of the locus coeruleus induces slow-onset potentiation and enhances everyday memory in rats

Memory formation is typically divided into phases associated with encoding, storage, consolidation, and retrieval. The neural determinants of these phases are thought to differ. This study first investigated the impact of the experience of novelty in rats incurred at a different time, before or after, the precise moment of memory encoding. Memory retention was enhanced. Optogenetic activation of the locus coeruleus mimicked this enhancement induced by novelty, both when given before and after the moment of encoding. Optogenetic activation of the locus coeruleus also induced a slow-onset potentiation of field potentials in area CA1 of the hippocampus evoked by CA3 stimulation. Despite the locus coeruleus being considered a primarily noradrenergic area, both effects of such stimulation were blocked by the dopamine D1/D5 receptor antagonist SCH 23390. These findings substantiate and enrich the evidence implicating the locus coeruleus in cellular aspects of memory consolidation in hippocampus.

Synaptic memory and CaMKII

Ca2+/calmodulin-dependent protein kinase II (CaMKII) and long-term potentiation (LTP) were discovered within a decade of each other and have been inextricably intertwined ever since. However, like many marriages, it has had its up and downs. Based on the unique biochemical properties of CaMKII, it was proposed as a memory molecule before any physiological linkage was made to LTP. However, as reviewed here, the convincing linkage of CaMKII to synaptic physiology and behavior took many decades. New technologies were critical in this journey, including in vitro brain slices, mouse genetics, single-cell molecular genetics, pharmacological reagents, protein structure, and two-photon microscopy, as were new investigators attracted by the exciting challenge. This review tracks this journey and assesses the state of this marriage 40 years on. The collective literature impels us to propose a relatively simple model for synaptic memory involving the following steps that drive the process: 1) Ca2+ entry through N-methyl-d-aspartate (NMDA) receptors activates CaMKII. 2) CaMKII undergoes autophosphorylation resulting in constitutive, Ca2+-independent activity and exposure of a binding site for the NMDA receptor subunit GluN2B. 3) Active CaMKII translocates to the postsynaptic density (PSD) and binds to the cytoplasmic C-tail of GluN2B. 4) The CaMKII-GluN2B complex initiates a structural rearrangement of the PSD that may involve liquid-liquid phase separation. 5) This rearrangement involves the PSD-95 scaffolding protein, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs), and their transmembrane AMPAR-regulatory protein (TARP) auxiliary subunits, resulting in an accumulation of AMPARs in the PSD that underlies synaptic potentiation. 6) The stability of the modified PSD is maintained by the stability of the CaMKII-GluN2B complex. 7) By a process of subunit exchange or interholoenzyme phosphorylation CaMKII maintains synaptic potentiation in the face of CaMKII protein turnover. There are many other important proteins that participate in enlargement of the synaptic spine or modulation of the steps that drive and maintain the potentiation. In this review we critically discuss the data underlying each of the steps. As will become clear, some of these steps are more firmly grounded than others, and we provide suggestions as to how the evidence supporting these steps can be strengthened or, based on the new data, be replaced. Although the journey has been a long one, the prospect of having a detailed cellular and molecular understanding of learning and memory is at hand.

Homosynaptic plasticity induction causes heterosynaptic changes at the unstimulated neighbors in an induction pattern and location-specific manner

Dendritic spines are highly dynamic structures whose structural and functional fluctuations depend on multiple factors. Changes in synaptic strength are not limited to synapses directly involved in specific activity patterns. Unstimulated clusters of neighboring spines in and around the site of stimulation can also undergo alterations in strength. Usually, when plasticity is induced at single dendritic spines with glutamate uncaging, neighboring spines do not show any significant structural fluctuations. Here, using two-photon imaging and glutamate uncaging at single dendritic spines of hippocampal pyramidal neurons, we show that structural modifications at unstimulated neighboring spines occur and are a function of the temporal pattern of the plasticity-inducing stimulus. Further, the relative location of the unstimulated neighbors within the local dendritic segment correlates with the extent of heterosynaptic plasticity that is observed. These findings indicate that naturalistic patterns of activity at single spines can shape plasticity at nearby clusters of synapses, and may play a role in priming local inputs for further modifications.

