Diversity and dynamics of dendritic signaling

How do neurons age? A focused review on the aging of the microtubular cytoskeleton

Aging is the leading risk factor for Alzheimer's disease and other neurodegenerative diseases. We now understand that a breakdown in the neuronal cytoskeleton, mainly underpinned by protein modifications leading to the destabilization of microtubules, is central to the pathogenesis of Alzheimer's disease. This is accompanied by morphological defects across the somatodendritic compartment, axon, and synapse. However, knowledge of what occurs to the microtubule cytoskeleton and morphology of the neuron during physiological aging is comparatively poor. Several recent studies have suggested that there is an age-related increase in the phosphorylation of the key microtubule stabilizing protein tau, a modification, which is known to destabilize the cytoskeleton in Alzheimer's disease. This indicates that the cytoskeleton and potentially other neuronal structures reliant on the cytoskeleton become functionally compromised during normal physiological aging. The current literature shows age-related reductions in synaptic spine density and shifts in synaptic spine conformation which might explain age-related synaptic functional deficits. However, knowledge of what occurs to the microtubular and actin cytoskeleton, with increasing age is extremely limited. When considering the somatodendritic compartment, a regression in dendrites and loss of dendritic length and volume is reported whilst a reduction in soma volume/size is often seen. However, research into cytoskeletal change is limited to a handful of studies demonstrating reductions in and mislocalizations of microtubule-associated proteins with just one study directly exploring the integrity of the microtubules. In the axon, an increase in axonal diameter and age-related appearance of swellings is reported but like the dendrites, just one study investigates the microtubules directly with others reporting loss or mislocalization of microtubule-associated proteins. Though these are the general trends reported, there are clear disparities between model organisms and brain regions that are worthy of further investigation. Additionally, longitudinal studies of neuronal/cytoskeletal aging should also investigate whether these age-related changes contribute not just to vulnerability to disease but also to the decline in nervous system function and behavioral output that all organisms experience. This will highlight the utility, if any, of cytoskeletal fortification for the promotion of healthy neuronal aging and potential protection against age-related neurodegenerative disease. This review seeks to summarize what is currently known about the physiological aging of the neuron and microtubular cytoskeleton in the hope of uncovering mechanisms underpinning age-related risk to disease.

Neuronal maturation and axon regeneration: unfixing circuitry to enable repair

Mammalian neurons lose the ability to regenerate their central nervous system axons as they mature during embryonic or early postnatal development. Neuronal maturation requires a transformation from a situation in which neuronal components grow and assemble to one in which these components are fixed and involved in the machinery for effective information transmission and computation. To regenerate after injury, neurons need to overcome this fixed state to reactivate their growth programme. A variety of intracellular processes involved in initiating or sustaining neuronal maturation, including the regulation of gene expression, cytoskeletal restructuring and shifts in intracellular trafficking, have been shown to prevent axon regeneration. Understanding these processes will contribute to the identification of targets to promote repair after injury or disease.

VEGFD signaling balances stability and activity-dependent structural plasticity of dendrites

Mature neurons have stable dendritic architecture, which is essential for the nervous system to operate correctly. The ability to undergo structural plasticity, required to support adaptive processes like memory formation, is still present in mature neurons. It is unclear what molecular and cellular processes control this delicate balance between dendritic structural plasticity and stabilization. Failures in the preservation of optimal dendrite structure due to atrophy or maladaptive plasticity result in abnormal connectivity and are associated with various neurological diseases. Vascular endothelial growth factor D (VEGFD) is critical for the maintenance of mature dendritic trees. Here, we describe how VEGFD affects the neuronal cytoskeleton and demonstrate that VEGFD exerts its effects on dendrite stabilization by influencing the actin cortex and reducing microtubule dynamics. Further, we found that during synaptic activity-induced structural plasticity VEGFD is downregulated. Our findings revealed that VEGFD, acting on its cognate receptor VEGFR3, opposes structural changes by negatively regulating dendrite growth in cultured hippocampal neurons and in vivo in the adult mouse hippocampus with consequences on memory formation. A phosphoproteomic screening identified several regulatory proteins of the cytoskeleton modulated by VEGFD. Among the actin cortex-associated proteins, we found that VEGFD induces dephosphorylation of ezrin at tyrosine 478 via activation of the striatal-enriched protein tyrosine phosphatase (STEP). Activity-triggered structural plasticity of dendrites was impaired by expression of a phospho-deficient mutant ezrin in vitro and in vivo. Thus, VEGFD governs the equilibrium between stabilization and plasticity of dendrites by acting as a molecular brake of structural remodeling.

Approaching the Ideal Linearity in Epitaxial Crystalline-Type Memristor by Controlling Filament Growth

Brain-inspired neuromorphic computing has attracted widespread attention owing to its ability to perform parallel and energy-efficient computation. However, the synaptic weight of amorphous/polycrystalline oxide based memristor usually exhibits large nonlinear behavior with high asymmetry, which aggravates the complexity of peripheral circuit system. Controllable growth of conductive filaments is highly demanded for achieving the highly linear conductance modulation. However, the stochastic behavior of the filament growth in commonly used amorphous/polycrystalline oxide memristor makes it very challenging. Here, the epitaxially grown Hf0.5Zr0.5O2-based memristor with the linearity and symmetry approaching ideal case is reported. A layer of Cu nanoparticles is inserted into epitaxially grown Hf0.5Zr0.5O2 film to form the grain boundaries due to the breaking of the epitaxial growth. By combining with the local electric field enhancement, the growth of filament is confined in the grain boundaries due to the fact that the diffusion of oxygen vacancy in crystalline lattice is more difficult than that in the grain boundaries. Furthermore, the decimal operation and high-accuracy neural network are demonstrated by utilizing the highly linear and multi-level conductance modulation capacity. This method opens an avenue to control the filament growth for the application of resistance random access memory (RRAM) and neuromorphic computing.

The spiking output of the mouse olfactory bulb encodes large-scale temporal features of natural odor environments

In natural odor environments, odor travels in plumes. Odor concentration dynamics change in characteristic ways across the width and length of a plume. Thus, spatiotemporal dynamics of plumes have informative features for animals navigating to an odor source. Population activity in the olfactory bulb (OB) has been shown to follow odor concentration across plumes to a moderate degree (Lewis et al., 2021). However, it is unknown whether the ability to follow plume dynamics is driven by individual cells or whether it emerges at the population level. Previous research has explored the responses of individual OB cells to isolated features of plumes, but it is difficult to adequately sample the full feature space of plumes as it is still undetermined which features navigating mice employ during olfactory guided search. Here we released odor from an upwind odor source and simultaneously recorded both odor concentration dynamics and cellular response dynamics in awake, head-fixed mice. We found that longer timescale features of odor concentration dynamics were encoded at both the cellular and population level. At the cellular level, responses were elicited at the beginning of the plume for each trial, signaling plume onset. Plumes with high odor concentration elicited responses at the end of the plume, signaling plume offset. Although cellular level tracking of plume dynamics was observed to be weak, we found that at the population level, OB activity distinguished whiffs and blanks (accurately detected odor presence versus absence) throughout the duration of a plume. Even ~20 OB cells were enough to accurately discern odor presence throughout a plume. Our findings indicate that the full range of odor concentration dynamics and high frequency fluctuations are not encoded by OB spiking activity. Instead, relatively lower-frequency temporal features of plumes, such as plume onset, plume offset, whiffs, and blanks, are represented in the OB.

