Dendritic sodium spikes are required for long-term potentiation at distal synapses on hippocampal pyramidal neurons

The role of astrocytes from synaptic to non-synaptic plasticity

Information storage and transfer in the brain require a high computational power. Neuronal network display various local or global mechanisms to allow information storage and transfer in the brain. From synaptic to intrinsic plasticity, the rules of input-output function modulation have been well characterized in neurons. In the past years, astrocytes have been suggested to increase the computational power of the brain and we are only just starting to uncover their role in information processing. Astrocytes maintain a close bidirectional communication with neurons to modify neuronal network excitability, transmission, axonal conduction, and plasticity through various mechanisms including the release of gliotransmitters or local ion homeostasis. Astrocytes have been significantly studied in the context of long-term or short-term synaptic plasticity, but this is not the only mechanism involved in memory formation. Plasticity of intrinsic neuronal excitability also participates in memory storage through regulation of voltage-gated ion channels or axonal morphological changes. Yet, the contribution of astrocytes to these other forms of non-synaptic plasticity remains to be investigated. In this review, we summarized the recent advances on the role of astrocytes in different forms of plasticity and discuss new directions and ideas to be explored regarding astrocytes-neuronal communication and regulation of plasticity.

Multi-scale modelling of location- and frequency-dependent synaptic plasticity induced by transcranial magnetic stimulation in the dendrites of pyramidal neurons

Background

Repetitive transcranial magnetic stimulation (rTMS) induces long-term changes of synapses, but the mechanisms behind these modifications are not fully understood. Although there has been progress in the development of multi-scale modeling tools, no comprehensive module for simulating rTMS-induced synaptic plasticity in biophysically realistic neurons exists..

Objective

We developed a modelling framework that allows the replication and detailed prediction of long-term changes of excitatory synapses in neurons stimulated by rTMS.

Methods

We implemented a voltage-dependent plasticity model that has been previously established for simulating frequency-, time-, and compartment-dependent spatio-temporal changes of excitatory synapses in neuronal dendrites. The plasticity model can be incorporated into biophysical neuronal models and coupled to electrical field simulations.

Results

We show that the plasticity modelling framework replicates long-term potentiation (LTP)-like plasticity in hippocampal CA1 pyramidal cells evoked by 10-Hz repetitive magnetic stimulation (rMS). This plasticity was strongly distance dependent and concentrated at the proximal synapses of the neuron. We predicted a decrease in the plasticity amplitude for 5 Hz and 1 Hz protocols with decreasing frequency. Finally, we successfully modelled plasticity in distal synapses upon local electrical theta-burst stimulation (TBS) and predicted proximal and distal plasticity for rMS TBS. Notably, the rMS TBS-evoked synaptic plasticity exhibited robust facilitation by dendritic spikes and low sensitivity to inhibitory suppression.

Conclusion

The plasticity modelling framework enables precise simulations of LTP-like cellular effects with high spatio-temporal resolution, enhancing the efficiency of parameter screening and the development of plasticity-inducing rTMS protocols.

A voltage-based Event-Timing-Dependent Plasticity rule accounts for LTP subthreshold and suprathreshold for dendritic spikes in CA1 pyramidal neurons

Long-term potentiation (LTP) is a synaptic mechanism involved in learning and memory. Experiments have shown that dendritic sodium spikes (Na-dSpikes) are required for LTP in the distal apical dendrites of CA1 pyramidal cells. On the other hand, LTP in perisomatic dendrites can be induced by synaptic input patterns that can be both subthreshold and suprathreshold for Na-dSpikes. It is unclear whether these results can be explained by one unifying plasticity mechanism. Here, we show in biophysically and morphologically realistic compartmental models of the CA1 pyramidal cell that these forms of LTP can be fully accounted for by a simple plasticity rule. We call it the voltage-based Event-Timing-Dependent Plasticity (ETDP) rule. The presynaptic event is the presynaptic spike or release of glutamate. The postsynaptic event is the local depolarization that exceeds a certain plasticity threshold. Our model reproduced the experimentally observed LTP in a variety of protocols, including local pharmacological inhibition of dendritic spikes by tetrodotoxin (TTX). In summary, we have provided a validation of the voltage-based ETDP, suggesting that this simple plasticity rule can be used to model even complex spatiotemporal patterns of long-term synaptic plasticity in neuronal dendrites.

Dendritic effects of tDCS insights from a morphologically realistic model neuron

Transcranial direct current stimulation (tDCS) induces subcellular compartmental-dependent polarization, maximal in the distal portions of axons and dendrites. Using a morphologically realistic neuron model, we simulated tDCS-induced membrane polarization of the apical dendrite. Thus, we investigated the differential dendritic effects of anodal and cathodal tDCS on membrane potential polarization along the dendritic structure and its subsequent effects on dendritic membrane resistance, excitatory postsynaptic potential amplitude, backpropagating action potential amplitude, input/output relations, and long-term synaptic plasticity. We further showed that the effects of anodal and cathodal tDCS on the backpropagating action potential were asymmetric, and explained this asymmetry. Additionally, we showed that the effects on input/output relations were rather weak and limited to the low-mid range of stimulation frequencies, and that synaptic plasticity effects were mostly limited to the distal portion of the dendrite. Thus, we demonstrated how tDCS modifies dendritic physiology due to the dendrite's unique morphology and composition of voltage-gated ion channels.

Hippocampal place code plasticity in CA1 requires postsynaptic membrane fusion

Rapid delivery of glutamate receptors to the postsynaptic membrane via vesicle fusion is a central component of synaptic plasticity. However, it is unknown how this process supports specific neural computations during behavior. To bridge this gap, we combined conditional genetic deletion of a component of the postsynaptic membrane fusion machinery, Syntaxin3 (Stx3), in hippocampal CA1 neurons of mice with population in vivo calcium imaging. This approach revealed that Stx3 is necessary for forming the neural dynamics that support novelty processing, spatial reward memory and offline memory consolidation. In contrast, CA1 Stx3 was dispensable for maintaining aspects of the neural code that exist presynaptic to CA1 such as representations of context and space. Thus, manipulating postsynaptic membrane fusion identified computations that specifically require synaptic restructuring via membrane trafficking in CA1 and distinguished them from neural representation that could be inherited from upstream brain regions or learned through other mechanisms.

