Precision of Inhibition: Dendritic Inhibition by Individual GABAergic Synapses on Hippocampal Pyramidal Cells Is Confined in Space and Time

Excitatory and inhibitory synapses show a tight subcellular correlation that weakens over development

Neurons receive correlated levels of excitation and inhibition, a feature that is important for proper brain function. However, how this relationship between excitatory and inhibitory inputs is established during the dynamic period of circuit wiring remains unexplored. Using multiple techniques, including in utero electroporation, electron microscopy, and electrophysiology, we reveal a tight correlation in the distribution of excitatory and inhibitory synapses along the dendrites of developing CA1 hippocampal neurons. This correlation was present within short dendritic stretches (<20 μm) and, surprisingly, was most pronounced during early development, sharply declining with maturity. The tight matching between excitation and inhibition was unexpected, as inhibitory synapses lacked an active zone when formed and exhibited compromised evoked release. We propose that inhibitory synapses form as a stabilizing scaffold to counterbalance growing excitation levels. This relationship diminishes over time, suggesting a critical role for a subcellular balance in early neuronal function and circuit formation.

Demixing is a default process for biological condensates formed via phase separation

Excitatory and inhibitory synapses do not overlap even when formed on one submicron-sized dendritic protrusion. How excitatory and inhibitory postsynaptic cytomatrices or densities (e/iPSDs) are segregated is not understood. Broadly, why membraneless organelles are naturally segregated in cellular subcompartments is unclear. Using biochemical reconstitutions in vitro and in cells, we demonstrate that ePSDs and iPSDs spontaneously segregate into distinct condensed molecular assemblies through phase separation. Tagging iPSD scaffold gephyrin with a PSD-95 intrabody (dissociation constant ~4 nM) leads to mistargeting of gephyrin to ePSD condensates. Unexpectedly, formation of iPSD condensates forces the intrabody-tagged gephyrin out of ePSD condensates. Thus, instead of diffusion-governed spontaneous mixing, demixing is a default process for biomolecules in condensates. Phase separation can generate biomolecular compartmentalization specificities that cannot occur in dilute solutions.

Postweaning Development Influences Endogenous VPAC1 Modulation of LTP Induced by Theta-Burst Stimulation: A Link to Maturation of the Hippocampal GABAergic System

Long-term potentiation (LTP) induced by theta-burst stimulation (TBS) undergoes postweaning developmental changes partially linked to GABAergic circuit maturation. Endogenous vasoactive intestinal peptide (VIP) acting on its VPAC1 receptor strongly influences LTP induced by theta-burst stimulation (TBS), an effect dependent on GABAergic transmission. Although VPAC1 receptor levels are developmentally regulated during embryogenesis, their variation along postweaning development is unknown, as is the VPAC1 modulation of LTP or its relation to hippocampal GABAergic circuit maturation. As such, we investigated how VPAC1 modulation of LTP adjusts from weaning to adulthood along with GABAergic circuit maturation. As described, LTP induced by mild TBS (5 bursts, 4 pulses delivered at 100 Hz) was increasingly greater from weaning to adulthood. The influence of the VPAC1 receptor antagonist PG 97-269 (100 nM) on TBS-induced LTP was much larger in juvenile (3-week-old) than in young adult (6-7-week-old) or adult (12-week-old) rats. This effect was not associated with a developmental decrease in synaptic VPAC1 receptor levels. However, an increase in pre and post-synaptic GABAergic synaptic markers suggests an increase in the number of GABAergic synaptic contacts that is more prominent than the one observed in glutamatergic connections during this period. Conversely, endogenous VPAC2 receptor activation did not significantly influence TBS-induced LTP. VPAC2 receptor levels enhance pronouncedly during postweaning development, but not at synaptic sites. Given the involvement of VIP interneurons in several aspects of hippocampal-dependent learning, neurodevelopmental disorders, and epilepsy, this could provide important insights into the role of VIP modulation of hippocampal synaptic plasticity during normal and altered brain development potentially contributing to epileptogenesis.

Hypernegative GABAA Reversal Potential in Pyramidal Cells Contributes to Medial Prefrontal Cortex Deactivation in a Mouse Model of Neuropathic Pain

Deactivation of the medial prefrontal cortex (mPFC) has been broadly reported in both neuropathic pain models and human chronic pain patients. Several cellular mechanisms may contribute to the inhibition of mPFC activity, including enhanced GABAergic inhibition. The functional effect of GABAA(γ-aminobutyric acid type A)-receptor activation depends on the concentration of intracellular chloride in the postsynaptic neuron, which is mainly regulated by the activity of Na-K-2Cl cotransporter isoform 1 (NKCC1) and K-Cl cotransporter isoform 2 (KCC2), 2 potassium-chloride cotransporters that import and extrude chloride, respectively. Recent work has shown that the NKCC1-KCC2 ratio is affected in numerous pathological conditions, and we hypothesized that it may contribute to the alteration of mPFC function in neuropathic pain. We used quantitative in situ hybridization to assess the level of expression of NKCC1 and KCC2 in the mPFC of a mouse model of neuropathic pain (spared nerve injury), and we found that KCC2 transcript is increased in the mPFC of spared nerve injury mice while NKCC1 is not affected. Perforated patch recordings further showed that this results in the hypernegative reversal potential of the GABAA current in pyramidal neurons of the mPFC. Computational simulations suggested that this change in GABAA reversal potential is sufficient to significantly reduce the overall activity of the cortical network. Thus, our results identify a novel pathological modulation of GABAA function and a new mechanism by which mPFC function is inhibited in neuropathic pain. Our data also help explain previous findings showing that activation of mPFC interneurons has proalgesic effect in neuropathic, but not in control conditions. PERSPECTIVE: Chronic pain is associated with the presence of depolarizing GABAA current in the spinal cord, suggesting that pharmacological NKCC1 antagonism has analgesic effects. However, our results show that in neuropathic pain, GABAA current is actually hyperinhibitory in the mPFC, where it contributes to the mPFC functional deactivation. This suggests caution in the use of NKCC1 antagonism to treat pain.

Local and long-range GABAergic circuits in hippocampal area CA1 and their link to Alzheimer's disease

GABAergic inhibitory neurons are the principal source of inhibition in the brain. Traditionally, their role in maintaining the balance of excitation-inhibition has been emphasized. Beyond homeostatic functions, recent circuit mapping and functional manipulation studies have revealed a wide range of specific roles that GABAergic circuits play in dynamically tilting excitation-inhibition coupling across spatio-temporal scales. These span from gating of compartment- and input-specific signaling, gain modulation, shaping input-output functions and synaptic plasticity, to generating signal-to-noise contrast, defining temporal windows for integration and rate codes, as well as organizing neural assemblies, and coordinating inter-regional synchrony. GABAergic circuits are thus instrumental in controlling single-neuron computations and behaviorally-linked network activity. The activity dependent modulation of sensory and mnemonic information processing by GABAergic circuits is pivotal for the formation and maintenance of episodic memories in the hippocampus. Here, we present an overview of the local and long-range GABAergic circuits that modulate the dynamics of excitation-inhibition and disinhibition in the main output area of the hippocampus CA1, which is crucial for episodic memory. Specifically, we link recent findings pertaining to GABAergic neuron molecular markers, electrophysiological properties, and synaptic wiring with their function at the circuit level. Lastly, given that area CA1 is particularly impaired during early stages of Alzheimer's disease, we emphasize how these GABAergic circuits may contribute to and be involved in the pathophysiology.