Neuronal Subtypes and Connectivity of the Adult Mouse Paralaminar Amygdala

The paralaminar nucleus of the amygdala (PL) comprises neurons that exhibit delayed maturation. PL neurons are born during gestation but mature during adolescent ages, differentiating into excitatory neurons. These late-maturing PL neurons contribute to the increase in size and cell number of the amygdala between birth and adulthood. However, the function of the PL upon maturation is unknown, as the region has only recently begun to be characterized in detail. In this study, we investigated key defining features of the adult mouse PL; the intrinsic morpho-electric properties of its neurons, and its input and output circuit connectivity. We identify two subtypes of excitatory neurons in the PL based on unsupervised clustering of electrophysiological properties. These subtypes are defined by differential action potential firing properties and dendritic architecture, suggesting divergent functional roles. We further uncover major axonal inputs to the adult PL from the main olfactory network and basolateral amygdala. We also find that axonal outputs from the PL project reciprocally to these inputs and to diverse targets including the amygdala, frontal cortex, hippocampus, hypothalamus, and brainstem. Thus, the adult mouse PL is centrally placed to play a major role in the integration of olfactory sensory information, to coordinate affective and autonomic behavioral responses to salient odor stimuli.

Engram mechanisms of memory linking and identity

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

Dendritic excitations govern back-propagation via a spike-rate accelerometer

Dendrites on neurons support nonlinear electrical excitations, but the computational significance of these events is not well understood. We developed molecular, optical, and analytical tools to map sub-millisecond voltage dynamics throughout the dendritic trees of CA1 pyramidal neurons under diverse optogenetic and synaptic stimulus patterns, in acute brain slices. We observed history-dependent spike back-propagation in distal dendrites, driven by locally generated Na+ spikes (dSpikes). Dendritic depolarization created a transient window for dSpike propagation, opened by A-type K V channel inactivation, and closed by slow N a V inactivation. Collisions of dSpikes with synaptic inputs triggered calcium channel and N-methyl-D-aspartate receptor (NMDAR)-dependent plateau potentials, with accompanying complex spikes at the soma. This hierarchical ion channel network acts as a spike-rate accelerometer, providing an intuitive picture of how dendritic excitations shape associative plasticity rules.

Genetic deletion of zinc transporter ZnT3 induces progressive cognitive deficits in mice by impairing dendritic spine plasticity and glucose metabolism

Zinc transporter 3 (ZnT3) is abundantly expressed in the brain, residing in synaptic vesicles, where it plays important roles in controlling the luminal zinc levels. In this study, we found that ZnT3 knockout in mice decreased zinc levels in the hippocampus and cortex, and was associated with progressive cognitive impairments, assessed at 2, 6, and 9-month of age. The results of Golgi-Cox staining demonstrated that ZnT3 deficiency was associated with an increase in dendritic complexity and a decrease in the density of mature dendritic spines, indicating potential synaptic plasticity deficit. Since ZnT3 deficiency was previously linked to glucose metabolism abnormalities, we tested the expression levels of genes related to insulin signaling pathway in the hippocampus and cortex. We found that the Expression of glucose transporters, GLUT3, GLUT4, and the insulin receptor in the whole tissue and synaptosome fraction of the hippocampus of the ZnT3 knockout mice were significantly reduced, as compared to wild-type controls. Expression of AKT (A serine/threonine protein kinase) and insulin-induced AKT phosphorylation was also reduced in the hippocampus of ZnT3 knockout mice. We hypothesize that the ZnT3 deficiency and reduced brain zinc levels may cause cognitive impairment by negatively affecting glycose metabolism via decreased expression of key components of insulin signaling, as well as via changes in synaptic plasticity. These finding may provide new therapeutic target for treatments of neurodegenerative disorders.

Structural changes of CA1 pyramidal neurons after stroke in the contralesional hippocampus

Significant progress has been made with regard to understanding how the adult brain responds after a stroke. However, a large number of patients continue to suffer lifelong disabilities without adequate treatment. In the present study, we have analyzed possible microanatomical alterations in the contralesional hippocampus from the ischemic stroke mouse model tMCAo 12-14 weeks after transient middle cerebral artery occlusion. After individually injecting Lucifer yellow into pyramidal neurons from the CA1 field of the hippocampus, we performed a detailed three-dimensional analysis of the neuronal complexity, dendritic spine density, and morphology. We found that, in both apical (stratum radiatum) and basal (stratum oriens) arbors, CA1 pyramidal neurons in the contralesional hippocampus of tMCAo mice have a significantly higher neuronal complexity, as well as reduced spine density and alterations in spine volume and spine length. Our results show that when the ipsilateral hippocampus is dramatically damaged, the contralesional hippocampus exhibits several statistically significant selective alterations. However, these alterations are not as significant as expected, which may help to explain the recovery of hippocampal function after stroke. Further anatomical and physiological studies are necessary to better understand the modifications in the "intact" contralesional lesioned brain regions, which are probably fundamental to recover functions after stroke.

An Agent-Based Model to Reproduce the Boolean Logic Behaviour of Neuronal Self-Organised Communities through Pulse Delay Modulation and Generation of Logic Gates

The human brain is arguably the most complex "machine" to ever exist. Its detailed functioning is yet to be fully understood, let alone modelled. Neurological processes have logical signal-processing and biophysical aspects, and both affect the brain's structure, functioning and adaptation. Mathematical approaches based on both information and graph theory have been extensively used in an attempt to approximate its biological functioning, along with Artificial Intelligence frameworks inspired by its logical functioning. In this article, an approach to model some aspects of the brain learning and signal processing is presented, mimicking the metastability and backpropagation found in the real brain while also accounting for neuroplasticity. Several simulations are carried out with this model to demonstrate how dynamic neuroplasticity, neural inhibition and neuron migration can reshape the brain's logical connectivity to synchronise signal processing and obtain certain target latencies. This work showcases the importance of dynamic logical and biophysical remodelling in brain plasticity. Combining mathematical (agents, graph theory, topology and backpropagation) and biomedical ingredients (metastability, neuroplasticity and migration), these preliminary results prove complex brain phenomena can be reproduced-under pertinent simplifications-via affordable computations, which can be construed as a starting point for more ambitiously accurate simulations.

Neuronal subtypes and connectivity of the adult mouse paralaminar amygdala

The paralaminar nucleus of the amygdala (PL) is comprised of neurons which exhibit delayed maturation. PL neurons are born during gestation but mature during adolescent ages, differentiating into excitatory neurons. The PL is prominent in the adult amygdala, contributing to its increased neuron number and relative size compared to childhood. However, the function of the PL is unknown, as the region has only recently begun to be characterized in detail. In this study, we investigated key defining features of the adult PL; the intrinsic morpho-electric properties of its neurons, and its input and output connectivity. We identify two subtypes of excitatory neurons in the PL based on unsupervised clustering of electrophysiological properties. These subtypes are defined by differential action potential firing properties and dendritic architecture, suggesting divergent functional roles. We further uncover major axonal inputs to the adult PL from the main olfactory network and basolateral amygdala. We also find that axonal outputs from the PL project reciprocally to major inputs, and to diverse targets including the amygdala, frontal cortex, hippocampus, hypothalamus, and brainstem. Thus, the adult PL is centrally placed to play a major role in the integration of olfactory sensory information, likely coordinating affective and autonomic behavioral responses to salient odor stimuli.

Significance Statement

Mammalian amygdala development includes a growth period from childhood to adulthood, believed to support emotional and social learning. This amygdala growth is partly due to the maturation of neurons during adolescence in the paralaminar amygdala. However, the functional properties of these neurons are unknown. In our recent studies, we characterized the paralaminar amygdala in the mouse. Here, we investigate the properties of the adult PL in the mouse, revealing the existence of two neuronal subtypes that may play distinct functional roles in the adult brain. We further reveal the brain-wide input and output connectivity of the PL, indicating that the PL combines olfactory cues for emotional processing and delivers information to regions associated with reward and autonomic states.