Cenobamate (YKP3089) and Drug-Resistant Epilepsy: A Review of the Literature

Cenobamate (CNB), ([(R)-1-(2-chlorophenyl)-2-(2H-tetrazol-2-yl)ethyl], is a novel tetrazole alkyl carbamate derivative. In November 2019, the Food and Drug Administration approved Xcopri®, marketed by SK Life Science Inc., (Paramus, NJ, USA) for adult focal seizures. The European Medicines Agency approved Ontozry® by Arvelle Therapeutics Netherlands B.V.(Amsterdam, The Neatherlands) in March 2021. Cenobamate is a medication that could potentially change the perspectives regarding the management and prognosis of refractory epilepsy. In this way, this study aims to review the literature on CNB's pharmacological properties, pharmacokinetics, efficacy, and safety. CNB is a highly effective drug in managing focal onset seizures, with more than twenty percent of individuals with drug-resistant epilepsy achieving seizure freedom. This finding is remarkable in the antiseizure medication literature. The mechanism of action of CNB is still poorly understood, but it is associated with transient and persistent sodium currents and GABAergic neurotransmission. In animal studies, CNB showed sustained efficacy and potency in the 6 Hz test regardless of the stimulus intensity. CNB was revealed to be the most cost-effective drug among different third-generation antiseizure medications. Also, CNB could have neuroprotective effects. However, there are still concerns regarding its potential for abuse and suicidality risk, which future studies should clearly assess, after which protocols should be changed. The major drawback of CNB therapy is the slow and complex titration and maintenance phases preventing the wide use of this new agent in clinical practice.

Macromolecular rate theory explains the temperature dependence of membrane conductance kinetics

The factor Q10 is used in neuroscience to adjust reaction rates of voltage-activated membrane conductances to different temperatures and is widely assumed to be constant. By performing an analysis of published data of the reaction rates of sodium, potassium, and calcium membrane conductances, we demonstrate that 1) Q10 is temperature dependent, 2) this relationship is similar across conductances, and 3) there is a strong effect at low temperatures (<15°C). We show that macromolecular rate theory (MMRT) explains this temperature dependency. MMRT predicts the existence of optimal temperatures at which reaction rates decrease as temperature increases, a phenomenon that we also found in the published data sets. We tested the consequences of using MMRT-adjusted reaction rates in the Hodgkin-Huxley model of the squid's giant axon. The MMRT-adjusted model reproduces the temperature dependence of the rising and falling times of the action potential. Furthermore, the model also reproduces these properties for different squid species that live in different climates. In a second example, we compare spiking patterns of biophysical models based on human pyramidal neurons from the Allen Cell Types database at room and physiological temperatures. The original models, calibrated at 34°C, failed to generate realistic spikes at room temperature in more than half of the tested models, while the MMRT produces realistic spiking in all conditions. In another example, we show that using the MMRT correction in hippocampal pyramidal cell models results in 100% differences in voltage responses. Finally, we show that the shape of the Q10 function results in systematic errors in predicting reaction rates. We propose that the optimal temperature could be a thermodynamical barrier to avoid over excitation in neurons. While this study is centered on membrane conductances, our results have important consequences for all biochemical reactions involved in cell signaling.

Lateral entorhinal cortex inputs modulate hippocampal dendritic excitability by recruiting a local disinhibitory microcircuit

The lateral entorhinal cortex (LEC) provides multisensory information to the hippocampus, directly to the distal dendrites of CA1 pyramidal neurons. LEC neurons perform important functions for episodic memory processing, coding for contextually salient elements of an environment or experience. However, we know little about the functional circuit interactions between the LEC and the hippocampus. We combine functional circuit mapping and computational modeling to examine how long-range glutamatergic LEC projections modulate compartment-specific excitation-inhibition dynamics in hippocampal area CA1. We demonstrate that glutamatergic LEC inputs can drive local dendritic spikes in CA1 pyramidal neurons, aided by the recruitment of a disinhibitory VIP interneuron microcircuit. Our circuit mapping and modeling further reveal that LEC inputs also recruit CCK interneurons that may act as strong suppressors of dendritic spikes. These results highlight a cortically driven GABAergic microcircuit mechanism that gates nonlinear dendritic computations, which may support compartment-specific coding of multisensory contextual features within the hippocampus.

Introducing the Dendrify framework for incorporating dendrites to spiking neural networks

Computational modeling has been indispensable for understanding how subcellular neuronal features influence circuit processing. However, the role of dendritic computations in network-level operations remains largely unexplored. This is partly because existing tools do not allow the development of realistic and efficient network models that account for dendrites. Current spiking neural networks, although efficient, are usually quite simplistic, overlooking essential dendritic properties. Conversely, circuit models with morphologically detailed neuron models are computationally costly, thus impractical for large-network simulations. To bridge the gap between these two extremes and facilitate the adoption of dendritic features in spiking neural networks, we introduce Dendrify, an open-source Python package based on Brian 2. Dendrify, through simple commands, automatically generates reduced compartmental neuron models with simplified yet biologically relevant dendritic and synaptic integrative properties. Such models strike a good balance between flexibility, performance, and biological accuracy, allowing us to explore dendritic contributions to network-level functions while paving the way for developing more powerful neuromorphic systems.

Dendritic Excitability and Synaptic Plasticity In Vitro and In Vivo

Much of our understanding of dendritic and synaptic physiology comes from in vitro experimentation, where the afforded mechanical stability and convenience of applying drugs allowed patch-clamping based recording techniques to investigate ion channel distributions, their gating kinetics, and to uncover dendritic integrative and synaptic plasticity rules. However, with current efforts to study these questions in vivo, there is a great need to translate existing knowledge between in vitro and in vivo experimental conditions. In this review, we identify discrepancies between in vitro and in vivo ionic composition of extracellular media and discuss how changes in ionic composition alter dendritic excitability and plasticity induction. Here, we argue that under physiological in vivo ionic conditions, dendrites are expected to be more excitable and the threshold for synaptic plasticity induction to be lowered. Consequently, the plasticity rules described in vitro vary significantly from those implemented in vivo.

Reorganization of CA1 dendritic dynamics by hippocampal sharp-wave ripples during learning

The hippocampus plays a critical role in memory consolidation, mediated by coordinated network activity during sharp-wave ripple (SWR) events. Despite the link between SWRs and hippocampal plasticity, little is known about how network state affects information processing in dendrites, the primary sites of synaptic input integration and plasticity. Here, we monitored somatic and basal dendritic activity in CA1 pyramidal cells in behaving mice using longitudinal two-photon calcium imaging integrated with simultaneous local field potential recordings. We found immobility was associated with an increase in dendritic activity concentrated during SWRs. Coincident dendritic and somatic activity during SWRs predicted increased coupling during subsequent exploration of a novel environment. In contrast, somatic-dendritic coupling and SWR recruitment varied with cells' tuning distance to reward location during a goal-learning task. Our results connect SWRs with the stabilization of information processing within CA1 neurons and suggest that these mechanisms may be dynamically biased by behavioral demands.

Optimizing a Neuron for Reliable Dendritic Subunit Pooling

In certain biologically relevant computing scenarios, a neuron "pools" the outputs of multiple independent functional subunits, firing if any one of them crosses threshold. Recent studies suggest that active dendrites could provide the thresholding mechanism, so that both the thresholding and pooling operations could take place within a single neuron. A pooling neuron faces a difficult task, however. Dendrites can produce highly variable responses depending on the density and spatial patterning of their synaptic inputs, and bona fide dendritic firing may be very rare, making it difficult for a neuron to reliably detect when one of its many dendrites has "gone suprathreshold". Our goal has been to identify biological adaptations that optimize a neuron's performance at the binary subunit pooling (BSP) task. Katz et al. (2009) pointed to the importance of spine density gradients in shaping dendritic responses. In a similar vein, we used a compartmental model to study how a neuron's performance at the BSP task is affected by different spine density layouts and other biological variables. We found BSP performance was optimized when dendrites have (1) a decreasing spine density gradient (true for many types of pyramidal neurons); (2) low-to-medium resistance spine necks; (3) strong NMDA currents; (4) fast spiking Na+ channels; and (5) powerful hyperpolarizing inhibition. Our findings provide a normative account that links several neuronal properties within the context of a behaviorally relevant task, and thus provide new insights into nature's subtle strategies for optimizing the computing capabilities of neural tissue.

