Distance-dependent differences in synapse number and AMPA receptor expression in hippocampal CA1 pyramidal neurons

Strategies to dissect microglia-synaptic interactions during aging and in Alzheimer's disease

Age is the largest risk factor for developing Alzheimer's disease (AD), a neurodegenerative disorder that causes a progressive and severe dementia. The underlying cause of cognitive deficits seen in AD is thought to be the disconnection of neural circuits that control memory and executive functions. Insight into the mechanisms by which AD diverges from normal aging will require identifying precisely which cellular events are driven by aging and which are impacted by AD-related pathologies. Since microglia, the brain-resident macrophages, are known to have critical roles in the formation and maintenance of neural circuits through synaptic pruning, they are well-positioned to modulate synaptic connectivity in circuits sensitive to aging or AD. In this review, we provide an overview of the current state of the field and on emerging technologies being employed to elucidate microglia-synaptic interactions in aging and AD. We also discuss the importance of leveraging genetic diversity to study how these interactions are shaped across more realistic contexts. We propose that these approaches will be essential to define specific aging- and disease-relevant trajectories for more personalized therapeutics aimed at reducing the effects of age or AD pathologies on the brain. This article is part of the Special Issue on "Microglia".

Equal levels of pre- and postsynaptic potentiation produce unequal outcomes

Which proportion of the long-term potentiation (LTP) expressed in the bulk of excitatory synapses is postsynaptic and which presynaptic remains debatable. To understand better the possible impact of either LTP form, we explored a realistic model of a CA1 pyramidal cell equipped with known membrane mechanisms and multiple, stochastic excitatory axo-spinous synapses. Our simulations were designed to establish an input-output transfer function, the dependence between the frequency of presynaptic action potentials triggering probabilistic synaptic discharges and the average frequency of postsynaptic spiking. We found that, within the typical physiological range, potentiation of the postsynaptic current results in a greater overall output than an equivalent increase in presynaptic release probability. This difference grows stronger at lower input frequencies and lower release probabilities. Simulations with a non-hierarchical circular network of principal neurons indicated that equal increases in either synaptic fidelity or synaptic strength of individual connections also produce distinct changes in network activity, although the network phenomenology is likely to be complex. These observations should help to interpret the machinery of LTP phenomena documented in situ. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

A novel multivariate time series forecasting dendritic neuron model for COVID-19 pandemic transmission tendency

A novel coronavirus discovered in late 2019 (COVID-19) quickly spread into a global epidemic and, thankfully, was brought under control by 2022. Because of the virus's unknown mutations and the vaccine's waning potency, forecasting is still essential for resurgence prevention and medical resource management. Computational efficiency and long-term accuracy are two bottlenecks for national-level forecasting. This study develops a novel multivariate time series forecasting model, the densely connected highly flexible dendritic neuron model (DFDNM) to predict daily and weekly positive COVID-19 cases. DFDNM's high flexibility mechanism improves its capacity to deal with nonlinear challenges. The dense introduction of shortcut connections alleviates the vanishing and exploding gradient problems, encourages feature reuse, and improves feature extraction. To deal with the rapidly growing parameters, an improved variation of the adaptive moment estimation (AdamW) algorithm is employed as the learning algorithm for the DFDNM because of its strong optimization ability. The experimental results and statistical analysis conducted across three Japanese prefectures confirm the efficacy and feasibility of the DFDNM while outperforming various state-of-the-art machine learning models. To the best of our knowledge, the proposed DFDNM is the first to restructure the dendritic neuron model's neural architecture, demonstrating promising use in multivariate time series prediction. Because of its optimal performance, the DFDNM may serve as an important reference for national and regional government decision-makers aiming to optimize pandemic prevention and medical resource management. We also verify that DFDMN is efficiently applicable not only to COVID-19 transmission prediction, but also to more general multivariate prediction tasks. It leads us to believe that it might be applied as a promising prediction model in other fields.

Regulation by Presynaptic NMDA Receptors of Non-Linear Postsynaptic Summation of the Cortical Input to CA1 Pyramidal Neurons

Entorhinal cortex (EC) LIII and LII glutamatergic neurons make monosynaptic connections onto distal apical dendrites of hippocampal CA1 and CA2 pyramidal neurons (PNs), respectively, through perforant path (PP) projections. We previously reported that a brief train of PP stimuli evokes strong supralinear temporal summation of excitatory postsynaptic potentials (EPSPs) in CA1 PNs that requires NMDAR activation, with relatively little summation in CA2 PNs in mice of either sex. Here we provide evidence from combined immunogold electron microscopy, cell-type specific genetic deletion and pharmacology that the NMDARs required for supralinear temporal summation of the CA1 PP EPSP are presynaptic, located in the PP terminals. Moreover, we found that the number of NMDARs in PP terminals innervating CA1 PNs is significantly greater than that found in PP terminals innervating CA2 PNs, providing a potential explanation for the difference in temporal summation in these two classes of hippocampal PNs.

Tyro3 promotes the maturation of glutamatergic synapses

The receptor tyrosine kinase Tyro3 is abundantly expressed in neurons of the neocortex, hippocampus, and striatum, but its role in these cells is unknown. We found that neuronal expression of this receptor was markedly up-regulated in the postnatal mouse neocortex immediately prior to the final development of glutamatergic synapses. In the absence of Tyro3, cortical and hippocampal synapses never completed end-stage differentiation and remained electrophysiologically and ultrastructurally immature. Tyro3-/- cortical neurons also exhibited diminished plasma membrane expression of the GluA2 subunits of AMPA-type glutamate receptors, which are essential to mature synaptic function. Correspondingly, GluA2 membrane insertion in wild-type neurons was stimulated by Gas6, a Tyro3 ligand widely expressed in the postnatal brain. Behaviorally, Tyro3-/- mice displayed learning enhancements in spatial recognition and fear-conditioning assays. Together, these results demonstrate that Tyro3 promotes the functional maturation of glutamatergic synapses by driving plasma membrane translocation of GluA2 AMPA receptor subunits.

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.

Sexually dimorphic characteristics of dopamine D1 receptor-expressing neurons within the shell of the nucleus accumbens of adolescent mice

Background

Adolescence, a developmental stage, is characterized by psychosocial and biological changes. The nucleus accumbens (NAc), a striatal brain region composed of the core (NAcC) and shell (NAcSh), has been linked to risk-taking behavior and implicated in reward seeking and evaluation. Most neurons in the NAc are medium spiny neurons (MSNs) that express dopamine D1 receptors (D1R+) and/or dopamine D2 receptors (D2R+). Changes in dopaminergic and glutamatergic systems occur during adolescence and converge in the NAc. While there are previous investigations into sex differences in membrane excitability and synaptic glutamate transmission in both subdivisions of the NAc, to our knowledge, none have specified NAcSh D1R+MSNs from mice during mid-adolescence.

Methods

Sagittal brain slices containing the NAc were prepared from B6.Cg-Tg(Drd1a-tdTomato)6Calak/J mice of both sexes from postnatal days 35-47. Stained smears were made from vaginal samples from female mice to identify the stage of Estrous at death. Whole-cell electrophysiology recordings were collected from NAcSh D1R+MSNs in the form of membrane-voltage responses to current injections and spontaneous excitatory postsynaptic currents (sEPSCs).