Functional neuroanatomy of monoaminergic systems in the basolateral nuclear complex of the amygdala: Neuronal targets, receptors, and circuits

This review discusses neuroanatomical aspects of the three main monoaminergic systems innervating the basolateral nuclear complex (BNC) of the amygdala (serotonergic, noradrenergic, and dopaminergic systems). It mainly focuses on immunohistochemical (IHC) and in situ hybridization (ISH) studies that have analyzed the relationship of specific monoaminergic inputs and their receptors to specific neuronal subtypes in the BNC in order to better understand the anatomical substrates of the monoaminergic modulation of BNC circuitry. First, light and electron microscopic IHC investigations identifying the main BNC neuronal subpopulations and characterizing their local circuitry, including connections with discrete PN compartments and other INs, are reviewed. Then, the relationships of each of the three monoaminergic systems to distinct PN and IN cell types, are examined in detail. For each system, the neuronal targets and their receptor expression are discussed. In addition, pertinent electrophysiological investigations are discussed. The last section of the review compares and contrasts various aspects of each of the three monoaminergic systems. It is concluded that the large number of different receptors, each with a distinct mode of action, expressed by distinct cell types with different connections and functions, should offer innumerable ways to subtlety regulate the activity of the BNC by therapeutic drugs in psychiatric diseases in which there are alterations of BNC monoaminergic modulatory systems, such as in anxiety disorders, depression, and drug addiction. It is suggested that an important area for future studies is to investigate how the three systems interact in concert at the neuronal and neuronal network levels.

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.

Where is the error? Hierarchical predictive coding through dendritic error computation

Top-down feedback in cortex is critical for guiding sensory processing, which has prominently been formalized in the theory of hierarchical predictive coding (hPC). However, experimental evidence for error units, which are central to the theory, is inconclusive and it remains unclear how hPC can be implemented with spiking neurons. To address this, we connect hPC to existing work on efficient coding in balanced networks with lateral inhibition and predictive computation at apical dendrites. Together, this work points to an efficient implementation of hPC with spiking neurons, where prediction errors are computed not in separate units, but locally in dendritic compartments. We then discuss the correspondence of this model to experimentally observed connectivity patterns, plasticity, and dynamics in cortex.

Introduction: What Are Dendritic Spines?

Dendritic spines are cellular specializations that greatly increase the connectivity of neurons and modulate the "weight" of most postsynaptic excitatory potentials. Spines are found in very diverse animal species providing neural networks with a high integrative and computational possibility and plasticity, enabling the perception of sensorial stimuli and the elaboration of a myriad of behavioral displays, including emotional processing, memory, and learning. Humans have trillions of spines in the cerebral cortex, and these spines in a continuum of shapes and sizes can integrate the features that differ our brain from other species. In this chapter, we describe (1) the discovery of these small neuronal protrusions and the search for the biological meaning of dendritic spines; (2) the heterogeneity of shapes and sizes of spines, whose structure and composition are associated with the fine-tuning of synaptic processing in each nervous area, as well as the findings that support the role of dendritic spines in increasing the wiring of neural circuits and their functions; and (3) within the intraspine microenvironment, the integration and activation of signaling biochemical pathways, the compartmentalization of molecules or their spreading outside the spine, and the biophysical properties that can affect parent dendrites. We also provide (4) examples of plasticity involving dendritic spines and neural circuits relevant to species survival and comment on (5) current research advancements and challenges in this exciting research field.

Regulation of circuit organization and function through inhibitory synaptic plasticity

Diverse inhibitory neurons in the mammalian brain shape circuit connectivity and dynamics through mechanisms of synaptic plasticity. Inhibitory plasticity can establish excitation/inhibition (E/I) balance, control neuronal firing, and affect local calcium concentration, hence regulating neuronal activity at the network, single neuron, and dendritic level. Computational models can synthesize multiple experimental results and provide insight into how inhibitory plasticity controls circuit dynamics and sculpts connectivity by identifying phenomenological learning rules amenable to mathematical analysis. We highlight recent studies on the role of inhibitory plasticity in modulating excitatory plasticity, forming structured networks underlying memory formation and recall, and implementing adaptive phenomena and novelty detection. We conclude with experimental and modeling progress on the role of interneuron-specific plasticity in circuit computation and context-dependent learning.

From mechanisms to markers: novel noninvasive EEG proxy markers of the neural excitation and inhibition system in humans

Brain function is a product of the balance between excitatory and inhibitory (E/I) brain activity. Variation in the regulation of this activity is thought to give rise to normal variation in human traits, and disruptions are thought to potentially underlie a spectrum of neuropsychiatric conditions (e.g., Autism, Schizophrenia, Downs' Syndrome, intellectual disability). Hypotheses related to E/I dysfunction have the potential to provide cross-diagnostic explanations and to combine genetic and neurological evidence that exists within and between psychiatric conditions. However, the hypothesis has been difficult to test because: (1) it lacks specificity-an E/I dysfunction could pertain to any level in the neural system- neurotransmitters, single neurons/receptors, local networks of neurons, or global brain balance - most researchers do not define the level at which they are examining E/I function; (2) We lack validated methods for assessing E/I function at any of these neural levels in humans. As a result, it has not been possible to reliably or robustly test the E/I hypothesis of psychiatric disorders in a large cohort or longitudinal patient studies. Currently available, in vivo markers of E/I in humans either carry significant risks (e.g., deep brain electrode recordings or using Positron Emission Tomography (PET) with radioactive tracers) and/or are highly restrictive (e.g., limited spatial extent for Transcranial Magnetic Stimulation (TMS) and Magnetic Resonance Spectroscopy (MRS). More recently, a range of novel Electroencephalography (EEG) features has been described, which could serve as proxy markers for E/I at a given level of inference. Thus, in this perspective review, we survey the theories and experimental evidence underlying 6 novel EEG markers and their biological underpinnings at a specific neural level. These cheap-to-record and scalable proxy markers may offer clinical utility for identifying subgroups within and between diagnostic categories, thus directing more tailored sub-grouping and, therefore, treatment strategies. However, we argue that studies in clinical populations are premature. To maximize the potential of prospective EEG markers, we first need to understand the link between underlying E/I mechanisms and measurement techniques.