Rapid synaptic plasticity contributes to a learned conjunctive code of position and choice-related information in the hippocampus

To successfully perform goal-directed navigation, animals must know where they are and what they are doing-e.g., looking for water, bringing food back to the nest, or escaping from a predator. Hippocampal neurons code for these critical variables conjunctively, but little is known about how this "where/what" code is formed or flexibly routed to other brain regions. To address these questions, we performed intracellular whole-cell recordings in mouse CA1 during a cued, two-choice virtual navigation task. We demonstrate that plateau potentials in CA1 pyramidal neurons rapidly strengthen synaptic inputs carrying conjunctive information about position and choice. Plasticity-induced response fields were modulated by cues only in animals previously trained to collect rewards based on available cues. Thus, we reveal that gradual learning is required for the formation of a conjunctive population code, upstream of CA1, while plateau-potential-induced synaptic plasticity in CA1 enables flexible routing of the code to downstream brain regions.

Dendritic Branch-constrained N-Methyl-d-Aspartate Receptor-mediated Spikes Drive Synaptic Plasticity in Hippocampal CA3 Pyramidal Cells

N-methyl-d-aspartate receptor-mediated ( spikes can be causally linked to the induction of synaptic long-term potentiation (LTP) in hippocampal and cortical pyramidal cells. However, it is unclear if they regulate plasticity at a local or global scale in the dendritic tree. Here, we used dendritic patch-clamp recordings and calcium imaging to investigate the integrative properties of single dendrites of hippocampal CA3 cells. We show that local hyperpolarization of a single dendritic segment prevents NMDA spikes, their associated calcium transients, as well as LTP in a branch-specific manner. This result provides direct, causal evidence that the single dendritic branch can operate as a functional unit in regulating CA3 pyramidal cell plasticity.

Frequency-Dependent Synaptic Dynamics Differentially Tune CA1 and CA2 Pyramidal Neuron Responses to Cortical Input

Entorhinal cortex neurons make monosynaptic connections onto distal apical dendrites of CA1 and CA2 pyramidal neurons through the perforant path (PP) projection. Previous studies show that differences in dendritic properties and synaptic input density enable the PP inputs to produce a much stronger excitation of CA2 compared with CA1 pyramidal neurons. Here, using mice of both sexes, we report that the difference in PP efficacy varies substantially as a function of presynaptic firing rate. Although a single PP stimulus evokes a 5- to 6-fold greater EPSP in CA2 compared with CA1, a brief high-frequency train of PP stimuli evokes a strongly facilitating postsynaptic response in CA1, with relatively little change in CA2. Furthermore, we demonstrate that blockade of NMDARs significantly reduces strong temporal summation in CA1 but has little impact on that in CA2. As a result of the differences in the frequency- and NMDAR-dependent temporal summation, naturalistic patterns of presynaptic activity evoke CA1 and CA2 responses with distinct dynamics, differentially tuning CA1 and CA2 responses to bursts of presynaptic firing versus single presynaptic spikes, respectively.SIGNIFICANCE STATEMENT Recent studies have demonstrated that abundant entorhinal cortical innervation and efficient dendritic propagation enable hippocampal CA2 pyramidal neurons to produce robust excitation evoked by single cortical stimuli, compared with CA1. Here we uncovered, unexpectedly, that the difference in efficacy of cortical excitation varies substantially as a function of presynaptic firing rate. A burst of stimuli evokes a strongly facilitating response in CA1, but not in CA2. As a result, the postsynaptic response of CA1 and CA2 to presynaptic naturalistic firing displays contrasting temporal dynamics, which depends on the activation of NMDARs. Thus, whereas CA2 responds to single stimuli, CA1 is selectively recruited by bursts of cortical input.

Conductance-based models and the fragmentation problem: A case study based on hippocampal CA1 pyramidal cell models and epilepsy

Epilepsy has been a central topic in computational neuroscience, and in silico models have shown to be excellent tools to integrate and evaluate findings from animal and clinical settings. Among the different languages and tools for computational modeling development, NEURON stands out as one of the most used and mature neurosimulators. However, despite the vast quantity of models developed with NEURON, a fragmentation problem is evident in the great majority of models related to the same type of cell or cell properties. This fragmentation causes a lack of interoperability between the models because of differences in parameters. The problem is not related to the neurosimulator, which is prepared to reuse elements of other models, but related to decisions made during the model development, when it is not uncommon to adjust parameter values according to the necessities of the study. Here, this problem is presented by studying computational models related to temporal lobe epilepsy and the definitions of hippocampal CA1 pyramidal cells. The current assessment aims to highlight the implications of fragmentation for reliable modeling and the need to adopt a framework that allows a better interoperability between different models. This article is part of the Special Issue "NEWroscience 2018".

Altered A-Type Potassium Channel Function Impairs Dendritic Spike Initiation and Temporoammonic Long-Term Potentiation in Fragile X Syndrome

Fragile X syndrome (FXS) is the leading monogenetic cause of cognitive impairment and autism spectrum disorder. Area CA1 of the hippocampus receives current information about the external world from the entorhinal cortex via the temporoammonic (TA) pathway. Given its role in learning and memory, it is surprising that little is known about TA long-term potentiation (TA-LTP) in FXS. We found that TA-LTP was impaired in male fmr1 KO mice. Although there were no significant differences in basal synaptic transmission, synaptically evoked dendritic calcium signals were smaller in KO neurons. Using dendritic recording, we found no difference in complex spikes or pharmacologically isolated Ca2+ spikes; however, the threshold for fast, Na+-dependent dendritic spikes was depolarized in fmr1 KO mice. Cell-attached patch-clamp recordings found no difference in Na+ channels between wild-type and fmr1 KO CA1 dendrites. Dendritic spike threshold and TA-LTP were restored by blocking A-type K+ channels with either 150 µm Ba2+ or the more specific toxin AmmTx3. The impairment of TA-LTP shown here, coupled with previously described enhanced Schaffer collateral LTP, may contribute to spatial memory alterations in FXS. Furthermore, as both of these LTP phenotypes are attributed to changes in A-type K+ channels in FXS, our findings provide a potential therapeutic target to treat cognitive impairments in FXS.SIGNIFICANCE STATEMENT Alterations in synaptic function and plasticity are likely contributors to learning and memory impairments in many neurologic disorders. Fragile X syndrome is marked by dysfunctional learning and memory and changes in synaptic structure and function. This study shows a lack of LTP at temporoammonic synapses in CA1 neurons associated with biophysical differences in A-type K+ channels in fmr1 KO CA1 neurons. Our results, along with previous findings on A-type K+ channel effects on Schaffer collateral LTP, reveal differential effects of a single ion channelopathy on LTP at the two major excitatory pathways of CA1 pyramidal neurons. These findings expand our understanding of memory deficits in FXS and provide a potential therapeutic target for the treatment of memory dysfunction in FXS.