Results

The action potential duration was longer in males than infemales. Additionally, the frequency of sEPSCs was higher in females, and the mean event amplitude was smaller than that in males. We found no evidence of the observed sex differences being driven by the stage of the Estrous cycle and no physiological parameter significantly varied with respect to the Estrous cycle.

Conclusions

Taken together, our results indicate that NAcSh D1R+MSNs exhibit sex differences during mid-adolescence that are independent of the stage of Estrous, in both AP waveform and glutamate transmission, possibly due to changes in voltage-gated potassium channels and α-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) glutamate receptors, respectively.

Modification of the synaptic cleft under excitatory conditions

The synaptic cleft is the extracellular part of the synapse, bridging the pre- and postsynaptic membranes. The geometry and molecular organization of the cleft is gaining increased attention as an important determinant of synaptic efficacy. The present study by electron microscopy focuses on short-term morphological changes at the synaptic cleft under excitatory conditions. Depolarization of cultured hippocampal neurons with high K+ results in an increased frequency of synaptic profiles with clefts widened at the periphery (open clefts), typically exhibiting patches of membranes lined by postsynaptic density, but lacking associated presynaptic membranes (18.0% open clefts in high K+ compared to 1.8% in controls). Similarly, higher frequencies of open clefts were observed in adult brain upon a delay of perfusion fixation to promote excitatory/ischemic conditions. Inhibition of basal activity in cultured neurons through the application of TTX results in the disappearance of open clefts whereas application of NMDA increases their frequency (19.0% in NMDA vs. 5.3% in control and 2.6% in APV). Depletion of extracellular Ca2+ with EGTA also promotes an increase in the frequency of open clefts (16.6% in EGTA vs. 4.0% in controls), comparable to that by depolarization or NMDA, implicating dissociation of Ca2+-dependent trans-synaptic bridges. Dissociation of transsynaptic bridges under excitatory conditions may allow perisynaptic mobile elements, such as AMPA receptors to enter the cleft. In addition, peripheral opening of the cleft would facilitate neurotransmitter clearance and thus may have a homeostatic and/or protective function.

Dendritic distribution of autophagosomes underlies pathway-selective induction of LTD

The mechanism of long-term depression (LTD), a cellular substrate for learning, memory, and behavioral flexibility, is extensively studied in Schaffer collateral (SC) synapses, with inhibition of autophagy identified as a key factor. SC inputs terminate at basal and proximal apical dendrites, whereas distal apical dendrites receive inputs from the temporoammonic pathway (TAP). Here, we demonstrate that TAP and SC synapses have a shared LTD mechanism reliant on NMDA receptors, caspase-3, and autophagy inhibition. Despite this shared LTD mechanism, proximal apical dendrites contain more autophagosomes than distal apical dendrites. Additionally, unlike SC LTD, which diminishes with age, TAP LTD persists into adulthood. Our previous study shows that the high autophagy in adulthood disallows SC LTD induction. The reduction of autophagosomes from proximal to distal dendrites, combined with distinct LTD inducibility at SC and TAP synapses, suggests a model where the differential distribution of autophagosomes in dendrites gates LTD inducibility at specific circuits.

Neuronal glutamate transporters control reciprocal inhibition and gain modulation in D1 medium spiny neurons

Understanding the function of glutamate transporters has broad implications for explaining how neurons integrate information and relay it through complex neuronal circuits. Most of what is currently known about glutamate transporters, specifically their ability to maintain glutamate homeostasis and limit glutamate diffusion away from the synaptic cleft, is based on studies of glial glutamate transporters. By contrast, little is known about the functional implications of neuronal glutamate transporters. The neuronal glutamate transporter EAAC1 is widely expressed throughout the brain, particularly in the striatum, the primary input nucleus of the basal ganglia, a region implicated with movement execution and reward. Here, we show that EAAC1 limits synaptic excitation onto a population of striatal medium spiny neurons identified for their expression of D1 dopamine receptors (D1-MSNs). In these cells, EAAC1 also contributes to strengthen lateral inhibition from other D1-MSNs. Together, these effects contribute to reduce the gain of the input-output relationship and increase the offset at increasing levels of synaptic inhibition in D1-MSNs. By reducing the sensitivity and dynamic range of action potential firing in D1-MSNs, EAAC1 limits the propensity of mice to rapidly switch between behaviors associated with different reward probabilities. Together, these findings shed light on some important molecular and cellular mechanisms implicated with behavior flexibility in mice.

Genetic context controls early microglia-synaptic interactions in mouse models of Alzheimer's disease

Common features of Alzheimer's disease (AD) include amyloid pathology, microglia activation and synaptic dysfunction, however, the causal relationships amongst them remains unclear. Further, human data suggest susceptibility and resilience to AD neuropathology is controlled by genetic context, a factor underexplored in mouse models. To this end, we leveraged viral strategies to label an AD-vulnerable neuronal circuit in CA1 dendrites projecting to the frontal cortex in genetically diverse C57BL/6J (B6) and PWK/PhJ (PWK) APP/PS1 mouse strains and used PLX5622 to non-invasively deplete brain microglia. Reconstructions of labeled neurons revealed microglia-dependent changes in dendritic spine density and morphology in B6 wild-type (WT) and APP/PS1 yet a marked stability of spines across PWK mice. We further showed that synaptic changes depend on direct microglia-dendrite interactions in B6. APP/PS1 but not PWK. APP/PS1 mice. Collectively, these results demonstrate that microglia-dependent synaptic alterations in a specific AD-vulnerable projection pathway are differentially controlled by genetic context.

Neural Information Processing and Computations of Two-Input Synapses

Information processing in artificial neural networks is largely dependent on the nature of neuron models. While commonly used models are designed for linear integration of synaptic inputs, accumulating experimental evidence suggests that biological neurons are capable of nonlinear computations for many converging synaptic inputs via homo- and heterosynaptic mechanisms. This nonlinear neuronal computation may play an important role in complex information processing at the neural circuit level. Here we characterize the dynamics and coding properties of neuron models on synaptic transmissions delivered from two hidden states. The neuronal information processing is influenced by the cooperative and competitive interactions among synapses and the coherence of the hidden states. Furthermore, we demonstrate that neuronal information processing under two-input synaptic transmission can be mapped to linearly nonseparable XOR as well as basic AND/OR operations. In particular, the mixtures of linear and nonlinear neuron models outperform the fashion-MNIST test compared to the neural networks consisting of only one type. This study provides a computational framework for assessing information processing of neuron and synapse models that may be beneficial for the design of brain-inspired artificial intelligence algorithms and neuromorphic systems.

The Shaping of AMPA Receptor Surface Distribution by Neuronal Activity

Neurotransmission is critically dependent on the number, position, and composition of receptor proteins on the postsynaptic neuron. Of these, α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptors (AMPARs) are responsible for the majority of postsynaptic depolarization at excitatory mammalian synapses following glutamate release. AMPARs are continually trafficked to and from the cell surface, and once at the surface, AMPARs laterally diffuse in and out of synaptic domains. Moreover, the subcellular distribution of AMPARs is shaped by patterns of activity, as classically demonstrated by the synaptic insertion or removal of AMPARs following the induction of long-term potentiation (LTP) and long-term depression (LTD), respectively. Crucially, there are many subtleties in the regulation of AMPARs, and exactly how local and global synaptic activity drives the trafficking and retention of synaptic AMPARs of different subtypes continues to attract attention. Here we will review how activity can have differential effects on AMPAR distribution and trafficking along with its subunit composition and phosphorylation state, and we highlight some of the controversies and remaining questions. As the AMPAR field is extensive, to say the least, this review will focus primarily on cellular and molecular studies in the hippocampus. We apologise to authors whose work could not be cited directly owing to space limitations.