Novelty-induced memory consolidation is accompanied by increased Agap3 transcription: a cross-species study

Novelty-induced memory consolidation is a well-established phenomenon that depends on the activation of a locus coeruleus-hippocampal circuit. It is associated with the expression of activity-dependent genes that may mediate initial or cellular memory consolidation. Several genes have been identified to date, however, to fully understand the mechanisms of memory consolidation, additional candidates must be identified. In this cross-species study, we used a contextual novelty-exploration paradigm to identify changes in gene expression in the dorsal hippocampus of both mice and rats. We found that changes in gene expression following contextual novelty varied between the two species, with 9 genes being upregulated in mice and 3 genes in rats. Comparison across species revealed that ArfGAP with a GTPase domain, an ankyrin repeat and PH domain 3 (Agap3) was the only gene being upregulated in both, suggesting a potentially conserved role for Agap3. AGAP3 is known to regulate α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA)-type glutamate receptor trafficking in the synapse, which suggests that increased transcription of Agap3 may be involved in maintaining functional plasticity. While we identified several genes affected by contextual novelty exploration, we were unable to fully reverse these changes using SCH 23390, a dopamine D1/D5 receptor antagonist. Further research on the role of AGAP3 in novelty-induced memory consolidation could lead to better understanding of this process and guide future research.

Linking spontaneous and stimulated spine dynamics

Our brains continuously acquire and store memories through synaptic plasticity. However, spontaneous synaptic changes can also occur and pose a challenge for maintaining stable memories. Despite fluctuations in synapse size, recent studies have shown that key population-level synaptic properties remain stable over time. This raises the question of how local synaptic plasticity affects the global population-level synaptic size distribution and whether individual synapses undergoing plasticity escape the stable distribution to encode specific memories. To address this question, we (i) studied spontaneously evolving spines and (ii) induced synaptic potentiation at selected sites while observing the spine distribution pre- and post-stimulation. We designed a stochastic model to describe how the current size of a synapse affects its future size under baseline and stimulation conditions and how these local effects give rise to population-level synaptic shifts. Our study offers insights into how seemingly spontaneous synaptic fluctuations and local plasticity both contribute to population-level synaptic dynamics.

The dendritic engram

Accumulating evidence from a wide range of studies, including behavioral, cellular, molecular and computational findings, support a key role of dendrites in the encoding and recall of new memories. Dendrites can integrate synaptic inputs in non-linear ways, provide the substrate for local protein synthesis and facilitate the orchestration of signaling pathways that regulate local synaptic plasticity. These capabilities allow them to act as a second layer of computation within the neuron and serve as the fundamental unit of plasticity. As such, dendrites are integral parts of the memory engram, namely the physical representation of memories in the brain and are increasingly studied during learning tasks. Here, we review experimental and computational studies that support a novel, dendritic view of the memory engram that is centered on non-linear dendritic branches as elementary memory units. We highlight the potential implications of dendritic engrams for the learning and memory field and discuss future research directions.

The temporal pattern of synaptic activation determines the longevity of structural plasticity at dendritic spines

Learning is thought to involve physiological and structural changes at individual synapses. Synaptic plasticity has predominantly been studied using regular stimulation patterns, but neuronal activity in the brain normally follows a Poisson distribution. We used two-photon imaging and glutamate uncaging to investigate the structural plasticity of single dendritic spines using naturalistic activation patterns sampled from a Poisson distribution. We showed that naturalistic activation patterns elicit structural plasticity that is both NMDAR and protein synthesis-dependent. Furthermore, we uncovered that the longevity of structural plasticity is dependent on the temporal structure of the naturalistic pattern. Finally, we found that during the delivery of the naturalistic activity, spines underwent rapid structural growth that predicted the longevity of plasticity. This was not observed with regularly spaced activity. These data reveal that different temporal organizations of the same number of synaptic stimulations can produce rather distinct short and long-lasting structural plasticity.