Prolonged development of long-term potentiation at lateral entorhinal cortex synapses onto adult-born neurons

Critical period plasticity at adult-born neuron synapses is widely believed to contribute to the learning and memory functions of the hippocampus. Experience regulates circuit integration and for a transient interval, until cells are ~6 weeks old, new neurons display enhanced long-term potentiation (LTP) at afferent and efferent synapses. Since neurogenesis declines substantially with age, this raises questions about the extent of lasting plasticity offered by adult-born neurons. Notably, however, the hippocampus receives sensory information from two major cortical pathways. Broadly speaking, the medial entorhinal cortex conveys spatial information to the hippocampus via the medial perforant path (MPP), and the lateral entorhinal cortex, via the lateral perforant path (LPP), codes for the cues and items that make experiences unique. While enhanced critical period plasticity at MPP synapses is relatively well characterized, no studies have examined long-term plasticity at LPP synapses onto adult-born neurons, even though the lateral entorhinal cortex is uniquely vulnerable to aging and Alzheimer's pathology. We therefore investigated LTP at LPP inputs both within (4-6 weeks) and beyond (8+ weeks) the traditional critical period. At immature stages, adult-born neurons did not undergo significant LTP at LPP synapses, and often displayed long-term depression after theta burst stimulation. However, over the course of 3-4 months, adult-born neurons displayed increasingly greater amounts of LTP. Analyses of short-term plasticity point towards a presynaptic mechanism, where transmitter release probability declines as cells mature, providing a greater dynamic range for strengthening synapses. Collectively, our findings identify a novel form of new neuron plasticity that develops over an extended interval, and may therefore be relevant for maintaining cognitive function in aging.

A new reduced-morphology model for CA1 pyramidal cells and its validation and comparison with other models using HippoUnit

Modeling long-term neuronal dynamics may require running long-lasting simulations. Such simulations are computationally expensive, and therefore it is advantageous to use simplified models that sufficiently reproduce the real neuronal properties. Reducing the complexity of the neuronal dendritic tree is one option. Therefore, we have developed a new reduced-morphology model of the rat CA1 pyramidal cell which retains major dendritic branch classes. To validate our model with experimental data, we used HippoUnit, a recently established standardized test suite for CA1 pyramidal cell models. The HippoUnit allowed us to systematically evaluate the somatic and dendritic properties of the model and compare them to models publicly available in the ModelDB database. Our model reproduced (1) somatic spiking properties, (2) somatic depolarization block, (3) EPSP attenuation, (4) action potential backpropagation, and (5) synaptic integration at oblique dendrites of CA1 neurons. The overall performance of the model in these tests achieved higher biological accuracy compared to other tested models. We conclude that, due to its realistic biophysics and low morphological complexity, our model captures key physiological features of CA1 pyramidal neurons and shortens computational time, respectively. Thus, the validated reduced-morphology model can be used for computationally demanding simulations as a substitute for more complex models.

Effects of direct current stimulation on synaptic plasticity in a single neuron

BACKGROUND

Transcranial direct current stimulation (DCS) has lasting effects that may be explained by a boost in synaptic long-term potentiation (LTP). We hypothesized that this boost is the result of a modulation of somatic spiking in the postsynaptic neuron, as opposed to indirect network effects. To test this directly we record somatic spiking in a postsynaptic neuron during LTP induction with concurrent DCS.

METHODS

We performed rodent in-vitro patch-clamp recordings at the soma of individual CA1 pyramidal neurons. LTP was induced with theta-burst stimulation (TBS) applied concurrently with DCS. To test the causal role of somatic polarization, we manipulated polarization via current injections. We also used a computational multi-compartment neuron model that captures the effect of electric fields on membrane polarization and activity-dependent synaptic plasticity.

RESULTS

TBS-induced LTP was enhanced when paired with anodal DCS as well as depolarizing current injections. In both cases, somatic spiking during the TBS was increased, suggesting that evoked somatic activity is the primary factor affecting LTP modulation. However, the boost of LTP with DCS was less than expected given the increase in spiking activity alone. In some cells, we also observed DCS-induced spiking, suggesting DCS also modulates LTP via induced network activity. The computational model reproduces these results and suggests that they are driven by both direct changes in postsynaptic spiking and indirect changes due to network activity.

CONCLUSION

DCS enhances synaptic plasticity by increasing postsynaptic somatic spiking, but we also find that an increase in network activity may boost but also limit this enhancement.

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.

NMDA Receptor and L-Type Calcium Channel Modulate Prion Formation

Transmissible neurodegenerative prion diseases are characterized by the conversion of the cellular prion protein (PrP^C) to misfolded isoforms denoted as prions or PrP^Sc. Although the conversion can occur in the test tube containing recombinant prion protein or cell lysates, efficient prion formation depends on the integrity of intact cell functions. Since neurons are main targets for prion replication, we asked whether their most specialized function, i.e. synaptic plasticity, could be a factor by which PrP^Sc formation can be modulated.Immortalized gonadotropin-releasing hormone cells infected with the Rocky Mountain Laboratory prion strain were treated with L-type calcium channels (LTCCs) and NMDA receptors (NMDARs) stimulators or inhibitors. Western blotting was used to monitor the effects on PrP^Sc formation in relation to ERK signalling.Infected cells showed enhanced levels of phosphorylated ERK (pERK) compared with uninfected cells. Exposure of infected cells to the LTCC agonist Bay K8644 enhanced pERK and PrP^Sc levels. Although treatment with an LTCC blocker (nimodipine) or an NMDAR competitive antagonist (D-AP5) had no effects, their combination reduced both pERK and PrP^Sc levels. Treatment with the non-competitive NMDAR channel blocker MK-801 markedly reduced pERK and PrP^Sc levels.Our study shows that changes in LTCCs and NMDARs activities can modulate PrP^Sc formation through ERK signalling. During synaptic plasticity, while ERK signalling promotes long-term potentiation accompanied by expansion of post-synaptic lipid rafts, other NMDA receptor-depending signalling pathways, p38-JNK, have opposing effects. Our findings indicate that contrasting intracellular signals of synaptic plasticity can influence time-dependent prion conversion.

