Plasticity of dendritic function

Distinct Modulation of I h by Synaptic Potentiation in Excitatory and Inhibitory Neurons

Selective modifications in the expression or function of dendritic ion channels regulate the propagation of synaptic inputs and determine the intrinsic excitability of a neuron. Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels open upon membrane hyperpolarization and conduct a depolarizing inward current (I h). HCN channels are enriched in the dendrites of hippocampal pyramidal neurons where they regulate the integration of synaptic inputs. Synaptic plasticity can bidirectionally modify dendritic HCN channels in excitatory neurons depending on the strength of synaptic potentiation. In inhibitory neurons, however, the dendritic expression and modulation of HCN channels are largely unknown. In this study, we systematically compared the modulation of I h by synaptic potentiation in hippocampal CA1 pyramidal neurons and stratum radiatum (sRad) interneurons in mouse organotypic cultures. I h properties were similar in inhibitory and excitatory neurons and contributed to resting membrane potential and action potential firing. We found that in sRad interneurons, HCN channels were downregulated after synaptic plasticity, irrespective of the strength of synaptic potentiation. This suggests differential regulation of I h in excitatory and inhibitory neurons, possibly signifying their distinct role in network activity.

The plasticity of pyramidal neurons in the behaving brain

Neurons are plastic. That is, they change their activity according to different behavioural conditions. This endows pyramidal neurons with an incredible computational power for the integration and processing of synaptic inputs. Plasticity can be investigated at different levels of investigation within a single neuron, from spines to dendrites, to synaptic input. Although most of our knowledge stems from the in vitro brain slice preparation, plasticity plays a vital role during behaviour by providing a flexible substrate for the execution of appropriate actions in our ever-changing environment. Owing to advances in recording techniques, the plasticity of neurons and the neural networks in which they are embedded is now beginning to be realized in the in vivo intact brain. This review focuses on the structural and functional synaptic plasticity of pyramidal neurons, with a specific focus on the latest developments from in vivo studies. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Functional architecture of intracellular oscillations in hippocampal dendrites

Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions, report an advancing gradient of dendritic theta phase along the basal-tuft axis, and describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find that spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.

Functional architecture of intracellular oscillations in hippocampal dendrites

Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions and report an advancing gradient of dendritic theta phase along the basal-tuft axis, then describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.

The impact of Hodgkin-Huxley models on dendritic research

For the past seven decades, the Hodgkin-Huxley (HH) formalism has been an invaluable tool in the arsenal of neuroscientists, allowing for robust and reproducible modelling of ionic conductances and the electrophysiological phenomena they underlie. Despite its apparent age, its role as a cornerstone of computational neuroscience has not waned. The discovery of dendritic regenerative events mediated by ionic and synaptic conductances has solidified the importance of HH-based models further, yielding new predictions concerning dendritic integration, synaptic plasticity and neuronal computation. These predictions are often validated through in vivo and in vitro experiments, advancing our understanding of the neuron as a biological system and emphasizing the importance of HH-based detailed computational models as an instrument of dendritic research. In this article, we discuss recent studies in which the HH formalism is used to shed new light on dendritic function and its role in neuronal phenomena.

Voltage dynamics of dendritic integration and back-propagation in vivo

Neurons integrate synaptic inputs within their dendrites and produce spiking outputs, which then propagate down the axon and back into the dendrites where they contribute to plasticity. Mapping the voltage dynamics in dendritic arbors of live animals is crucial for understanding neuronal computation and plasticity rules. Here we combine patterned channelrhodopsin activation with dual-plane structured illumination voltage imaging, for simultaneous perturbation and monitoring of dendritic and somatic voltage in Layer 2/3 pyramidal neurons in anesthetized and awake mice. We examined the integration of synaptic inputs and compared the dynamics of optogenetically evoked, spontaneous, and sensory-evoked back-propagating action potentials (bAPs). Our measurements revealed a broadly shared membrane voltage throughout the dendritic arbor, and few signatures of electrical compartmentalization among synaptic inputs. However, we observed spike rate acceleration-dependent propagation of bAPs into distal dendrites. We propose that this dendritic filtering of bAPs may play a critical role in activity-dependent plasticity.

Synergies between synaptic and HCN channel plasticity dictates firing rate homeostasis and mutual information transfer in hippocampal model neuron

Homeostasis is a precondition for any physiological system of any living organism. Nonetheless, models of learning and memory that are based on processes of synaptic plasticity are unstable by nature according to Hebbian rules, and it is not fully clear how homeostasis is maintained during these processes. This is where theoretical and computational frameworks can help in gaining a deeper understanding of the various cellular processes that enable homeostasis in the face of plasticity. A previous simplistic single compartmental model with a single synapse showed that maintaining input/output response homeostasis and stable synaptic learning could be enabled by introducing a linear relationship between synaptic plasticity and HCN conductance plasticity. In this study, we aimed to examine whether this approach could be extended to a more morphologically realistic model that entails multiple synapses and gradients of various VGICs. In doing so, we found that a linear relationship between synaptic plasticity and HCN conductance plasticity was able to maintain input/output response homeostasis in our morphologically realistic model, where the slope of the linear relationship was dependent on baseline HCN conductance and synaptic permeability values. An increase in either baseline HCN conductance or synaptic permeability value led to a decrease in the slope of the linear relationship. We further show that in striking contrast to the single compartment model, here linear relationship was insufficient in maintaining stable synaptic learning despite maintaining input/output response homeostasis. Additionally, we showed that homeostasis of input/output response profiles was at the expense of decreasing the mutual information transfer due to the increase in noise entropy, which could not be fully rescued by optimizing the linear relationship between synaptic and HCN conductance plasticity. Finally, we generated a place cell model based on theta oscillations and show that synaptic plasticity disrupts place cell activity. Whereas synaptic plasticity accompanied by HCN conductance plasticity through linear relationship maintains the stability of place cell activity. Our study establishes potential differences between a single compartmental model and a morphologically realistic model.

Active Dendrites and Local Field Potentials: Biophysical Mechanisms and Computational Explorations

Neurons and glial cells are endowed with membranes that express a rich repertoire of ion channels, transporters, and receptors. The constant flux of ions across the neuronal and glial membranes results in voltage fluctuations that can be recorded from the extracellular matrix. The high frequency components of this voltage signal contain information about the spiking activity, reflecting the output from the neurons surrounding the recording location. The low frequency components of the signal, referred to as the local field potential (LFP), have been traditionally thought to provide information about the synaptic inputs that impinge on the large dendritic trees of various neurons. In this review, we discuss recent computational and experimental studies pointing to a critical role of several active dendritic mechanisms that can influence the genesis and the location-dependent spectro-temporal dynamics of LFPs, spanning different brain regions. We strongly emphasize the need to account for the several fast and slow dendritic events and associated active mechanisms - including gradients in their expression profiles, inter- and intra-cellular spatio-temporal interactions spanning neurons and glia, heterogeneities and degeneracy across scales, neuromodulatory influences, and activitydependent plasticity - towards gaining important insights about the origins of LFP under different behavioral states in health and disease. We provide simple but essential guidelines on how to model LFPs taking into account these dendritic mechanisms, with detailed methodology on how to account for various heterogeneities and electrophysiological properties of neurons and synapses while studying LFPs.

