Neuromantic - from semi-manual to semi-automatic reconstruction of neuron morphology

Postsynaptic spiking determines anti-Hebbian LTD in visual cortex basket cells

Long-term plasticity at pyramidal cell to basket cell (PC → BC) synapses is important for the functioning of cortical microcircuits. It is well known that at neocortical PC → PC synapses, dendritic calcium (Ca2+) dynamics signal coincident pre-and postsynaptic spiking which in turn triggers long-term potentiation (LTP). However, the link between dendritic Ca2+ dynamics and long-term plasticity at PC → BC synapses of primary visual cortex (V1) is not as well known. Here, we explored if PC → BC synaptic plasticity in developing V1 is sensitive to postsynaptic spiking. Two-photon (2P) Ca2+ imaging revealed that action potentials (APs) in dendrites of V1 layer-5 (L5) BCs back-propagated decrementally but actively to the location of PC → BC putative synaptic contacts. Pairing excitatory inputs with postsynaptic APs elicited dendritic Ca2+ supralinearities for pre-before-postsynaptic but not post-before-presynaptic temporal ordering, suggesting that APs could impact synaptic plasticity. In agreement, extracellular stimulation as well as high-throughput 2P optogenetic mapping of plasticity both revealed that pre-before-postsynaptic but not post-before-presynaptic pairing resulted in anti-Hebbian long-term depression (LTD). Our results demonstrate that V1 BC dendritic Ca2+ nonlinearities and synaptic plasticity at PC → BC connections are both sensitive to somatic spiking.

Lasting effects of adolescent social instability stress on dendritic morphology in the nucleus accumbens in female and male Long Evans rats

Social instability stress (SS) in adolescence in rats leads to long-lasting changes in social behaviour and reward-related behaviour relative to control rats. Given the role of the nucleus accumbens (NAc) in such behaviours, we investigated the morphology of medium spiny neurons (MSNs), which are most neurons in the NAc, in adult female and male rats exposed to SS in adolescence. Irrespective of sex, SS rats had increased number of dendritic spines in both the core and shell regions of the NAc (2.3 % and 18.1 % increase, respectively). In the core, SS rats had a 16 % reduction in the total dendritic lengths of MSNs, whereas in the shell, SS rats had a greater dendritic length closer to the soma, and particularly in SS female rats, whereas the opposite was found farther from the soma (SS 10.6 % > CTL overall). Although the extent to which such structural changes may underlie the enduring effects of SS in adolescence requires investigation, the results add to evidence that changes to the social environment in adolescence can determine adult neuronal structural.

The short-term plasticity of VIP interneurons in motor cortex

Short-term plasticity is an important feature in the brain for shaping neural dynamics and for information processing. Short-term plasticity is known to depend on many factors including brain region, cortical layer, and cell type. Here we focus on vasoactive-intestinal peptide (VIP) interneurons (INs). VIP INs play a key disinhibitory role in cortical circuits by inhibiting other IN types, including Martinotti cells (MCs) and basket cells (BCs). Despite this prominent role, short-term plasticity at synapses to and from VIP INs is not well described. In this study, we therefore characterized the short-term plasticity at inputs and outputs of genetically targeted VIP INs in mouse motor cortex. To explore inhibitory to inhibitory (I → I) short-term plasticity at layer 2/3 (L2/3) VIP IN outputs onto L5 MCs and BCs, we relied on a combination of whole-cell recording, 2-photon microscopy, and optogenetics, which revealed that VIP IN→MC/BC synapses were consistently short-term depressing. To explore excitatory (E) → I short-term plasticity at inputs to VIP INs, we used extracellular stimulation. Surprisingly, unlike VIP IN outputs, E → VIP IN synapses exhibited heterogeneous short-term dynamics, which we attributed to the target VIP IN cell rather than the input. Computational modeling furthermore linked the diversity in short-term dynamics at VIP IN inputs to a wide variability in probability of release. Taken together, our findings highlight how short-term plasticity at VIP IN inputs and outputs is specific to synapse type. We propose that the broad diversity in short-term plasticity of VIP IN inputs forms a basis to code for a broad range of contrasting signal dynamics.

Long-range inhibition from prelimbic to cingulate areas of the medial prefrontal cortex enhances network activity and response execution

It is well established that the medial prefrontal cortex (mPFC) exerts top-down control of many behaviors, but little is known regarding how cross-talk between distinct areas of the mPFC influences top-down signaling. We performed virus-mediated tracing and functional studies in male mice, homing in on GABAergic projections whose axons are located mainly in layer 1 and that connect two areas of the mPFC, namely the prelimbic area (PrL) with the cingulate area 1 and 2 (Cg1/2). We revealed the identity of the targeted neurons that comprise two distinct types of layer 1 GABAergic interneurons, namely single-bouquet cells (SBCs) and neurogliaform cells (NGFs), and propose that this connectivity links GABAergic projection neurons with cortical canonical circuits. In vitro electrophysiological and in vivo calcium imaging studies support the notion that the GABAergic projection neurons from the PrL to the Cg1/2 exert a crucial role in regulating the activity in the target area by disinhibiting layer 5 output neurons. Finally, we demonstrated that recruitment of these projections affects impulsivity and mechanical responsiveness, behaviors which are known to be modulated by Cg1/2 activity.

Computational Tools for Neuronal Morphometric Analysis: A Systematic Search and Review

Morphometry is fundamental for studying and correlating neuronal morphology with brain functions. With increasing computational power, it is possible to extract morphometric characteristics automatically, including features such as length, volume, and number of neuron branches. However, to the best of our knowledge, there is no mapping of morphometric tools yet. In this context, we conducted a systematic search and review to identify and analyze tools within the scope of neuron analysis. Thus, the work followed a well-defined protocol and sought to answer the following research questions: What open-source tools are available for neuronal morphometric analysis? What morphometric characteristics are extracted by these tools? For this, aiming for greater robustness and coverage, the study was based on the paper analysis as well as the study of documentation and tests with the tools available in repositories. We analyzed 1,586 papers and mapped 23 tools, where NeuroM, L-Measure, and NeuroMorphoVis extract the most features. Furthermore, we contribute to the body of knowledge with the unprecedented presentation of 150 unique morphometric features whose terminologies were categorized and standardized. Overall, the study contributes to advancing the understanding of the complex mechanisms underlying the brain.