LOV2-based photoactivatable CaMKII and its application to single synapses: Local Optogenetics

Optogenetic techniques offer a high spatiotemporal resolution to manipulate cellular activity. For instance, Channelrhodopsin-2 with global light illumination is the most widely used to control neuronal activity at the cellular level. However, the cellular scale is much larger than the diffraction limit of light (<1 μm) and does not fully exploit the features of the "high spatial resolution" of optogenetics. For instance, until recently, there were no optogenetic methods to induce synaptic plasticity at the level of single synapses. To address this, we developed an optogenetic tool named photoactivatable CaMKII (paCaMKII) by fusing a light-sensitive domain (LOV2) to CaMKIIα, which is a protein abundantly expressed in neurons of the cerebrum and hippocampus and essential for synaptic plasticity. Combining photoactivatable CaMKII with two-photon excitation, we successfully activated it in single spines, inducing synaptic plasticity (long-term potentiation) in hippocampal neurons. We refer to this method as "Local Optogenetics", which involves the local activation of molecules and measurement of cellular responses. In this review, we will discuss the characteristics of LOV2, the recent development of its derivatives, and the development and application of paCaMKII.

Synaptic turnover promotes efficient learning in bio-realistic spiking neural networks

While artificial machine learning systems achieve superhuman performance in specific tasks such as language processing, image and video recognition, they do so use extremely large datasets and huge amounts of power. On the other hand, the brain remains superior in several cognitively challenging tasks while operating with the energy of a small lightbulb. We use a biologically constrained spiking neural network model to explore how the neural tissue achieves such high efficiency and assess its learning capacity on discrimination tasks. We found that synaptic turnover, a form of structural plasticity, which is the ability of the brain to form and eliminate synapses continuously, increases both the speed and the performance of our network on all tasks tested. Moreover, it allows accurate learning using a smaller number of examples. Importantly, these improvements are most significant under conditions of resource scarcity, such as when the number of trainable parameters is halved and when the task difficulty is increased. Our findings provide new insights into the mechanisms that underlie efficient learning in the brain and can inspire the development of more efficient and flexible machine learning algorithms.

Pin1 and Alzheimer's disease

Alzheimer's disease (AD) is an immense and growing public health crisis. Despite over 100 years of investigation, the etiology remains elusive and therapy ineffective. Despite current gaps in knowledge, recent studies have identified dysfunction or loss-of-function of Pin1, a unique cis-trans peptidyl prolyl isomerase, as an important step in AD pathogenesis. Here I review the functionality of Pin1 and its role in neurodegeneration.

Computational insights into mRNA and protein dynamics underlying synaptic plasticity rules

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

Hippocampal engram networks for fear memory recruit new synapses and modify pre-existing synapses in vivo

As basic units of neural networks, ensembles of synapses underlie cognitive functions such as learning and memory. These synaptic engrams show elevated synaptic density among engram cells following contextual fear memory formation. Subsequent analysis of the CA3-CA1 engram synapse revealed larger spine sizes, as the synaptic connectivity correlated with the memory strength. Here, we elucidate the synapse dynamics between CA3 and CA1 by tracking identical synapses at multiple time points by adapting two-photon microscopy and dual-eGRASP technique in vivo. After memory formation, synaptic connections between engram populations are enhanced in conjunction with synaptogenesis within the hippocampal network. However, extinction learning specifically correlated with the disappearance of CA3 engram to CA1 engram (E-E) synapses. We observed "newly formed" synapses near pre-existing synapses, which clustered CA3-CA1 engram synapses after fear memory formation. Overall, we conclude that dynamics at CA3 to CA1 E-E synapses are key sites for modification during fear memory states.

Generalized extinction of fear memory depends on co-allocation of synaptic plasticity in dendrites

Memories can be modified by new experience in a specific or generalized manner. Changes in synaptic connections are crucial for memory storage, but it remains unknown how synaptic changes associated with different memories are distributed within neuronal circuits and how such distributions affect specific or generalized modification by novel experience. Here we show that fear conditioning with two different auditory stimuli (CS) and footshocks (US) induces dendritic spine elimination mainly on different dendritic branches of layer 5 pyramidal neurons in the mouse motor cortex. Subsequent fear extinction causes CS-specific spine formation and extinction of freezing behavior. In contrast, spine elimination induced by fear conditioning with >2 different CS-USs often co-exists on the same dendritic branches. Fear extinction induces CS-nonspecific spine formation and generalized fear extinction. Moreover, activation of somatostatin-expressing interneurons increases the occurrence of spine elimination induced by different CS-USs on the same dendritic branches and facilitates the generalization of fear extinction. These findings suggest that specific or generalized modification of existing memories by new experience depends on whether synaptic changes induced by previous experiences are segregated or co-exist at the level of individual dendritic branches.