Life and death in the hippocampus: What's bad?

The hippocampal formation is crucial for the generation and regulation of several brain functions, including memory and learning processes; however, it is vulnerable to neurological disorders, such as epilepsy. Temporal lobe epilepsy (TLE), the most common type of epilepsy, changes the hippocampal circuitry and excitability, under the contribution of both neuronal degeneration and abnormal neurogenesis. Classically, neurodegeneration affects sensitive areas of the hippocampus, such as dentate gyrus (DG) hilus, as well as specific fields of the Ammon's horn, CA3, and CA1. In addition, the proliferation, migration, and abnormal integration of newly generated hippocampal granular cells (GCs) into the brain characterize TLE neurogenesis. Robust studies over the years have intensely discussed the effects of death and life in the hippocampus, though there are still questions to be answered about their possible benefits and risks. Here, we review the impacts of death and life in the hippocampus, discussing its influence on TLE, providing new perspectives or insights for the implementation of new possible therapeutic targets. This article is part of the Special Issue "NEWroscience 2018".

Effects of Ih and TASK-like shunting current on dendritic impedance in layer 5 pyramidal-tract neurons

Pyramidal neurons in neocortex have complex input-output relationships that depend on their morphologies, ion channel distributions, and the nature of their inputs, but which cannot be replicated by simple integrate-and-fire models. The impedance properties of their dendritic arbors, such as resonance and phase shift, shape neuronal responses to synaptic inputs and provide intraneuronal functional maps reflecting their intrinsic dynamics and excitability. Experimental studies of dendritic impedance have shown that neocortical pyramidal tract neurons exhibit distance-dependent changes in resonance and impedance phase with respect to the soma. We, therefore, investigated how well several biophysically detailed multicompartment models of neocortical layer 5 pyramidal tract neurons reproduce the location-dependent impedance profiles observed experimentally. Each model tested here exhibited location-dependent impedance profiles, but most captured either the observed impedance amplitude or phase, not both. The only model that captured features from both incorporates hyperpolarization-activated cyclic nucleotide-gated (HCN) channels and a shunting current, such as that produced by Twik-related acid-sensitive K+ (TASK) channels. TASK-like channel density in this model was proportional to local HCN channel density. We found that although this shunting current alone is insufficient to produce resonance or realistic phase response, it modulates all features of dendritic impedance, including resonance frequencies, resonance strength, synchronous frequencies, and total inductive phase. We also explored how the interaction of HCN channel current (Ih) and a TASK-like shunting current shape synaptic potentials and produce degeneracy in dendritic impedance profiles, wherein different combinations of Ih and shunting current can produce the same impedance profile.NEW & NOTEWORTHY We simulated chirp current stimulation in the apical dendrites of 5 biophysically detailed multicompartment models of neocortical pyramidal tract neurons and found that a combination of HCN channels and TASK-like channels produced the best fit to experimental measurements of dendritic impedance. We then explored how HCN and TASK-like channels can shape the dendritic impedance as well as the voltage response to synaptic currents.

Neuromorphic Engineering: From Biological to Spike-Based Hardware Nervous Systems

The human brain is a sophisticated, high-performance biocomputer that processes multiple complex tasks in parallel with high efficiency and remarkably low power consumption. Scientists have long been pursuing an artificial intelligence (AI) that can rival the human brain. Spiking neural networks based on neuromorphic computing platforms simulate the architecture and information processing of the intelligent brain, providing new insights for building AIs. The rapid development of materials engineering, device physics, chip integration, and neuroscience has led to exciting progress in neuromorphic computing with the goal of overcoming the von Neumann bottleneck. Herein, fundamental knowledge related to the structures and working principles of neurons and synapses of the biological nervous system is reviewed. An overview is then provided on the development of neuromorphic hardware systems, from artificial synapses and neurons to spike-based neuromorphic computing platforms. It is hoped that this review will shed new light on the evolution of brain-like computing.

The Input-Output Relation of Primary Nociceptive Neurons is Determined by the Morphology of the Peripheral Nociceptive Terminals

The output from the peripheral terminals of primary nociceptive neurons, which detect and encode the information regarding noxious stimuli, is crucial in determining pain sensation. The nociceptive terminal endings are morphologically complex structures assembled from multiple branches of different geometry, which converge in a variety of forms to create the terminal tree. The output of a single terminal is defined by the properties of the transducer channels producing the generation potentials and voltage-gated channels, translating the generation potentials into action potential (AP) firing. However, in the majority of cases, noxious stimuli activate multiple terminals; thus, the output of the nociceptive neuron is defined by the integration and computation of the inputs of the individual terminals. Here, we used a computational model of nociceptive terminal tree to study how the architecture of the terminal tree affects the input-output relation of the primary nociceptive neurons. We show that the input-output properties of the nociceptive neurons depend on the length, the axial resistance (Ra), and location of individual terminals. Moreover, we show that activation of multiple terminals by a capsaicin-like current allows summation of the responses from individual terminals, thus leading to increased nociceptive output. Stimulation of the terminals in simulated models of inflammatory or neuropathic hyperexcitability led to a change in the temporal pattern of AP firing, emphasizing the role of temporal code in conveying key information about changes in nociceptive output in pathologic conditions, leading to pain hypersensitivity.SIGNIFICANCE STATEMENT Noxious stimuli are detected by terminal endings of primary nociceptive neurons, which are organized into morphologically complex terminal trees. The information from multiple terminals is integrated along the terminal tree, computing the neuronal output, which propagates toward the CNS, thus shaping the pain sensation. Here, we revealed that the structure of the nociceptive terminal tree determines the output of nociceptive neurons. We show that the integration of noxious information depends on the morphology of the terminal trees and how this integration and, consequently, the neuronal output change under pathologic conditions. Our findings help to predict how nociceptive neurons encode noxious stimuli and how this encoding changes in pathologic conditions, leading to pain.

Short-term depression and long-term plasticity together tune sensitive range of synaptic plasticity

Synaptic efficacy is subjected to activity-dependent changes on short- and long time scales. While short-term changes decay over minutes, long-term modifications last from hours up to a lifetime and are thought to constitute the basis of learning and memory. Both plasticity mechanisms have been studied extensively but how their interaction shapes synaptic dynamics is little known. To investigate how both short- and long-term plasticity together control the induction of synaptic depression and potentiation, we used numerical simulations and mathematical analysis of a calcium-based model, where pre- and postsynaptic activity induces calcium transients driving synaptic long-term plasticity. We found that the model implementing known synaptic short-term dynamics in the calcium transients can be successfully fitted to long-term plasticity data obtained in visual- and somatosensory cortex. Interestingly, the impact of spike-timing and firing rate changes on plasticity occurs in the prevalent firing rate range, which is different in both cortical areas considered here. Our findings suggest that short- and long-term plasticity are together tuned to adapt plasticity to area-specific activity statistics such as firing rates.