The spike-timing-dependent plasticity of VIP interneurons in motor cortex

The plasticity of inhibitory interneurons (INs) plays an important role in the organization and maintenance of cortical microcircuits. Given the many different IN types, there is an even greater diversity in synapse-type-specific plasticity learning rules at excitatory to excitatory (E→I), I→E, and I→I synapses. I→I synapses play a key disinhibitory role in cortical circuits. Because they typically target other INs, vasoactive intestinal peptide (VIP) INs are often featured in I→I→E disinhibition, which upregulates activity in nearby excitatory neurons. VIP IN dysregulation may thus lead to neuropathologies such as epilepsy. In spite of the important activity regulatory role of VIP INs, their long-term plasticity has not been described. Therefore, we characterized the phenomenology of spike-timing-dependent plasticity (STDP) at inputs and outputs of genetically defined VIP INs. Using a combination of whole-cell recording, 2-photon microscopy, and optogenetics, we explored I→I STDP at layer 2/3 (L2/3) VIP IN outputs onto L5 Martinotti cells (MCs) and basket cells (BCs). We found that VIP IN→MC synapses underwent causal long-term depression (LTD) that was presynaptically expressed. VIP IN→BC connections, however, did not undergo any detectable plasticity. Conversely, using extracellular stimulation, we explored E→I STDP at inputs to VIP INs which revealed long-term potentiation (LTP) for both causal and acausal timings. Taken together, our results demonstrate that VIP INs possess synapse-type-specific learning rules at their inputs and outputs. This suggests the possibility of harnessing VIP IN long-term plasticity to control activity-related neuropathologies such as epilepsy.

Multimodal sensory control of motor performance by glycinergic interneurons of the mouse spinal cord deep dorsal horn

Sensory feedback is integral for contextually appropriate motor output, yet the neural circuits responsible remain elusive. Here, we pinpoint the medial deep dorsal horn of the mouse spinal cord as a convergence point for proprioceptive and cutaneous input. Within this region, we identify a population of tonically active glycinergic inhibitory neurons expressing parvalbumin. Using anatomy and electrophysiology, we demonstrate that deep dorsal horn parvalbumin-expressing interneuron (dPV) activity is shaped by convergent proprioceptive, cutaneous, and descending input. Selectively targeting spinal dPVs, we reveal their widespread ipsilateral inhibition onto pre-motor and motor networks and demonstrate their role in gating sensory-evoked muscle activity using electromyography (EMG) recordings. dPV ablation altered limb kinematics and step-cycle timing during treadmill locomotion and reduced the transitions between sub-movements during spontaneous behavior. These findings reveal a circuit basis by which sensory convergence onto dorsal horn inhibitory neurons modulates motor output to facilitate smooth movement and context-appropriate transitions.

Morphological heterogeneity of neurons in the human central amygdaloid nucleus

The central amygdaloid nucleus (CeA) has an ancient phylogenetic development and functions relevant for animal survival. Local cells receive intrinsic amygdaloidal information that codes emotional stimuli of fear, integrate them, and send cortical and subcortical output projections that prompt rapid visceral and social behavior responses. We aimed to describe the morphology of the neurons that compose the human CeA (N = 8 adult men). Cells within CeA coronal borders were identified using the thionine staining and were further analyzed using the "single-section" Golgi method followed by open-source software procedures for two-dimensional and three-dimensional image reconstructions. Our results evidenced varied neuronal cell body features, number and thickness of primary shafts, dendritic branching patterns, and density and shape of dendritic spines. Based on these criteria, we propose the existence of 12 morphologically different spiny neurons in the human CeA and discuss the variability in the dendritic architecture within cellular types, including likely interneurons. Some dendritic shafts were long and straight, displayed few collaterals, and had planar radiation within the coronal neuropil volume. Most of the sampled neurons showed a few to moderate density of small stubby/wide spines. Long spines (thin and mushroom) were observed occasionally. These novel data address the synaptic processing and plasticity in the human CeA. Our morphological description can be combined with further transcriptomic, immunohistochemical, and electrophysiological/connectional approaches. It serves also to investigate how neurons are altered in neurological and psychiatric disorders with hindered emotional perception, in anxiety, following atrophy in schizophrenia, and along different stages of Alzheimer's disease.

Lusca: FIJI (ImageJ) based tool for automated morphological analysis of cellular and subcellular structures

The human body consists of diverse subcellular, cellular and supracellular structures. Neurons possess varying-sized projections that interact with different cellular structures leading to the development of highly complex morphologies. Aiming to enhance image analysis of complex biological forms including neurons using available FIJI (ImageJ) plugins, Lusca, an advanced open-source tool, was developed. Lusca utilizes machine learning for image segmentation with intensity and size thresholds. It performs particle analysis to ascertain parameters such as area/volume, quantity, and intensity, in addition to skeletonization for determining length, branching, and width. Moreover, in conjunction with colocalization measurements, it provides an extensive set of 29 morphometric parameters for both 2D and 3D analysis. This is a significant enhancement compared to other scripts that offer only 5-15 parameters. Consequently, it ensures quicker and more precise quantification by effectively eliminating noise and discerning subtle details. With three times larger execution speed, fewer false positive and negative results, and the capacity to measure various parameters, Lusca surpasses other existing open-source solutions. Its implementation of machine learning-based segmentation facilitates versatile applications for different cell types and biological structures, including mitochondria, fibres, and vessels. Lusca's automated and precise measurement capability makes it an ideal choice for diverse biological image analyses.

The gut metabolite indole-3-propionic acid activates ERK1 to restore social function and hippocampal inhibitory synaptic transmission in a 16p11.2 microdeletion mouse model

BACKGROUND

Microdeletion of the human chromosomal region 16p11.2 (16p11.2+ / - ) is a prevalent genetic factor associated with autism spectrum disorder (ASD) and other neurodevelopmental disorders. However its pathogenic mechanism remains unclear, and effective treatments for 16p11.2+ / -  syndrome are lacking. Emerging evidence suggests that the gut microbiota and its metabolites are inextricably linked to host behavior through the gut-brain axis and are therefore implicated in ASD development. Despite this, the functional roles of microbial metabolites in the context of 16p11.2+ / -  are yet to be elucidated. This study aims to investigate the therapeutic potential of indole-3-propionic acid (IPA), a gut microbiota metabolite, in addressing behavioral and neural deficits associated with 16p11.2+ / - , as well as the underlying molecular mechanisms.