Temporal dendritic heterogeneity incorporated with spiking neural networks for learning multi-timescale dynamics

It is widely believed the brain-inspired spiking neural networks have the capability of processing temporal information owing to their dynamic attributes. However, how to understand what kind of mechanisms contributing to the learning ability and exploit the rich dynamic properties of spiking neural networks to satisfactorily solve complex temporal computing tasks in practice still remains to be explored. In this article, we identify the importance of capturing the multi-timescale components, based on which a multi-compartment spiking neural model with temporal dendritic heterogeneity, is proposed. The model enables multi-timescale dynamics by automatically learning heterogeneous timing factors on different dendritic branches. Two breakthroughs are made through extensive experiments: the working mechanism of the proposed model is revealed via an elaborated temporal spiking XOR problem to analyze the temporal feature integration at different levels; comprehensive performance benefits of the model over ordinary spiking neural networks are achieved on several temporal computing benchmarks for speech recognition, visual recognition, electroencephalogram signal recognition, and robot place recognition, which shows the best-reported accuracy and model compactness, promising robustness and generalization, and high execution efficiency on neuromorphic hardware. This work moves neuromorphic computing a significant step toward real-world applications by appropriately exploiting biological observations.

Preserved neural dynamics across animals performing similar behaviour

Animals of the same species exhibit similar behaviours that are advantageously adapted to their body and environment. These behaviours are shaped at the species level by selection pressures over evolutionary timescales. Yet, it remains unclear how these common behavioural adaptations emerge from the idiosyncratic neural circuitry of each individual. The overall organization of neural circuits is preserved across individuals1 because of their common evolutionarily specified developmental programme2-4. Such organization at the circuit level may constrain neural activity5-8, leading to low-dimensional latent dynamics across the neural population9-11. Accordingly, here we suggested that the shared circuit-level constraints within a species would lead to suitably preserved latent dynamics across individuals. We analysed recordings of neural populations from monkey and mouse motor cortex to demonstrate that neural dynamics in individuals from the same species are surprisingly preserved when they perform similar behaviour. Neural population dynamics were also preserved when animals consciously planned future movements without overt behaviour12 and enabled the decoding of planned and ongoing movement across different individuals. Furthermore, we found that preserved neural dynamics extend beyond cortical regions to the dorsal striatum, an evolutionarily older structure13,14. Finally, we used neural network models to demonstrate that behavioural similarity is necessary but not sufficient for this preservation. We posit that these emergent dynamics result from evolutionary constraints on brain development and thus reflect fundamental properties of the neural basis of behaviour.

Sculpting the dendritic landscape: Actin, microtubules, and the art of arborization

Dendrites are intricately designed neuronal compartments that play a vital role in the gathering and processing of sensory or synaptic inputs. Their diverse and elaborate structures are distinct features of neuronal organization and function. Central to the generation of these dendritic arbors is the neuronal cytoskeleton. In this review, we delve into the current progress toward our understanding of how dendrite arbors are generated and maintained, focusing on the role of the actin and microtubule cytoskeleton.

Solving classification tasks by a receptron based on nonlinear optical speckle fields

Among several approaches to tackle the problem of energy consumption in modern computing systems, two solutions are currently investigated: one consists of artificial neural networks (ANNs) based on photonic technologies, the other is a different paradigm compared to ANNs and it is based on random networks of non-linear nanoscale junctions resulting from the assembling of nanoparticles or nanowires as substrates for neuromorphic computing. These networks show the presence of emergent complexity and collective phenomena in analogy with biological neural networks characterized by self-organization, redundancy, and non-linearity. Starting from this background, we propose and formalize a generalization of the perceptron model to describe a classification device based on a network of interacting units where the input weights are non-linearly dependent. We show that this model, called "receptron", provides substantial advantages compared to the perceptron as, for example, the solution of non-linearly separable Boolean functions with a single device. The receptron model is used as a starting point for the implementation of an all-optical device that exploits the non-linearity of optical speckle fields produced by a solid scatterer. By encoding these speckle fields we generated a large variety of target Boolean functions. We demonstrate that by properly setting the model parameters, different classes of functions with different multiplicity can be solved efficiently. The optical implementation of the receptron scheme opens the way for the fabrication of a completely new class of optical devices for neuromorphic data processing based on a very simple hardware.

A Memristors-Based Dendritic Neuron for High-Efficiency Spatial-Temporal Information Processing

Diverse microscopic ionic dynamics help mediate the ability of a biological neural network to handle complex tasks with low energy consumption. Thus, rich internal ionic dynamics in memristors based on transition metal oxide are expected to provide a unique and useful platform for implementing energy-efficient neuromorphic computing. To this end, a titanium oxide (TiOx )-based interface-type dynamic memristor and an niobium oxide (NbOx )-based Mott memristor are integrated as an artificial dendrite and spike-firing soma, respectively, to construct a dendritic neuron unit for realizing high-efficiency spatial-temporal information processing. Further, a dendritic neural network is hardware-implemented for spatial-temporal information processing to highlight the computational advantages achieved by incorporating dendritic functions in the network. Human motion recognition is demonstrated using the Nanyang Technological University-Red Green Blue (NTU-RGB) dataset as a benchmark spatial-temporal task; it shows a nearly 20% improvement in accuracy for the memristors-based hardware incorporating dendrites and a 1000× advantage in power efficiency compared to that of the graphics processing unit (GPU). The dendritic neuron developed in this study can be considered a critical building block for implementing more bio-plausible neural networks that can manage complex spatial-temporal tasks with high efficiency.

Hippocampal transcriptome analysis reveals mechanisms of cognitive impairment in beagle dogs with type 1 diabetes

Diabetic encephalopathy is a common complication of type 1 diabetes. However, there have been few studies on cognitive impairment and hippocampal damage in type 1 diabetes mellitus (T1DM) using dogs as experimental animals. To investigate the effects of diabetes on the CNS, 40 adult beagles were divided into streptozotocin/alloxan type 1 diabetes model and control groups. The duration of diabetes in the model group was 120 days. A cognitive dysfunction scale was used to assess cognitive function. Hematoxylin and eosin and Golgi-Cox staining methods were used to observe morphological damage to the hippocampus. Transcriptomics was used to investigate differential gene expression in the hippocampus. The results showed that the cognitive dysfunction score of the model group was significantly higher than that of the control group. In addition, the number of normal neurons, the complexity of dendritic morphology, and the density of dendritic spines were decreased in the hippocampus of diabetic dogs. A total of 672 differentially expressed genes (DEGs) were identified, 289 of which were upregulated, and 383 were downregulated. Modified genes included DBH, IGFBP2, AVPR1A, and DRAXIN. In conclusion, type 1 diabetic dogs exhibit cognitive dysfunction. The DEGs were mainly enriched in metabolic, PI3K-Akt signaling, and neuroactive ligand-receptor interaction pathways.

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.