Synaptic long-term plasticity, the long-lasting change in efficacy of connections between neurons, is believed to underlie learning and memory. Synapses furthermore change their efficacy reversibly in an activity-dependent manner on the subsecond time scale, referred to as short-term plasticity. It is not known how both synaptic plasticity mechanisms—long- and short-term—interact during activity epochs. To address this question, we used a biologically-inspired plasticity model in which calcium drives changes in synaptic efficacy. We applied the model to plasticity data from visual- and somatosensory cortex and found that synaptic changes occur in very different firing rate ranges, which correspond to the prevalent firing rates in both structures. Our results suggest that short- and long-term plasticity act in a well concerted fashion.

Synergistic excitability plasticity in cerebellar functioning

The cerebellum, a universal processor for sensory acquisition and internal models, and its association with synaptic and nonsynaptic plasticity have been envisioned as the biological correlates of learning, perception, and even thought. Indeed, the cerebellum is no longer considered merely as the locus of motor coordination and its learning. Here, we introduce the mechanisms underlying the induction of multiple types of plasticity in cerebellar circuit and give an overview focusing on the plasticity of nonsynaptic intrinsic excitability. The discovery of long-term potentiation of synaptic responsiveness in hippocampal neurons led investigations into changes of their intrinsic excitability. This activity-dependent potentiation of neuronal excitability is distinct from that of synaptic efficacy. Systematic examination of excitability plasticity has indicated that the modulation of various types of Ca²⁺ - and voltage-dependent K⁺ channels underlies the phenomenon, which is also triggered by immune activity. Intrinsic plasticity is expressed specifically on dendrites and modifies the integrative processing and filtering effect. In Purkinje cells, modulation of the discordance of synaptic current on soma and dendrite suggested a novel type of cellular learning mechanism. This property enables a plausible synergy between synaptic efficacy and intrinsic excitability, by amplifying electrical conductivity and influencing the polarity of bidirectional synaptic plasticity. Furthermore, the induction of intrinsic plasticity in the cerebellum correlates with motor performance and cognitive processes, through functional connections from the cerebellar nuclei to neocortex and associated regions: for example, thalamus and midbrain. Taken together, recent advances in neuroscience have begun to shed light on the complex functioning of nonsynaptic excitability and the synergy.

Treatment with Mesenchymal-Derived Extracellular Vesicles Reduces Injury-Related Pathology in Pyramidal Neurons of Monkey Perilesional Ventral Premotor Cortex

Functional recovery after cortical injury, such as stroke, is associated with neural circuit reorganization, but the underlying mechanisms and efficacy of therapeutic interventions promoting neural plasticity in primates are not well understood. Bone marrow mesenchymal stem cell-derived extracellular vesicles (MSC-EVs), which mediate cell-to-cell inflammatory and trophic signaling, are thought be viable therapeutic targets. We recently showed, in aged female rhesus monkeys, that systemic administration of MSC-EVs enhances recovery of function after injury of the primary motor cortex, likely through enhancing plasticity in perilesional motor and premotor cortices. Here, using in vitro whole-cell patch-clamp recording and intracellular filling in acute slices of ventral premotor cortex (vPMC) from rhesus monkeys (Macaca mulatta) of either sex, we demonstrate that MSC-EVs reduce injury-related physiological and morphologic changes in perilesional layer 3 pyramidal neurons. At 14-16 weeks after injury, vPMC neurons from both vehicle- and EV-treated lesioned monkeys exhibited significant hyperexcitability and predominance of inhibitory synaptic currents, compared with neurons from nonlesioned control brains. However, compared with vehicle-treated monkeys, neurons from EV-treated monkeys showed lower firing rates, greater spike frequency adaptation, and excitatory:inhibitory ratio. Further, EV treatment was associated with greater apical dendritic branching complexity, spine density, and inhibition, indicative of enhanced dendritic plasticity and filtering of signals integrated at the soma. Importantly, the degree of EV-mediated reduction of injury-related pathology in vPMC was significantly correlated with measures of behavioral recovery. These data show that EV treatment dampens injury-related hyperexcitability and restores excitatory:inhibitory balance in vPMC, thereby normalizing activity within cortical networks for motor function.SIGNIFICANCE STATEMENT Neuronal plasticity can facilitate recovery of function after cortical injury, but the underlying mechanisms and efficacy of therapeutic interventions promoting this plasticity in primates are not well understood. Our recent work has shown that intravenous infusions of mesenchymal-derived extracellular vesicles (EVs) that are involved in cell-to-cell inflammatory and trophic signaling can enhance recovery of motor function after injury in monkey primary motor cortex. This study shows that this EV-mediated enhancement of recovery is associated with amelioration of injury-related hyperexcitability and restoration of excitatory-inhibitory balance in perilesional ventral premotor cortex. These findings demonstrate the efficacy of mesenchymal EVs as a therapeutic to reduce injury-related pathologic changes in the physiology and structure of premotor pyramidal neurons and support recovery of function.

Modification of Synaptic-Input Clustering by Intrinsic Excitability Plasticity on Cerebellar Purkinje Cell Dendrites

The role of dendrites in the integration of widespread synaptic activity has been studied in experiments and theories (Johnston et al., 1996; Magee, 2007). However, whether the conduction of synaptic currents from dendrites to the soma depends on excitability of those dendritic branches is unclear. How modulation of the branch excitability affects the conduction of synaptic inputs and their selection on dendrites is also elusive. Here, I performed simultaneous voltage-clamp recordings from the soma and dendrites of single cerebellar Purkinje neurons in male Sprague-Dawley rats and analyzed the relationship between spontaneous EPSCs on both sides. I found that EPSCs on distal dendrites have a salient discordance in amplitude compared with those on the soma. Furthermore, individual ratios of the EPSC concurrently recorded on the soma and dendrites were not unique, but discrete, suggesting the occurrence of various attenuations in different paths of dendritic branches to the soma. The obtained data and simulations indicate several distinct groups (4.5 ± 0.3, n = 22 somatodendritic recordings) of co-occurred synaptic inputs in Purkinje cell dendrites. This clustering of synaptic currents was suggested to emerge at farther distances than the secondary bifurcations. Finally, ratios of the co-EPSCs were uniformly distributed after either intrinsic plasticity induction or SK-channel blockade. Overall, results suggest that in Purkinje cells the excitability along the dendrite processes modulates the conduction of EPSCs and makes active inputs heterogeneous through SK channel activity, intrinsic plasticity, and dendritic branching. These properties of dendrites may confer branch-specific computational power to neurons.SIGNIFICANCE STATEMENT I have previously studied the "non-synaptic" plasticity of the intrinsic excitability in the cerebellar Purkinje cells (Belmeguenai et al., 2010), and branch-specific increase of intrinsic excitability of the dendrites (Ohtsuki et al., 2012b; Ohtsuki and Hansel, 2018) through the downregulation of SK (small conductance Ca2+-activated K+) channels. In this study, I show that a dendritic filtering of synaptic electroconductivity is heterogeneous among the branches on distal dendrites and that the increase in the dendritic excitability accompanied with the intrinsic plasticity alters a state with the heterogeneity to a globally excitable state in Purkinje neurons. My findings propose a new learning model relying on the intrinsic excitability plasticity of the dendritic branch fields.