RESULTS

Mice with the 16p11.2+ / -  showed dysbiosis of the gut microbiota and a significant decrease in IPA levels in feces and blood circulation. Further, these mice exhibited significant social and cognitive memory impairments, along with hyperactivation of hippocampal dentate gyrus neurons and reduced inhibitory synaptic transmission in this region. However, oral administration of IPA effectively mitigated the histological and electrophysiological alterations, thereby ameliorating the social and cognitive deficits of the mice. Remarkably, IPA treatment significantly increased the phosphorylation level of ERK1, a protein encoded by the Mapk3 gene in the 16p11.2 region, without affecting the transcription and translation of the Mapk3 gene.

CONCLUSIONS

Our study reveals that 16p11.2+ / -  leads to a decline in gut metabolite IPA levels; however, IPA supplementation notably reverses the behavioral and neural phenotypes of 16p11.2+ / -  mice. These findings provide new insights into the critical role of gut microbial metabolites in ASD pathogenesis and present a promising treatment strategy for social and cognitive memory deficit disorders, such as 16p11.2 microdeletion syndrome. Video Abstract.

A combinatory genetic strategy for targeting neurogliaform neurons in the mouse basolateral amygdala

The mouse basolateral amygdala (BLA) contains various GABAergic interneuron subpopulations, which have distinctive roles in the neuronal microcircuit controlling numerous behavioral functions. In mice, roughly 15% of the BLA GABAergic interneurons express neuropeptide Y (NPY), a reasonably characteristic marker for neurogliaform cells (NGFCs) in cortical-like brain structures. However, genetically labeled putative NPY-expressing interneurons in the BLA yield a mixture of interneuron subtypes besides NGFCs. Thus, selective molecular markers are lacking for genetically accessing NGFCs in the BLA. Here, we validated the NGFC-specific labeling with a molecular marker, neuron-derived neurotrophic factor (NDNF), in the mouse BLA, as such specificity has been demonstrated in the neocortex and hippocampus. We characterized genetically defined NDNF-expressing (NDNF+) GABAergic interneurons in the mouse BLA by combining the Ndnf-IRES2-dgCre-D transgenic mouse line with viral labeling, immunohistochemical staining, and in vitro electrophysiology. We found that BLA NDNF+ GABAergic cells mainly expressed NGFC neurochemical markers NPY and reelin (Reln) and exhibited small round soma and dense axonal arborization. Whole-cell patch clamp recordings indicated that most NDNF+ interneurons showed late spiking and moderate firing adaptation. Moreover, ∼81% of BLA NDNF+ cells generated retroaxonal action potential after current injections or optogenetic stimulations, frequently developing into persistent barrage firing. Optogenetic activation of the BLA NDNF+ cell population yielded both GABAA- and GABAB receptor-mediated currents onto BLA pyramidal neurons (PNs). We demonstrate a combinatory strategy combining the NDNF-cre mouse line with viral transfection to specifically target adult mouse BLA NGFCs and further explore their functional and behavioral roles.

Structural and functional specializations of human fast-spiking neurons support fast cortical signaling

Fast-spiking interneurons (FSINs) provide fast inhibition that synchronizes neuronal activity and is critical for cognitive function. Fast synchronization frequencies are evolutionary conserved in the expanded human neocortex despite larger neuron-to-neuron distances that challenge fast input-output transfer functions of FSINs. Here, we test in human neurons from neurosurgery tissue, which mechanistic specializations of human FSINs explain their fast-signaling properties in human cortex. With morphological reconstructions, multipatch recordings, and biophysical modeling, we find that despite threefold longer dendritic path, human FSINs maintain fast inhibition between connected pyramidal neurons through several mechanisms: stronger synapse strength of excitatory inputs, larger dendrite diameter with reduced complexity, faster AP initiation, and faster and larger inhibitory output, while Na+ current activation/inactivation properties are similar. These adaptations underlie short input-output delays in fast inhibition of human pyramidal neurons through FSINs, explaining how cortical synchronization frequencies are conserved despite expanded and sparse network topology of human cortex.

CellRemorph: A Toolkit for Transforming, Selecting, and Slicing 3D Cell Structures on the Road to Morphologically Detailed Astrocyte Simulations

Understanding functions of astrocytes can be greatly enhanced by building and simulating computational models that capture their morphological details. Novel computational tools enable utilization of existing morphological data of astrocytes and building models that have appropriate level of details for specific simulation purposes. In addition to analyzing existing computational tools for constructing, transforming, and assessing astrocyte morphologies, we present here the CellRemorph toolkit implemented as an add-on for Blender, a 3D modeling platform increasingly recognized for its utility for manipulating 3D biological data. To our knowledge, CellRemorph is the first toolkit for transforming astrocyte morphologies from polygonal surface meshes into adjustable surface point clouds and vice versa, precisely selecting nanoprocesses, and slicing morphologies into segments with equal surface areas or volumes. CellRemorph is an open-source toolkit under the GNU General Public License and easily accessible via an intuitive graphical user interface. CellRemorph will be a valuable addition to other Blender add-ons, providing novel functionality that facilitates the creation of realistic astrocyte morphologies for different types of morphologically detailed simulations elucidating the role of astrocytes both in health and disease.

The developmental profile of visual cortex astrocytes

We investigated how astrocytes in layer 5 mouse visual cortex mature over postnatal days (P) 3-50. Across this age range, resting membrane potential increased, input resistance decreased, and membrane responses became more passive with age. Two-photon (2p) and confocal imaging of dye-loaded cells revealed that gap-junction coupling increased starting ∼P7. Morphological reconstructions revealed increased branch density but shorter branches after P20, suggesting that astrocyte branches may get pruned as tiling is established. Finally, we visualized spontaneous Ca²⁺ transients with 2p microscopy and found that Ca²⁺ events decorrelated, became more frequent and briefer with age. As astrocytes mature, spontaneous Ca²⁺ activity thus changes from relatively cell-wide, synchronous waves to local transients. Several astrocyte properties were stably mature from ∼P15, coinciding with eye opening, although morphology continued to develop. Our findings provide a descriptive foundation of astrocyte maturation, useful for the study of astrocytic impact on visual cortex critical period plasticity.