Loss of cholinergic receptor muscarinic 1 impairs cortical mitochondrial structure and function: implications in Alzheimer's disease

Introduction: Cholinergic Receptor Muscarinic 1 (CHRM1) is a G protein-coupled acetylcholine (ACh) receptor predominantly expressed in the cerebral cortex. In a retrospective postmortem brain tissues-based study, we demonstrated that severely (≥50% decrease) reduced CHRM1 proteins in the temporal cortex of Alzheimer's patients significantly correlated with poor patient outcomes. The G protein-mediated CHRM1 signal transduction cannot sufficiently explain the mechanistic link between cortical CHRM1 loss and the appearance of hallmark Alzheimer's pathophysiologies, particularly mitochondrial structural and functional abnormalities. Therefore, the objective of this study was to analyze the molecular, ultrastructural, and functional properties of cortical mitochondria using CHRM1 knockout (Chrm1^-/-) and wild-type mice to identify mitochondrial abnormalities. Methods: Isolated and enriched cortical mitochondrial fractions derived from wild-type and Chrm1^-/- mice were assessed for respiratory deficits (oxygen consumption) following the addition of different substrates. The supramolecular assembly of mitochondrial oxidative phosphorylation (OXPHOS)-associated protein complexes (complex I-V) and cortical mitochondrial ultrastructure were investigated by blue native polyacrylamide gel electrophoresis and transmission electron microscopy (TEM), respectively. A cocktail of antibodies, specific to Ndufb8, Sdhb, Uqcrc2, Mtco1, and Atp5a proteins representing different subunits of complexes I-V, respectively was used to characterize different OXPHOS-associated protein complexes. Results: Loss of Chrm1 led to a significant reduction in cortical mitochondrial respiration (oxygen consumption) concomitantly associated with reduced oligomerization of ATP synthase (complex V) and supramolecular assembly of complexes I-IV (Respirasome). Overexpression of Chrm1 in transformed cells (lacking native Chrm1) significantly increased complex V oligomerization and respirasome assembly leading to enhanced respiration. TEM analysis revealed that Chrm1 loss led to mitochondrial ultrastructural defects and alteration in the tinctorial properties of cortical neurons causing a significant increase in the abundance of dark cortical neurons (Chrm1^-/- 85% versus wild-type 2%). Discussion: Our findings indicate a hitherto unknown effect of Chrm1 deletion in cortical neurons affecting mitochondrial function by altering multiple interdependent factors including ATP synthase oligomerization, respirasome assembly, and mitochondrial ultrastructure. The appearance of dark neurons in Chrm1^-/- cortices implies potentially enhanced glutamatergic signaling in pyramidal neurons under Chrm1 loss condition. The findings provide novel mechanistic insights into Chrm1 loss with the appearance of mitochondrial pathophysiological deficits in Alzheimer's disease.

The cytoplasmic localization of ADNP through 14-3-3 promotes sex-dependent neuronal morphogenesis, cortical connectivity, and calcium signaling

Defective neuritogenesis is a contributing pathogenic mechanism underlying a variety of neurodevelopmental disorders. Single gene mutations in activity-dependent neuroprotective protein (ADNP) are the most frequent among autism spectrum disorders (ASDs) leading to the ADNP syndrome. Previous studies showed that during neuritogenesis, Adnp localizes to the cytoplasm/neurites, and Adnp knockdown inhibits neuritogenesis in culture. Here, we hypothesized that Adnp is localized in the cytoplasm during neurite formation and that this process is mediated by 14-3-3. Indeed, applying the 14-3-3 inhibitor, difopein, blocked Adnp cytoplasmic localization. Furthermore, co-immunoprecipitations showed that Adnp bound 14-3-3 proteins and proteomic analysis identified several potential phosphorylation-dependent Adnp/14-3-3 binding sites. We further discovered that knockdown of Adnp using in utero electroporation of mouse layer 2/3 pyramidal neurons in the somatosensory cortex led to previously unreported changes in neurite formation beginning at P0. Defects were sustained throughout development, the most notable included increased basal dendrite number and axon length. Paralleling the observed morphological aberrations, ex vivo calcium imaging revealed that Adnp deficient neurons had greater and more frequent spontaneous calcium influx in female mice. GRAPHIC, a novel synaptic tracing technology substantiated this finding, revealing increased interhemispheric connectivity between female Adnp deficient layer 2/3 pyramidal neurons. We conclude that Adnp is localized to the cytoplasm by 14-3-3 proteins, where it regulates neurite formation, maturation, and functional cortical connectivity significantly building on our current understanding of Adnp function and the etiology of ADNP syndrome.

Altered dendritic morphology in dorsolateral prefrontal cortex of nonhuman primates prenatally exposed to maternal immune activation

Women who contract a viral or bacterial infection during pregnancy have an increased risk of giving birth to a child with a neurodevelopmental or psychiatric disorder. The effects of maternal infection are likely mediated by the maternal immune response, as preclinical animal models have confirmed that maternal immune activation (MIA) leads to long lasting changes in offspring brain and behavior development. The present study sought to determine the impact of MIA-exposure during the first or second trimester on neuronal morphology in dorsolateral prefrontal cortex (DLPFC) and hippocampus from brain tissue obtained from MIA-exposed and control male rhesus monkey (Macaca mulatta) during late adolescence. MIA-exposed offspring display increased neuronal dendritic branching in pyramidal cells in DLPFC infra- and supragranular layers relative to controls, with no significant differences observed between offspring exposed to maternal infection in the first and second trimester. In addition, the diameter of apical dendrites in DLPFC infragranular layer is significantly decreased in MIA-exposed offspring relative to controls, irrespective of trimester exposure. In contrast, alterations in hippocampal neuronal morphology of MIA-exposed offspring were not evident. These findings demonstrate that a maternal immune challenge during pregnancy has long-term consequences for primate offspring dendritic structure, selectively in a brain region vital for socioemotional and cognitive development.

New imaging instrument in animal models: Two-photon miniature microscope and large field of view miniature microscope for freely behaving animals

Over the past decade, novel optical imaging tools have been developed for imaging neuronal activities along with the evolution of fluorescence indicators with brighter expression and higher sensitivity. Miniature microscopes, as revolutionary approaches, enable the imaging of large populations of neuron ensembles in freely behaving rodents and mammals, which allows exploring the neural basis of behaviors. Recent progress in two-photon miniature microscopes and mesoscale single-photon miniature microscopes further expand those affordable methods to navigate neural activities during naturalistic behaviors. In this review article, two-photon miniature microscopy techniques are summarized historically from the first documented attempt to the latest ones, and comparisons are made. The driving force behind and their potential for neuroscientific inquiries are also discussed. Current progress in terms of the mesoscale, i.e., the large field-of-view miniature microscopy technique, is addressed as well. Then, pipelines for registering single cells from the data of two-photon and large field-of-view miniature microscopes are discussed. Finally, we present the potential evolution of the techniques.

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

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

Introducing the Dendrify framework for incorporating dendrites to spiking neural networks

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

Endogenous Modulators of NMDA Receptor Control Dendritic Field Expansion of Cortical Neurons

Impairments of N-methyl-D-aspartate receptor (NMDAR) activity have been implicated in several neuropsychiatric disorders, with pharmacological inhibition of NMDAR-mediated currents and associated neurobehavioral changes considered as a model of schizophrenia. We analyzed the effects of brief and long-term exposure of rat cortical cultures to the most prevalent endogenous modulators of NMDAR (kynurenic acid, pregnenolone sulfate, spermidine, and zinc) on neuronal viability, stimulation-induced release of glutamate, and dendritic morphology with synaptic density. Both, glutamate release and neuronal viability studies revealed no difference between the test and control groups. No differences were also observed in the number of dendritic branching and length, or density of synaptic connections and neuronal soma size. Comparison of the extent of dendritic projections and branching patterns, however, revealed enhanced distal arborization with the expansion of the dendritic area under prolonged treatment of cultures with physiological concentrations of NMDAR modulators, with differences reaching significance in spermidine and pregnenolone sulfate tests. Measurements of the density of glutamatergic synapses showed consistency across all neuronal groups, except those treated with pregnenolone sulfate, which showed a reduction of PSD-95-positive elements. Overall, our data suggest that constitutive glutamatergic activity mediated by NMDAR controls the dendritic field expansion and can influence the integrative properties of cortical neurons.