Approaches and Limitations in the Investigation of Synaptic Transmission and Plasticity

The numbers and strengths of synapses in the brain change throughout development, and even into adulthood, as synaptic inputs are added, eliminated, and refined in response to ongoing neural activity. A number of experimental techniques can assess these changes, including single-cell electrophysiological recording which offers measurements of synaptic inputs with high temporal resolution. Coupled with electrical stimulation, photoactivatable opsins, and caged compounds, to facilitate fine spatiotemporal control over release of neurotransmitters, electrophysiological recordings allow for precise dissection of presynaptic and postsynaptic mechanisms of action. Here, we discuss the strengths and pitfalls of various techniques commonly used to analyze synapses, including miniature excitatory/inhibitory (E/I) postsynaptic currents, evoked release, and optogenetic stimulation. Together, these techniques can provide multiple lines of convergent evidence to generate meaningful insight into the emergence of circuit connectivity and maturation. A full understanding of potential caveats and alternative explanations for findings is essential to avoid data misinterpretation.

Stores, Channels, Glue, and Trees: Active Glial and Active Dendritic Physiology

Glial cells and neuronal dendrites were historically assumed to be passive structures that play only supportive physiological roles, with no active contribution to information processing in the central nervous system. Research spanning the past few decades has clearly established this assumption to be far from physiological realities. Whereas the discovery of active channel conductances and their localized plasticity was the turning point for dendritic structures, the demonstration that glial cells release transmitter molecules and communicate across the neuroglia syncytium through calcium wave propagation constituted path-breaking discoveries for glial cell physiology. An additional commonality between these two structures is the ability of calcium stores within their endoplasmic reticulum (ER) to support active propagation of calcium waves, which play crucial roles in the spatiotemporal integration of information within and across cells. Although there have been several demonstrations of regulatory roles of glial cells and dendritic structures in achieving common physiological goals such as information propagation and adaptability through plasticity, studies assessing physiological interactions between these two active structures have been few and far. This lacuna is especially striking given the strong connectivity that is known to exist between these two structures through several complex and tightly intercoupled mechanisms that also recruit their respective ER structures. In this review, we present brief overviews of the parallel literatures on active dendrites and active glial physiology and make a strong case for future studies to directly assess the strong interactions between these two structures in regulating physiology and pathophysiology of the brain.

Fundamentals of the modern theory of the phenomenon of "pain" from the perspective of a systematic approach. Neurophysiological basis. Part 1: A brief presentation of key subcellular and cellular ctructural elements of the central nervous system

The phenomenon of “pain” is a psychophysiological phenomenon that is actualized in the mind of a person as a result of the systemic response of his body to certain external and internal stimuli. The heart of the corresponding mental processes is certain neurophysiological processes, which in turn are caused by a certain form of the systemic structural and functional organization of the central nervous system (CNS). Thus, the systemic structural and functional organization of the central nervous system of a person, determining the corresponding psychophysiological state in a specific time interval, determines its psycho-emotional states or reactions manifested by the pain phenomenon. The nervous system of the human body has a hierarchical structure and is a morphologically and functionally complete set of different, interconnected, nervous and structural formations. The basis of the structural formations of the nervous system is nervous tissue. It is a system of interconnected differentials of nerve cells, neuroglia and glial macrophages, providing specific functions of perception of stimulation, excitation, generation of nerve impulses and its transmission. The neuron and each of its compartments (spines, dendrites, catfish, axon) is an autonomous, plastic, active, structural formation with complex computational properties. One of them – dendrites – plays a key role in the integration and processing of information. Dendrites, due to their morphology, provide neurons with unique electrical and plastic properties and cause variations in their computational properties. The morphology of dendrites: 1) determines – a) the number and type of contacts that a particular neuron can form with other neurons; b) the complexity, diversity of its functions; c) its computational operations; 2) determines – a) variations in the computational properties of a neuron (variations of the discharges between bursts and regular forms of pulsation); b) back distribution of action potentials. Dendritic spines can form synaptic connection – one of the main factors for increasing the diversity of forms of synaptic connections of neurons. Their volume and shape can change over a short period of time, and they can rotate in space, appear and disappear by themselves. Spines play a key role in selectively changing the strength of synaptic connections during the memorization and learning process. Glial cells are active participants in diffuse transmission of nerve impulses in the brain. Astrocytes form a three-dimensional, functionally “syncytia-like” formation, inside of which there are neurons, thus causing their specific microenvironment. They and neurons are structurally and functionally interconnected, based on which their permanent interaction occurs. Oligodendrocytes provide conditions for the generation and transmission of nerve impulses along the processes of neurons and play a significant role in the processes of their excitation and inhibition. Microglial cells play an important role in the formation of the brain, especially in the formation and maintenance of synapses. Thus, the CNS should be considered as a single, functionally “syncytia-like”, structural entity. Because the three-dimensional distribution of dendritic branches in space is important for determining the type of information that goes to a neuron, it is necessary to consider the three-dimensionality of their structure when analyzing the implementation of their functions.

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

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

Two Distinct Sets of Ca2+ and K+ Channels Are Activated at Different Membrane Potentials by the Climbing Fiber Synaptic Potential in Purkinje Neuron Dendrites

In cerebellar Purkinje neuron dendrites, the transient depolarization associated with a climbing fiber (CF) EPSP activates voltage-gated Ca²⁺ channels (VGCCs), voltage-gated K⁺ channels (VGKCs), and Ca²⁺-activated SK and BK K⁺ channels. The resulting membrane potential (V _m) and Ca²⁺ transients play a fundamental role in dendritic integration and synaptic plasticity of parallel fiber inputs. Here we report a detailed investigation of the kinetics of dendritic Ca²⁺ and K⁺ channels activated by CF-EPSPs, based on optical measurements of V _m and Ca²⁺ transients and on a single-compartment NEURON model reproducing experimental data. We first measured V _m and Ca²⁺ transients associated with CF-EPSPs at different initial V _m, and we analyzed the changes in the Ca²⁺ transients produced by the block of each individual VGCCs, of A-type VGKCs and of SK and BK channels. Then, we constructed a model that includes six active ion channels to accurately match experimental signals and extract the physiological kinetics of each channel. We found that two different sets of channels are selectively activated. When the dendrite is hyperpolarized, CF-EPSPs mainly activate T-type VGCCs, SK channels, and A-type VGKCs that limit the transient V _m ∼ <0 mV. In contrast, when the dendrite is depolarized, T-type VGCCs and A-type VGKCs are inactivated and CF-EPSPs activate P/Q-type VGCCs, high-voltage activated VGKCs, and BK channels, leading to Ca²⁺ spikes. Thus, the potentially activity-dependent regulation of A-type VGKCs, controlling the activation of this second set of channels, is likely to play a crucial role in signal integration and plasticity in Purkinje neuron dendrites.SIGNIFICANCE STATEMENT The climbing fiber synaptic input transiently depolarizes the dendrite of cerebellar Purkinje neurons generating a signal that plays a fundamental role in dendritic integration. This signal is mediated by two types of Ca²⁺ channels and four types of K⁺ channels. Thus, understanding the kinetics of all of these channels is crucial for understanding PN function. To obtain this information, we used an innovative strategy that merges ultrafast optical membrane potential and Ca²⁺ measurements, pharmacological analysis, and computational modeling. We found that, according to the initial membrane potential, the climbing fiber depolarizing transient activates two distinct sets of channels. Moreover, A-type K⁺ channels limit the activation of P/Q-type Ca²⁺ channels and associated K⁺ channels, thus preventing the generation of Ca²⁺ spikes.