Differential dendritic integration of long-range inputs in association cortex via subcellular changes in synaptic AMPA-to-NMDA receptor ratio

Synaptic NMDA receptors can produce powerful dendritic supralinearities that expand the computational repertoire of single neurons and their respective circuits. This form of supralinearity may represent a general principle for synaptic integration in thin dendrites. However, individual cortical neurons receive many diverse classes of input that may require distinct postsynaptic decoding schemes. Here, we show that sensory, motor, and thalamic inputs preferentially target basal, apical oblique, and distal tuft dendrites, respectively, in layer 5b pyramidal neurons of the mouse retrosplenial cortex, a visuospatial association area. These dendritic compartments exhibited differential expression of NMDA receptor-mediated supralinearity due to systematic changes in the AMPA-to-NMDA receptor ratio. Our results reveal a new schema for integration in cortical pyramidal neurons, in which dendrite-specific changes in synaptic receptors support input-localized decoding. This coexistence of multiple modes of dendritic integration in single neurons has important implications for synaptic plasticity and cortical computation.

R-type voltage-gated Ca2+ channels mediate A-type K+ current regulation of synaptic input in hippocampal dendrites

The subthreshold voltage-gated transient K+ current (IA) carried by pore-forming Kv4.2 subunits regulates the propagation of synaptic input, dendritic excitability, and synaptic plasticity in CA1 pyramidal neuron dendrites of the hippocampus. We report that the Ca2+ channel subunit Cav2.3 regulates IA in this cell type. We initially identified Cav2.3 as a Kv4.2-interacting protein in a proteomic screen and we confirmed Cav2.3-Kv4.2 complex association using multiple techniques. Functionally, Cav2.3 Ca2+-entry increases Kv4.2-mediated whole-cell current due to an increase in Kv4.2 surface expression. Using pharmacology and Cav2.3 knockout mice, we show that Cav2.3 regulates the dendritic gradient of IA. Furthermore, the loss of Cav2.3 function leads to the enhancement of AMPA receptor-mediated synaptic currents and NMDA receptor-mediated spine Ca2+ influx. These results propose that Cav2.3 and Kv4.2 are integral constituents of an ion channel complex that affects synaptic function in the hippocampus.

Dendritic synapse geometry optimizes binaural computation in a sound localization circuit

Clustering of synapses allows neurons to overcome attenuation of electrical signals at dendrites. However, we show in avian binaural coincidence detectors computing interaural time difference for sound localization that clustering of synapses rather promotes the dendritic attenuation but augments the intensity tolerance of the binaural computations. Using glutamate uncaging, we found in the neurons that synapses were clustered at distal dendritic branches. Modeling revealed that this strengthened sublinear integration within a dendritic tree but enabled the integration of signals from different trees when inputs grow stronger, preventing monoaural output and maintaining the dynamic range of binaural computation. The extent of this clustering differed according to dendritic length and frequency tuning of neurons, being most prominent for long dendrites and low-frequency tuning. This ensures binaural spatial hearing for wide intensity and frequency ranges, highlighting the importance of coupling of synapse geometry with dendritic morphology and input frequency in sensory signal processing.

Developmental emergence of two-stage nonlinear synaptic integration in cerebellar interneurons

Synaptic transmission, connectivity, and dendritic morphology mature in parallel during brain development and are often disrupted in neurodevelopmental disorders. Yet how these changes influence the neuronal computations necessary for normal brain function are not well understood. To identify cellular mechanisms underlying the maturation of synaptic integration in interneurons, we combined patch-clamp recordings of excitatory inputs in mouse cerebellar stellate cells (SCs), three-dimensional reconstruction of SC morphology with excitatory synapse location, and biophysical modeling. We found that postnatal maturation of postsynaptic strength was homogeneously reduced along the somatodendritic axis, but dendritic integration was always sublinear. However, dendritic branching increased without changes in synapse density, leading to a substantial gain in distal inputs. Thus, changes in synapse distribution, rather than dendrite cable properties, are the dominant mechanism underlying the maturation of neuronal computation. These mechanisms favor the emergence of a spatially compartmentalized two-stage integration model promoting location-dependent integration within dendritic subunits.

Mechanisms of endocannabinoid control of synaptic plasticity

The endogenous cannabinoid transmitter system regulates synaptic transmission throughout the nervous system. Unlike conventional transmitters, specific stimuli induce synthesis of endocannabinoids (eCBs) in the postsynaptic neuron, and these travel backwards to modulate presynaptic inputs. In doing so, eCBs can induce short-term changes in synaptic strength and longer-term plasticity. While this eCB regulation is near ubiquitous, it displays major regional and synapse specific variations with different synapse specific forms of short-versus long-term plasticity throughout the brain. These differences are due to the plethora of pre- and postsynaptic mechanisms which have been implicated in eCB signalling, the intricacies of which are only just being realised. In this review, we shall describe the current understanding and highlight new advances in this area, with a focus on the retrograde action of eCBs at CB1 receptors (CB₁Rs).

Gamma-protocadherin localization at the synapse is associated with parameters of synaptic maturation

Clustered protocadherins (Pcdhs) are a family of ~60 cadherin-like proteins (divided into subclasses α, β, and γ) that regulate dendrite morphology and neural connectivity. Their expression is controlled through epigenetic regulation at a gene cluster encoding the molecules. During neural development, Pcdhs mediate dendrite self-avoidance in some neuronal types through an uncharacterized anti-adhesive mechanism. Pcdhs are also important for dendritic complexity in cortical neurons likely through a pro-adhesive mechanism. Pcdhs have also been postulated to participate in synaptogenesis and connectivity. Some synaptic defects were noted in knockout animals, including synaptic number and physiology, but the role of these molecules in synaptic development is not understood. The effect of Pcdh knockout on dendritic patterning may present a confound to studying synaptogenesis. We showed previously that Pcdh-γs are highly enriched in intracellular compartments in dendrites and spines with localization at only a few synaptic clefts. To gain insight into how Pcdh-γs might affect synapses, we compared synapses that harbored Pcdh-γs versus those that did not for parameters of synaptic maturation including pre- and postsynaptic size, postsynaptic perforations, and spine morphology by light microscopy in cultured hippocampal neurons and by serial section immuno-electron microscopy in hippocampal CA1. In mature neurons, synapses immunopositive for Pcdh-γs were larger in diameter with more frequent perforations. Analysis of spines in cultured neurons revealed that mushroom spines were more frequently immunopositive for Pcdh-γs at their tips than thin spines. These results suggest that Pcdh-γ function at the synapse may be related to promotion of synaptic maturation and stabilization.