Electrophysiology of Dendritic Spines: Information Processing, Dynamic Compartmentalization, and Synaptic Plasticity

For many years, synaptic transmission was considered as information transfer between presynaptic neuron and postsynaptic cell. At the synaptic level, it was thought that dendritic arbors were only receiving and integrating all information flow sent along to the soma, while axons were primarily responsible for point-to-point information transfer. However, it is important to highlight that dendritic spines play a crucial role as postsynaptic components in central nervous system (CNS) synapses, not only integrating and filtering signals to the soma but also facilitating diverse connections with axons from many different sources. The majority of excitatory connections from presynaptic axonal terminals occurs on postsynaptic spines, although a subset of GABAergic synapses also targets spine heads. Several studies have shown the vast heterogeneous morphological, biochemical, and functional features of dendritic spines related to synaptic processing. In this chapter (adding to the relevant data on the biophysics of spines described in Chap. 1 of this book), we address the up-to-date functional dendritic characteristics assessed through electrophysiological approaches, including backpropagating action potentials (bAPs) and synaptic potentials mediated in dendritic and spine compartmentalization, as well as describing the temporal and spatial dynamics of glutamate receptors in the spines related to synaptic plasticity.

Bi-directional Control of Synaptic Input Summation and Spike Generation by GABAergic Inputs at the Axon Initial Segment

Differing from other subtypes of inhibitory interneuron, chandelier or axo-axonic cells form depolarizing GABAergic synapses exclusively onto the axon initial segment (AIS) of targeted pyramidal cells (PCs). However, the debate whether these AIS-GABAergic inputs produce excitation or inhibition in neuronal processing is not resolved. Using realistic NEURON modeling and electrophysiological recording of cortical layer-5 PCs, we quantitatively demonstrate that the onset-timing of AIS-GABAergic input, relative to dendritic excitatory glutamatergic inputs, determines its bi-directional regulation of the efficacy of synaptic integration and spike generation in a PC. More specifically, AIS-GABAergic inputs promote the boosting effect of voltage-activated Na+ channels on summed synaptic excitation when they precede glutamatergic inputs by >15 ms, while for nearly concurrent excitatory inputs, they primarily produce a shunting inhibition at the AIS. Thus, our findings offer an integrative mechanism by which AIS-targeting interneurons exert sophisticated regulation of the input-output function in targeted PCs.

An insight into sex-specific neurotoxicity and molecular mechanisms of DEHP: A critical review

Di-2-Ethylhexyl Phthalate (DEHP) is often used as an additive in polyvinyl chloride (PVC) to give plastics flexibility, which makes DEHP widely used in food packaging, daily necessities, medical equipment, and other products. However, due to the unstable combination of DEHP and polymer, it will migrate to the environment in the materials and eventually contact the human body. It has been recorded that low-dose DEHP will increase neurotoxicity in the nervous system, and the human health effects of DEHP have been paid attention to because of the extensive exposure to DEHP and its high absorption during brain development. In this study, we review the evidence that DEHP exposure is associated with neurodevelopmental abnormalities and neurological diseases based on human epidemiological and animal behavioral studies. Besides, we also summarized the oxidative damage, apoptosis, and signal transduction disorder related to neurobehavioral abnormalities and nerve injury, and described the potential mechanisms of neurotoxicity caused by DEHP. Overall, we found exposure to DEHP during the critical developmental period will increase the risk of neurobehavioral abnormalities, depression, and autism spectrum disorders. This effect is sex-specific and will continue to adulthood and even have an intergenerational effect. However, the research results on the sex-dependence of DEHP neurotoxicity are inconsistent, and there is a lack of systematic mechanisms research as theoretical support. Future investigations need to be carried out in a large-scale population and model organisms to produce more consistent and convincing results. And we emphasize the importance of mechanism research, which can enhance the understanding of the environmental and human health risks of DEHP exposure.

Tuning Convolutional Spiking Neural Network With Biologically Plausible Reward Propagation

Spiking neural networks (SNNs) contain more biologically realistic structures and biologically inspired learning principles than those in standard artificial neural networks (ANNs). SNNs are considered the third generation of ANNs, powerful on the robust computation with a low computational cost. The neurons in SNNs are nondifferential, containing decayed historical states and generating event-based spikes after their states reaching the firing threshold. These dynamic characteristics of SNNs make it difficult to be directly trained with the standard backpropagation (BP), which is also considered not biologically plausible. In this article, a biologically plausible reward propagation (BRP) algorithm is proposed and applied to the SNN architecture with both spiking-convolution (with both 1-D and 2-D convolutional kernels) and full-connection layers. Unlike the standard BP that propagates error signals from postsynaptic to presynaptic neurons layer by layer, the BRP propagates target labels instead of errors directly from the output layer to all prehidden layers. This effort is more consistent with the top-down reward-guiding learning in cortical columns of the neocortex. Synaptic modifications with only local gradient differences are induced with pseudo-BP that might also be replaced with the spike-timing-dependent plasticity (STDP). The performance of the proposed BRP-SNN is further verified on the spatial (including MNIST and Cifar-10) and temporal (including TIDigits and DvsGesture) tasks, where the SNN using BRP has reached a similar accuracy compared to other state-of-the-art (SOTA) BP-based SNNs and saved 50% more computational cost than ANNs. We think that the introduction of biologically plausible learning rules to the training procedure of biologically realistic SNNs will give us more hints and inspiration toward a better understanding of the biological system's intelligent nature.

A developmental delay linked missense mutation in Kalirin-7 disrupts protein function and neuronal morphology

The Rac1 guanine exchange factor Kalirin-7 is a key regulator of dendritic spine morphology, LTP and dendritic arborization. Kalirin-7 dysfunction and genetic variation has been extensively linked to various neurodevelopmental and neurodegenerative disorders. Here we characterize a Kalirin-7 missense mutation, glu1577lys (E1577K), identified in a patient with severe developmental delay. The E1577K point mutation is located within the catalytic domain of Kalirin-7, and results in a robust reduction in Kalirin-7 Rac1 Guanosine exchange factor activity. In contrast to wild type Kalirin-7, the E1577K mutant failed to drive dendritic arborization, spine density, NMDAr targeting to, and activity within, spines. Together these results indicate that reduced Rac1-GEF activity as result of E1577K mutation impairs neuroarchitecture, connectivity and NMDAr activity, and is a likely contributor to impaired neurodevelopment in a patient with developmental delay.

From synapses to circuits and back: Bridging levels of understanding in animal models of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by behavioural changes that include memory loss and cognitive decline and is associated with the appearance of amyloid-β plaques and neurofibrillary tangles throughout the brain. Although aspects of the disease percolate across multiple levels of neuronal organization, from the cellular to the behavioural, it is increasingly clear that circuits are a critical junction between the cellular pathology and the behavioural phenotypes that bookend these levels of analyses. In this review, we discuss critical aspects of neural circuit research, beginning with synapses and progressing to network activity and how they influence our understanding of disease processed in AD.