Sequence learning, prediction, and replay in networks of spiking neurons

Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervised and continuous manner using local learning rules, permits a context specific prediction of future sequence elements, and generates mismatch signals in case the predictions are not met. While the HTM algorithm accounts for a number of biological features such as topographic receptive fields, nonlinear dendritic processing, and sparse connectivity, it is based on abstract discrete-time neuron and synapse dynamics, as well as on plasticity mechanisms that can only partly be related to known biological mechanisms. Here, we devise a continuous-time implementation of the temporal-memory (TM) component of the HTM algorithm, which is based on a recurrent network of spiking neurons with biophysically interpretable variables and parameters. The model learns high-order sequences by means of a structural Hebbian synaptic plasticity mechanism supplemented with a rate-based homeostatic control. In combination with nonlinear dendritic input integration and local inhibitory feedback, this type of plasticity leads to the dynamic self-organization of narrow sequence-specific subnetworks. These subnetworks provide the substrate for a faithful propagation of sparse, synchronous activity, and, thereby, for a robust, context specific prediction of future sequence elements as well as for the autonomous replay of previously learned sequences. By strengthening the link to biology, our implementation facilitates the evaluation of the TM hypothesis based on experimentally accessible quantities. The continuous-time implementation of the TM algorithm permits, in particular, an investigation of the role of sequence timing for sequence learning, prediction and replay. We demonstrate this aspect by studying the effect of the sequence speed on the sequence learning performance and on the speed of autonomous sequence replay.

Essentially all data processed by mammals and many other living organisms is sequential. This holds true for all types of sensory input data as well as motor output activity. Being able to form memories of such sequential data, to predict future sequence elements, and to replay learned sequences is a necessary prerequisite for survival. It has been hypothesized that sequence learning, prediction and replay constitute the fundamental computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) constitutes an abstract powerful algorithm implementing this form of computation and has been proposed to serve as a model of neocortical processing. In this study, we are reformulating this algorithm in terms of known biological ingredients and mechanisms to foster the verifiability of the HTM hypothesis based on electrophysiological and behavioral data. The proposed model learns continuously in an unsupervised manner by biologically plausible, local plasticity mechanisms, and successfully predicts and replays complex sequences. Apart from establishing contact to biology, the study sheds light on the mechanisms determining at what speed we can process sequences and provides an explanation of fast sequence replay observed in the hippocampus and in the neocortex.

Assessing Local and Branch-specific Activity in Dendrites

Dendrites are elaborate neural processes which integrate inputs from various sources in space and time. While decades of work have suggested an independent role for dendrites in driving nonlinear computations for the cell, only recently have technological advances enabled us to capture the variety of activity in dendrites and their coupling dynamics with the soma. Under certain circumstances, activity generated in a given dendritic branch remains isolated, such that the soma or even sister dendrites are not privy to these localized signals. Such branch-specific activity could radically increase the capacity and flexibility of coding for the cell as a whole. Here, we discuss these forms of localized and branch-specific activity, their functional relevance in plasticity and behavior, and their supporting biophysical and circuit-level mechanisms. We conclude by showcasing electrical and optical approaches in hippocampal area CA3, using original experimental data to discuss experimental and analytical methodology and key considerations to take when investigating the functional relevance of independent dendritic activity.

Endogenous VIP VPAC1 Receptor Activation Modulates Hippocampal Theta Burst Induced LTP: Transduction Pathways and GABAergic Mechanisms

Simple Summary

Regulation of synaptic plasticity through control of disinhibition is an important process in the prevention of excessive plasticity in both physiological and pathological conditions. Interneuron-selective interneurons, such as the ones expressing VIP in the hippocampus, may play a crucial role in this process. In this paper we showed that endogenous activation of VPAC₁—not VPAC₂ receptors—exerts an inhibitory control of long-term potentiation (LTP) induced by theta-burst stimulation (TBS) in the hippocampus, through a mechanism dependent on GABAergic transmission. This suggests that VPAC₁-mediated modulation of synaptic transmission at GABAergic synapses to interneurons will ultimately influence NMDA-dependent LTP expression by modulating inhibitory control of pyramidal cell dendrites and postsynaptic depolarization during LTP induction. Accordingly, the transduction pathways mostly involved in this effect were the ones involved in TBS-induced LTP expression like NMDA receptor activation and CaMKII activity. In addition, the actions of endogenous VIP through VPAC₁ receptors may indirectly influence the control of dendritic excitability by Kv4.2 channels.

Abstract

Vasoactive intestinal peptide (VIP), acting on both VPAC₁ and VPAC₂ receptors, is a key modulator of hippocampal synaptic transmission, pyramidal cell excitability and long-term depression (LTD), exerting its effects partly through modulation GABAergic disinhibitory circuits. Yet, the role of endogenous VIP and its receptors in modulation of hippocampal LTP and the involvement of disinhibition in this modulation have scarcely been investigated. We studied the modulation of CA1 LTP induced by TBS via endogenous VIP release in hippocampal slices from young-adult Wistar rats using selective VPAC₁ and VPAC₂ receptor antagonists, evaluating its consequence for the phosphorylation of CamKII, GluA1 AMPA receptor subunits and Kv4.2 potassium channels in total hippocampal membranes obtained from TBS stimulated slices. Endogenous VIP, acting on VPAC₁ (but not VPAC₂) receptors, inhibited CA1 hippocampal LTP induced by TBS in young adult Wistar rats and this effect was dependent on GABAergic transmission and relied on the integrity of NMDA and CaMKII-dependent LTP expression mechanisms but not on PKA and PKC activity. Furthermore, it regulated the autophosphorylation of CaMKII and the expression and Ser₄₃₈ phosphorylation of Kv4.2 potassium channels responsible for the A-current while inhibiting phosphorylation of Kv4.2 on Thr₆₀₇. Altogether, this suggests that endogenous VIP controls the expression of hippocampal CA1 LTP by regulating disinhibition through activation of VPAC₁ receptors in interneurons. This may impact the autophosphorylation of CaMKII during LTP, as well as the expression and phosphorylation of Kv4.2 K⁺ channels at hippocampal pyramidal cell dendrites.