NYX-2925 induces metabotropic N-methyl-d-aspartate receptor (NMDAR) signaling that enhances synaptic NMDAR and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor

N-methyl-d-aspartate receptors (NMDARs) mediate both physiological and pathophysiological processes, although selective ligands lack broad clinical utility. NMDARs are composed of multiple subunits, but N-methyl-d-aspartate receptor subunit 2 (GluN2) is predominately responsible for functional heterogeneity. Specifically, the GluN2A- and GluN2B-containing subtypes are enriched in adult hippocampus and cortex and impact neuronal communication via dynamic trafficking into and out of the synapse. We sought to understand if ((2S, 3R)-3-hydroxy-2-((R)-5-isobutyryl-1-oxo-2,5-diazaspiro[3,4]octan-2-yl) butanamide (NYX-2925), a novel NMDAR modulator, alters synaptic levels of GluN2A- or GluN2B-containing NMDARs. Low-picomolar NYX-2925 increased GluN2B colocalization with the excitatory post-synaptic marker post-synaptic density protein 95 (PSD-95) in rat primary hippocampal neurons within 30 min. Twenty-four hours following oral administration, 1 mg/kg NYX-2925 increased GluN2B in PSD-95-associated complexes ex vivo, and low-picomolar NYX-2925 regulated numerous trafficking pathways in vitro. Because the NYX-2925 concentration that increases synaptic GluN2B was markedly below that which enhances long-term potentiation (mid-nanomolar), we sought to elucidate the basis of this effect. Although NMDAR-dependent, NYX-2925-mediated colocalization of GluN2B with PSD-95 occurred independent of ion flux, as colocalization increased in the presence of either the NMDAR channel blocker (5R,10S)-(-)-5-Methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5,10-imine hydrogen maleate or glycine site antagonist 7-chlorokynurenic acid. Moreover, while mid-nanomolar NYX-2925 concentrations, which do not increase synaptic GluN2B, enhanced calcium transients, functional plasticity was only enhanced by picomolar NYX-2925. Thus, NYX-2925 concentrations that increase synaptic GluN2B facilitated the chemical long-term potentiation induced insertion of synaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor GluA1 subunit levels. Basal (unstimulated by chemical long-term potentiation) levels of synaptic GluA1 were only increased by mid-nanomolar NYX-2925. These data suggest that NYX-2925 facilitates homeostatic plasticity by initially increasing synaptic GluN2B via metabotropic-like NMDAR signaling. Cover Image for this issue: doi: 10.1111/jnc.14735.

Synaptic Plasticity Depends on the Fine-Scale Input Pattern in Thin Dendrites of CA1 Pyramidal Neurons

Coordinated long-term plasticity of nearby excitatory synaptic inputs has been proposed to shape experience-related neuronal information processing. To elucidate the induction rules leading to spatially structured forms of synaptic potentiation in dendrites, we explored plasticity of glutamate uncaging-evoked excitatory input patterns with various spatial distributions in perisomatic dendrites of CA1 pyramidal neurons in slices from adult male rats.

Coordinated long-term plasticity of nearby excitatory synaptic inputs has been proposed to shape experience-related neuronal information processing. To elucidate the induction rules leading to spatially structured forms of synaptic potentiation in dendrites, we explored plasticity of glutamate uncaging-evoked excitatory input patterns with various spatial distributions in perisomatic dendrites of CA1 pyramidal neurons in slices from adult male rats. We show that (1) the cooperativity rules governing the induction of synaptic LTP depend on dendritic location; (2) LTP of input patterns that are subthreshold or suprathreshold to evoke local dendritic spikes (d-spikes) requires different spatial organization; and (3) input patterns evoking d-spikes can strengthen nearby, nonsynchronous synapses by local heterosynaptic plasticity crosstalk mediated by NMDAR-dependent MEK/ERK signaling. These results suggest that multiple mechanisms can trigger spatially organized synaptic plasticity on various spatial and temporal scales, enriching the ability of neurons to use synaptic clustering for information processing.

SIGNIFICANCE STATEMENT A fundamental question in neuroscience is how neuronal feature selectivity is established via the combination of dendritic processing of synaptic input patterns with long-term synaptic plasticity. As these processes have been mostly studied separately, the relationship between the rules of integration and rules of plasticity remained elusive. Here we explore how the fine-grained spatial pattern and the form of voltage integration determine plasticity of different excitatory synaptic input patterns in perisomatic dendrites of CA1 pyramidal cells. We demonstrate that the plasticity rules depend highly on three factors: (1) the location of the input within the dendritic branch (proximal vs distal), (2) the strength of the input pattern (subthreshold or suprathreshold for dendritic spikes), and (3) the stimulation of neighboring synapses.

Dendritic action potentials and computation in human layer 2/3 cortical neurons

The active electrical properties of dendrites shape neuronal input and output and are fundamental to brain function. However, our knowledge of active dendrites has been almost entirely acquired from studies of rodents. In this work, we investigated the dendrites of layer 2 and 3 (L2/3) pyramidal neurons of the human cerebral cortex ex vivo. In these neurons, we discovered a class of calcium-mediated dendritic action potentials (dCaAPs) whose waveform and effects on neuronal output have not been previously described. In contrast to typical all-or-none action potentials, dCaAPs were graded; their amplitudes were maximal for threshold-level stimuli but dampened for stronger stimuli. These dCaAPs enabled the dendrites of individual human neocortical pyramidal neurons to classify linearly nonseparable inputs—a computation conventionally thought to require multilayered networks.

Data-Driven Predictive Modeling of Neuronal Dynamics Using Long Short-Term Memory

Modeling brain dynamics to better understand and control complex behaviors underlying various cognitive brain functions have been of interest to engineers, mathematicians and physicists over the last several decades. With the motivation of developing computationally efficient models of brain dynamics to use in designing control-theoretic neurostimulation strategies, we have developed a novel data-driven approach in a long short-term memory (LSTM) neural network architecture to predict the temporal dynamics of complex systems over an extended long time-horizon in future. In contrast to recent LSTM-based dynamical modeling approaches that make use of multi-layer perceptrons or linear combination layers as output layers, our architecture uses a single fully connected output layer and reversed-order sequence-to-sequence mapping to improve short time-horizon prediction accuracy and to make multi-timestep predictions of dynamical behaviors. We demonstrate the efficacy of our approach in reconstructing the regular spiking to bursting dynamics exhibited by an experimentally-validated 9-dimensional Hodgkin-Huxley model of hippocampal CA1 pyramidal neurons. Through simulations, we show that our LSTM neural network can predict the multi-time scale temporal dynamics underlying various spiking patterns with reasonable accuracy. Moreover, our results show that the predictions improve with increasing predictive time-horizon in the multi-timestep deep LSTM neural network.

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.

The Autism-Associated Gene Scn2a Contributes to Dendritic Excitability and Synaptic Function in the Prefrontal Cortex

Autism spectrum disorder (ASD) is strongly associated with de novo gene mutations. One of the most commonly affected genes is SCN2A. ASD-associated SCN2A mutations impair the encoded protein Na_V1.2, a sodium channel important for action potential initiation and propagation in developing excitatory cortical neurons. The link between an axonal sodium channel and ASD, a disorder typically attributed to synaptic or transcriptional dysfunction, is unclear. Here we show that Na_V1.2 is unexpectedly critical for dendritic excitability and synaptic function in mature pyramidal neurons in addition to regulating early developmental axonal excitability. Na_V1.2 loss reduced action potential backpropagation into dendrites, impairing synaptic plasticity and synaptic strength, even when Na_V1.2 expression was disrupted in a cell-autonomous fashion late in development. These results reveal a novel dendritic function for Na_V1.2, providing insight into cellular mechanisms probably underlying circuit and behavioral dysfunction in ASD.