Blue-Light-Blocking Lenses Ameliorate Structural Alterations in the Rodent Hippocampus

Evidence suggests that prolonged blue-light exposure can impact vision; however, less is known about its impact on non-visual higher-order functions in the brain, such as learning and memory. Blue-light-blocking lenses (BBLs) claim to reduce these potential impacts. Hence, we assessed structural and functional hippocampal alterations following blue-light exposure and the protective efficacy of BBLs. Male Wistar rats were divided into (n = 6 in each group) normal control (NC), blue-light exposure (LE), and blue-light with BBLs (Crizal Prevencia, CP and DuraVision Blue, DB) groups. After 28 days of light exposure (12:12 light: dark cycle), rats were trained for the Morris water maze memory retention test, and brain tissues were sectioned for hippocampal neuronal analysis using Golgi and Cresyl violet stains. The memory retention test was significantly delayed (p < 0.05) in LE compared with DB groups on day 1 of training. Comparison of Golgi-stained neurons showed significant structural alterations, particularly in the basal dendrites of hippocampal neurons in the LE group, with BBLs significantly mitigating these structural changes (p < 0.05). Comparison of Cresyl-violet-stained neurons revealed significantly (p < 0.001) increased degenerated hippocampal neurons in LE rats, with fewer degenerated neurons in the CP lens group for CA1 neurons (p < 0.05), and for both CP and DB groups (p < 0.05) for CA3 neurons. Thus, in addition to documented effects on visual centers, high-level blue-light exposure also results in degeneration in hippocampal neurons with associated behavioral deficits. These changes can be partially ameliorated with blue-light-blocking lenses.

Impact of Maternal Immune Activation on Nonhuman Primate Prefrontal Cortex Development: Insights for Schizophrenia

Late adolescence is a period of dynamic change in the brain as humans learn to navigate increasingly complex environments. In particular, prefrontal cortical (PFC) regions undergo extensive remodeling as the brain is fine-tuned to orchestrate cognitive control over attention, reasoning, and emotions. Late adolescence also presents a uniquely vulnerable period as neurodevelopmental illnesses, such as schizophrenia, become evident and worsen into young adulthood. Challenges in early development, including prenatal exposure to infection, may set the stage for a cascade of maladaptive events that ultimately result in aberrant PFC connectivity and function before symptoms emerge. A growing body of research suggests that activation of the mother's immune system during pregnancy may act as a disease primer, in combination with other environmental and genetic factors, contributing to an increased risk of neurodevelopmental disorders, including schizophrenia. Animal models provide an invaluable opportunity to examine the course of brain and behavioral changes in offspring exposed to maternal immune activation (MIA). Although the vast majority of MIA research has been carried out in rodents, here we highlight the translational utility of the nonhuman primate (NHP) as a model species more closely related to humans in PFC structure and function. In this review, we consider the protracted period of brain and behavioral maturation in the NHP, describe emerging findings from MIA NHP offspring in the context of rodent preclinical models, and lastly explore the translational relevance of the NHP MIA model to expand understanding of the etiology and developmental course of PFC pathology in schizophrenia.

Temporal and spatial profiles of evoked activity induced by magnetic stimulation using millimeter-sized coils in the mouse auditory cortex in vivo

Transcranial magnetic stimulation (TMS), a minimally/non-invasive method of electromagnetic stimulation of brain tissue, has been shown to be beneficial in clinical therapy for specific neurological diseases and disorders. Magnetic stimulation is also used to modulate human and animal brain activity in basic neuroscience studies. Among experimental animal models, mouse models are particularly popular and uniquely representative of brain disorders in basic neuroscience research. TMS in mouse models may play a substantial role in understanding TMS-induced changes in neural networks and plasticity. Although TMS techniques are widely used to examine rodent disease models, techniques specific for mice using small magnetic stimulators have not been intensively developed. Here, we provide a numerical simulation and a practical method of applying TMS to mice by constructing millimeter-sized TMS coils to deliver a low stimulation intensity while maintaining focality. Our results indicate the TMS coils can produce an electrical field with sufficient magnitude to activate the anesthetized mouse cortex in the presence and absence of the skull in vivo. Our results also show that, immediately after magnetic stimulation, local field and action potentials were reliably observed in a manner that depended on the distance between the coil and the brain, implying even a small coil could reliably evoke cortical activity. Therefore, our results show our millimeter-sized coils could produce electric fields sufficient to alter cortical excitability in mice. These coils could be useful in future preclinical studies to examine detailed mechanisms underlying TMS-induced changes in neural activity of the auditory cortex and other cortical regions.

Post-Synapses in the Brain: Role of Dendritic and Spine Structures

Brain synapses are neuronal structures of the greatest interest. For a long time, however, the knowledge about them was variable, and interest was mostly focused on their pre-synaptic portions, especially neurotransmitter release from axon terminals. In the present review interest is focused on post-synapses, the structures receiving and converting pre-synaptic messages. Upon further modulation, such messages are transferred to dendritic fibers. Dendrites are profoundly different from axons; they are shorter and of variable thickness. Their post-synapses are of two types. Those called flat/intended/aspines, integrated into dendritic fibers, are very frequent in inhibitory neurons. The spines, small and stemming protrusions, connected to dendritic fibers by their necks, are present in almost all excitatory neurons. Several structures and functions including the post-synaptic densities and associated proteins, the nanoscale mechanisms of compartmentalization, the cytoskeletons of actin and microtubules, are analogous in the two post-synaptic forms. However other properties, such as plasticity and its functions of learning and memory, are largely distinct. Several properties of spines, including emersion from dendritic fibers, growth, change in shape and decreases in size up to disappearance, are specific. Spinal heads correspond to largely independent signaling compartments. They are motile, their local signaling is fast, however transport through their thin necks is slow. When single spines are activated separately, their dendritic effects are often lacking; when multiple spines are activated concomitantly, their effects take place. Defects of post-synaptic responses, especially those of spines, take place in various brain diseases. Here alterations affecting symptoms and future therapy are shown to occur in neurodegenerative diseases and autism spectrum disorders.

Computational synthesis of cortical dendritic morphologies

Neuronal morphologies provide the foundation for the electrical behavior of neurons, the connectomes they form, and the dynamical properties of the brain. Comprehensive neuron models are essential for defining cell types, discerning their functional roles, and investigating brain-disease-related dendritic alterations. However, a lack of understanding of the principles underlying neuron morphologies has hindered attempts to computationally synthesize morphologies for decades. We introduce a synthesis algorithm based on a topological descriptor of neurons, which enables the rapid digital reconstruction of entire brain regions from few reference cells. This topology-guided synthesis generates dendrites that are statistically similar to biological reconstructions in terms of morpho-electrical and connectivity properties and offers a significant opportunity to investigate the links between neuronal morphology and brain function across different spatiotemporal scales. Synthesized cortical networks based on structurally altered dendrites associated with diverse brain pathologies revealed principles linking branching properties to the structure of large-scale networks.

Microanatomical study of pyramidal neurons in the contralesional somatosensory cortex after experimental ischemic stroke

At present, many studies support the notion that after stroke, remote regions connected to the infarcted area are also affected and may contribute to functional outcome. In the present study, we have analyzed possible microanatomical alterations in pyramidal neurons from the contralesional hemisphere after induced stroke. We performed intracellular injections of Lucifer yellow in pyramidal neurons from layer III in the somatosensory cortex of the contralesional hemisphere in an ischemic stroke mouse model. A detailed 3-dimensional analysis of the neuronal complexity and morphological alterations of dendritic spines was then performed. Our results demonstrate that pyramidal neurons from layer III in the somatosensory cortex of the contralesional hemisphere show selective changes in their dendritic arbors, namely, less dendritic complexity of the apical dendritic arbor-but no changes in the basal dendritic arbor. In addition, we found differences in spine morphology in both apical and basal dendrites comparing the contralesional hemisphere with the lesional hemisphere. Our results show that pyramidal neurons of remote areas connected to the infarct zone exhibit a series of selective changes in neuronal complexity and morphological distribution of dendritic spines, supporting the hypothesis that remote regions connected to the peri-infarcted area are also affected after stroke.