Cell-autonomous and differential endocannabinoid signaling impacts the development of presynaptic retinal ganglion cell axon connectivity in vivo

Cannabis exposure during gestation evokes significant molecular modifications to neurodevelopmental programs leading to neurophysiological and behavioral abnormalities in humans. The main neuronal receptor for Δ⁹-tetrahydrocannabinol (THC) is the type-1 cannabinoid receptor CB₁R, one of the most abundant G-protein-coupled receptors in the nervous system. While THC is the major psychoactive phytocannabinoid, endocannabinoids (eCBs) are the endogenous ligands of CB₁R and are known to act as retrograde messengers to modulate synaptic plasticity at different time scales in the adult brain. Accumulating evidence indicates that eCB signaling through activation of CB₁R plays a central role in neural development. During development, most CB₁R localized to axons of projection neurons, and in mice eCB signaling impacts axon fasciculation. Understanding of eCB-mediated structural plasticity during development, however, requires the identification of the precise spatial and temporal dynamics of CB₁R-mediated modifications at the level of individual neurons in the intact brain. Here, the cell-autonomous role of CB₁R and the effects of CB₁R-mediated eCB signaling were investigated using targeted single-cell knockdown and pharmacologic treatments in Xenopus. We imaged axonal arbors of retinal ganglion cells (RGCs) in real time following downregulation of CB₁R via morpholino (MO) knockdown. We also analyzed RGC axons with altered eCB signaling following treatment with URB597, a selective inhibitor of the enzyme that degrades Anandamide (AEA), or JZL184, an inhibitor of the enzyme that blocks 2-Arachidonoylglycerol (2-AG) hydrolysis, at two distinct stages of retinotectal development. Our results demonstrate that CB₁R knockdown impacts RGC axon branching at their target and that differential 2-AG and AEA-mediated eCB signaling contributes to presynaptic structural connectivity at the time that axons terminate and when retinotectal synaptic connections are made. Altering CB₁R levels through CB₁R MO knockdown similarly impacted dendritic morphology of tectal neurons, thus supporting both pre- and postsynaptic cell-autonomous roles for CB₁R-mediated eCB signaling.

Human cortical amygdala dendrites and spines morphology under open‐source three‐dimensional reconstruction procedures

Visualizing nerve cells has been fundamental for the systematic description of brain structure and function in humans and other species. Different approaches aimed to unravel the morphological features of neuron types and diversity. The inherent complexity of the human nervous tissue and the need for proper histological processing have made studying human dendrites and spines challenging in postmortem samples. In this study, we used Golgi data and open-source software for 3D image reconstruction of human neurons from the cortical amygdaloid nucleus to show different dendrites and pleomorphic spines at different angles. Procedures required minimal equipment and generated high-quality images for differently shaped cells. We used the "single-section" Golgi method adapted for the human brain to engender 3D reconstructed images of the neuronal cell body and the dendritic ramification by adopting a neuronal tracing procedure. In addition, we elaborated 3D reconstructions to visualize heterogeneous dendritic spines using a supervised machine learning-based algorithm for image segmentation. These tools provided an additional upgrade and enhanced visual display of information related to the spatial orientation of dendritic branches and for dendritic spines of varied sizes and shapes in these human subcortical neurons. This same approach can be adapted for other techniques, areas of the central or peripheral nervous system, and comparative analysis between species.

Inhibitory projections connecting the dentate gyri in the two hemispheres support spatial and contextual memory

The dentate gyrus (DG) receives substantial input from the homologous brain area of the contralateral hemisphere. This input is by and large excitatory. Viral-tracing experiments provided anatomical evidence for the existence of GABAergic connectivity between the two DGs, but the function of these projections has remained elusive. Combining electrophysiological and optogenetic approaches, we demonstrate that somatostatin-expressing contralateral DG (SOM⁺ cDG)-projecting neurons preferentially engage dendrite-targeting interneurons over principal neurons. Single-unit recordings from freely moving mice reveal that optogenetic stimulation of SOM⁺ cDG projections modulates the activity of GABAergic neurons and principal neurons over multiple timescales. Importantly, we demonstrate that optogenetic silencing of SOM⁺ cDG projections during spatial memory encoding, but not during memory retrieval, results in compromised DG-dependent memory. Moreover, optogenetic stimulation of SOM⁺ cDG projections is sufficient to disrupt contextual memory recall. Collectively, our findings reveal that SOM⁺ long-range projections mediate inter-DG inhibition and contribute to learning and memory.

A report on digitised neuronal tracing method to study neurons in their entirety

Conventional camera lucida (CL) aided neuronal tracing technique for studying neural plasticity is a demanding procedure. Stereo Investigator-Neurolucida enabled neuronal tracing system is not accessible to all researchers. This necessitates alternate simple and less challenging digitised neuronal tracing methods. This report describes a novel digitised neuronal tracing method using widefield microscopy, and its effectiveness is compared with the traditional camera lucida aided neuronal tracing method. Golgi-Cox stained hippocampal cornu ammonis area-3 (CA3) pyramidal neuron photomicrographs were serially captured at a depth of every 2µm in the z-axis by a wide field microscope from the point of appearance to the disappearance. These images were stacked along the axis perpendicular to the image plane to reconstruct the neuron in its entirety, digitally traced and dendritic quantification was performed using open source software. The same neurons were manually traced using camera lucida, and Sholl analysis was done manually to quantify the dendritic arborisation pattern. The dendritic quantification data were not significantly different in both methods. Hence, the technology-enabled, less demanding, and equally accurate neuronal tracing can be adopted instead of manual tracing and analysis of neurons.

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A simple digitised neuronal tracing method is described.

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It is fast, rigorous, and comparable to traditional tracing techniques.

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Helps the researcher to repeatedly probe data to reduce errors.

Retinal horizontal cells use different synaptic sites for global feedforward and local feedback signaling

In the outer plexiform layer (OPL) of the mammalian retina, cone photoreceptors (cones) provide input to more than a dozen types of cone bipolar cells (CBCs). In the mouse, this transmission is modulated by a single horizontal cell (HC) type. HCs perform global signaling within their laterally coupled network but also provide local, cone-specific feedback. However, it is unknown how HCs provide local feedback to cones at the same time as global forward signaling to CBCs and where the underlying synapses are located. To assess how HCs simultaneously perform different modes of signaling, we reconstructed the dendritic trees of five HCs as well as cone axon terminals and CBC dendrites in a serial block-face electron microscopy volume and analyzed their connectivity. In addition to the fine HC dendritic tips invaginating cone axon terminals, we also identified "bulbs," short segments of increased dendritic diameter on the primary dendrites of HCs. These bulbs are in an OPL stratum well below the cone axon terminal base and make contacts with other HCs and CBCs. Our results from immunolabeling, electron microscopy, and glutamate imaging suggest that HC bulbs represent GABAergic synapses that do not receive any direct photoreceptor input. Together, our data suggest the existence of two synaptic strata in the mouse OPL, spatially separating cone-specific feedback and feedforward signaling to CBCs. A biophysical model of a HC dendritic branch and voltage imaging support the hypothesis that this spatial arrangement of synaptic contacts allows for simultaneous local feedback and global feedforward signaling by HCs.