Unraveling the mysteries of dendritic spine dynamics: Five key principles shaping memory and cognition

Recent research extends our understanding of brain processes beyond just action potentials and chemical transmissions within neural circuits, emphasizing the mechanical forces generated by excitatory synapses on dendritic spines to modulate presynaptic function. From in vivo and in vitro studies, we outline five central principles of synaptic mechanics in brain function: P1: Stability - Underpinning the integral relationship between the structure and function of the spine synapses. P2: Extrinsic dynamics - Highlighting synapse-selective structural plasticity which plays a crucial role in Hebbian associative learning, distinct from pathway-selective long-term potentiation (LTP) and depression (LTD). P3: Neuromodulation - Analyzing the role of G-protein-coupled receptors, particularly dopamine receptors, in time-sensitive modulation of associative learning frameworks such as Pavlovian classical conditioning and Thorndike's reinforcement learning (RL). P4: Instability - Addressing the intrinsic dynamics crucial to memory management during continual learning, spotlighting their role in "spine dysgenesis" associated with mental disorders. P5: Mechanics - Exploring how synaptic mechanics influence both sides of synapses to establish structural traces of short- and long-term memory, thereby aiding the integration of mental functions. We also delve into the historical background and foresee impending challenges.

BitBrain and Sparse Binary Coincidence (SBC) memories: Fast, robust learning and inference for neuromorphic architectures

We present an innovative working mechanism (the SBC memory) and surrounding infrastructure (BitBrain) based upon a novel synthesis of ideas from sparse coding, computational neuroscience and information theory that enables fast and adaptive learning and accurate, robust inference. The mechanism is designed to be implemented efficiently on current and future neuromorphic devices as well as on more conventional CPU and memory architectures. An example implementation on the SpiNNaker neuromorphic platform has been developed and initial results are presented. The SBC memory stores coincidences between features detected in class examples in a training set, and infers the class of a previously unseen test example by identifying the class with which it shares the highest number of feature coincidences. A number of SBC memories may be combined in a BitBrain to increase the diversity of the contributing feature coincidences. The resulting inference mechanism is shown to have excellent classification performance on benchmarks such as MNIST and EMNIST, achieving classification accuracy with single-pass learning approaching that of state-of-the-art deep networks with much larger tuneable parameter spaces and much higher training costs. It can also be made very robust to noise. BitBrain is designed to be very efficient in training and inference on both conventional and neuromorphic architectures. It provides a unique combination of single-pass, single-shot and continuous supervised learning; following a very simple unsupervised phase. Accurate classification inference that is very robust against imperfect inputs has been demonstrated. These contributions make it uniquely well-suited for edge and IoT applications.

Logistics of neuronal protein turnover: Numbers and mechanisms

Research in the past twenty years or so has revealed that neurons synthesize and degrade proteins at their synapses to enable synaptic proteome remodelling on demand and in real-time. Here we provide a quantitative overview of the decentralized neuronal protein-turnover logistics. We first analyse the huge neuronal protein turnover demand that arises from subcellular compartments outside the cell body, followed by an overview of key quantities and modulation strategies in neuronal protein turnover logistics. In the end, we briefly review recent progress in neuronal local protein synthesis and summarize diverse protein-degradation mechanisms that are found near synapses.

Synaptic memory survives molecular turnover

Activation of Ca²⁺/calmodulin-dependent kinase II (CaMKII) plays a critical role in long-term potentiation (LTP), a long accepted cellular model for learning and memory. However, how LTP and memories survive the turnover of synaptic proteins, particularly CaMKII, remains a mystery. Here, we take advantage of the finding that constitutive Ca²⁺-independent CaMKII activity, acquired prior to slice preparation, provides a lasting memory trace at synapses. In slice culture, this persistent CaMKII activity, in the absence of Ca²⁺ stimulation, remains stable over a 2-wk period, well beyond the turnover of CaMKII protein. We propose that the nascent CaMKII protein present at 2 wk acquired its activity from preexisting active CaMKII molecules, which transferred their activity to newly synthesized CaMKII molecules and thus maintain the memory in the face of protein turnover.