Three-Dimensional Structure of Dendritic Spines Revealed by Volume Electron Microscopy Techniques

Electron microscopy (EM)-based synaptology is a fundamental discipline for achieving a complex wiring diagram of the brain. A quantitative understanding of synaptic ultrastructure also serves as a basis to estimate the relative magnitude of synaptic transmission across individual circuits in the brain. Although conventional light microscopic techniques have substantially contributed to our ever-increasing understanding of the morphological characteristics of the putative synaptic junctions, EM is the gold standard for systematic visualization of the synaptic morphology. Furthermore, a complete three-dimensional reconstruction of an individual synaptic profile is required for the precise quantitation of different parameters that shape synaptic transmission. While volumetric imaging of synapses can be routinely obtained from the transmission EM (TEM) imaging of ultrathin sections, it requires an unimaginable amount of effort and time to reconstruct very long segments of dendrites and their spines from the serial section TEM images. The challenges of low throughput EM imaging have been addressed to an appreciable degree by the development of automated EM imaging tools that allow imaging and reconstruction of dendritic segments in a realistic time frame. Here, we review studies that have been instrumental in determining the three-dimensional ultrastructure of synapses. With a particular focus on dendritic spine synapses in the rodent brain, we discuss various key studies that have highlighted the structural diversity of spines, the principles of their organization in the dendrites, their presynaptic wiring patterns, and their activity-dependent structural remodeling.

The importance of ultrastructural analysis of memory

Plasticity of glutamatergic synapses in the hippocampus is believed to underlie learning and memory processes. Surprisingly, very few studies report long-lasting structural changes of synapses induced by behavioral training. It remains, therefore, unclear which synaptic changes in the hippocampus contribute to memory storage. Here, we systematically compare how long-term potentiation of synaptic transmission (LTP) (a primary form of synaptic plasticity and cellular model of memory) and behavioral training affect hippocampal glutamatergic synapses at the ultrastructural level enabled by electron microscopy. The review of the literature indicates that while LTP induces growth of dendritic spines and post-synaptic densities (PSD), that represent postsynaptic part of a glutamatergic synapse, after behavioral training there is transient (< 6 h) synaptogenesis and long-lasting (> 24 h) increase in PSD volume (without a significant change of dendritic spine volume), indicating that training-induced PSD growth may reflect long-term enhancement of synaptic functions. Additionally, formation of multi-innervated spines (MIS), is associated with long-term memory in aged mice and LTP-deficient mutant mice. Since volume of PSD, as well as atypical synapses, can be reliably observed only with electron microscopy, we argue that the ultrastructural level of analysis is required to reveal synaptic changes that are associated with long-term storage of information in the brain.

Chronic Low Dose Neutron Exposure Results in Altered Neurotransmission Properties of the Hippocampus-Prefrontal Cortex Axis in Both Mice and Rats

The proposed deep space exploration to the moon and later to Mars will result in astronauts receiving significant chronic exposures to space radiation (SR). SR exposure results in multiple neurocognitive impairments. Recently, our cross-species (mouse/rat) studies reported impaired associative memory formation in both species following a chronic 6-month low dose exposure to a mixed field of neutrons (1 mGy/day for a total dose pf 18 cGy). In the present study, we report neutron exposure induced synaptic plasticity in the medial prefrontal cortex, accompanied by microglial activation and significant synaptic loss in the hippocampus. In a parallel study, neutron exposure was also found to alter fluorescence assisted single synaptosome LTP (FASS-LTP) in the hippocampus of rats, that may be related to a reduced ability to insert AMPAR into the post-synaptic membrane, which may arise from increased phosphorylation of the serine 845 residue of the GluA1 subunit. Thus, we demonstrate for the first time, that low dose chronic neutron irradiation impacts homeostatic synaptic plasticity in the hippocampal-cortical circuit in two rodent species, and that the ability to successfully encode associative recognition memory is a dynamic, multicircuit process, possibly involving compensatory changes in AMPAR density on the synaptic surface.

NMDA Receptors Enhance the Fidelity of Synaptic Integration

Excitatory synaptic transmission in many neurons is mediated by two coexpressed ionotropic glutamate receptor subtypes, AMPA and NMDA receptors, that differ in kinetics, ion selectivity, and voltage-sensitivity. AMPA receptors have fast kinetics and are voltage-insensitive, while NMDA receptors have slower kinetics and increased conductance at depolarized membrane potentials. Here, we report that the voltage dependency and kinetics of NMDA receptors act synergistically to stabilize synaptic integration of EPSPs across spatial and voltage domains. Simulations of synaptic integration in simplified and morphologically realistic dendritic trees revealed that the combined presence of AMPA and NMDA conductances reduce the variability of somatic responses to spatiotemporal patterns of excitatory synaptic input presented at different initial membrane potentials and/or in different dendritic domains. This moderating effect of the NMDA conductance on synaptic integration was robust across a wide range of AMPA-to-NMDA ratios, and results from synergistic interaction of NMDA kinetics (which reduces variability across membrane potential) and voltage dependence (which favors stabilization across dendritic location). When combined with AMPA conductance, the NMDA conductance compensates for voltage-dependent and impedance-dependent changes in synaptic driving force, and distance-dependent attenuation of synaptic potentials arriving at the axon, to increase the fidelity of synaptic integration and EPSP-spike coupling across both neuron state (i.e., initial membrane potential) and dendritic location of synaptic input. Thus, synaptic NMDA receptors convey advantages for synaptic integration that are independent of, but fully compatible with, their importance for coincidence detection and synaptic plasticity.

Cognitive aging is associated with redistribution of synaptic weights in the hippocampus

Behaviors that rely on the hippocampus are particularly susceptible to chronological aging, with many aged animals (including humans) maintaining cognition at a young adult-like level, but many others the same age showing marked impairments. It is unclear whether the ability to maintain cognition over time is attributable to brain maintenance, sufficient cognitive reserve, compensatory changes in network function, or some combination thereof. While network dysfunction within the hippocampal circuit of aged, learning-impaired animals is well-documented, its neurobiological substrates remain elusive. Here we show that the synaptic architecture of hippocampal regions CA1 and CA3 is maintained in a young adult-like state in aged rats that performed comparably to their young adult counterparts in both trace eyeblink conditioning and Morris water maze learning. In contrast, among learning-impaired, but equally aged rats, we found that a redistribution of synaptic weights amplifies the influence of autoassociational connections among CA3 pyramidal neurons, yet reduces the synaptic input onto these same neurons from the dentate gyrus. Notably, synapses within hippocampal region CA1 showed no group differences regardless of cognitive ability. Taking the data together, we find the imbalanced synaptic weights within hippocampal CA3 provide a substrate that can explain the abnormal firing characteristics of both CA3 and CA1 pyramidal neurons in aged, learning-impaired rats. Furthermore, our work provides some clarity with regard to how some animals cognitively age successfully, while others' lifespans outlast their "mindspans."