Distal Dendritic Enrichment of HCN1 Channels in Hippocampal CA1 Is Promoted by Estrogen, but Does Not Require Reelin

HCN1 compartmentalization in CA1 pyramidal cells, essential for hippocampal information processing, is believed to be controlled by the extracellular matrix protein Reelin. Expression of Reelin, in turn, is stimulated by 17β-estradiol (E2). In this study, we therefore tested whether E2 regulates the compartmentalization of HCN1 in CA1 via Reelin. In organotypic entorhino-hippocampal cultures, we found that E2 promotes HCN1 distal dendritic enrichment via the G protein-coupled estrogen receptor GPER1, but apparently independent of Reelin, because GST-RAP, known to reduce Reelin signaling, did not prevent E2-induced HCN1 enrichment in distal CA1. We therefore re-examined the role of Reelin for the regulation of HCN1 compartmentalization and could not detect effects of reduced Reelin signaling on HCN1 distribution in CA1, either in the (developmental) slice culture model or in tamoxifen-inducible conditional reelin knockout mice during adulthood. We conclude that for HCN1 channel compartmentalization in CA1 pyramidal cells, Reelin is not as essential as previously proposed, and E2 effects on HCN1 distribution in CA1 are mediated by mechanisms that do not involve Reelin. Because HCN1 localization was not altered at different phases of the estrous cycle, gonadally derived estradiol is unlikely to regulate HCN1 channel compartmentalization, while the pattern of immunoreactivity of aromatase, the final enzyme of estradiol synthesis, argues for a role of local hippocampal E2 synthesis.

Degeneracy in the robust expression of spectral selectivity, subthreshold oscillations, and intrinsic excitability of entorhinal stellate cells

Biological heterogeneities are ubiquitous and play critical roles in the emergence of physiology at multiple scales. Although neurons in layer II (LII) of the medial entorhinal cortex (MEC) express heterogeneities in channel properties, the impact of such heterogeneities on the robustness of their cellular-scale physiology has not been assessed. Here, we performed a 55-parameter stochastic search spanning nine voltage- or calcium-activated channels to assess the impact of channel heterogeneities on the concomitant emergence of 10 in vitro electrophysiological characteristics of LII stellate cells (SCs). We generated 150,000 models and found a heterogeneous subpopulation of 449 valid models to robustly match all electrophysiological signatures. We employed this heterogeneous population to demonstrate the emergence of cellular-scale degeneracy in SCs, whereby disparate parametric combinations expressing weak pairwise correlations resulted in similar models. We then assessed the impact of virtually knocking out each channel from all valid models and demonstrate that the mapping between channels and measurements was many-to-many, a critical requirement for the expression of degeneracy. Finally, we quantitatively predict that the spike-triggered average of SCs should be endowed with theta-frequency spectral selectivity and coincidence detection capabilities in the fast gamma-band. We postulate this fast gamma-band coincidence detection as an instance of cellular-scale-efficient coding, whereby SC response characteristics match the dominant oscillatory signals in LII MEC. The heterogeneous population of valid SC models built here unveils the robust emergence of cellular-scale physiology despite significant channel heterogeneities, and forms an efficacious substrate for evaluating the impact of biological heterogeneities on entorhinal network function.

NEW & NOTEWORTHY We assessed the impact of heterogeneities in channel properties on the robustness of cellular-scale physiology of medial entorhinal cortical stellate neurons. We demonstrate that neuronal models with disparate channel combinations were endowed with similar physiological characteristics, as a consequence of the many-to-many mapping between channel properties and the physiological characteristics that they modulate. We predict that the spike-triggered average of stellate cells should be endowed with theta-frequency spectral selectivity and fast gamma-band coincidence detection capabilities.

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.

Down-Regulation of KV4 Channel in Drosophila Mushroom Body Neurons Contributes to Aβ42-Induced Courtship Memory Deficits

Accumulation of amyloid-β (Aβ) is widely believed to be an early event in the pathogenesis of Alzheimer's disease (AD). K_v4 is an A-type K⁺ channel, and our previous report shows the degradation of K_v4, induced by the Aβ42 accumulation, may be a critical contributor to the hyperexcitability of neurons in a Drosophila AD model. Here, we used well-established courtship memory assay to investigate the contribution of the K_v4 channel to short-term memory (STM) deficits in the Aβ42-expressing AD model. We found that Aβ42 over-expression in Drosophila leads to age-dependent courtship STM loss, which can be also induced by driving acute Aβ42 expression post-developmentally. Interestingly, mutants with eliminated K_v4-mediated A-type K⁺ currents (I_A) by transgenically expressing dominant-negative subunit (DNK_v4) phenocopied Aβ42 flies in defective courtship STM. K_v4 channels in mushroom body (MB) and projection neurons (PNs) were found to be required for courtship STM. Furthermore, the STM phenotypes can be rescued, at least partially, by restoration of K_v4 expression in Aβ42 flies, indicating the STM deficits could be partially caused by K_v4 degradation. In addition, I_A is significantly decreased in MB neurons (MBNs) but not in PNs, suggesting K_v4 degradation in MBNs, in particular, plays a critical role in courtship STM loss in Aβ42 flies. These data highlight causal relationship between region-specific K_v4 degradation and age-dependent learning decline in the AD model, and provide a mechanism for the disturbed cognitive function in AD.

mTORC1 Is a Local, Postsynaptic Voltage Sensor Regulated by Positive and Negative Feedback Pathways

The mammalian/mechanistic target of rapamycin complex 1 (mTORC1) serves as a regulator of mRNA translation. Recent studies suggest that mTORC1 may also serve as a local, voltage sensor in the postsynaptic region of neurons. Considering biochemical, bioinformatics and imaging data, we hypothesize that the activity state of mTORC1 dynamically regulates local membrane potential by promoting and repressing protein synthesis of select mRNAs. Our hypothesis suggests that mTORC1 uses positive and negative feedback pathways, in a branch-specific manner, to maintain neuronal excitability within an optimal range. In some dendritic branches, mTORC1 activity oscillates between the "On" and "Off" states. We define this as negative feedback. In contrast, positive feedback is defined as the pathway that leads to a prolonged depolarized or hyperpolarized resting membrane potential, whereby mTORC1 activity is constitutively on or off, respectively. We propose that inactivation of mTORC1 increases the expression of voltage-gated potassium alpha (Kv1.1 and 1.2) and beta (Kvβ2) subunits, ensuring that the membrane resets to its resting membrane potential after experiencing increased synaptic activity. In turn, reduced mTORC1 activity increases the protein expression of syntaxin-1A and promotes the surface expression of the ionotropic glutamate receptor N-methyl-D-aspartate (NMDA)-type subunit 1 (GluN1) that facilitates increased calcium entry to turn mTORC1 back on. Under conditions such as learning and memory, mTORC1 activity is required to be high for longer periods of time. Thus, the arm of the pathway that promotes syntaxin-1A and Kv1 protein synthesis will be repressed. Moreover, dendritic branches that have low mTORC1 activity with increased Kv expression would balance dendrites with constitutively high mTORC1 activity, allowing for the neuron to maintain its overall activity level within an ideal operating range. Finally, such a model suggests that recruitment of more positive feedback dendritic branches within a neuron is likely to lead to neurodegenerative disorders.