Synaptic Plasticity Is Predicted by Spatiotemporal Firing Rate Patterns and Robust to In Vivo-like Variability

Synaptic plasticity, the experience-induced change in connections between neurons, underlies learning and memory in the brain. Most of our understanding of synaptic plasticity derives from in vitro experiments with precisely repeated stimulus patterns; however, neurons exhibit significant variability in vivo during repeated experiences. Further, the spatial pattern of synaptic inputs to the dendritic tree influences synaptic plasticity, yet is not considered in most synaptic plasticity rules. Here, we investigate how spatiotemporal synaptic input patterns produce plasticity with in vivo-like conditions using a data-driven computational model with a plasticity rule based on calcium dynamics. Using in vivo spike train recordings as inputs to different size clusters of spines, we show that plasticity is strongly robust to trial-to-trial variability of spike timing. In addition, we derive general synaptic plasticity rules describing how spatiotemporal patterns of synaptic inputs control the magnitude and direction of plasticity. Synapses that strongly potentiated have greater firing rates and calcium concentration later in the trial, whereas strongly depressing synapses have hiring firing rates early in the trial. The neighboring synaptic activity influences the direction and magnitude of synaptic plasticity, with small clusters of spines producing the greatest increase in synaptic strength. Together, our results reveal that calcium dynamics can unify diverse plasticity rules and reveal how spatiotemporal firing rate patterns control synaptic plasticity.

A computational model to explore how temporal stimulation patterns affect synapse plasticity

Plasticity-related proteins (PRPs), which are synthesized in a synapse activation-dependent manner, are shared by multiple synapses to a limited spatial extent for a specific period. In addition, stimulated synapses can utilize shared PRPs through synaptic tagging and capture (STC). In particular, the phenomenon by which short-lived early long-term potentiation is transformed into long-lived late long-term potentiation using shared PRPs is called “late-associativity,” which is the underlying principle of “cluster plasticity.” We hypothesized that the competitive capture of PRPs by multiple synapses modulates late-associativity and affects the fate of each synapse in terms of whether it is integrated into a synapse cluster. We tested our hypothesis by developing a computational model to simulate STC, late-associativity, and the competitive capture of PRPs. The experimental results obtained using the model revealed that the number of competing synapses, timing of stimulation to each synapse, and basal PRP level in the dendritic compartment altered the effective temporal window of STC and influenced the conditions under which late-associativity occurs. Furthermore, it is suggested that the competitive capture of PRPs results in the selection of synapses to be integrated into a synapse cluster via late-associativity.

Tag and capture: how salient experiences target and rescue nearby events in memory

The long-term fate of a memory is not exclusively determined by the events occurring at the moment of encoding. Research at the cellular, circuit, and behavioral levels is beginning to reveal how neurochemical activations in the moments surrounding an event can retroactively and proactively rescue weak memory for seemingly mundane experiences. We review emerging evidence showing enhancement of weakly formed memories encoded minutes to hours before or after a related motivationally relevant experience. We discuss proposed neurobiological mechanisms for strengthening weak memories formed in temporal proximity to a strong event, and how this knowledge could be leveraged to improve memory for information that is prone to forgetting.

An interactive time series image analysis software for dendritic spines

Live fluorescence imaging has demonstrated the dynamic nature of dendritic spines, with changes in shape occurring both during development and in response to activity. The structure of a dendritic spine correlates with its functional efficacy. Learning and memory studies have shown that a great deal of the information stored by a neuron is contained in the synapses. High precision tracking of synaptic structures can give hints about the dynamic nature of memory and help us understand how memories evolve both in biological and artificial neural networks. Experiments that aim to investigate the dynamics behind the structural changes of dendritic spines require the collection and analysis of large time-series datasets. In this paper, we present an open-source software called SpineS for automatic longitudinal structural analysis of dendritic spines with additional features for manual intervention to ensure optimal analysis. We have tested the algorithm on in-vitro, in-vivo, and simulated datasets to demonstrate its performance in a wide range of possible experimental scenarios.