Cortical response selectivity derives from strength in numbers of synapses

Single neocortical neurons are driven by populations of excitatory inputs, which form the basis of neuronal selectivity to features of sensory input. Excitatory connections are thought to mature during development through activity-dependent Hebbian plasticity1, whereby similarity between presynaptic and postsynaptic activity selectively strengthens some synapses and weakens others2. Evidence in support of this process includes measurements of synaptic ultrastructure and in vitro and in vivo physiology and imaging studies3-8. These corroborating lines of evidence lead to the prediction that a small number of strong synaptic inputs drive neuronal selectivity, whereas weak synaptic inputs are less correlated with the somatic output and modulate activity overall6,7. Supporting evidence from cortical circuits, however, has been limited to measurements of neighbouring, connected cell pairs, raising the question of whether this prediction holds for a broad range of synapses converging onto cortical neurons. Here we measure the strengths of functionally characterized excitatory inputs contacting single pyramidal neurons in ferret primary visual cortex (V1) by combining in vivo two-photon synaptic imaging and post hoc electron microscopy. Using electron microscopy reconstruction of individual synapses as a metric of strength, we find no evidence that strong synapses have a predominant role in the selectivity of cortical neuron responses to visual stimuli. Instead, selectivity appears to arise from the total number of synapses activated by different stimuli. Moreover, spatial clustering of co-active inputs appears to be reserved for weaker synapses, enhancing the contribution of weak synapses to somatic responses. Our results challenge the role of Hebbian mechanisms in shaping neuronal selectivity in cortical circuits, and suggest that selectivity reflects the co-activation of large populations of presynaptic neurons with similar properties and a mixture of strengths.

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.

Deep Learning-Assisted High-Throughput Analysis of Freeze-Fracture Replica Images Applied to Glutamate Receptors and Calcium Channels at Hippocampal Synapses

The molecular anatomy of synapses defines their characteristics in transmission and plasticity. Precise measurements of the number and distribution of synaptic proteins are important for our understanding of synapse heterogeneity within and between brain regions. Freeze-fracture replica immunogold electron microscopy enables us to analyze them quantitatively on a two-dimensional membrane surface. Here, we introduce Darea software, which utilizes deep learning for analysis of replica images and demonstrate its usefulness for quick measurements of the pre- and postsynaptic areas, density and distribution of gold particles at synapses in a reproducible manner. We used Darea for comparing glutamate receptor and calcium channel distributions between hippocampal CA3-CA1 spine synapses on apical and basal dendrites, which differ in signaling pathways involved in synaptic plasticity. We found that apical synapses express a higher density of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors and a stronger increase of AMPA receptors with synaptic size, while basal synapses show a larger increase in N-methyl-D-aspartate (NMDA) receptors with size. Interestingly, AMPA and NMDA receptors are segregated within postsynaptic sites and negatively correlated in density among both apical and basal synapses. In the presynaptic sites, Cav2.1 voltage-gated calcium channels show similar densities in apical and basal synapses with distributions consistent with an exclusion zone model of calcium channel-release site topography.

Distance-dependent regulation of NMDAR nanoscale organization along hippocampal neuron dendrites

Hippocampal pyramidal neurons are characterized by a unique arborization subdivided in segregated dendritic domains receiving distinct excitatory synaptic inputs with specific properties and plasticity rules that shape their respective contributions to synaptic integration and action potential firing. Although the basal regulation and plastic range of proximal and distal synapses are known to be different, the composition and nanoscale organization of key synaptic proteins at these inputs remains largely elusive. Here we used superresolution imaging and single nanoparticle tracking in rat hippocampal neurons to unveil the nanoscale topography of native GluN2A- and GluN2B-NMDA receptors (NMDARs)-which play key roles in the use-dependent adaptation of glutamatergic synapses-along the dendritic arbor. We report significant changes in the nanoscale organization of GluN2B-NMDARs between proximal and distal dendritic segments, whereas the topography of GluN2A-NMDARs remains similar along the dendritic tree. Remarkably, the nanoscale organization of GluN2B-NMDARs at proximal segments depends on their interaction with calcium/calmodulin-dependent protein kinase II (CaMKII), which is not the case at distal segments. Collectively, our data reveal that the nanoscale organization of NMDARs changes along dendritic segments in a subtype-specific manner and is shaped by the interplay with CaMKII at proximal dendritic segments, shedding light on our understanding of the functional diversity of hippocampal glutamatergic synapses.

Membrane potential dynamics underlying context-dependent sensory responses in the hippocampus

As animals navigate, they must identify features within context. In the mammalian brain, the hippocampus has the ability to separately encode different environmental contexts, even when they share some prominent features. To do so, neurons respond to sensory features in a context-dependent manner; however, it is not known how this encoding emerges. To examine this, we performed electrical recordings in the hippocampus as mice navigated in two distinct virtual environments. In CA1, both synaptic input to single neurons and population activity strongly tracked visual cues in one environment, whereas responses were almost completely absent when the same cue was presented in a second environment. A very similar, highly context-dependent pattern of cue-driven spiking was also observed in CA3. These results indicate that CA1 inherits a complex spatial code from upstream regions, including CA3, that have already computed a context-dependent representation of environmental features.

Impact of functional synapse clusters on neuronal response selectivity

Clustering of functionally similar synapses in dendrites is thought to affect neuronal input-output transformation by triggering local nonlinearities. However, neither the in vivo impact of synaptic clusters on somatic membrane potential (sVm), nor the rules of cluster formation are elucidated. We develop a computational approach to measure the effect of functional synaptic clusters on sVm response of biophysical model CA1 and L2/3 pyramidal neurons to in vivo-like inputs. We demonstrate that small synaptic clusters appearing with random connectivity do not influence sVm. With structured connectivity,  ~10-20 synapses/cluster are optimal for clustering-based tuning via state-dependent mechanisms, but larger selectivity is achieved by 2-fold potentiation of the same synapses. We further show that without nonlinear amplification of the effect of random clusters, action potential-based, global plasticity rules cannot generate functional clustering. Our results suggest that clusters likely form via local synaptic interactions, and have to be moderately large to impact sVm responses.

Lamina-specific AMPA receptor dynamics following visual deprivation in vivo

Regulation of AMPA receptor (AMPAR) expression is central to synaptic plasticity and brain function, but how these changes occur in vivo remains elusive. Here, we developed a method to longitudinally monitor the expression of synaptic AMPARs across multiple cortical layers in awake mice using two-photon imaging. We observed that baseline AMPAR expression in individual spines is highly dynamic with more dynamics in primary visual cortex (V1) layer 2/3 (L2/3) neurons than V1 L5 neurons. Visual deprivation through binocular enucleation induces a synapse-specific and depth-dependent change of synaptic AMPARs in V1 L2/3 neurons, wherein deep synapses are potentiated more than superficial synapses. The increase is specific to L2/3 neurons and absent on apical dendrites of L5 neurons, and is dependent on expression of the AMPAR-binding protein GRIP1. Our study demonstrates that specific neuronal connections, across cortical layers and even within individual neurons, respond uniquely to changes in sensory experience.