Spindle-Shaped Neurons in the Human Posteromedial (Precuneus) Cortex

The human posteromedial cortex (PMC), which includes the precuneus (PC), represents a multimodal brain area implicated in emotion, conscious awareness, spatial cognition, and social behavior. Here, we describe the presence of Nissl-stained elongated spindle-shaped neurons (suggestive of von Economo neurons, VENs) in the cortical layer V of the anterior and central PC of adult humans. The adapted "single-section" Golgi method for postmortem tissue was used to study these neurons close to pyramidal ones in layer V until merging with layer VI polymorphic cells. From three-dimensional (3D) reconstructed images, we describe the cell body, two main longitudinally oriented ascending and descending dendrites as well as the occurrence of spines from proximal to distal segments. The primary dendritic shafts give rise to thin collateral branches with a radial orientation, and pleomorphic spines were observed with a sparse to moderate density along the dendritic length. Other spindle-shaped cells were observed with straight dendritic shafts and rare branches or with an axon emerging from the soma. We discuss the morphology of these cells and those considered VENs in cortical areas forming integrated brain networks for higher-order activities. The presence of spindle-shaped neurons and the current discussion on the morphology of putative VENs address the need for an in-depth neurochemical and transcriptomic characterization of the PC cytoarchitecture. These findings would include these spindle-shaped cells in the synaptic and information processing by the default mode network and for general intelligence in healthy individuals and in neuropsychiatric disorders involving the PC in the context of the PMC functioning.

Cancer as a Model System for Testing Metabolic Scaling Theory

Biological allometries, such as the scaling of metabolism to mass, are hypothesized to result from natural selection to maximize how vascular networks fill space yet minimize internal transport distances and resistance to blood flow. Metabolic scaling theory argues two guiding principles—conservation of fluid flow and space-filling fractal distributions—describe a diversity of biological networks and predict how the geometry of these networks influences organismal metabolism. Yet, mostly absent from past efforts are studies that directly, and independently, measure metabolic rate from respiration and vascular architecture for the same organ, organism, or tissue. Lack of these measures may lead to inconsistent results and conclusions about metabolism, growth, and allometric scaling. We present simultaneous and consistent measurements of metabolic scaling exponents from clinical images of lung cancer, serving as a first-of-its-kind test of metabolic scaling theory, and identifying potential quantitative imaging biomarkers indicative of tumor growth. We analyze data for 535 clinical PET-CT scans of patients with non-small cell lung carcinoma to establish the presence of metabolic scaling between tumor metabolism and tumor volume. Furthermore, we use computer vision and mathematical modeling to examine predictions of metabolic scaling based on the branching geometry of the tumor-supplying blood vessel networks in a subset of 56 patients diagnosed with stage II-IV lung cancer. Examination of the scaling of maximum standard uptake value with metabolic tumor volume, and metabolic tumor volume with gross tumor volume, yield metabolic scaling exponents of 0.64 (0.20) and 0.70 (0.17), respectively. We compare these to the value of 0.85 (0.06) derived from the geometric scaling of the tumor-supplying vasculature. These results: (1) inform energetic models of growth and development for tumor forecasting; (2) identify imaging biomarkers in vascular geometry related to blood volume and flow; and (3) highlight unique opportunities to develop and test the metabolic scaling theory of ecology in tumors transitioning from avascular to vascular geometries.

Within-Trial Persistence of Learned Behavior as a Dissociable Behavioral Component in Hippocampus-Dependent Memory Tasks: A Potential Postlearning Role of Immature Neurons in the Adult Dentate Gyrus

The term “memory strength” generally refers to how well one remembers something. But more precisely it contains multiple modalities, such as how easily, how accurately, how confidently and how vividly we remember it. In human, these modalities of memory strength are dissociable. In this study, we asked whether we can isolate a behavioral component that is dissociable from others in hippocampus-dependent memory tasks in mice, which potentially reflect a modality of memory strength. Using a virus-mediated inducible method, we ablated immature neurons in the dentate gyrus in mice after we trained the mice with hippocampus-dependent memory tasks normally. In memory retrieval tests, these ablated mice initially showed intact performance. However, the ablated mice ceased learned behavior prematurely within a trial compared with control mice. In addition, the ablated mice showed shorter duration of individual episodes of learned behavior. Both affected behavioral measurements point to persistence of learned behavior. Thus, the effect of the postlearning manipulation showed dissociation between initial performance and persistence of learned behavior. These two behavioral components are likely to reflect different brain functions and be mediated by separate mechanisms, which might represent different modalities of memory strength. These simple dissociable measurements in widely used behavioral paradigms would be useful to understand detailed mechanisms underlying the expression of learned behavior and potentially different modalities of memory strength in mice. We also discuss a potential role that immature neurons in the dentate gyrus may play in persistence of learned behavior.

Comparing Automated Morphology Quantification Software on Dendrites of Uninjured and Injured Drosophila Neurons

Dendrites shape inputs and integration of depolarization that controls neuronal activity in the nervous system. Neuron pathologies can damage dendrite architecture and cause abnormalities in morphologies after injury. Dendrite regeneration can be quantified by various parameters, including total dendrite length and number of dendrite branches using manual or automated image analysis approaches. However, manual quantification is tedious and time consuming and automated approaches are often trained using wildtype neurons, making them poorly suited for analysis of genetically manipulated or injured dendrite arbors. In this study, we tested how well automated image analysis software performed on class IV Drosophila neurons, which have several hundred individual dendrite branches. We applied each software to automatically quantify features of uninjured neurons and neurons that regenerated new dendrites after injury. Regenerated arbors exhibit defects across multiple features of dendrite morphology, which makes them challenging for automated pipelines to analyze. We compared the performances of three automated pipelines against manual quantification using Simple Neurite Tracer in ImageJ: one that is commercially available (Imaris) and two developed by independent research groups (DeTerm and Tireless Tracing Genie). Out of the three software tested, we determined that Imaris is the most efficient at reconstructing dendrite architecture, but does not accurately measure total dendrite length even after intensive manual editing. Imaris outperforms both DeTerm and Tireless Tracing Genie for counting dendrite branches, and is better able to recreate previous conclusions from this same dataset. This thorough comparison of strengths and weaknesses of each software demonstrates their utility for analyzing regenerated neuron phenotypes in future studies.