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

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

Separable actions of acetylcholine and noradrenaline on neuronal ensemble formation in hippocampal CA3 circuits

In the hippocampus, episodic memories are thought to be encoded by the formation of ensembles of synaptically coupled CA3 pyramidal cells driven by sparse but powerful mossy fiber inputs from dentate gyrus granule cells. The neuromodulators acetylcholine and noradrenaline are separately proposed as saliency signals that dictate memory encoding but it is not known if they represent distinct signals with separate mechanisms. Here, we show experimentally that acetylcholine, and to a lesser extent noradrenaline, suppress feed-forward inhibition and enhance Excitatory-Inhibitory ratio in the mossy fiber pathway but CA3 recurrent network properties are only altered by acetylcholine. We explore the implications of these findings on CA3 ensemble formation using a hierarchy of models. In reconstructions of CA3 pyramidal cells, mossy fiber pathway disinhibition facilitates postsynaptic dendritic depolarization known to be required for synaptic plasticity at CA3-CA3 recurrent synapses. We further show in a spiking neural network model of CA3 how acetylcholine-specific network alterations can drive rapid overlapping ensemble formation. Thus, through these distinct sets of mechanisms, acetylcholine and noradrenaline facilitate the formation of neuronal ensembles in CA3 that encode salient episodic memories in the hippocampus but acetylcholine selectively enhances the density of memory storage.

A subthreshold synaptic mechanism regulating BDNF expression and resting synaptic strength

Recent studies have demonstrated that protein translation can be regulated by spontaneous excitatory neurotransmission. However, the impact of spontaneous neurotransmitter release on gene transcription remains unclear. Here, we study the effects of the balance between inhibitory and excitatory spontaneous neurotransmission on brain-derived neurotrophic factor (BDNF) regulation and synaptic plasticity. Blockade of spontaneous inhibitory events leads to an increase in the transcription of Bdnf and Npas4 through altered synaptic calcium signaling, which can be blocked by antagonism of NMDA receptors (NMDARs) or L-type voltage-gated calcium channels (VGCCs). Transcription is bidirectionally altered by manipulating spontaneous inhibitory, but not excitatory, currents. Moreover, blocking spontaneous inhibitory events leads to multiplicative downscaling of excitatory synaptic strength in a manner that is dependent on both transcription and BDNF signaling. These results reveal a role for spontaneous inhibitory neurotransmission in BDNF signaling that sets excitatory synaptic strength at rest.

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

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

Unique properties of dually innervated dendritic spines in pyramidal neurons of the somatosensory cortex uncovered by 3D correlative light and electron microscopy

Pyramidal neurons (PNs) are covered by thousands of dendritic spines receiving excitatory synaptic inputs. The ultrastructure of dendritic spines shapes signal compartmentalization, but ultrastructural diversity is rarely taken into account in computational models of synaptic integration. Here, we developed a 3D correlative light-electron microscopy (3D-CLEM) approach allowing the analysis of specific populations of synapses in genetically defined neuronal types in intact brain circuits. We used it to reconstruct segments of basal dendrites of layer 2/3 PNs of adult mouse somatosensory cortex and quantify spine ultrastructural diversity. We found that 10% of spines were dually innervated and 38% of inhibitory synapses localized to spines. Using our morphometric data to constrain a model of synaptic signal compartmentalization, we assessed the impact of spinous versus dendritic shaft inhibition. Our results indicate that spinous inhibition is locally more efficient than shaft inhibition and that it can decouple voltage and calcium signaling, potentially impacting synaptic plasticity.

Hippocampal CA1 theta burst-induced LTP from weaning to adulthood: Cellular and molecular mechanisms in young male rats revisited

Long-term potentiation (LTP) is a highly studied cellular process, yet determining the transduction and gamma aminobutyric acid (GABAergic) pathways that are the essential versus modulatory for LTP elicited by theta burst stimulation (TBS) in the hippocampal Cornu Ammonis 1 (CA1) area is still elusive, due to the use of different TBS intensities, patterns or different rodent/cellular models. We now characterised the developmental maturation and the transduction and GABAergic pathways required for mild TBS-induced LTP in hippocampal CA1 area in male rats. LTP induced by TBS (5x4) (five bursts of four pulses delivered at 100 Hz) lasted for up to 3 h and was increasingly larger from weaning to adulthood. Stronger TBS patterns - TBS (15x4) or three TBS (15x4) separated by 6 min induced nearly maximal LTP not being the best choice to study the value of LTP-enhancing drugs. LTP induced by TBS (5x4) in young adults was fully dependent on N-methyl D-aspartate (NMDA) receptor and calmodulin-dependent protein kinase II (CaMKII) activity but independent of protein kinase A (PKA) or protein kinase C (PKC) activity. Furthermore, it was partially dependent on GABA_B receptor activation and was potentiated by GABA_A receptor blockade and less by GAT-1 transporter blockade. AMPA GluA1 phosphorylation on Ser₈₃₁ (CaMKII target) but not GluA1 Ser₈₄₅ (PKA target) was essential for LTP expression. The phosphorylation of the Kv4.2 channel was observed at Ser₄₃₈ (CaMKII target) but not at Thr₆₀₂ or Thr₆₀₇ (ERK/MAPK pathway target). This suggests that cellular kinases like PKA, PKC, or kinases of the ERK/MAPK family although important modulators of TBS (5x4)-induced LTP may not be essential for its expression in the CA1 area of the hippocampus.

Epistemic Autonomy: Self-supervised Learning in the Mammalian Hippocampus

Biological cognition is based on the ability to autonomously acquire knowledge, or epistemic autonomy. Such self-supervision is largely absent in artificial neural networks (ANN) because they depend on externally set learning criteria. Yet training ANN using error backpropagation has created the current revolution in artificial intelligence, raising the question of whether the epistemic autonomy displayed in biological cognition can be achieved with error backpropagation-based learning. We present evidence suggesting that the entorhinal-hippocampal complex combines epistemic autonomy with error backpropagation. Specifically, we propose that the hippocampus minimizes the error between its input and output signals through a modulatory counter-current inhibitory network. We further discuss the computational emulation of this principle and analyze it in the context of autonomous cognitive systems.

Emergence of local and global synaptic organization on cortical dendrites

Synaptic inputs on cortical dendrites are organized with remarkable subcellular precision at the micron level. This organization emerges during early postnatal development through patterned spontaneous activity and manifests both locally where nearby synapses are significantly correlated, and globally with distance to the soma. We propose a biophysically motivated synaptic plasticity model to dissect the mechanistic origins of this organization during development and elucidate synaptic clustering of different stimulus features in the adult. Our model captures local clustering of orientation in ferret and receptive field overlap in mouse visual cortex based on the receptive field diameter and the cortical magnification of visual space. Including action potential back-propagation explains branch clustering heterogeneity in the ferret and produces a global retinotopy gradient from soma to dendrite in the mouse. Therefore, by combining activity-dependent synaptic competition and species-specific receptive fields, our framework explains different aspects of synaptic organization regarding stimulus features and spatial scales.