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.

Strings on a Violin: Location Dependence of Frequency Tuning in Active Dendrites

Strings on a violin are tuned to generate distinct sound frequencies in a manner that is firmly dependent on finger location along the fingerboard. Sound frequencies emerging from different violins could be very different based on their architecture, the nature of strings and their tuning. Analogously, active neuronal dendrites, dendrites endowed with active channel conductances, are tuned to distinct input frequencies in a manner that is dependent on the dendritic location of the synaptic inputs. Further, disparate channel expression profiles and differences in morphological characteristics could result in dendrites on different neurons of the same subtype tuned to distinct frequency ranges. Alternately, similar location-dependence along dendritic structures could be achieved through disparate combinations of channel profiles and morphological characteristics, leading to degeneracy in active dendritic spectral tuning. Akin to strings on a violin being tuned to different frequencies than those on a viola or a cello, different neuronal subtypes exhibit distinct channel profiles and disparate morphological characteristics endowing each neuronal subtype with unique location-dependent frequency selectivity. Finally, similar to the tunability of musical instruments to elicit distinct location-dependent sounds, neuronal frequency selectivity and its location-dependence are tunable through activity-dependent plasticity of ion channels and morphology. In this morceau, we explore the origins of neuronal frequency selectivity, and survey the literature on the mechanisms behind the emergence of location-dependence in distinct forms of frequency tuning. As a coda to this composition, we present some future directions for this exciting convergence of biophysical mechanisms that endow a neuron with frequency multiplexing capabilities.

Pyramidal Neurons Are Not Generalizable Building Blocks of Cortical Networks

A key challenge in cortical neuroscience is to gain a comprehensive understanding of how pyramidal neuron heterogeneity across different areas and species underlies the functional specialization of individual neurons, networks, and areas. Comparative studies have been important in this endeavor, providing data relevant to the question of which of the many inherent properties of individual pyramidal neurons are necessary and sufficient for species-specific network and areal function. In this mini review, the importance of pyramidal neuron structural properties for signaling are outlined, followed by a summary of our recent work comparing the structural features of mouse (C57/BL6 strain) and rhesus monkey layer 3 (L3) pyramidal neurons in primary visual and frontal association cortices and their implications for neuronal and areal function. Based on these and other published data, L3 pyramidal neurons plausibly might be considered broadly “generalizable” from one area to another in the mouse neocortex due to their many similarities, but major differences in the properties of these neurons in diverse areas in the rhesus monkey neocortex rules this out in the primate. Further, fundamental differences in the dendritic topology of mouse and rhesus monkey pyramidal neurons highlight the implausibility of straightforward scaling and/or extrapolation from mouse to primate neurons and cortical networks.

Biologically based neural circuit modelling for the study of fear learning and extinction

The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.

Subcellular Patch-clamp Recordings from the Somatodendritic Domain of Nigral Dopamine Neurons

Dendrites of dopaminergic neurons receive and convey synaptic input, support action potential back-propagation and neurotransmitter release. Understanding these fundamental functions will shed light on the information transfer in these neurons. Dendritic patch-clamp recordings provide the possibility to directly examine the electrical properties of dendrites and underlying voltage-gated ion channels. However, these fine structures are not easily accessible to patch pipettes because of their small diameter. This report describes a step-by-step procedure to collect stable and reliable recordings from the dendrites of dopaminergic neurons in acute slices. Electrophysiological measurements are combined with post hoc recovery of cell morphology. Successful experiments rely on improved preparation of slices, solutions and pipettes, adequate adjustment of the optics and stability of the pipette in contact with the recorded structure. Standard principles of somatic patch-clamp recording are applied to dendrites but with a gentler approach of the pipette. These versatile techniques can be implemented to address various questions concerning the excitable properties of dendrites.

Fast 3D Imaging of Spine, Dendritic, and Neuronal Assemblies in Behaving Animals

Understanding neural computation requires methods such as 3D acousto-optical (AO) scanning that can simultaneously read out neural activity on both the somatic and dendritic scales. AO point scanning can increase measurement speed and signal-to-noise ratio (SNR) by several orders of magnitude, but high optical resolution requires long point-to-point switching time, which limits imaging capability. Here we present a novel technology, 3D DRIFT AO scanning, which can extend each scanning point to small 3D lines, surfaces, or volume elements for flexible and fast imaging of complex structures simultaneously in multiple locations. Our method was demonstrated by fast 3D recording of over 150 dendritic spines with 3D lines, over 100 somata with squares and cubes, or multiple spiny dendritic segments with surface and volume elements, including in behaving animals. Finally, a 4-fold improvement in total excitation efficiency resulted in about 500 × 500 × 650 μm scanning volume with genetically encoded calcium indicators (GECIs).

Induction and Consolidation of Calcium-Based Homo- and Heterosynaptic Potentiation and Depression

The adaptive mechanisms of homo- and heterosynaptic plasticity play an important role in learning and memory. In order to maintain plasticity-induced changes for longer time scales (up to several days), they have to be consolidated by transferring them from a short-lasting early-phase to a long-lasting late-phase state. The underlying processes of this synaptic consolidation are already well-known for homosynaptic plasticity, however, it is not clear whether the same processes also enable the induction and consolidation of heterosynaptic plasticity. In this study, by extending a generic calcium-based plasticity model with the processes of synaptic consolidation, we show in simulations that indeed heterosynaptic plasticity can be induced and, furthermore, consolidated by the same underlying processes as for homosynaptic plasticity. Furthermore, we show that by local diffusion processes the heterosynaptic effect can be restricted to a few synapses neighboring the homosynaptically changed ones. Taken together, this generic model reproduces many experimental results of synaptic tagging and consolidation, provides several predictions for heterosynaptic induction and consolidation, and yields insights into the complex interactions between homo- and heterosynaptic plasticity over a broad variety of time (minutes to days) and spatial scales (several micrometers).

Is realistic neuronal modeling realistic?

Scientific models are abstractions that aim to explain natural phenomena. A successful model shows how a complex phenomenon arises from relatively simple principles while preserving major physical or biological rules and predicting novel experiments. A model should not be a facsimile of reality; it is an aid for understanding it. Contrary to this basic premise, with the 21st century has come a surge in computational efforts to model biological processes in great detail. Here we discuss the oxymoronic, realistic modeling of single neurons. This rapidly advancing field is driven by the discovery that some neurons don't merely sum their inputs and fire if the sum exceeds some threshold. Thus researchers have asked what are the computational abilities of single neurons and attempted to give answers using realistic models. We briefly review the state of the art of compartmental modeling highlighting recent progress and intrinsic flaws. We then attempt to address two fundamental questions. Practically, can we realistically model single neurons? Philosophically, should we realistically model single neurons? We use layer 5 neocortical pyramidal neurons as a test case to examine these issues. We subject three publically available models of layer 5 pyramidal neurons to three simple computational challenges. Based on their performance and a partial survey of published models, we conclude that current compartmental models are ad hoc, unrealistic models functioning poorly once they are stretched beyond the specific problems for which they were designed. We then attempt to plot possible paths for generating realistic single neuron models.