Miro1-dependent mitochondrial dynamics in parvalbumin interneurons

The spatiotemporal distribution of mitochondria is crucial for precise ATP provision and calcium buffering required to support neuronal signaling. Fast-spiking GABAergic interneurons expressing parvalbumin (PV+) have a high mitochondrial content reflecting their large energy utilization. The importance for correct trafficking and precise mitochondrial positioning remains poorly elucidated in inhibitory neurons. Miro1 is a Ca²⁺-sensing adaptor protein that links mitochondria to the trafficking apparatus, for their microtubule-dependent transport along axons and dendrites, in order to meet the metabolic and Ca²⁺-buffering requirements of the cell. Here, we explore the role of Miro1 in PV+ interneurons and how changes in mitochondrial trafficking could alter network activity in the mouse brain. By employing live and fixed imaging, we found that the impairments in Miro1-directed trafficking in PV+ interneurons altered their mitochondrial distribution and axonal arborization, while PV+ interneuron-mediated inhibition remained intact. These changes were accompanied by an increase in the ex vivo hippocampal γ-oscillation (30–80 Hz) frequency and promoted anxiolysis. Our findings show that precise regulation of mitochondrial dynamics in PV+ interneurons is crucial for proper neuronal signaling and network synchronization.

Improving the Usability of Virtual Reality Neuron Tracing with Topological Elements

Researchers in the field of connectomics are working to reconstruct a map of neural connections in the brain in order to understand at a fundamental level how the brain processes information. Constructing this wiring diagram is done by tracing neurons through high-resolution image stacks acquired with fluorescence microscopy imaging techniques. While a large number of automatic tracing algorithms have been proposed, these frequently rely on local features in the data and fail on noisy data or ambiguous cases, requiring time-consuming manual correction. As a result, manual and semi-automatic tracing methods remain the state-of-the-art for creating accurate neuron reconstructions. We propose a new semi-automatic method that uses topological features to guide users in tracing neurons and integrate this method within a virtual reality (VR) framework previously used for manual tracing. Our approach augments both visualization and interaction with topological elements, allowing rapid understanding and tracing of complex morphologies. In our pilot study, neuroscientists demonstrated a strong preference for using our tool over prior approaches, reported less fatigue during tracing, and commended the ability to better understand possible paths and alternatives. Quantitative evaluation of the traces reveals that users' tracing speed increased, while retaining similar accuracy compared to a fully manual approach.

Improving Blood Vessel Tortuosity Measurements via Highly Sampled Numerical Integration of the Frenet-Serret Equations

Measures of vascular tortuosity-how curved and twisted a vessel is-are associated with a variety of vascular diseases. Consequently, measurements of vessel tortuosity that are accurate and comparable across modality, resolution, and size are greatly needed. Yet in practice, precise and consistent measurements are problematic-mismeasurements, inability to calculate, or contradictory and inconsistent measurements occur within and across studies. Here, we present a new method of measuring vessel tortuosity that ensures improved accuracy. Our method relies on numerical integration of the Frenet-Serret equations. By reconstructing the three-dimensional vessel coordinates from tortuosity measurements, we explain how to identify and use a minimally-sufficient sampling rate based on vessel radius while avoiding errors associated with oversampling and overfitting. Our work identifies a key failing in current practices of filtering asymptotic measurements and highlights inconsistencies and redundancies between existing tortuosity metrics. We demonstrate our method by applying it to manually constructed vessel phantoms with known measures of tortuousity, and 9,000 vessels from medical image data spanning human cerebral, coronary, and pulmonary vascular trees, and the carotid, abdominal, renal, and iliac arteries.

A simple method defines 3D morphology and axon projections of filled neurons in a small CNS volume: Steps toward understanding functional network circuitry

BACKGROUND

Fundamental to understanding neuronal network function is defining neuron morphology, location, properties, and synaptic connectivity in the nervous system. A significant challenge is to reconstruct individual neuron morphology and connections at a whole CNS scale and bring together functional and anatomical data to understand the whole network.

NEW METHOD

We used a PC controlled micropositioner to hold a fixed whole mount of Xenopus tadpole CNS and replace the stage on a standard microscope. This allowed direct recording in 3D coordinates of features and axon projections of one or two neurons dye-filled during whole-cell recording to study synaptic connections. Neuron reconstructions were normalised relative to the ventral longitudinal axis of the nervous system. Coordinate data were stored as simple text files.

RESULTS

Reconstructions were at 1 μm resolution, capturing axon lengths in mm. The output files were converted to SWC format and visualised in 3D reconstruction software NeuRomantic. Coordinate data are tractable, allowing correction for histological artefacts. Through normalisation across multiple specimens we could infer features of network connectivity of mapped neurons of different types.

COMPARISON WITH EXISTING METHODS

Unlike other methods using fluorescent markers and utilising large-scale imaging, our method allows direct acquisition of 3D data on neurons whose properties and synaptic connections have been studied using whole-cell recording.

CONCLUSIONS

This method can be used to reconstruct neuron 3D morphology and follow axon projections in the CNS. After normalisation to a common CNS framework, inferences on network connectivity at a whole nervous system scale contribute to network modelling to understand CNS function.

Bayesian inference for biophysical neuron models enables stimulus optimization for retinal neuroprosthetics

While multicompartment models have long been used to study the biophysics of neurons, it is still challenging to infer the parameters of such models from data including uncertainty estimates. Here, we performed Bayesian inference for the parameters of detailed neuron models of a photoreceptor and an OFF- and an ON-cone bipolar cell from the mouse retina based on two-photon imaging data. We obtained multivariate posterior distributions specifying plausible parameter ranges consistent with the data and allowing to identify parameters poorly constrained by the data. To demonstrate the potential of such mechanistic data-driven neuron models, we created a simulation environment for external electrical stimulation of the retina and optimized stimulus waveforms to target OFF- and ON-cone bipolar cells, a current major problem of retinal neuroprosthetics.