Interneuron Types and Their Circuits in the Basolateral Amygdala

The basolateral amygdala (BLA) is a cortical structure based on its cell types, connectivity features, and developmental characteristics. This part of the amygdala is considered to be the main entry site of processed and multisensory information delivered via cortical and thalamic afferents. Although GABAergic inhibitory cells in the BLA comprise only 20% of the entire neuronal population, they provide essential control over proper network operation. Previous studies have uncovered that GABAergic cells in the basolateral amygdala are as diverse as those present in other cortical regions, including the hippocampus and neocortex. To understand the role of inhibitory cells in various amygdala functions, we need to reveal the connectivity and input-output features of the different types of GABAergic cells. Here, I review the recent achievements in uncovering the diversity of GABAergic cells in the basolateral amygdala with a specific focus on the microcircuit organization of these inhibitory cells.

The Subcortical-Allocortical- Neocortical continuum for the Emergence and Morphological Heterogeneity of Pyramidal Neurons in the Human Brain

Human cortical and subcortical areas integrate emotion, memory, and cognition when interpreting various environmental stimuli for the elaboration of complex, evolved social behaviors. Pyramidal neurons occur in developed phylogenetic areas advancing along with the allocortex to represent 70-85% of the neocortical gray matter. Here, we illustrate and discuss morphological features of heterogeneous spiny pyramidal neurons emerging from specific amygdaloid nuclei, in CA3 and CA1 hippocampal regions, and in neocortical layers II/III and V of the anterolateral temporal lobe in humans. Three-dimensional images of Golgi-impregnated neurons were obtained using an algorithm for the visualization of the cell body, dendritic length, branching pattern, and pleomorphic dendritic spines, which are specialized plastic postsynaptic units for most excitatory inputs. We demonstrate the emergence and development of human pyramidal neurons in the cortical and basomedial (but not the medial, MeA) nuclei of the amygdala with cells showing a triangular cell body shape, basal branched dendrites, and a short apical shaft with proximal ramifications as "pyramidal-like" neurons. Basomedial neurons also have a long and distally ramified apical dendrite not oriented to the pial surface. These neurons are at the beginning of the allocortex and the limbic lobe. "Pyramidal-like" to "classic" pyramidal neurons with laminar organization advance from the CA3 to the CA1 hippocampal regions. These cells have basal and apical dendrites with specific receptive synaptic domains and several spines. Neocortical pyramidal neurons in layers II/III and V display heterogeneous dendritic branching patterns adapted to the space available and the afferent inputs of each brain area. Dendritic spines vary in their distribution, density, shapes, and sizes (classified as stubby/wide, thin, mushroom-like, ramified, transitional forms, "atypical" or complex forms, such as thorny excrescences in the MeA and CA3 hippocampal region). Spines were found isolated or intermingled, with evident particularities (e.g., an extraordinary density in long, deep CA1 pyramidal neurons), and some showing a spinule. We describe spiny pyramidal neurons considerably improving the connectional and processing complexity of the brain circuits. On the other hand, these cells have some vulnerabilities, as found in neurodegenerative Alzheimer's disease and in temporal lobe epilepsy.

Immunohistochemical Identification of Interneuronal Subpopulations in the Basolateral Amygdala of the Rhesus Monkey (Macaca mulatta)

Inhibitory circuits in the basolateral nuclear complex of the amygdala (BNC) critical for controlling the acquisition, expression, and extinction of emotional responses are mediated by GABAergic interneurons (INs). Studies in rodents have demonstrated that separate IN subpopulations, identified by their expression of calcium-binding proteins and neuropeptides, play discrete roles in the intrinsic circuitry of the BNC. Far less is known about IN subpopulations in primates. In order to fill in this gap in our understanding of primate INs, the present investigation used dual-labeling immunohistochemistry for IN markers to identify subpopulations expressing cholecystokinin (CCK), calbindin (CB), calretinin (CR), and somatostatin (SOM) in somata and axon terminals in the monkey BNC. In general, colocalization patterns seen in somata and axon terminals were similar. It was found that there was virtually no colocalization of CB and CR, the two calcium-binding proteins investigated. Three subtypes of CCK-immunoreactive (CCK+) INs were identified on the basis of their expression of CR or CB: (1) CCK+/CR+; (2) CCK+/CB+); and (3) CCK+/CR-/CB-. Almost no colocalization of CCK with SOM was observed, but there was extensive colocalization of SOM and CB. CCK+, CR+, and CCK+/CR+ double-labeled axon terminals were seen surrounding pyramidal cell somata in basket-like plexuses, as well as in the neuropil. CB+, SOM+, and CB+/SOM+ terminals did not form baskets, suggesting that these IN subpopulations are mainly dendrite-targeting neurons. In general, the IN subpopulations in the monkey are not dissimilar to those seen in rodents but, unlike rodents, CB+ INs in the monkey are not basket cells.

A Dendrite-Focused Framework for Understanding the Actions of Ketamine and Psychedelics

Pilot studies have hinted that serotonergic psychedelics such as psilocybin may relieve depression, and could possibly do so by promoting neural plasticity. Intriguingly, another psychotomimetic compound, ketamine, is a fast-acting antidepressant and induces synapse formation. The similarities in behavioral and neural effects have been puzzling because the compounds target distinct molecular receptors in the brain. In this opinion article, we develop a conceptual framework that suggests the actions of ketamine and serotonergic psychedelics may converge at the dendrites, to both enhance and suppress membrane excitability. We speculate that mismatches in the opposing actions on dendritic excitability may relate to these compounds' cell-type and region selectivity, their moderate range of effects and toxicity, and their plasticity-promoting capacities.

Neuronal Activity at Synapse Resolution: Reporters and Effectors for Synaptic Neuroscience

The development of methods for the activity-dependent tagging of neurons enabled a new way to tackle the problem of engram identification at the cellular level, giving rise to groundbreaking findings in the field of memory studies. However, the resolution of activity-dependent tagging remains limited to the whole-cell level. Notably, events taking place at the synapse level play a critical role in the establishment of new memories, and strong experimental evidence shows that learning and synaptic plasticity are tightly linked. Here, we provide a comprehensive review of the currently available techniques that enable to identify and track the neuronal activity with synaptic spatial resolution. We also present recent technologies that allow to selectively interfere with specific subsets of synapses. Lastly, we discuss how these technologies can be applied to the study of learning and memory.

Endocannabinoid Signaling Mediates Local Dendritic Coordination between Excitatory and Inhibitory Synapses

Dendritic inhibitory synapses are most efficient in modulating excitatory inputs localized on the same dendrite, but it is unknown whether their location is random or regulated. Here, we show that the formation of inhibitory synapses can be directed by excitatory synaptic activity on the same dendrite. We stimulated dendritic spines close to a GABAergic axon crossing by pairing two-photon glutamate uncaging with postsynaptic depolarization in CA1 pyramidal cells. We found that repeated spine stimulation promoted growth of a GABAergic bouton onto the same dendrite. The dendritic feedback signal required postsynaptic activation of DAGL, which produces the endocannabinoid 2-AG, and was mediated by CB1 receptors. We could also induce inhibitory bouton growth by local, brief applications of 2-AG. Our findings reveal a dendritic signaling mechanism to trigger growth of an inhibitory bouton at dendritic locations with strong excitatory synaptic activity, and this mechanism may serve to ensure inhibitory control over clustered excitatory inputs.