Scn2a Haploinsufficiency in Mice Suppresses Hippocampal Neuronal Excitability, Excitatory Synaptic Drive, and Long-Term Potentiation, and Spatial Learning and Memory

Nav1.2, a voltage-gated sodium channel subunit encoded by the Scn2a gene, has been implicated in various brain disorders, including epilepsy, autism spectrum disorder, intellectual disability, and schizophrenia. Nav1.2 is known to regulate the generation of action potentials in the axon initial segment and their propagation along axonal pathways. Nav1.2 also regulates synaptic integration and plasticity by promoting back-propagation of action potentials to dendrites, but whether Nav1.2 deletion in mice affects neuronal excitability, synaptic transmission, synaptic plasticity, and/or disease-related animal behaviors remains largely unclear. Here, we report that mice heterozygous for the Scn2a gene (Scn2a^+/- mice) show decreased neuronal excitability and suppressed excitatory synaptic transmission in the presence of network activity in the hippocampus. In addition, Scn2a^+/- mice show suppressed hippocampal long-term potentiation (LTP) in association with impaired spatial learning and memory, but show largely normal locomotor activity, anxiety-like behavior, social interaction, repetitive behavior, and whole-brain excitation. These results suggest that Nav1.2 regulates hippocampal neuronal excitability, excitatory synaptic drive, LTP, and spatial learning and memory in mice.

How Dendrites Affect Online Recognition Memory

In order to record the stream of autobiographical information that defines our unique personal history, our brains must form durable memories from single brief exposures to the patterned stimuli that impinge on them continuously throughout life. However, little is known about the computational strategies or neural mechanisms that underlie the brain's ability to perform this type of "online" learning. Based on increasing evidence that dendrites act as both signaling and learning units in the brain, we developed an analytical model that relates online recognition memory capacity to roughly a dozen dendritic, network, pattern, and task-related parameters. We used the model to determine what dendrite size maximizes storage capacity under varying assumptions about pattern density and noise level. We show that over a several-fold range of both of these parameters, and over multiple orders-of-magnitude of memory size, capacity is maximized when dendrites contain a few hundred synapses-roughly the natural number found in memory-related areas of the brain. Thus, in comparison to entire neurons, dendrites increase storage capacity by providing a larger number of better-sized learning units. Our model provides the first normative theory that explains how dendrites increase the brain's capacity for online learning; predicts which combinations of parameter settings we should expect to find in the brain under normal operating conditions; leads to novel interpretations of an array of existing experimental results; and provides a tool for understanding which changes associated with neurological disorders, aging, or stress are most likely to produce memory deficits-knowledge that could eventually help in the design of improved clinical treatments for memory loss.

Dendritic sodium spikes endow neurons with inverse firing rate response to correlated synaptic activity

Many neurons possess dendrites enriched with sodium channels and are capable of generating action potentials. However, the role of dendritic sodium spikes remain unclear. Here, we study computational models of neurons to investigate the functional effects of dendritic spikes. In agreement with previous studies, we found that point neurons or neurons with passive dendrites increase their somatic firing rate in response to the correlation of synaptic bombardment for a wide range of input conditions, i.e. input firing rates, synaptic conductances, or refractory periods. However, neurons with active dendrites show the opposite behavior: for a wide range of conditions the firing rate decreases as a function of correlation. We found this property in three types of models of dendritic excitability: a Hodgkin-Huxley model of dendritic spikes, a model with integrate and fire dendrites, and a discrete-state dendritic model. We conclude that fast dendritic spikes confer much broader computational properties to neurons, sometimes opposite to that of point neurons.

Flux-Independent NMDAR Signaling: Molecular Mediators, Cellular Functions, and Complexities

The glutamate (Glu) N-methyl-d-aspartate (NMDA) receptor (NMDAR) plays a critical role in synaptic communication given mainly by its ionotropic function that permeates Ca²⁺. This in turn activates calmodulin that triggers CaMKII, MAPK, CREB, and PI3K pathways, among others. However, NMDAR signaling is more complex. In the last two decades several groups have shown that the NMDAR also elicits flux-independent signaling (f-iNMDARs). It has been demonstrated that agonist (Glu or NMDA) or co-agonist (Glycine or d-Serine) bindings initiate intracellular events, including conformational changes, exchange of molecular interactions, release of second messengers, and signal transduction, that result in different cellular events including endocytosis, LTD, cell death, and neuroprotection, among others. Interestingly, f-iNMDARs has also been observed in pathological conditions and non-neuronal cells. Here, the molecular and cellular events elicited by these flux-independent actions (non-canonical or metabotropic-like) of the NMDAR are reviewed. Considering the NMDAR complexity, it is possible that these flux-independent events have a more relevant role in intracellular signaling that has been disregarded for decades. Moreover, considering the wide expression and function of the NMDAR in non-neuronal cells and other tissues beyond the nervous system and some evolutionary traits, f-iNMDARs calls for a reconsideration of how we understand the biology of this complex receptor.

mGluR5-dependent modulation of dendritic excitability in CA1 pyramidal neurons mediated by enhancement of persistent Na+ currents

KEY POINTS

High-frequency stimulation (HFS) of the Schaffer collateral pathway activates metabotropic glutamate receptor 5 (mGluR5) signalling in the proximal apical dendrites of CA1 pyramidal neurons. The synaptic activation of mGluR5-mediated calcium signalling causes a significant increase in persistent sodium current (INa,P ) in the dendrites. Increased INa,P by HFS underlies potentiation of synaptic inputs at both the proximal and distal dendrite, leading to an enhanced probability of action potential firing associated with decreased action potential thresholds. Therefore, HFS-induced activation of intracellular mGluR5 serves an important role as an instructive signal for potentiation of upcoming inputs by increasing dendritic excitability.

ABSTRACT

Dendritic Na+ channels in pyramidal neurons are known to amplify synaptic signals, thereby facilitating action potential (AP) generation. However, the mechanisms that modulate dendritic Na+ channels have remained largely uncharacterized. Here, we report a new form of short-term plasticity in which proximal excitatory synaptic inputs to hippocampal CA1 pyramidal neurons transiently elevate dendritic excitability. High-frequency stimulations (HFS) to the Schaffer collateral (SC) pathway activate mGluR5-dependent Ca2+ signalling in the apical dendrites, which, with calmodulin, upregulates specifically Nav1.6 channel-mediated persistent Na+ currents (INa,P ) in the dendrites. This HFS-induced increase in dendritic INa,P results in transient increases in the amplitude of excitatory postsynaptic potentials induced by both proximal SC and distal perforant path stimulation, leading to the enhanced probability of AP firing associated with decreased AP thresholds. Taken together, our study identifies dendritic INa,P as a novel target for mediating activity-dependent modulation of dendritic integration and neuronal output.