Integration of Within-Cell Experimental Data With Multi-Compartmental Modeling Predicts H-Channel Densities and Distributions in Hippocampal OLM Cells

Determining biophysical details of spatially extended neurons is a challenge that needs to be overcome if we are to understand the dynamics of brain function from cellular perspectives. Moreover, we now know that we should not average across recordings from many cells of a given cell type to obtain quantitative measures such as conductance since measures can vary multiple-fold for a given cell type. In this work we examine whether a tight combination of experimental and computational work can address this challenge. The oriens-lacunosum/moleculare (OLM) interneuron operates as a “gate” that controls incoming sensory and ongoing contextual information in the CA1 of the hippocampus, making it essential to understand how its biophysical properties contribute to memory function. OLM cells fire phase-locked to the prominent hippocampal theta rhythms, and we previously used computational models to show that OLM cells exhibit high or low theta spiking resonance frequencies that depend respectively on whether their dendrites have hyperpolarization-activated cation channels (h-channels) or not. However, whether OLM cells actually possess dendritic h-channels is unknown at present. We performed a set of whole-cell recordings of OLM cells from mouse hippocampus and constructed three multi-compartment models using morphological and electrophysiological parameters extracted from the same OLM cell, including per-cell pharmacologically isolated h-channel currents. We found that the models best matched experiments when h-channels were present in the dendrites of each of the three model cells created. This strongly suggests that h-channels must be present in OLM cell dendrites and are not localized to their somata. Importantly, this work shows that a tight integration of model and experiment can help tackle the challenge of characterizing biophysical details and distributions in spatially extended neurons. Full spiking models were built for two of the OLM cells, matching their current clamp cell-specific electrophysiological recordings. Overall, our work presents a technical advancement in modeling OLM cells. Our models are available to the community to use to gain insight into cellular dynamics underlying hippocampal function.

Dendritic and Spine Heterogeneity of von Economo Neurons in the Human Cingulate Cortex

The human cingulate cortex (CC), included in the paralimbic cortex, participates in emotion, visceral responses, attention, cognition, and social behaviors. The CC has spindle-shaped/fusiform cell body neurons in its layer V, the von Economo neurons (VENs). VENs have further developed in primates, and the characterization of human VENs can benefit from the detailed descriptions of the shape of dendrites and spines. Here, we advance this issue and studied VENs in the anterior and midcingulate cortex from four neurologically normal adult subjects. We used the thionin technique and the adapted “single-section” Golgi method for light microscopy. Three-dimensional (3D) reconstructions were carried out for the visualization of Golgi-impregnated VENs’ cell body, ascending and descending dendrites, and collateral branches. We also looked for the presence, density, and shape of spines from proximal to distal dendrites. These neurons have a similar aspect for the soma, but features of spiny dendrites evidenced a morphological heterogeneity of CC VENs. Only for the description of this continuum of shapes, we labeled the most common feature as VEN 1, which has main dendritic shafts but few branches and sparse spines. VEN 2 shows an intermediate aspect, whereas VEN 3 displays the most profuse dendritic ramification and more spines with varied shapes from proximal to distal branches. Morphometric data exemplify the dendritic features of these cells. The heterogeneity of the dendritic architecture and spines suggests additional functional implications for the synaptic and information processing in VENs in integrated networks of normal and, possibly, neurological/psychiatric conditions involving the human CC.

Distinct Synchronous Network Activity During the Second Postnatal Week of Medial Entorhinal Cortex Development

The medial entorhinal cortex (MEC) contains specialized cell types whose firing is tuned to aspects of an animal’s position and orientation in the environment, reflecting a neuronal representation of space. The spatially tuned firing properties of these cells quickly emerge during the third postnatal week of development in rodents. Spontaneous synchronized network activity (SSNA) has been shown to play a crucial role in the development of neuronal circuits prior to week 3. SSNA in MEC is well described in rodents during the first postnatal week, but there are little data about its development immediately prior to eye opening and spatial exploration. Furthermore, existing data lack single-cell resolution and are not integrated across layers. In this study, we addressed the question of whether the characteristics and underlying mechanisms of SSNA during the second postnatal week resemble that of the first week or whether distinct features emerge during this period. Using a combined calcium imaging and electrophysiology approach in vitro, we confirm that in mouse MEC during the second postnatal week, SSNA persists and in fact peaks, and is dependent on ionotropic glutamatergic signaling. However, SSNA differs from that observed during the first postnatal week in two ways: First, EC does not drive network activity in the hippocampus but only in neighboring neocortex (NeoC). Second, GABA does not drive network activity but influences it in a manner that is dependent both on age and receptor type. Therefore, we conclude that while there is a partial mechanistic overlap in SSNA between the first and second postnatal weeks, unique mechanistic features do emerge during the second week, suggestive of different or additional functions of MEC within the hippocampal-entorhinal circuitry with increasing maturation.

The natverse, a versatile toolbox for combining and analysing neuroanatomical data

To analyse neuron data at scale, neuroscientists expend substantial effort reading documentation, installing dependencies and moving between analysis and visualisation environments. To facilitate this, we have developed a suite of interoperable open-source R packages called the natverse. The natverse allows users to read local and remote data, perform popular analyses including visualisation and clustering and graph-theoretic analysis of neuronal branching. Unlike most tools, the natverse enables comparison across many neurons of morphology and connectivity after imaging or co-registration within a common template space. The natverse also enables transformations between different template spaces and imaging modalities. We demonstrate tools that integrate the vast majority of Drosophila neuroanatomical light microscopy and electron microscopy connectomic datasets. The natverse is an easy-to-use environment for neuroscientists to solve complex, large-scale analysis challenges as well as an open platform to create new code and packages to share with the community.

Gradual wiring of olfactory input to amygdala feedback circuits

The amygdala facilitates odor driven behavioral responses by enhancing the saliency of olfactory signals. Before this processing, olfactory input is refined through the feedback provided by amygdala corticofugal projection (ACPs). Although the saliency of odor signals is subject to developmental changes, the stage at which this cortical feedback first occurs is not known. Using optogenetically-assisted intracellular recordings of the mouse cortical amygdala, we identified changes in the electrophysiological properties of ACPs at different developmental stages. These were consistent with a decrease in neuronal excitability and an increase in the amount of incoming accessory olfactory bulb (AOB) inputs, as confirmed by estimates of release probability, quantal size and contact number at the AOB-to-ACP synapse. Moreover, the proportion of ACPs activated in response to odors was dependent on the stage of development as revealed by c-Fos expression analysis. These results update standard accounts of how the amygdala processes social signals by emphasizing the occurrence of critical periods in the development of its sensory gating functions.