Conditions for Synaptic Specificity during the Maintenance Phase of Synaptic Plasticity

Activity-dependent modifications of synaptic efficacies are a cellular substrate of learning and memory. Experimental evidence shows that these modifications are synapse specific and that the long-lasting effects are associated with the sustained increase in concentration of specific proteins like PKMζ However, such proteins are likely to diffuse away from their initial synaptic location and spread out to neighboring synapses, potentially compromising synapse specificity. In this article, we address the issue of synapse specificity during memory maintenance. Assuming that the long-term maintenance of synaptic plasticity is accomplished by a molecular switch, we carry out analytical calculations and perform simulations using the reaction-diffusion package in NEURON to determine the limits of synapse specificity during maintenance. Moreover, we explore the effects of the diffusion and degradation rates of proteins and of the geometrical characteristics of dendritic spines on synapse specificity. We conclude that the necessary conditions for synaptic specificity during maintenance require that molecular switches reside in dendritic spines. The requirement for synaptic specificity when the molecular switch resides in spines still imposes strong limits on the diffusion and turnover of rates of maintenance molecules, as well as on the morphologic properties of synaptic spines. These constraints are quite general and apply to most existing models suggested for maintenance. The parameter values can be experimentally evaluated, and if they do not fit the appropriate predicted range, the validity of this class of maintenance models would be challenged.

A Proposed Role for Interactions between Argonautes, miRISC, and RNA Binding Proteins in the Regulation of Local Translation in Neurons and Glia

The first evidence of local translation in the CNS appeared nearly 40 years ago, when electron microscopic studies showed polyribosomes localized to the base of dendritic spines. Since then, local translation has been established as an important regulatory mechanism for gene expression in polarized or functionally compartmentalized cells. While much attention has been placed on characterizing the local transcriptome and regulatory "grammar" directing mRNA localization in neurons and glia, less is understood about how these cells subsequently de-repress mRNA translation in their peripheral processes to produce a rapid translational response to stimuli. MicroRNA-mediated translation regulation offers a possible solution to this question. Not only do miRNAs provide the specificity needed for targeted gene regulation, but association and dynamic interactions between Argonaute (AGO) with sequence-specific RNA-binding proteins may provide a molecular switch to allow for de-repression of target mRNAs. Here, we review the expression and activity of different AGO proteins in miRNA-induced silencing complexes in neurons and glia and discuss known pathways of miRNA-mediated regulation, including activity-dependent pre-miRNA maturation in dendrites. We further detail work on AGO and RNA-binding protein interactions that allow for the reversal of miRNA-mediated translational silencing, and we propose a model for how intercellular communication may play a role in the regulation of local translation.

Learning Higher-Order Transitional Probabilities in Nonhuman Primates

The extraction of cooccurrences between two events, A and B, is a central learning mechanism shared by all species capable of associative learning. Formally, the cooccurrence of events A and B appearing in a sequence is measured by the transitional probability (TP) between these events, and it corresponds to the probability of the second stimulus given the first (i.e., p(B|A)). In the present study, nonhuman primates (Guinea baboons, Papio papio) were exposed to a serial version of the XOR (i.e., exclusive-OR), in which they had to process sequences of three stimuli: A, B, and C. In this manipulation, first-order TPs (i.e., AB and BC) were uninformative due to their transitional probabilities being equal to .5 (i.e., p(B|A) = p(C|B) = .5), while second-order TPs were fully predictive of the upcoming stimulus (i.e., p(C|AB) = 1). In Experiment 1, we found that baboons were able to learn second-order TPs, while no learning occurred on first-order TPs. In Experiment 2, this pattern of results was replicated, and a final test ruled out an alternative interpretation in terms of proximity to the reward. These results indicate that a nonhuman primate species can learn a nonlinearly separable problem such as the XOR. They also provide fine-grained empirical data to test models of statistical learning on the interaction between the learning of different orders of TPs. Recent bioinspired models of associative learning are also introduced as promising alternatives to the modeling of statistical learning mechanisms.