Distinct current modules shape cellular dynamics in model neurons

Numerous intrinsic currents are known to collectively shape neuronal membrane potential dynamics, or neuronal signatures. Although how sets of currents shape specific signatures such as spiking characteristics or oscillations has been studied individually, it is less clear how a neuron's suite of currents jointly shape its entire set of signatures. Biophysical conductance-based models of neurons represent a viable tool to address this important question. We hypothesized that currents are grouped into distinct modules that shape specific neuronal characteristics or signatures, such as resting potential, sub-threshold oscillations, and spiking waveforms, for several classes of neurons. For such a grouping to occur, the currents within one module should have minimal functional interference with currents belonging to other modules. This condition is satisfied if the gating functions of currents in the same module are grouped together on the voltage axis; in contrast, such functions are segregated along the voltage axis for currents belonging to different modules. We tested this hypothesis using four published example case models and found it to be valid for these classes of neurons. This insight into the neurobiological organization of currents also suggests an intuitive, systematic, and robust methodology to develop biophysical single-cell models with multiple biological characteristics applicable for both hand- and automated-tuning approaches. We illustrate the methodology using two example case rodent pyramidal neurons, from the lateral amygdala and the hippocampus. The methodology also helped reveal that a single-core compartment model could capture multiple neuronal properties. Such biophysical single-compartment models have potential to improve the fidelity of large network models.

Modulation of Synaptic Plasticity by Glutamatergic Gliotransmission: A Modeling Study

Glutamatergic gliotransmission, that is, the release of glutamate from perisynaptic astrocyte processes in an activity-dependent manner, has emerged as a potentially crucial signaling pathway for regulation of synaptic plasticity, yet its modes of expression and function in vivo remain unclear. Here, we focus on two experimentally well-identified gliotransmitter pathways, (i) modulations of synaptic release and (ii) postsynaptic slow inward currents mediated by glutamate released from astrocytes, and investigate their possible functional relevance on synaptic plasticity in a biophysical model of an astrocyte-regulated synapse. Our model predicts that both pathways could profoundly affect both short- and long-term plasticity. In particular, activity-dependent glutamate release from astrocytes could dramatically change spike-timing-dependent plasticity, turning potentiation into depression (and vice versa) for the same induction protocol.

Activity-Dependent Plasticity of Spike Pauses in Cerebellar Purkinje Cells

The plasticity of intrinsic excitability has been described in several types of neurons, but the significance of non-synaptic mechanisms in brain plasticity and learning remains elusive. Cerebellar Purkinje cells are inhibitory neurons that spontaneously fire action potentials at high frequencies and regulate activity in their target cells in the cerebellar nuclei by generating a characteristic spike burst-pause sequence upon synaptic activation. Using patch-clamp recordings from mouse Purkinje cells, we find that depolarization-triggered intrinsic plasticity enhances spike firing and shortens the duration of spike pauses. Pause plasticity is absent from mice lacking SK2-type potassium channels (SK2(-/-) mice) and in occlusion experiments using the SK channel blocker apamin, while apamin wash-in mimics pause reduction. Our findings demonstrate that spike pauses can be regulated through an activity-dependent, exclusively non-synaptic, SK2 channel-dependent mechanism and suggest that pause plasticity-by altering the Purkinje cell output-may be crucial to cerebellar information storage and learning.

Analogous synaptic plasticity profiles emerge from disparate channel combinations

An open question within the Bienenstock-Cooper-Munro theory for synaptic modification concerns the specific mechanism that is responsible for regulating the sliding modification threshold (SMT). In this conductance-based modeling study on hippocampal pyramidal neurons, we quantitatively assessed the impact of seven ion channels (R- and T-type calcium, fast sodium, delayed rectifier, A-type, and small-conductance calcium-activated (SK) potassium and HCN) and two receptors (AMPAR and NMDAR) on a calcium-dependent Bienenstock-Cooper-Munro-like plasticity rule. Our analysis with R- and T-type calcium channels revealed that differences in their activation-inactivation profiles resulted in differential impacts on how they altered the SMT. Further, we found that the impact of SK channels on the SMT critically depended on the voltage dependence and kinetics of the calcium sources with which they interacted. Next, we considered interactions among all the seven channels and the two receptors through global sensitivity analysis on 11 model parameters. We constructed 20,000 models through uniform randomization of these parameters and found 360 valid models based on experimental constraints on their plasticity profiles. Analyzing these 360 models, we found that similar plasticity profiles could emerge with several nonunique parametric combinations and that parameters exhibited weak pairwise correlations. Finally, we used seven sets of virtual knock-outs on these 360 models and found that the impact of different channels on the SMT was variable and differential. These results suggest that there are several nonunique routes to regulate the SMT, and call for a systematic analysis of the variability and state dependence of the mechanisms underlying metaplasticity during behavior and pathology.

From a meso- to micro-scale connectome: array tomography and mGRASP

Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors.

Retinoic Acid and LTP Recruit Postsynaptic AMPA Receptors Using Distinct SNARE-Dependent Mechanisms

Retinoic acid (RA)-dependent homeostatic plasticity and NMDA receptor-dependent long-term potentiation (LTP), a form of Hebbian plasticity, both enhance synaptic strength by increasing the abundance of postsynaptic AMPA receptors (AMPARs). However, it is unclear whether the molecular mechanisms mediating AMPAR trafficking during homeostatic and Hebbian plasticity differ, and it is unknown how RA signaling impacts Hebbian plasticity. Here, we show that RA increases postsynaptic AMPAR abundance using an activity-dependent mechanism that requires a unique SNARE (soluble NSF-attachment protein receptor)-dependent fusion machinery different from that mediating LTP. Specifically, RA-induced AMPAR trafficking did not involve complexin, which activates SNARE complexes containing syntaxin-1 or -3, but not complexes containing syntaxin-4, whereas LTP required complexin. Moreover, RA-induced AMPAR trafficking utilized the Q-SNARE syntaxin-4, whereas LTP utilized syntaxin-3; both additionally required the Q-SNARE SNAP-47 and the R-SNARE synatobrevin-2. Finally, acute RA treatment blocked subsequent LTP expression, probably by increasing AMPAR trafficking. Thus, RA-induced homeostatic plasticity involves a novel, activity-dependent postsynaptic AMPAR-trafficking pathway mediated by a unique SNARE-dependent fusion machinery.