Multimodal determinants of phase-locked dynamics across deep-superficial hippocampal sublayers during theta oscillations

Theta oscillations play a major role in temporarily defining the hippocampal rate code by translating behavioral sequences into neuronal representations. However, mechanisms constraining phase timing and cell-type-specific phase preference are unknown. Here, we employ computational models tuned with evolutionary algorithms to evaluate phase preference of individual CA1 pyramidal cells recorded in mice and rats not engaged in any particular memory task. We applied unbiased and hypothesis-free approaches to identify effects of intrinsic and synaptic factors, as well as cell morphology, in determining phase preference. We found that perisomatic inhibition delivered by complementary populations of basket cells interacts with input pathways to shape phase-locked specificity of deep and superficial pyramidal cells. Somatodendritic integration of fluctuating glutamatergic inputs defined cycle-by-cycle by unsupervised methods demonstrated that firing selection is tuneable across sublayers. Our data identify different mechanisms of phase-locking selectivity that are instrumental for flexible dynamical representations of theta sequences.

Theta oscillations have been implicated in hippocampal processing but mechanisms constraining phase timing of specific cell types are unknown. Here, the authors combine single-cell and multisite recordings with evolutionary computational models to evaluate mechanisms of phase preference of deep and superficial CA1 pyramidal cells.

Perceptron Learning and Classification in a Modeled Cortical Pyramidal Cell

The perceptron learning algorithm and its multiple-layer extension, the backpropagation algorithm, are the foundations of the present-day machine learning revolution. However, these algorithms utilize a highly simplified mathematical abstraction of a neuron; it is not clear to what extent real biophysical neurons with morphologically-extended non-linear dendritic trees and conductance-based synapses can realize perceptron-like learning. Here we implemented the perceptron learning algorithm in a realistic biophysical model of a layer 5 cortical pyramidal cell with a full complement of non-linear dendritic channels. We tested this biophysical perceptron (BP) on a classification task, where it needed to correctly binarily classify 100, 1,000, or 2,000 patterns, and a generalization task, where it was required to discriminate between two "noisy" patterns. We show that the BP performs these tasks with an accuracy comparable to that of the original perceptron, though the classification capacity of the apical tuft is somewhat limited. We concluded that cortical pyramidal neurons can act as powerful classification devices.

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.

Inhibitory Plasticity: From Molecules to Computation and Beyond

Synaptic plasticity is the cellular and molecular counterpart of learning and memory and, since its first discovery, the analysis of the mechanisms underlying long-term changes of synaptic strength has been almost exclusively focused on excitatory connections. Conversely, inhibition was considered as a fixed controller of circuit excitability. Only recently, inhibitory networks were shown to be finely regulated by a wide number of mechanisms residing in their synaptic connections. Here, we review recent findings on the forms of inhibitory plasticity (IP) that have been discovered and characterized in different brain areas. In particular, we focus our attention on the molecular pathways involved in the induction and expression mechanisms leading to changes in synaptic efficacy, and we discuss, from the computational perspective, how IP can contribute to the emergence of functional properties of brain circuits.

The functional organization of excitation and inhibition in the dendrites of mouse direction-selective ganglion cells

Recent studies indicate that the precise timing and location of excitation and inhibition (E/I) within active dendritic trees can significantly impact neuronal function. How synaptic inputs are functionally organized at the subcellular level in intact circuits remains unclear. To address this issue, we took advantage of the retinal direction-selective ganglion cell circuit, where directionally tuned inhibition is known to shape non-directional excitatory signals. We combined two-photon calcium imaging with genetic, pharmacological, and single-cell ablation methods to examine the extent to which inhibition ‘vetoes’ excitation at the level of individual dendrites of direction-selective ganglion cells. We demonstrate that inhibition shapes direction selectivity independently within small dendritic segments (<10µm) with remarkable accuracy. The data suggest that the parallel processing schemes proposed for direction encoding could be more fine-grained than previously envisioned.

Cell-type-specific control of basolateral amygdala neuronal circuits via entorhinal cortex-driven feedforward inhibition

The basolateral amygdala (BLA) plays a vital role in associating sensory stimuli with salient valence information. Excitatory principal neurons (PNs) undergo plastic changes to encode this association; however, local BLA inhibitory interneurons (INs) gate PN plasticity via feedforward inhibition (FFI). Despite literature implicating parvalbumin expressing (PV+) INs in FFI in cortex and hippocampus, prior anatomical experiments in BLA implicate somatostatin expressing (Sst+) INs. The lateral entorhinal cortex (LEC) projects to BLA where it drives FFI. In the present study, we explored the role of interneurons in this circuit. Using mice, we combined patch clamp electrophysiology, chemogenetics, unsupervised cluster analysis, and predictive modeling and found that a previously unreported subpopulation of fast-spiking Sst+ INs mediate LEC→BLA FFI.

Preserving the balance: diverse forms of long-term GABAergic synaptic plasticity

Cellular mechanisms that regulate the interplay of synaptic excitation and inhibition are thought to be central to the functional stability of healthy neuronal circuits. A growing body of literature demonstrates the capacity for inhibitory GABAergic synapses to exhibit long-term plasticity in response to changes in neuronal activity. Here, we review this expanding field of research, focusing on the diversity of mechanisms that link glutamatergic signalling, postsynaptic action potentials and inhibitory synaptic strength. Several lines of evidence indicate that multiple, parallel forms of plasticity serve to regulate activity at both the input and output domains of individual neurons. Overall, these varied phenomena serve to promote both stability and flexibility over the life of the organism.

Dendritic inhibition differentially regulates excitability of dentate gyrus parvalbumin-expressing interneurons and granule cells

Fast-spiking parvalbumin-expressing interneurons (PVIs) and granule cells (GCs) of the dentate gyrus receive layer-specific dendritic inhibition. Its impact on PVI and GC excitability is, however, unknown. By applying whole-cell recordings, GABA uncaging and single-cell-modeling, we show that proximal dendritic inhibition in PVIs is less efficient in lowering perforant path-mediated subthreshold depolarization than distal inhibition but both are highly efficient in silencing PVIs. These inhibitory effects can be explained by proximal shunting and distal strong hyperpolarizing inhibition. In contrast, GC proximal but not distal inhibition is the primary regulator of their excitability and recruitment. In GCs inhibition is hyperpolarizing along the entire somato-dendritic axis with similar strength. Thus, dendritic inhibition differentially controls input-output transformations in PVIs and GCs. Dendritic inhibition in PVIs is suited to balance PVI discharges in dependence on global network activity thereby providing strong and tuned perisomatic inhibition that contributes to the sparse representation of information in GC assemblies.