Postsynaptic integrative properties of dorsal CA1 pyramidal neuron subpopulations

The population activity of CA1 pyramidal neurons (PNs) segregates along anatomical axes with different behaviors, suggesting that CA1 PNs are functionally subspecialized based on somatic location. In dorsal CA1, spatial encoding is biased toward CA2 (CA1c) and in deep layers of the radial axis. In contrast, nonspatial coding peaks toward subiculum (CA1a) and in superficial layers. While preferential innervation by spatial vs. nonspatial input from entorhinal cortex (EC) may contribute to this specialization, it cannot fully explain the range of in vivo responses. Differences in intrinsic properties thus may play a critical role in modulating such synaptic input differences. In this study we examined the postsynaptic integrative properties of dorsal CA1 PNs in six subpopulations along the transverse (CA1c, CA1b, CA1a) and radial (deep, superficial) axes. Our results suggest that active and passive properties of deep and superficial neurons evolve over the transverse axis to promote the functional specialization of CA1c vs. CA1a as dictated by their cortical input. We also find that CA1b is not merely an intermediate mix of its neighbors, but uniquely balances low excitability with superior input integration of its mixed input, as may be required for its proposed role in sequence encoding. Thus synaptic input and intrinsic properties combine to functionally compartmentalize CA1 processing into at least three transverse axis regions defined by the processing schemes of their composite radial axis subpopulations.NEW & NOTEWORTHY There is increasing interest in CA1 pyramidal neuron heterogeneity and the functional relevance of this diversity. We find that active and passive properties evolve over the transverse and radial axes in dorsal CA1 to promote the functional specialization of CA1c and CA1a for spatial and nonspatial memory, respectively. Furthermore, CA1b is not a mean of its neighbors, but features low excitability and superior integrative capabilities, relevant to its role in nonspatial sequence encoding.

Simple models of quantitative firing phenotypes in hippocampal neurons: Comprehensive coverage of intrinsic diversity

Patterns of periodic voltage spikes elicited by a neuron help define its dynamical identity. Experimentally recorded spike trains from various neurons show qualitatively distinguishable features such as delayed spiking, spiking with or without frequency adaptation, and intrinsic bursting. Moreover, the input-dependent responses of a neuron not only show different quantitative features, such as higher spike frequency for a stronger input current injection, but can also exhibit qualitatively different responses, such as spiking and bursting under different input conditions, thus forming a complex phenotype of responses. In previous work, the comprehensive knowledge base of hippocampal neuron types Hippocampome.org systematically characterized various spike pattern phenotypes experimentally identified from 120 neuron types/subtypes. In this paper, we present a complete set of simple phenomenological models that quantitatively reproduce the diverse and complex phenotypes of hippocampal neurons. In addition to point-neuron models, we created compact multi-compartment models with up to four compartments, which will allow spatial segregation of synaptic integration in network simulations. Electrotonic compartmentalization observed in our compact multi-compartment models is qualitatively consistent with experimental observations. The models were created using an automated pipeline based on evolutionary algorithms. This work maps 120 neuron types/subtypes in the rodent hippocampus to a low-dimensional model space and adds another dimension to the knowledge accumulated in Hippocampome.org. Computationally efficient representations of intrinsic dynamics, along with other pieces of knowledge available in Hippocampome.org, provide a biologically realistic platform to explore the large-scale interactions of various neuron types at the mesoscopic level.

Dendritic computations captured by an effective point neuron model

Modeling single-neuron dynamics is the first step to quantitatively understand brain computation. Yet, the existing point neuron models fail to capture dendritic effects, which are crucial for neuronal information processing. We derive an effective point neuron model, which incorporates an additional synaptic integration current arising from the nonlinear interaction between synaptic currents across spatial dendrites. Our model captures the somatic voltage response of a neuron with complex dendrites and is capable of performing rich dendritic computations. Besides its computational efficiency in simulations, our model suggests reexamination of previous studies involving the decomposition of excitatory and inhibitory synaptic inputs based on the existing point neuron framework, e.g., the inhibition is often underestimated in experiment.

Complex dendrites in general present formidable challenges to understanding neuronal information processing. To circumvent the difficulty, a prevalent viewpoint simplifies the neuronal morphology as a point representing the soma, and the excitatory and inhibitory synaptic currents originated from the dendrites are treated as linearly summed at the soma. Despite its extensive applications, the validity of the synaptic current description remains unclear, and the existing point neuron framework fails to characterize the spatiotemporal aspects of dendritic integration supporting specific computations. Using electrophysiological experiments, realistic neuronal simulations, and theoretical analyses, we demonstrate that the traditional assumption of linear summation of synaptic currents is oversimplified and underestimates the inhibition effect. We then derive a form of synaptic integration current within the point neuron framework to capture dendritic effects. In the derived form, the interaction between each pair of synaptic inputs on the dendrites can be reliably parameterized by a single coefficient, suggesting the inherent low-dimensional structure of dendritic integration. We further generalize the form of synaptic integration current to capture the spatiotemporal interactions among multiple synaptic inputs and show that a point neuron model with the synaptic integration current incorporated possesses the computational ability of a spatial neuron with dendrites, including direction selectivity, coincidence detection, logical operation, and a bilinear dendritic integration rule discovered in experiment. Our work amends the modeling of synaptic inputs and improves the computational power of a modeling neuron within the point neuron framework.

Sleep Deprivation by Exposure to Novel Objects Increases Synapse Density and Axon-Spine Interface in the Hippocampal CA1 Region of Adolescent Mice

Sleep has been hypothesized to rebalance overall synaptic strength after ongoing learning during waking leads to net synaptic potentiation. If so, because synaptic strength and size are correlated, synapses on average should be larger after wake and smaller after sleep. This prediction was recently confirmed in mouse cerebral cortex using serial block-face electron microscopy (SBEM). However, whether these findings extend to other brain regions is unknown. Moreover, sleep deprivation by gentle handling was reported to produce hippocampal spine loss, raising the question of whether synapse size and number are differentially affected by sleep and waking. Here we applied SBEM to measure axon-spine interface (ASI), the contact area between pre-synapse and post-synapse, and synapse density in CA1 stratum radiatum. Adolescent YFP-H mice were studied after 6-8 h of sleep (S = 6), spontaneous wake at night (W = 4) or wake enforced during the day by novelty exposure (EW = 4; males/females balanced). In each animal ≥425 ASIs were measured and synaptic vesicles were counted in ~100 synapses/mouse. Reconstructed dendrites included many small, nonperforated synapses and fewer large, perforated synapses. Relative to S, ASI sizes in perforated synapses shifted toward higher values after W and more so after EW. ASI sizes in nonperforated synapses grew after EW relative to S and W, and so did their density. ASI size correlated with presynaptic vesicle number but the proportion of readily available vesicles decreased after EW, suggesting presynaptic fatigue. Thus, CA1 synapses undergo changes consistent with sleep-dependent synaptic renormalization and their number increases after extended wake.SIGNIFICANCE STATEMENT Sleep benefits learning, memory consolidation, and the integration of new with old memories, but the underlying mechanisms remain highly debated. One hypothesis suggests that sleep's cognitive benefits stem from its ability to renormalize total synaptic strength, after ongoing learning during wake leads to net synaptic potentiation. Supporting evidence for this hypothesis mainly comes from the cerebral cortex, including the observation that cortical synapses are larger after wake and smaller after sleep. Using serial electron microscopy, we find here that sleep/wake synaptic changes consistent with sleep-dependent synaptic renormalization also occur in the CA1 region. Thus, the role of sleep in maintaining synaptic homeostasis may extend to the hippocampus, a key area for learning and synaptic plasticity.