Dysfunction of cortical dendritic integration in neuropathic pain reversed by serotoninergic neuromodulation

Neuropathic pain is caused by long-term modifications of neuronal function in the peripheral nervous system, the spinal cord, and supraspinal areas. Although functional changes in the forebrain are thought to contribute to the development of persistent pain, their significance and precise subcellular nature remain unexplored. Using somatic and dendritic whole-cell patch-clamp recordings from neurons in the anterior cingulate cortex, we discovered that sciatic nerve injury caused an activity-dependent dysfunction of hyperpolarization-activated cyclic nucleotide-regulated (HCN) channels in the dendrites of layer 5 pyramidal neurons resulting in enhanced integration of excitatory postsynaptic inputs and increased neuronal firing. Specific activation of the serotonin receptor type 7 (5-HT7R) alleviated the lesion-induced pathology by increasing HCN channel function, restoring normal dendritic integration, and reducing mechanical pain hypersensitivity in nerve-injured animals in vivo. Thus, serotoninergic neuromodulation at the forebrain level can reverse the dendritic dysfunction induced by neuropathic pain and may represent a potential therapeutical target.

Activation of InsP₃ receptors is sufficient for inducing graded intrinsic plasticity in rat hippocampal pyramidal neurons

The synaptic plasticity literature has focused on establishing necessity and sufficiency as two essential and distinct features in causally relating a signaling molecule to plasticity induction, an approach that has been surprisingly lacking in the intrinsic plasticity literature. In this study, we complemented the recently established necessity of inositol trisphosphate (InsP3) receptors (InsP3R) in a form of intrinsic plasticity by asking if InsP3R activation was sufficient to induce intrinsic plasticity in hippocampal neurons. Specifically, incorporation of d-myo-InsP3 in the recording pipette reduced input resistance, maximal impedance amplitude, and temporal summation but increased resonance frequency, resonance strength, sag ratio, and impedance phase lead. Strikingly, the magnitude of plasticity in all these measurements was dependent on InsP3 concentration, emphasizing the graded dependence of such plasticity on InsP3R activation. Mechanistically, we found that this InsP3-induced plasticity depended on hyperpolarization-activated cyclic nucleotide-gated channels. Moreover, this calcium-dependent form of plasticity was critically reliant on the release of calcium through InsP3Rs, the influx of calcium through N-methyl-d-aspartate receptors and voltage-gated calcium channels, and on the protein kinase A pathway. Our results delineate a causal role for InsP3Rs in graded adaptation of neuronal response dynamics, revealing novel regulatory roles for the endoplasmic reticulum in neural coding and homeostasis.

Activity-dependent gating of calcium spikes by A-type K+ channels controls climbing fiber signaling in Purkinje cell dendrites

In cerebellar Purkinje cell dendrites, heterosynaptic calcium signaling induced by the proximal climbing fiber (CF) input controls plasticity at distal parallel fiber (PF) synapses. The substrate and regulation of this long-range dendritic calcium signaling are poorly understood. Using high-speed calcium imaging, we examine the role of active dendritic conductances. Under basal conditions, CF stimulation evokes T-type calcium signaling displaying sharp proximodistal decrement. Combined mGluR1 receptor activation and depolarization, two activity-dependent signals, unlock P/Q calcium spikes initiation and propagation, mediating efficient CF signaling at distal sites. These spikes are initiated in proximal smooth dendrites, independently from somatic sodium action potentials, and evoke high-frequency bursts of all-or-none fast-rising calcium transients in PF spines. Gradual calcium spike burst unlocking arises from increasing inactivation of mGluR1-modulated low-threshold A-type potassium channels located in distal dendrites. Evidence for graded activity-dependent CF calcium signaling at PF synapses refines current views on cerebellar supervised learning rules.

Active dendrites regulate spectral selectivity in location-dependent spike initiation dynamics of hippocampal model neurons

How does the presence of plastic active dendrites in a pyramidal neuron alter its spike initiation dynamics? To answer this question, we measured the spike-triggered average (STA) from experimentally constrained, conductance-based hippocampal neuronal models of various morphological complexities. We transformed the STA computed from these models to the spectral and the spectrotemporal domains and found that the spike initiation dynamics exhibited temporally localized selectivity to a characteristic frequency. In the presence of the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, the STA characteristic frequency strongly correlated with the subthreshold resonance frequency in the theta frequency range. Increases in HCN channel density or in input variance increased the STA characteristic frequency and its selectivity strength. In the absence of HCN channels, the STA exhibited weak delta frequency selectivity and the characteristic frequency was related to the repolarization dynamics of the action potentials and the recovery kinetics of sodium channels from inactivation. Comparison of STA obtained with inputs at various dendritic locations revealed that nonspiking and spiking dendrites increased and reduced the spectrotemporal integration window of the STA with increasing distance from the soma as direct consequences of passive filtering and dendritic spike initiation, respectively. Finally, the presence of HCN channels set the STA characteristic frequency in the theta range across the somatodendritic arbor and specific STA measurements were strongly related to equivalent transfer-impedance-related measurements. Our results identify explicit roles for plastic active dendrites in neural coding and strongly recommend a dynamically reconfigurable multi-STA model to characterize location-dependent input feature selectivity in pyramidal neurons.

Variable dendritic integration in hippocampal CA3 pyramidal neurons

The hippocampal CA3 region is essential for pattern completion and generation of sharp-wave ripples. During these operations, coordinated activation of ensembles of CA3 pyramidal neurons produces spatiotemporally structured input patterns arriving onto dendrites of recurrently connected CA3 neurons. To understand how such input patterns are translated into specific output patterns, we characterized dendritic integration in CA3 pyramidal cells using two-photon imaging and glutamate uncaging. We found that thin dendrites of CA3 pyramidal neurons integrate synchronous synaptic input in a highly supralinear fashion. The amplification was primarily mediated by NMDA receptor activation and was present over a relatively broad range of spatiotemporal input patterns. The decay of voltage responses, temporal summation, and action potential output was regulated in a compartmentalized fashion mainly by a G-protein-activated inwardly rectifying K⁺ current. Our results suggest that plastic dendritic integrative mechanisms may support ensemble behavior in pyramidal neurons of the hippocampal circuitry.

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Active nonlinear dendritic integration in CA3 pyramidal neurons

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NMDARs mediate amplification of synchronous synaptic inputs

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Compartmentalized control of dendritic integration and somatic output by K+ channels

Channelopathies and dendritic dysfunction in fragile X syndrome

Dendritic spine abnormalities and the metabotropic glutamate receptor theory put the focus squarely on synapses and protein synthesis as the cellular locus of fragile X syndrome. Synapses however, are only partly responsible for information processing in neuronal networks. Neurotransmitter triggered excitatory postsynaptic potentials (EPSPs) are shaped and integrated by dendritic voltage-gated ion channels. These EPSPs, and in some cases the resultant dendritic spikes, are further modified by dendritic voltage-gated ion channels as they propagate to the soma. If the resultant somatic depolarization is large enough, action potential(s) will be triggered and propagate both orthodromically down the axon, where it may trigger neurotransmitter release, and antidromically back into the dendritic tree, where it can activate and modify dendritic voltage-gated and receptor activated ion channels. Several channelopathies, both soma-dendritic (L-type calcium channels, Slack potassium channels, h-channels, A-type potassium channels) and axo-somatic (BK channels and delayed rectifier potassium channels) were identified in the fmr1-/y mouse model of fragile X syndrome. Pathological function of these channels will strongly influence the excitability of individual neurons as well as overall network function. In this chapter we discuss the role of voltage-gated ion channels in neuronal processing and describe how identified channelopathies in models of fragile X syndrome may play a role in dendritic pathophysiology.