L-Type Voltage-Gated Ca2+ Channels Regulate Synaptic-Activity-Triggered Recycling Endosome Fusion in Neuronal Dendrites

The repertoire and abundance of proteins displayed on the surface of neuronal dendrites are tuned by regulated fusion of recycling endosomes (REs) with the dendritic plasma membrane. While this process is critical for neuronal function and plasticity, how synaptic activity drives RE fusion remains unexplored. We demonstrate a multistep fusion mechanism that requires Ca²⁺ from distinct sources. NMDA receptor Ca²⁺ initiates RE fusion with the plasma membrane, while L-type voltage-gated Ca²⁺ channels (L-VGCCs) regulate whether fused REs collapse into the membrane or reform without transferring their cargo to the cell surface. Accordingly, NMDA receptor activation triggered AMPA-type glutamate receptor trafficking to the dendritic surface in an L-VGCC-dependent manner. Conversely, potentiating L-VGCCs enhanced AMPA receptor surface expression only when NMDA receptors were also active. Thus L-VGCCs play a role in tuning activity-triggered surface expression of key synaptic proteins by gating the mode of RE fusion.

Persistent Sodium Current Mediates the Steep Voltage Dependence of Spatial Coding in Hippocampal Pyramidal Neurons

The mammalian hippocampus forms a cognitive map using neurons that fire according to an animal's position ("place cells") and many other behavioral and cognitive variables. The responses of these neurons are shaped by their presynaptic inputs and the nature of their postsynaptic integration. In CA1 pyramidal neurons, spatial responses in vivo exhibit a strikingly supralinear dependence on baseline membrane potential. The biophysical mechanisms underlying this nonlinear cellular computation are unknown. Here, through a combination of in vitro, in vivo, and in silico approaches, we show that persistent sodium current mediates the strong membrane potential dependence of place cell activity. This current operates at membrane potentials below the action potential threshold and over seconds-long timescales, mediating a powerful and rapidly reversible amplification of synaptic responses, which drives place cell firing. Thus, we identify a biophysical mechanism that shapes the coding properties of neurons composing the hippocampal cognitive map.

Dendritic spikes in hippocampal granule cells are necessary for long-term potentiation at the perforant path synapse

Long-term potentiation (LTP) of synaptic responses is essential for hippocampal memory function. Perforant-path (PP) synapses on hippocampal granule cells (GCs) contribute to the formation of associative memories, which are considered the cellular correlates of memory engrams. However, the mechanisms of LTP at these synapses are not well understood. Due to sparse firing activity and the voltage attenuation in their dendrites, it remains unclear how associative LTP at distal synapses occurs. Here, we show that NMDA receptor-dependent LTP can be induced at PP-GC synapses without backpropagating action potentials (bAPs) in acute rat brain slices. Dendritic recordings reveal substantial attenuation of bAPs as well as local dendritic Na⁺ spike generation during PP-GC input. Inhibition of dendritic Na⁺ spikes impairs LTP induction at PP-GC synapse. These data suggest that dendritic spikes may constitute a key cellular mechanism for memory formation in the dentate gyrus.

Changes in the element concentration of the dorsal hippocampus CA1 region during memory consolidation and reconsolidation

The concentration and distribution of Mg, P, Cl, K, Cu and Zn in the dorsal hippocampus CA1 region of rat brains were studied during memory consolidation and reconsolidation processes stimulated with inhibitory avoidance (IA) tests. Experimental rats were divided into four groups: i) group not submitted to inhibitory avoidance task (IA-N); ii) group submitted to inhibitory avoidance training session (IA-Y); iii) group submitted to inhibitory avoidance reactivation session but did not step down from the platform (IAR-N); and iv) group submitted to avoidance reactivation session and stepped down from the platform (IAR-Y). Elemental concentration and distribution in the CA1 hippocampus region were obtained through the Particle-Induced X-ray Emission (PIXE) technique. The results indicate that the concentration of Mg, P, Cl, K and Cu increased during memory consolidation. During the memory reconsolidation process, the concentrations of Mg, P, Cl and K increased, while Cu and Zn had no significant changes with respect to their basal condition. These results show that the major part of these elements may be engaged in memory consolidation could be also participating in memory reconsolidation. For all elements, the general trend related to their concentration did not change during reconsolidation regardless the presence of a novelty event, i.e. stepping down from the platform.

Unconventional NMDA Receptor Signaling

In the classical view, NMDA receptors (NMDARs) are stably expressed at the postsynaptic membrane, where they act via Ca²⁺ to signal coincidence detection in Hebbian plasticity. More recently, it has been established that NMDAR-mediated transmission can be dynamically regulated by neural activity. In addition, NMDARs have been found presynaptically, where they cannot act as conventional coincidence detectors. Unexpectedly, NMDARs have also been shown to signal metabotropically, without the need for Ca²⁺ This review highlights novel findings concerning these unconventional modes of NMDAR action.

Sodium channel subtypes are differentially localized to pre- and post-synaptic sites in rat hippocampus

Voltage-gated Na⁺ channels (Na_v ) modulate neuronal excitability, but the roles of the various Na_v subtypes in specific neuronal functions such as synaptic transmission are unclear. We investigated expression of the three major brain Na_v subtypes (Na_v 1.1, Na_v 1.2, Na_v 1.6) in area CA1 and dentate gyrus of rat hippocampus. Using light and electron microscopy, we found labeling for all three Na_v subtypes on dendrites, dendritic spines, and axon terminals, but the proportion of pre- and post-synaptic labeling for each subtype varied within and between subregions of CA1 and dentate gyrus. In the central hilus (CH) of the dentate gyrus, Na_v 1.1 immunoreactivity was selectively expressed in presynaptic profiles, while Na_v 1.2 and Na_v 1.6 were expressed both pre- and post-synaptically. In contrast, in the stratum radiatum (SR) of CA1, Na_v 1.1, Na_v 1.2, and Na_v 1.6 were selectively expressed in postsynaptic profiles. We next compared differences in Na_v subtype expression between CH and SR axon terminals and between CH and SR dendrites and spines. Na_v 1.1 and Na_v 1.2 immunoreactivity was preferentially localized to CH axon terminals compared to SR, and in SR dendrites and spines compared to CH. No differences in Na_v 1.6 immunoreactivity were found between axon terminals of CH and SR or between dendrites and spines of CH and SR. All Na_v subtypes in both CH and SR were preferentially associated with asymmetric synapses rather than symmetric synapses. These findings indicate selective presynaptic and postsynaptic Na_v expression in glutamatergic synapses of CH and SR supporting neurotransmitter release and synaptic plasticity.

Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level

Synaptic plasticity is thought to be the principal neuronal mechanism underlying learning. Models of plastic networks typically combine point neurons with spike-timing-dependent plasticity (STDP) as the learning rule. However, a point neuron does not capture the local non-linear processing of synaptic inputs allowed for by dendrites. Furthermore, experimental evidence suggests that STDP is not the only learning rule available to neurons. By implementing biophysically realistic neuron models, we study how dendrites enable multiple synaptic plasticity mechanisms to coexist in a single cell. In these models, we compare the conditions for STDP and for synaptic strengthening by local dendritic spikes. We also explore how the connectivity between two cells is affected by these plasticity rules and by different synaptic distributions. Finally, we show that how memory retention during associative learning can be prolonged in networks of neurons by including dendrites.