Compartment-specific tuning of dendritic feature selectivity by intracellular Ca2+ release

Dendritic calcium signaling is central to neural plasticity mechanisms that allow animals to adapt to the environment. Intracellular calcium release (ICR) from the endoplasmic reticulum has long been thought to shape these mechanisms. However, ICR has not been investigated in mammalian neurons in vivo. We combined electroporation of single CA1 pyramidal neurons, simultaneous imaging of dendritic and somatic activity during spatial navigation, optogenetic place field induction, and acute genetic augmentation of ICR cytosolic impact to reveal that ICR supports the establishment of dendritic feature selectivity and shapes integrative properties determining output-level receptive fields. This role for ICR was more prominent in apical than in basal dendrites. Thus, ICR cooperates with circuit-level architecture in vivo to promote the emergence of behaviorally relevant plasticity in a compartment-specific manner.

Activity-dependent modulation of NMDA receptors by endogenous zinc shapes dendritic function in cortical neurons

NMDA receptors (NMDARs) have been proposed to control single-neuron computations in vivo. However, whether specific mechanisms regulate the function of such receptors and modulate input-output transformations performed by cortical neurons under in vivo-like conditions is understudied. Here, we report that in layer 2/3 pyramidal neurons (L2/3 PNs), repeated synaptic stimulation results in an activity-dependent decrease in NMDAR function by vesicular zinc. Such a mechanism shifts the threshold for dendritic non-linearities and strongly reduces LTP. Modulation of NMDARs is cell and pathway specific, being present selectively in L2/3-L2/3 connections but absent in inputs originating from L4 neurons. Numerical simulations highlight that activity-dependent modulation of NMDARs influences dendritic computations, endowing L2/3 PN dendrites with the ability to sustain non-linear integrations constant across different regimes of synaptic activity like those found in vivo. Our results unveil vesicular zinc as an important endogenous modulator of dendritic function in cortical PNs.

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Vesicular zinc release downregulates function of synaptic NMDARs in cortical neurons

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Zinc modulation of NMDARs is activity dependent, pathway and cell specific

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Endogenous zinc controls dendritic non-linearities and synaptic plasticity in L2/3 PNs

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Modulation of NMDARs normalizes dendritic function during ongoing synaptic activity

Pathway-specific TNF-mediated metaplasticity in hippocampal area CA1

Long-term potentiation (LTP) is regulated in part by metaplasticity, the activity-dependent alterations in neural state that coordinate the direction, amplitude, and persistence of future synaptic plasticity. Previously, we documented a heterodendritic metaplasticity effect whereby high-frequency priming stimulation in stratum oriens (SO) of hippocampal CA1 suppressed subsequent LTP in the stratum radiatum (SR). The cytokine tumor necrosis factor (TNF) mediated this heterodendritic metaplasticity in wild-type rodents and in a mouse model of Alzheimer’s disease. Here, we investigated whether LTP at other afferent synapses to CA1 pyramidal cells were similarly affected by priming stimulation. We found that priming stimulation in SO inhibited LTP only in SR and not in a second independent pathway in SO, nor in stratum lacunosum moleculare (SLM). Synapses in SR were also more sensitive than SO or SLM to the LTP-inhibiting effects of pharmacological TNF priming. Neither form of priming was sex-specific, while the metaplasticity effects were absent in TNFR1 knock-out mice. Our findings demonstrate an unexpected pathway specificity for the heterodendritic metaplasticity in CA1. That Schaffer collateral/commissural synapses in SR are particularly susceptible to such metaplasticity may reflect an important control of information processing in this pathway in addition to its sensitivity to neuroinflammation under disease conditions.

NeuroGPU: Accelerating multi-compartment, biophysically detailed neuron simulations on GPUs

BACKGROUND

The membrane potential of individual neurons depends on a large number of interacting biophysical processes operating on spatial-temporal scales spanning several orders of magnitude. The multi-scale nature of these processes dictates that accurate prediction of membrane potentials in specific neurons requires the utilization of detailed simulations. Unfortunately, constraining parameters within biologically detailed neuron models can be difficult, leading to poor model fits. This obstacle can be overcome partially by numerical optimization or detailed exploration of parameter space. However, these processes, which currently rely on central processing unit (CPU) computation, often incur orders of magnitude increases in computing time for marginal improvements in model behavior. As a result, model quality is often compromised to accommodate compute resources.

NEW METHOD

Here, we present a simulation environment, NeuroGPU, that takes advantage of the inherent parallelized structure of the graphics processing unit (GPU) to accelerate neuronal simulation.

RESULTS & COMPARISON WITH EXISTING METHODS

NeuroGPU can simulate most biologically detailed models 10-200 times faster than NEURON simulation running on a single core and 5 times faster than GPU simulators (CoreNEURON). NeuroGPU is designed for model parameter tuning and best performs when the GPU is fully utilized by running multiple (> 100) instances of the same model with different parameters. When using multiple GPUs, NeuroGPU can reach to a speed-up of 800 fold compared to single core simulations, especially when simulating the same model morphology with different parameters. We demonstrate the power of NeuoGPU through large-scale parameter exploration to reveal the response landscape of a neuron. Finally, we accelerate numerical optimization of biophysically detailed neuron models to achieve highly accurate fitting of models to simulation and experimental data.

CONCLUSIONS

Thus, NeuroGPU is the fastest available platform that enables rapid simulation of multi-compartment, biophysically detailed neuron models on commonly used computing systems accessible by many scientists.

Low-cost and easy-fabrication lightweight drivable electrode array for multiple-regions electrophysiological recording in free-moving mice

OBJECTIVE

Extracellular electrophysiology has been widely applied to neural circuit dissections. However, long-term multiregional recording in free-moving mice remains a challenge. Low-cost and easy-fabrication of elaborate drivable electrodes is required for their prevalence.

APPROACH

A three-layer nested construct (OD ~1.80 mm, length ~10 mm, <0.1g) was recruited as a drivable component, which consisted of an ethylene-vinyl acetate copolymer (EVA) heat-shrinkable tube, non-closed loop ceramic bushing, and stainless ferrule with a bulge twining silver wire. The supporting and working components were equipped with drivable components to be assembled into a drivable microwire electrode array with a nested structure (drivable MEANS). Two drivable microwire electrode arrays were independently implanted for chronic recording in different brain areas at respective angles. An optic fiber was easily loaded into the drivable MEANS to achieve optogenetic modulation and electrophysiological recording simultaneously.

MAIN RESULTS

The drivable MEANS had lightweight (~ 0.37 g), small (~ 15 mm ×15 mm × 4 mm), and low cost (≤ $64.62). Two drivable MEANS were simultaneously implanted in mice, and high-quality electrophysiological recordings could be applied ≥ 5 months after implantation in freely behaving animals. Electrophysiological recordings and analysis of the lateral septum (LS) and lateral hypothalamus (LH) in food-seeking behavior demonstrated that our drivable MEANS can be used to dissect the function of neural circuits. An optical fiber-integrated drivable MEANS (~ 0.47 g) was used to stimulate and record LS neurons, which suggested that changes in working components can achieve more functions than electrophysiological recordings, such as optical stimulation, drug release, and calcium imaging.

SIGNIFICANCE

Drivable MEANS is an easily fabricated, lightweight drivable microwire electrode array for multiple-region electrophysiological recording in free-moving mice. Our design is likely to be a valuable platform for both current and prospective users, as well as for developers of multifunctional electrodes for free-moving mice.