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

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

NGL-1/LRRC4C Deletion Moderately Suppresses Hippocampal Excitatory Synapse Development and Function in an Input-Independent Manner

Netrin-G ligand-1 (NGL-1), also known as LRRC4C, is a postsynaptic densities (PSDs)-95-interacting postsynaptic adhesion molecule that interacts trans-synaptically with presynaptic netrin-G1. NGL-1 and its family member protein NGL-2 are thought to promote excitatory synapse development through largely non-overlapping neuronal pathways. While NGL-2 is critical for excitatory synapse development in specific dendritic segments of neurons in an input-specific manner, whether NGL-1 has similar functions is unclear. Here, we show that Lrrc4c deletion in male mice moderately suppresses excitatory synapse development and function, but surprisingly, does so in an input-independent manner. While NGL-1 is mainly detected in the stratum lacunosum moleculare (SLM) layer of the hippocampus relative to the stratum radiatum (SR) layer, NGL-1 deletion leads to decreases in the number of PSDs in both SLM and SR layers in the ventral hippocampus. In addition, both SLM and SR excitatory synapses display suppressed short-term synaptic plasticity in the ventral hippocampus. These morphological and functional changes are either absent or modest in the dorsal hippocampus. The input-independent synaptic changes induced by Lrrc4c deletion involve abnormal translocation of NGL-2 from the SR to SLM layer. These results suggest that Lrrc4c deletion moderately suppresses hippocampal excitatory synapse development and function in an input-independent manner.

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.

Determination of effective synaptic conductances using somatic voltage clamp

The interplay between excitatory and inhibitory neurons imparts rich functions of the brain. To understand the synaptic mechanisms underlying neuronal computations, a fundamental approach is to study the dynamics of excitatory and inhibitory synaptic inputs of each neuron. The traditional method of determining input conductance, which has been applied for decades, employs the synaptic current-voltage (I-V) relation obtained via voltage clamp. Due to the space clamp effect, the measured conductance is different from the local conductance on the dendrites. Therefore, the interpretation of the measured conductance remains to be clarified. Using theoretical analysis, electrophysiological experiments, and realistic neuron simulations, here we demonstrate that there does not exist a transform between the local conductance and the conductance measured by the traditional method, due to the neglect of a nonlinear interaction between the clamp current and the synaptic current in the traditional method. Consequently, the conductance determined by the traditional method may not correlate with the local conductance on the dendrites, and its value could be unphysically negative as observed in experiment. To circumvent the challenge of the space clamp effect and elucidate synaptic impact on neuronal information processing, we propose the concept of effective conductance which is proportional to the local conductance on the dendrite and reflects directly the functional influence of synaptic inputs on somatic membrane potential dynamics, and we further develop a framework to determine the effective conductance accurately. Our work suggests re-examination of previous studies involving conductance measurement and provides a reliable approach to assess synaptic influence on neuronal computation.

To understand synaptic mechanisms underlying neuronal computations, a fundamental approach is to use voltage clamp to measure the dynamics of excitatory and inhibitory input conductances. Due to the space clamp effect, the measured conductance in general deviates from the local input conductance on the dendrites, hence its biological interpretation is questionable, as we demonstrate in this work. We further propose the concept of effective conductance that is proportional to the local input conductance on the dendrites and reflects directly the synaptic impact on spike generation, and develop a framework to determine the effective conductance reliably. Our work provides a biologically plausible metric for elucidating synaptic influence on neuronal computation under the constraint of the space clamp effect.

Dendritic mechanisms of hippocampal place field formation

Place cells in the hippocampus are thought to form a cognitive map of space and a memory of places. How this map forms when animals are exposed to novel environments has been the subject of a great deal of research. Numerous technical advances over the past decade greatly increased our understanding of the precise mechanisms underlying place field formation. In particular, it is now possible to connect cellular and circuit mechanisms of integration, firing, and plasticity discovered in brain slices, to processes taking place in vivo as animals learn and encode novel environments. Here, we focus on recent results and describe the dendritic mechanisms most likely responsible for the formation of place fields. We also discuss key open questions that are likely to be answered in the coming years.

Specificity of Primate Amygdalar Pathways to Hippocampus

The amygdala projects to hippocampus in pathways through which affective or social stimuli may influence learning and memory. We investigated the still unknown amygdalar termination patterns and their postsynaptic targets in hippocampus from system to synapse in rhesus monkeys of both sexes. The amygdala robustly innervated the stratum lacunosum-moleculare layer of cornu ammonis fields and uncus anteriorly. Sparser terminations in posterior hippocampus innervated the radiatum and pyramidal layers at the prosubicular/CA1 juncture. The terminations, which were larger than other afferents in the surrounding neuropil, position the amygdala to influence hippocampal input anteriorly, and its output posteriorly. Most amygdalar boutons (76-80%) innervated spines of excitatory hippocampal neurons, and most of the remaining innervated presumed inhibitory neurons, identified by morphology and label with parvalbumin or calretinin, which distinguished nonoverlapping neurochemical classes of hippocampal inhibitory neurons. In CA1, amygdalar axons innervated some calretinin neurons, which disinhibit pyramidal neurons. By contrast, in CA3 the amygdala innervated both calretinin and parvalbumin neurons; the latter strongly inhibit nearby excitatory neurons. In CA3, amygdalar pathways also made closely spaced dual synapses on excitatory neurons. The strong excitatory synapses in CA3 may facilitate affective context representations and trigger sharp-wave ripples associated with memory consolidation. When the amygdala is excessively activated during traumatic events, the specialized innervation of excitatory neurons and the powerful parvalbumin inhibitory neurons in CA3 may allow the suppression of activity of nearby neurons that receive weaker nonamygdalar input, leading to biased passage of highly charged affective stimuli and generalized fear.SIGNIFICANCE STATEMENT Strong pathways from the amygdala targeted the anterior hippocampus, and more weakly its posterior sectors, positioned to influence a variety of emotional and cognitive functions. In hippocampal field CA1, the amygdala innervated some calretinin neurons, which disinhibit excitatory neurons. By contrast, in CA3 the amygdala innervated calretinin as well as some of the powerful parvalbumin inhibitory neurons and may help balance the activity of neural ensembles to allow social interactions, learning, and memory. These results suggest that when the amygdala is hyperactive during emotional upheaval, it strongly activates excitatory hippocampal neurons and parvalbumin inhibitory neurons in CA3, which can suppress nearby neurons that receive weaker input from other sources, biasing the passage of stimuli with high emotional import and leading to generalized fear.

Impacts of Spike Shape Variations on Synaptic Communication

Understanding the communication theoretical capabilities of information transmission among neurons, known as neuro-spike communication, is a significant step in developing bio-inspired solutions for nanonetworking. In this paper, we focus on a part of this communication known as synaptic transmission for pyramidal neurons in the Cornu Ammonis area of the hippocampus location in the brain and propose a communication-based model for it that includes effects of spike shape variation on neural calcium signaling and the vesicle release process downstream of it. For this aim, we find impacts of spike shape variation on opening of voltage-dependent calcium channels, which control the release of vesicles from the pre-synaptic neuron by changing the influx of calcium ions. Moreover, we derive the structure of the optimum receiver based on the Neyman-Pearson detection method to find the effects of spike shape variations on the functionality of neuro-spike communication. Numerical results depict that changes in both spike width and amplitude affect the error detection probability. Moreover, these two factors do not control the performance of the system independently. Hence, a proper model for neuro-spike communication should contain effects of spike shape variations during axonal transmission on both synaptic propagation and spike generation mechanisms to enable us to accurately explain the performance of this communication paradigm.