Fast-spiking parvalbumin-expressing interneurons (PVIs) and granule cells of the dentate gyrus receive layer-specific dendritic inhibition. The authors show that distal and proximal dendritic inhibition differentially control input-output transformations in PVIs and granule cells.

Single Synapse LTP: A Matter of Context?

The most commonly studied form of synaptic plasticity is long-term potentiation (LTP). Over the last 15 years, it has been possible to induce structural and functional LTP in dendritic spines using two-photon glutamate uncaging, allowing for studying the signaling mechanisms of LTP with single synapse resolution. In this review, we compare different stimulation methods to induce single synapse LTP and discuss how LTP is expressed. We summarize the underlying signaling mechanisms that have been studied with high spatiotemporal resolution. Finally, we discuss how LTP in a single synapse can be affected by excitatory and inhibitory synapses nearby. We argue that single synapse LTP is highly dependent on context: the choice of induction method, the history of the dendritic spine and the dendritic vicinity crucially affect signaling pathways and expression of single synapse LTP.

Functional clustering of dendritic activity during decision-making

The active properties of dendrites can support local nonlinear operations, but previous imaging and electrophysiological measurements have produced conflicting views regarding the prevalence and selectivity of local nonlinearities in vivo. We imaged calcium signals in pyramidal cell dendrites in the motor cortex of mice performing a tactile decision task. A custom microscope allowed us to image the soma and up to 300 μm of contiguous dendrite at 15 Hz, while resolving individual spines. New analysis methods were used to estimate the frequency and spatial scales of activity in dendritic branches and spines. The majority of dendritic calcium transients were coincident with global events. However, task-associated calcium signals in dendrites and spines were compartmentalized by dendritic branching and clustered within branches over approximately 10 μm. Diverse behavior-related signals were intermingled and distributed throughout the dendritic arbor, potentially supporting a large learning capacity in individual neurons.

Semaphorin4D Induces Inhibitory Synapse Formation by Rapid Stabilization of Presynaptic Boutons via MET Coactivation

Changes in inhibitory connections are essential for experience-dependent circuit adaptations. Defects in inhibitory synapses are linked to neurodevelopmental disorders, but the molecular processes underlying inhibitory synapse formation are not well understood. Here we use high-resolution two-photon microscopy in organotypic hippocampal slices from GAD65-GFP mice of both sexes to examine the signaling pathways induced by the postsynaptic signaling molecule Semaphorin4D (Sema4D) during inhibitory synapse formation. By monitoring changes in individual GFP-labeled presynaptic boutons, we found that the primary action of Sema4D is to induce stabilization of presynaptic boutons within tens of minutes. Stabilized boutons rapidly recruited synaptic vesicles, followed by accumulation of postsynaptic gephyrin and were functional after 24 h, as determined by electrophysiology and immunohistochemistry. Inhibitory boutons are only sensitive to Sema4D at a specific stage during synapse formation and sensitivity to Sema4D is regulated by network activity. We further examined the intracellular signaling cascade triggered by Sema4D and found that bouton stabilization occurs through rapid remodeling of the actin cytoskeleton. This could be mimicked by the actin-depolymerizing drug latrunculin B or by reducing ROCK activity. We discovered that the intracellular signaling cascade requires activation of the receptor tyrosine kinase MET, which is a well known autism risk factor. By using a viral approach to reduce MET levels specifically in inhibitory neurons, we found that their axons are no longer sensitive to Sema4D signaling. Together, our data yield important insights into the molecular pathway underlying activity-dependent Sema4D-induced synapse formation and reveal a novel role for presynaptic MET at inhibitory synapses.SIGNIFICANCE STATEMENT GABAergic synapses provide the main inhibitory control of neuronal activity in the brain. We wanted to unravel the sequence of molecular events that take place when formation of inhibitory synapses is triggered by a specific signaling molecule, Sema4D. We find that this signaling pathway depends on network activity and involves specific remodeling of the intracellular actin cytoskeleton. We also reveal a previously unknown role for MET at inhibitory synapses. Our study provides novel insights into the dynamic process of inhibitory synapse formation. As defects in GABAergic synapses have been implied in many brain disorders, and mutations in MET are strong risk factors for autism, our findings urge for a further investigation of the role of MET at inhibitory synapses.

Sparse Associative Memory

It is still unknown how associative biological memories operate. Hopfield networks are popular models of associative memory, but they suffer from spurious memories and low efficiency. Here, we present a new model of an associative memory that overcomes these deficiencies. We call this model sparse associative memory (SAM) because it is based on sparse projections from neural patterns to pattern-specific neurons. These sparse projections have been shown to be sufficient to uniquely encode a neural pattern. Based on this principle, we investigate theoretically and in simulation our SAM model, which turns out to have high memory efficiency and a vanishingly small probability of spurious memories. This model may serve as a basic building block of brain functions involving associative memory.

GABAergic inhibition reduces the impact of synaptic excitation on somatic excitation

The effect of excitatory synaptic input on the excitation of the cell body is believed to vary depending on where and when the synaptic activation occurs in dendritic trees and the spatiotemporal modulation by inhibitory synaptic input. However, few studies have examined how individual synaptic inputs influence the excitability of the cell body in spontaneously active neuronal networks mainly because of the lack of an appropriate method. We developed a calcium imaging technique that monitors synaptic inputs to hundreds of spines from a single neuron with millisecond resolution in combination with whole-cell patch-clamp recordings of somatic excitation. In rat hippocampal CA3 pyramidal neurons ex vivo, a fraction of the excitatory synaptic inputs were not detectable in the cell body against background noise. These synaptic inputs partially restored their somatic impact when a GABA_A receptor blocker was intracellularly perfused. Thus, GABAergic inhibition reduces the influence of some excitatory synaptic inputs on the somatic excitability. Numerical simulation using a single neuron model demonstrates that the timing and locus of a dendritic GABAergic input are critical to exert this effect. Moreover, logistic regression analyses suggest that the GABAergic inputs sectionalize spine activity; that is, only some subsets of synchronous synaptic activity seemed to be preferably passed to the cell body. Thus, dendrites actively sift inputs from specific presynaptic cell assemblies.

Timed Synaptic Inhibition Shapes NMDA Spikes, Influencing Local Dendritic Processing and Global I/O Properties of Cortical Neurons

The NMDA spike is a long-lasting nonlinear phenomenon initiated locally in the dendritic branches of a variety of cortical neurons. It plays a key role in synaptic plasticity and in single-neuron computations. Combining dynamic system theory and computational approaches, we now explore how the timing of synaptic inhibition affects the NMDA spike and its associated membrane current. When impinging on its early phase, individual inhibitory synapses strongly, but transiently, dampen the NMDA spike; later inhibition prematurely terminates it. A single inhibitory synapse reduces the NMDA-mediated Ca²⁺ current, a key player in plasticity, by up to 45%. NMDA spikes in distal dendritic branches/spines are longer-lasting and more resilient to inhibition, enhancing synaptic plasticity at these branches. We conclude that NMDA spikes are highly sensitive to dendritic inhibition; sparse weak inhibition can finely tune synaptic plasticity both locally at the dendritic branch level and globally at the level of the neuron's output.