Histone Deacetylase 2 Knockdown Ameliorates Morphological Abnormalities of Dendritic Branches and Spines to Improve Synaptic Plasticity in an APP/PS1 Transgenic Mouse Model

Disease-modifying therapies, such as neuroprotective and neurorestorative interventions, are strongly desired for Alzheimer’s disease (AD) treatment. Several studies have suggested that histone deacetylase 2 (HDAC2) inhibition can exhibit disease-modifying effects in AD patients. However, whether HDAC2 inhibition shows neuroprotective and neurorestorative effects under neuropathic conditions, such as amyloid β (Aβ)-elevated states, remains poorly understood. Here, we performed HDAC2-specific knockdown in CA1 pyramidal cells and showed that HDAC2 knockdown increased the length of dendrites and the number of mushroom-like spines of CA1 basal dendrites in APP/PS1 transgenic mouse model. Furthermore, HDAC2 knockdown also ameliorated the deficits in hippocampal CA1 long-term potentiation and memory impairment in contextual fear conditioning tests. Taken together, our results support the notion that specific inhibition of HDAC2 has the potential to slow the disease progression of AD through ameliorating Aβ-induced neuronal impairments.

Nonlinear Dendritic Coincidence Detection for Supervised Learning

Cortical pyramidal neurons have a complex dendritic anatomy, whose function is an active research field. In particular, the segregation between its soma and the apical dendritic tree is believed to play an active role in processing feed-forward sensory information and top-down or feedback signals. In this work, we use a simple two-compartment model accounting for the nonlinear interactions between basal and apical input streams and show that standard unsupervised Hebbian learning rules in the basal compartment allow the neuron to align the feed-forward basal input with the top-down target signal received by the apical compartment. We show that this learning process, termed coincidence detection, is robust against strong distractions in the basal input space and demonstrate its effectiveness in a linear classification task.

Rpsa Signaling Regulates Cortical Neuronal Morphogenesis via Its Ligand, PEDF, and Plasma Membrane Interaction Partner, Itga6

Neuromorphological defects underlie neurodevelopmental disorders and functional defects. We identified a function for Rpsa in regulating neuromorphogenesis using in utero electroporation to knockdown Rpsa, resulting in apical dendrite misorientation, fewer/shorter extensions, and decreased spine density with altered spine morphology in upper neuronal layers and decreased arborization in upper/lower cortical layers. Rpsa knockdown disrupts multiple aspects of cortical development, including radial glial cell fiber morphology and neuronal layering. We investigated Rpsa's ligand, PEDF, and interacting partner on the plasma membrane, Itga6. Rpsa, PEDF, and Itga6 knockdown cause similar phenotypes, with Rpsa and Itga6 overexpression rescuing morphological defects in PEDF-deficient neurons in vivo. Additionally, Itga6 overexpression increases and stabilizes Rpsa expression on the plasma membrane. GCaMP6s was used to functionally analyze Rpsa knockdown via ex vivo calcium imaging. Rpsa-deficient neurons showed less fluctuation in fluorescence intensity, suggesting defective subthreshold calcium signaling. The Serpinf1 gene coding for PEDF is localized at chromosome 17p13.3, which is deleted in patients with the neurodevelopmental disorder Miller-Dieker syndrome. Our study identifies a role for Rpsa in early cortical development and for PEDF-Rpsa-Itga6 signaling in neuromorphogenesis, thus implicating these molecules in the etiology of neurodevelopmental disorders like Miller-Dieker syndrome and identifying them as potential therapeutics.

Excitatory Repetitive Transcranial Magnetic Stimulation Over Prefrontal Cortex in a Guinea Pig Model Ameliorates Tinnitus

Tinnitus, a phantom auditory perception that can seriously affect quality of life, is generally triggered by cochlear trauma and associated with aberrant activity throughout the auditory pathways, often referred to as hyperactivity. Studies suggest that non-auditory structures, such as prefrontal cortex (PFC), may be involved in tinnitus generation, by affecting sensory gating in auditory thalamus, allowing hyperactivity to reach the cortex and lead to perception. Indeed, human studies have shown that repetitive transcranial magnetic stimulation (rTMS) of PFC can alleviate tinnitus. The current study investigated whether this therapeutic effect is achieved through inhibition of thalamic hyperactivity, comparing effects of two common clinical rTMS protocols with sham treatment, in a guinea pig tinnitus model. Animals underwent acoustic trauma and once tinnitus developed were treated with either intermittent theta burst stimulation (iTBS), 20 Hz rTMS, or sham rTMS (10 days, 10 min/day; weekdays only). Tinnitus was reassessed and extracellular recordings of spontaneous tonic and burst firing rates in auditory thalamus made. To verify effects in PFC, densities of neurons positive for calcium-binding proteins, calbindin and parvalbumin, were investigated using immunohistochemistry. Both rTMS protocols significantly reduced tinnitus compared to sham. However, spontaneous tonic firing decreased following 20 Hz stimulation and increased following iTBS in auditory thalamus. Burst rate was significantly different between 20 Hz and iTBS stimulation, and burst duration was increased only after 20 Hz treatment. Density of calbindin, but not parvalbumin positive neurons, was significantly increased in the most dorsal region of PFC indicating that rTMS directly affected PFC. Our results support the involvement of PFC in tinnitus modulation, and the therapeutic benefit of rTMS on PFC in treating tinnitus, but indicate this is not achieved solely by suppression of thalamic hyperactivity.

Local and Global Dynamics of Dendritic Activity in the Pyramidal Neuron

There has been increasing interest in the measurement and comparison of activity across compartments of the pyramidal neuron. Dendritic activity can occur both locally, on a single dendritic segment, or globally, involving multiple compartments of the single neuron. Little is known about how these dendritic dynamics shape and contribute to information processing and behavior. Although it has been difficult to characterize local and global activity in vivo due to the technical challenge of simultaneously recording from the entire dendritic arbor and soma, the rise of calcium imaging has driven the increased feasibility and interest of these experiments. However, the distinction between local and global activity made by calcium imaging requires careful consideration. In this review we describe local and global activity, discuss the difficulties and caveats of this distinction, and present the evidence of local and global activity in information processing and behavior.

Coherence and cognition in the cortex: the fundamental role of parvalbumin, myelin, and the perineuronal net

The calcium binding protein parvalbumin is expressed in interneurons of two main morphologies, the basket and chandelier cells, which target perisomatic domains on principal cells and are extensively interconnected in laminar networks by synapses and gap junctions. Beyond its utility as a convenient cellular marker, parvalbumin is an unambiguous identifier of the key role that these interneurons play in the fundamental functions of the cortex. They provide a temporal framework for principal cell activity by propagating gamma oscillation, providing coherence for cortical information processing and the basis for timing-dependent plasticity processes. As these parvalbumin networks mature, they are physically and functionally stabilised by axonal myelination and development of the extracellular matrix structure termed the perineuronal net. This maturation correlates with the emergence of high-speed, highly energetic activity and provides a coherent foundation for the unique ability of the cortex to cross-correlate activity across sensory modes and internal representations.

Differential Structure of Hippocampal CA1 Pyramidal Neurons in the Human and Mouse

Pyramidal neurons are the most common cell type and are considered the main output neuron in most mammalian forebrain structures. In terms of function, differences in the structure of the dendrites of these neurons appear to be crucial in determining how neurons integrate information. To further shed light on the structure of the human pyramidal neurons we investigated the geometry of pyramidal cells in the human and mouse CA1 region-one of the most evolutionary conserved archicortical regions, which is critically involved in the formation, consolidation, and retrieval of memory. We aimed to assess to what extent neurons corresponding to a homologous region in different species have parallel morphologies. Over 100 intracellularly injected and 3D-reconstructed cells across both species revealed that dendritic and axonal morphologies of human cells are not only larger but also have structural differences, when compared to mouse. The results show that human CA1 pyramidal cells are not a stretched version of mouse CA1 cells. These results indicate that there are some morphological parameters of the pyramidal cells that are conserved, whereas others are species-specific.