Single excitatory axons form clustered synapses onto CA1 pyramidal cell dendrites

CA1 pyramidal neurons are a major output of the hippocampus and encode features of experience that constitute episodic memories. Feature-selective firing of these neurons results from the dendritic integration of inputs from multiple brain regions. While it is known that synchronous activation of spatially clustered inputs can contribute to firing through the generation of dendritic spikes, there is no established mechanism for spatiotemporal synaptic clustering. Here we show that single presynaptic axons form multiple, spatially clustered inputs onto the distal, but not proximal, dendrites of CA1 pyramidal neurons. These compound connections exhibit ultrastructural features indicative of strong synapses and occur much more commonly in entorhinal than in thalamic afferents. Computational simulations revealed that compound connections depolarize dendrites in a biophysically efficient manner, owing to their inherent spatiotemporal clustering. Our results suggest that distinct afferent projections use different connectivity motifs that differentially contribute to dendritic integration.

Glutamatergic synapses are structurally and biochemically complex because of multiple plasticity processes: long-term potentiation, long-term depression, short-term potentiation and scaling

Synapses are complex because they perform multiple functions, including at least six mechanistically different forms of plasticity. Here, I comment on recent developments regarding these processes. (i) Short-term potentiation (STP), a Hebbian process that requires small amounts of synaptic input, appears to make strong contributions to some forms of working memory. (ii) The rules for long-term potentiation (LTP) induction in CA3 have been clarified: induction does not depend obligatorily on backpropagating sodium spikes but, rather, on dendritic branch-specific N-methyl-d-aspartate (NMDA) spikes. (iii) Late LTP, a process that requires a dopamine signal (and is therefore neoHebbian), is mediated by trans-synaptic growth of the synapse, a growth that occurs about an hour after LTP induction. (iv) LTD processes are complex and include both homosynaptic and heterosynaptic forms. (v) Synaptic scaling produced by changes in activity levels are not primarily cell-autonomous, but rather depend on network activity. (vi) The evidence for distance-dependent scaling along the primary dendrite is firm, and a plausible structural-based mechanism is suggested.Ideas about the mechanisms of synaptic function need to take into consideration newly emerging data about synaptic structure. Recent super-resolution studies indicate that glutamatergic synapses are modular (module size 70-80 nm), as predicted by theoretical work. Modules are trans-synaptic structures and have high concentrations of postsynaptic density-95 (PSD-95) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptor. These modules function as quasi-independent loci of AMPA-mediated transmission and may be independently modifiable, suggesting a new understanding of quantal transmission.This article is part of the themed issue 'Integrating Hebbian and homeostatic plasticity.'

Topological Regulation of Synaptic AMPA Receptor Expression by the RNA-Binding Protein CPEB3

Synaptic receptors gate the neuronal response to incoming signals, but they are not homogeneously distributed on dendrites. A spatially defined receptor distribution can preferentially amplify certain synaptic inputs, resize receptive fields of neurons, and optimize information processing within a neuronal circuit. Thus, a longstanding question is how the spatial organization of synaptic receptors is achieved. Here, we find that action potentials provide local signals that influence the distribution of synaptic AMPA receptors along dendrites in mouse cerebellar stellate cells. Graded dendritic depolarizations elevate CPEB3 protein at proximal dendrites, where we suggest that CPEB3 binds to GluA2 mRNA, suppressing GluA2 protein synthesis leading to a distance-dependent increase in synaptic GluA2 AMPARs. The activity-induced expression of CPEB3 requires increased Ca(2+) and PKC activation. Our results suggest a cell-autonomous mechanism where sustained postsynaptic firing drives graded local protein synthesis, thus directing the spatial organization of synaptic AMPARs.

Heterophilic Type II Cadherins Are Required for High-Magnitude Synaptic Potentiation in the Hippocampus

Hippocampal CA3 neurons form synapses with CA1 neurons in two layers, stratum oriens (SO) and stratum radiatum (SR). Each layer develops unique synaptic properties but molecular mechanisms that mediate these differences are unknown. Here, we show that SO synapses normally have significantly more mushroom spines and higher-magnitude long-term potentiation (LTP) than SR synapses. Further, we discovered that these differences require the Type II classic cadherins, cadherins-6, -9, and -10. Though cadherins typically function via trans-cellular homophilic interactions, our results suggest presynaptic cadherin-9 binds postsynaptic cadherins-6 and -10 to regulate mushroom spine density and high-magnitude LTP in the SO layer. Loss of these cadherins has no effect on the lower-magnitude LTP typically observed in the SR layer, demonstrating that cadherins-6, -9, and -10 are gatekeepers for high-magnitude LTP. Thus, Type II cadherins may uniquely contribute to the specificity and strength of synaptic changes associated with learning and memory.

Parvalbumin-expressing interneurons can act solo while somatostatin-expressing interneurons act in chorus in most cases on cortical pyramidal cells

Neural circuits in the cerebral cortex consist primarily of excitatory pyramidal (Pyr) cells and inhibitory interneurons. Interneurons are divided into several subtypes, in which the two major groups are those expressing parvalbumin (PV) or somatostatin (SOM). These subtypes of interneurons are reported to play distinct roles in tuning and/or gain of visual response of pyramidal cells in the visual cortex. It remains unclear whether there is any quantitative and functional difference between the PV → Pyr and SOM → Pyr connections. We compared unitary inhibitory postsynaptic currents (uIPSCs) evoked by electrophysiological activation of single presynaptic interneurons with population IPSCs evoked by photo-activation of a mass of interneurons in vivo and in vitro in transgenic mice in which PV or SOM neurons expressed channelrhodopsin-2, and found that at least about 14 PV neurons made strong connections with a postsynaptic Pyr cell while a much larger number of SOM neurons made weak connections. Activation or suppression of single PV neurons modified visual responses of postsynaptic Pyr cells in 6 of 7 pairs whereas that of single SOM neurons showed no significant modification in 8 of 11 pairs, suggesting that PV neurons can act solo whereas most of SOM neurons may act in chorus on Pyr cells.

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.

The characterization of hippocampal theta-driving neurons - a time-delayed mutual information approach

Interneurons are important for computation in the brain, in particular, in the information processing involving the generation of theta oscillations in the hippocampus. Yet the functional role of interneurons in the theta generation remains to be elucidated. Here we use time-delayed mutual information to investigate information flow related to a special class of interneurons—theta-driving neurons in the hippocampal CA1 region of the mouse—to characterize the interactions between theta-driving neurons and theta oscillations. For freely behaving mice, our results show that information flows from the activity of theta-driving neurons to the theta wave, and the firing activity of theta-driving neurons shares a substantial amount of information with the theta wave regardless of behavioral states. Via realistic simulations of a CA1 pyramidal neuron, we further demonstrate that theta-driving neurons possess the characteristics of the cholecystokinin-expressing basket cells (CCK-BC). Our results suggest that it is important to take into account the role of CCK-BC in the generation and information processing of theta oscillations.