Potassium channels contribute to activity-dependent regulation of dendritic inhibition

GABAergic inhibition plays a critical role in the regulation of neuronal activity. In the neocortex, inhibitory interneurons that target the dendrites of pyramidal cells influence both electrical and biochemical postsynaptic signaling. Voltage-gated ion channels strongly shape dendritic excitability and the integration of excitatory inputs, but their contribution to GABAergic signaling is less well understood. By combining 2-photon calcium imaging and focal GABA uncaging, we show that voltage-gated potassium channels normally suppress the GABAergic inhibition of calcium signals evoked by back-propagating action potentials in dendritic spines and shafts of cortical pyramidal neurons. Moreover, the voltage-dependent inactivation of these channels leads to enhancement of dendritic calcium inhibition following somatic spiking. Computational modeling reveals that the enhancement of calcium inhibition involves an increase in action potential depolarization coupled with the nonlinear relationship between membrane voltage and calcium channel activation. Overall, our findings highlight the interaction between intrinsic and synaptic properties and reveal a novel mechanism for the activity-dependent regulation of GABAergic inhibition.

Functional implications of inhibitory synapse placement on signal processing in pyramidal neuron dendrites

A rich literature describes inhibitory innervation of pyramidal neurons in terms of the distinct inhibitory cell types that target the soma, axon initial segment, or dendritic arbor. Less attention has been devoted to how localization of inhibition to specific parts of the pyramidal dendritic arbor influences dendritic signal detection and integration. The effect of inhibitory inputs can vary based on their placement on dendritic spines versus shaft, their distance from the soma, and the branch order of the dendrite they inhabit. Inhibitory synapses are also structurally dynamic, and the implications of these dynamics depend on their dendritic location. Here we consider the heterogeneous roles of inhibitory synapses as defined by their strategic placement on the pyramidal cell dendritic arbor.

Detailed Dendritic Excitatory/Inhibitory Balance through Heterosynaptic Spike-Timing-Dependent Plasticity

The balance between excitatory and inhibitory inputs is a key feature of cortical dynamics. Such a balance is arguably preserved in dendritic branches, yet its underlying mechanism and functional roles remain unknown. In this study, we developed computational models of heterosynaptic spike-timing-dependent plasticity (STDP) to show that the excitatory/inhibitory balance in dendritic branches is robustly achieved through heterosynaptic interactions between excitatory and inhibitory synapses. The model reproduces key features of experimental heterosynaptic STDP well, and provides analytical insights. Furthermore, heterosynaptic STDP explains how the maturation of inhibitory neurons modulates the selectivity of excitatory neurons for binocular matching in the critical period plasticity. The model also provides an alternative explanation for the potential mechanism underlying the somatic detailed balance that is commonly associated with inhibitory STDP. Our results propose heterosynaptic STDP as a critical factor in synaptic organization and the resultant dendritic computation.SIGNIFICANCE STATEMENT Recent experimental studies reveal that relative differences in spike timings experienced among neighboring glutamatergic and GABAergic synapses on a dendritic branch significantly influences changes in the efficiency of these synapses. This heterosynaptic form of spike-timing-dependent plasticity (STDP) is potentially important for shaping the synaptic organization and computation of neurons, but its functional role remains elusive. Through computational modeling at the parameter regime where previous experimental results are well reproduced, we show that heterosynaptic plasticity serves to finely balance excitatory and inhibitory inputs on the dendrite. Our results suggest a principle of GABA-driven neural circuit formation.

Learning with three factors: modulating Hebbian plasticity with errors

Synaptic plasticity is a central theme in neuroscience. A framework of three-factor learning rules provides a powerful abstraction, helping to navigate through the abundance of models of synaptic plasticity. It is well-known that the dopamine modulation of learning is related to reward, but theoretical models predict other functional roles of the modulatory third factor; it may encode errors for supervised learning, summary statistics of the population activity for unsupervised learning or attentional feedback. Specialized structures may be needed in order to generate and propagate third factors in the neural network.

Layer-specific modulation of neocortical dendritic inhibition during active wakefulness

γ-Aminobutyric acid (GABA)ergic inputs are strategically positioned to gate synaptic integration along the dendritic arbor of pyramidal cells. However, their spatiotemporal dynamics during behavior are poorly understood. Using an optical-tagging electrophysiological approach to record and label somatostatin-expressing (Sst) interneurons (GABAergic neurons specialized for dendritic inhibition), we discovered a layer-specific modulation of their activity in behaving mice. Sst interneuron subtypes, residing in different cortical layers and innervating complementary laminar domains, exhibited opposite activity changes during transitions to active wakefulness. The relative weight of vasoactive intestinal peptide-expressing (Vip) interneuron-mediated inhibition of distinct Sst interneurons and cholinergic modulation determined their in vivo activity. These results reveal a state-dependent laminar influence of Sst interneuron-mediated inhibition, with implications for the compartmentalized regulation of dendritic signaling in the mammalian neocortex.

Perisomatic GABAergic synapses of basket cells effectively control principal neuron activity in amygdala networks

Efficient control of principal neuron firing by basket cells is critical for information processing in cortical microcircuits, however, the relative contribution of their perisomatic and dendritic synapses to spike inhibition is still unknown. Using in vitro electrophysiological paired recordings we reveal that in the mouse basal amygdala cholecystokinin- and parvalbumin-containing basket cells provide equally potent control of principal neuron spiking. We performed pharmacological manipulations, light and electron microscopic investigations to show that, although basket cells innervate the entire somato-denditic membrane surface of principal neurons, the spike controlling effect is achieved primarily via the minority of synapses targeting the perisomatic region. As the innervation patterns of individual basket cells on their different postsynaptic partners show high variability, the impact of inhibitory control accomplished by single basket cells is also variable. Our results show that both basket cell types can powerfully regulate the activity in amygdala networks predominantly via their perisomatic synapses.

DOI:http://dx.doi.org/10.7554/eLife.20721.001

Live imaging of inhibitory axons: Synapse formation as a dynamic trial-and-error process

In this review I discuss recent live imaging studies that demonstrate that synapses, and in particular inhibitory synapses, are highly dynamic structures. The ongoing changes of presynaptic boutons within axons emphasize the stochastic aspect of inhibitory synapse formation and paint a picture of a dynamic trial-and-error process. Furthermore, I discuss recent and previous insights in the molecular and mechanistic pathways that underlie synapse formation, with a specific focus on the formation of inhibitory presynaptic boutons.