A Simplified Plasticity Model Based on Synaptic Tagging and Capture Theory: Simplified STC

The formation and consolidation of memory play a vital role for survival in an ever-changing environment. In the brain, the change and stabilization of potentiated and depressed synapses are the neural basis of memory formation and maintenance. These changes can be induced by rather short stimuli (only a few seconds or even less) but should then be stable for months or years. Recently, the neural mechanism of conversion from rapid change during the early phase of synaptic plasticity into a stable memory trace in the late phase of synaptic plasticity is more and more clear at the protein and molecular levels, among which synaptic tagging and capture (STC) theory is one of the most popular theories. According to the STC theory, the change and stabilization of synaptic efficiency mainly depend on three processes related to calcium concentration, including synaptic tagging, synthesis of plasticity-related product (PRP), and the capture of PRP by tagged synapse. Based on the STC theory, several computational models are proposed. However, these models hardly take simplicity and biological interpretability into account simultaneously. Here, we propose a simplified STC (SM-STC) model to address this issue. In the SM-STC model, the concentration of calcium ion in each neuronal compartment and synapse is first calculated, and then the tag state of synapse and PRP are updated, and the coupling effect of tagged synapse and PRP is further considered to determine the plasticity state of the synapse, either potentiation or depression. We simulated the Schaffer collaterals pathway of the hippocampus targeting a multicompartment CA1 neuron for several hours of biological time. The results show that the SM-STC model can produce a broad range of experimental phenomena known in the physiological experiments, including long-term potentiation induced by high-frequency stimuli, long-term depression induced by low-frequency stimuli, and cross-capture with two stimuli separated by a delay. Thus, the SM-STC model proposed in this study provides an effective learning rule for brain-like computation on the premise of ensuring biological plausibility and computational efficiency.

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

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

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LTP of individual dendritic spines causes iLTD at neighboring GABAergic synapses

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

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

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iLTD is associated with reduced gephyrin clustering and increased GABAAR mobility

Chronic neuronal excitation leads to dual metaplasticity in the signaling for structural long-term potentiation

Synaptic plasticity is long-lasting changes in synaptic currents and structure. When neurons are exposed to signals that induce aberrant neuronal excitation, they increase the threshold for the induction of long-term potentiation (LTP), known as metaplasticity. However, the metaplastic regulation of structural LTP (sLTP) remains unclear. We investigate glutamate uncaging/photoactivatable (pa)CaMKII-dependent sLTP induction in hippocampal CA1 neurons after chronic neuronal excitation by GABA_A receptor antagonists. We find that the neuronal excitation decreases the glutamate uncaging-evoked Ca²⁺ influx mediated by GluN2B-containing NMDA receptors and suppresses sLTP induction. In addition, single-spine optogenetic stimulation using paCaMKII indicates the suppression of CaMKII signaling. While the inhibition of Ca²⁺ influx is protein synthesis independent, the paCaMKII-induced sLTP suppression depends on it. Our findings demonstrate that chronic neuronal excitation suppresses sLTP in two independent ways (i.e., dual inhibition of Ca²⁺ influx and CaMKII signaling). This dual inhibition mechanism may contribute to robust neuronal protection in excitable environments.

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

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

Sleep promotes the formation of dendritic filopodia and spines near learning-inactive existing spines

Changes in synaptic connections are believed to underlie long-term memory storage. Previous studies have suggested that sleep is important for synapse formation after learning, but how sleep is involved in the process of synapse formation remains unclear. To address this question, we used transcranial two-photon microscopy to investigate the effect of postlearning sleep on the location of newly formed dendritic filopodia and spines of layer 5 pyramidal neurons in the primary motor cortex of adolescent mice. We found that newly formed filopodia and spines were partially clustered with existing spines along individual dendritic segments 24 h after motor training. Notably, posttraining sleep was critical for promoting the formation of dendritic filopodia and spines clustered with existing spines within 8 h. A fraction of these filopodia was converted into new spines and contributed to clustered spine formation 24 h after motor training. This sleep-dependent spine formation via filopodia was different from retraining-induced new spine formation, which emerged from dendritic shafts without prior presence of filopodia. Furthermore, sleep-dependent new filopodia and spines tended to be formed away from existing spines that were active at the time of motor training. Taken together, these findings reveal a role of postlearning sleep in regulating the number and location of new synapses via promoting filopodial formation.