Synaptic plasticity is the neuronal mechanism underlying learning. Here the authors construct biophysical models of pyramidal neurons that reproduce observed plasticity gradients along the dendrite and show that dendritic spike dependent LTP which is predominant in distal sections can prolong memory retention.

Modelling plasticity in dendrites: from single cells to networks

One of the key questions in neuroscience is how our brain self-organises to efficiently process information. To answer this question, we need to understand the underlying mechanisms of plasticity and their role in shaping synaptic connectivity. Theoretical neuroscience typically investigates plasticity on the level of neural networks. Neural network models often consist of point neurons, completely neglecting neuronal morphology for reasons of simplicity. However, during the past decades it became increasingly clear that inputs are locally processed in the dendrites before they reach the cell body. Dendritic properties enable local interactions between synapses and location-dependent modulations of inputs, rendering the position of synapses on dendrites highly important. These insights changed our view of neurons, such that we now think of them as small networks of nearly independent subunits instead of a simple point. Here, we propose that understanding how the brain processes information strongly requires that we consider the following properties: which plasticity mechanisms are present in the dendrites and how do they enable the self-organisation of synapses across the dendritic tree for efficient information processing? Ultimately, dendritic plasticity mechanisms can be studied in networks of neurons with dendrites, possibly uncovering unknown mechanisms that shape the connectivity in our brains.

Fast two-photon imaging of subcellular voltage dynamics in neuronal tissue with genetically encoded indicators

Monitoring voltage dynamics in defined neurons deep in the brain is critical for unraveling the function of neuronal circuits but is challenging due to the limited performance of existing tools. In particular, while genetically encoded voltage indicators have shown promise for optical detection of voltage transients, many indicators exhibit low sensitivity when imaged under two-photon illumination. Previous studies thus fell short of visualizing voltage dynamics in individual neurons in single trials. Here, we report ASAP2s, a novel voltage indicator with improved sensitivity. By imaging ASAP2s using random-access multi-photon microscopy, we demonstrate robust single-trial detection of action potentials in organotypic slice cultures. We also show that ASAP2s enables two-photon imaging of graded potentials in organotypic slice cultures and in Drosophila. These results demonstrate that the combination of ASAP2s and fast two-photon imaging methods enables detection of neural electrical activity with subcellular spatial resolution and millisecond-timescale precision.

DOI:http://dx.doi.org/10.7554/eLife.25690.001

Synaptic plasticity in dendrites: complications and coping strategies

The elaborate morphology, nonlinear membrane mechanisms and spatiotemporally varying synaptic activation patterns of dendrites complicate the expression, compartmentalization and modulation of synaptic plasticity. To grapple with this complexity, we start with the observation that neurons in different brain areas face markedly different learning problems, and dendrites of different neuron types contribute to the cell's input-output function in markedly different ways. By committing to specific assumptions regarding a neuron's learning problem and its input-output function, specific inferences can be drawn regarding the synaptic plasticity mechanisms and outcomes that we 'ought' to expect for that neuron. Exploiting this assumption-driven approach can help both in interpreting existing experimental data and designing future experiments aimed at understanding the brain's myriad learning processes.

The Segregated Expression of Voltage-Gated Potassium and Sodium Channels in Neuronal Membranes: Functional Implications and Regulatory Mechanisms

Neurons are highly polarized cells with apparent functional and morphological differences between dendrites and axon. A critical determinant for the molecular and functional identity of axonal and dendritic segments is the restricted expression of voltage-gated ion channels (VGCs). Several studies show an uneven distribution of ion channels and their differential regulation within dendrites and axons, which is a prerequisite for an appropriate integration of synaptic inputs and the generation of adequate action potential (AP) firing patterns. This review article will focus on the signaling pathways leading to segmented expression of voltage-gated potassium and sodium ion channels at the neuronal plasma membrane and the regulatory mechanisms ensuring segregated functions. We will also discuss the relevance of proper ion channel targeting for neuronal physiology and how alterations in polarized distribution contribute to neuronal pathology.

Mapping the function of neuronal ion channels in model and experiment

Ion channel models are the building blocks of computational neuron models. Their biological fidelity is therefore crucial for the interpretation of simulations. However, the number of published models, and the lack of standardization, make the comparison of ion channel models with one another and with experimental data difficult. Here, we present a framework for the automated large-scale classification of ion channel models. Using annotated metadata and responses to a set of voltage-clamp protocols, we assigned 2378 models of voltage- and calcium-gated ion channels coded in NEURON to 211 clusters. The IonChannelGenealogy (ICGenealogy) web interface provides an interactive resource for the categorization of new and existing models and experimental recordings. It enables quantitative comparisons of simulated and/or measured ion channel kinetics, and facilitates field-wide standardization of experimentally-constrained modeling.

Dendritic Spikes in Sensory Perception

What is the function of dendritic spikes? One might argue that they provide conditions for neuronal plasticity or that they are essential for neural computation. However, despite a long history of dendritic research, the physiological relevance of dendritic spikes in brain function remains unknown. This could stem from the fact that most studies on dendrites have been performed in vitro. Fortunately, the emergence of novel techniques such as improved two-photon microscopy, genetically encoded calcium indicators (GECIs), and optogenetic tools has provided the means for vital breakthroughs in in vivo dendritic research. These technologies enable the investigation of the functions of dendritic spikes in behaving animals, and thus, help uncover the causal relationship between dendritic spikes, and sensory information processing and synaptic plasticity. Understanding the roles of dendritic spikes in brain function would provide mechanistic insight into the relationship between the brain and the mind. In this review article, we summarize the results of studies on dendritic spikes from a historical perspective and discuss the recent advances in our understanding of the role of dendritic spikes in sensory perception.

Dendritic NMDA spikes are necessary for timing-dependent associative LTP in CA3 pyramidal cells

The computational repertoire of neurons is enhanced by regenerative electrical signals initiated in dendrites. These events, referred to as dendritic spikes, can act as cell-intrinsic amplifiers of synaptic input. Among these signals, dendritic NMDA spikes are of interest in light of their correlation with synaptic LTP induction. Because it is not possible to block NMDA spikes pharmacologically while maintaining NMDA receptors available to initiate synaptic plasticity, it remains unclear whether NMDA spikes alone can trigger LTP. Here we use dendritic recordings and calcium imaging to analyse the role of NMDA spikes in associative LTP in CA3 pyramidal cells. We show that NMDA spikes produce regenerative branch-specific calcium transients. Decreasing the probability of NMDA spikes reduces LTP, whereas increasing their probability enhances LTP. NMDA spikes and LTP occur without back-propagating action potentials. However, action potentials can facilitate LTP induction by promoting NMDA spikes. Thus, NMDA spikes are necessary and sufficient to produce the critical postsynaptic depolarization required for associative LTP in CA3 pyramidal cells.