High-Frequency Microdomain Ca2+ Transients and Waves during Early Myelin Internode Remodeling

Ensheathment of axons by myelin is a highly complex and multi-cellular process. Cytosolic calcium (Ca²⁺) changes in the myelin sheath have been implicated in myelin synthesis, but the source of this Ca²⁺ and the role of neuronal activity is not well understood. Using one-photon Ca²⁺ imaging, we investigated myelin sheath formation in the mouse somatosensory cortex and found a high rate of spontaneous microdomain Ca²⁺ transients and large-amplitude Ca²⁺ waves propagating along the internode. The frequency of Ca²⁺ transients and waves rapidly declines with maturation and reactivates during remyelination. Unexpectedly, myelin microdomain Ca²⁺ transients occur independent of neuronal action potential generation or network activity but are nearly completely abolished when the mitochondrial permeability transition pores are blocked. These findings are supported by the discovery of mitochondria organelles in non-compacted myelin. Together, the results suggest that myelin microdomain Ca²⁺ signals are cell-autonomously driven by high activity of mitochondria during myelin remodeling.

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Developing myelin sheaths show high rates of calcium transients and calcium waves

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Myelin calcium transients are independent from neuronal activity

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Adaxonal and paranodal myelin contained mitochondria

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Calcium transients require opening of mitochondrial permeability transition pores

NeuroPath2Path: Classification and elastic morphing between neuronal arbors using path-wise similarity

Neuron shape and connectivity affect function. Modern imaging methods have proven successful at extracting morphological information. One potential path to achieve analysis of this morphology is through graph theory. Encoding by graphs enables the use of high throughput informatic methods to extract and infer brain function. However, the application of graph-theoretic methods to neuronal morphology comes with certain challenges in term of complex subgraph matching and the difficulty in computing intermediate shapes in between two imaged temporal samples. Here we report a novel, efficacious graph-theoretic method that rises to the challenges. The morphology of a neuron, which consists of its overall size, global shape, local branch patterns, and cell-specific biophysical properties, can vary significantly with the cell's identity, location, as well as developmental and physiological state. Various algorithms have been developed to customize shape based statistical and graph related features for quantitative analysis of neuromorphology, followed by the classification of neuron cell types using the features. Unlike the classical feature extraction based methods from imaged or 3D reconstructed neurons, we propose a model based on the rooted path decomposition from the soma to the dendrites of a neuron and extract morphological features from each constituent path. We hypothesize that measuring the distance between two neurons can be realized by minimizing the cost of continuously morphing the set of all rooted paths of one neuron to another. To validate this claim, we first establish the correspondence of paths between two neurons using a modified Munkres algorithm. Next, an elastic deformation framework that employs the square root velocity function is established to perform the continuous morphing, which, as an added benefit, provides an effective visualization tool. We experimentally show the efficacy of NeuroPath2Path, NeuroP2P, over the state of the art.

TraceMontage: A method for merging multiple independent neuronal traces

BACKGROUND

The ability to reconstruct neuronal networks, local microcircuits, or the entire connectome is a central goal of modern neuroscience. Recently, advancements in sample preparation (e.g., sample expansion and Brainbow labeling) and optical (e.g., confocal and light sheet) techniques have enabled the imaging of increasingly large neural systems with high contrast. Tracing neuronal structures from these images proves challenging, however, necessitating tools that integrate multiple neuronal traces, potentially derived by various methods, into one combined (montaged) result.

NEW METHOD

Here, we present TraceMontage, an ImageJ/Fiji plugin for the combination of multiple neuron traces of a single image, either redundantly or non-redundantly. Internally, it uses graph theory to connect topological patterns in the 3-D spatial coordinates of neuronal trees. The software generates a single output tracing file containing the montage traces of the input tracing files and provides several measures of consistency analysis among multiple tracers.

RESULTS AND COMPARISON TO EXISTING METHOD(S)

To our knowledge, our software is the first dedicated method for the combination of tracing results. Combining multiple tracers increases the accuracy and speed of tracing of densely-labeled samples by harnessing collaborative effort. This utility is demonstrated using fluorescence microscope images from the hippocampus and primary visual cortex (V1) in Brainbow-labeled mice.

CONCLUSIONS

TraceMontage provides researchers the ability to combine neuronal tracing data generated by either the same or different method(s). As datasets become larger, the ability to trace images in this parallel manner will help connectomics scale to increasingly larger neural systems.

Purkinje Cells Pathology in Alzheimer's Disease

Alzheimer's disease (AD) is one of the main causes of dementia in senium and presenium. It is clinically characterized by memory impairment, deterioration of intellectual faculties, and loss of professional skills. The cerebellum is a critical part in the distributed neural circuits participating not only in motor function but also in autonomic, limbic, and cognitive behaviors. In present study, we aim to investigate the morphological changes in the Purkinje cells in different cerebellar regions in AD and to correlate them with the underlying AD pathology. Purkinje cells exhibit significant morphometric alterations in AD and prominently in the anterior lobe which is related to higher cognitive functions. The present study gives new insights into the cerebellar pathology in AD and confirms that Purkinje cells pathology is a key finding in AD brains and that AD is characterized by regional-specific atrophy picked in the anterior cerebellar lobe.

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.

Gpr158 Deficiency Impacts Hippocampal CA1 Neuronal Excitability, Dendritic Architecture, and Affects Spatial Learning

G-protein-coupled receptor 158 (Gpr158) is highly expressed in striatum, hippocampus and prefrontal cortex. It gained attention as it was implicated in physiological responses to stress and depression. Recently, Gpr158 has been shown to act as a pathway-specific synaptic organizer in the hippocampus, required for proper mossy fiber-CA3 neurocircuitry establishment, structure, and function. Although rodent Gpr158 expression is highest in CA3, considerable expression occurs in CA1 especially after the first postnatal month. Here, we combined hippocampal-dependent behavioral paradigms with subsequent electrophysiological and morphological analyses from the same group of mice to assess the effects of Gpr158 deficiency on CA1 physiology and function. We demonstrate deficits in spatial memory acquisition and retrieval in the Morris water maze paradigm, along with deficits in the acquisition of extinction memory in the passive avoidance test in Gpr158 KO mice. Electrophysiological recordings from CA1 pyramidal neurons revealed normal basal excitatory and inhibitory synaptic transmission, however, Schaffer collateral stimulation yielded dramatically reduced post-synaptic currents. Interestingly, intrinsic excitability of CA1 pyramidals was found increased, potentially acting as a compensatory mechanism to the reductions in Schaffer collateral-mediated drive. Both ex vivo and in vitro, neurons deficient for or with lowered levels of Gpr158 exhibited robust reductions in dendritic architecture and complexity, i.e., reduced length, surface, bifurcations, and branching. This effect was localized in the apical but not basal dendrites of adult CA1 pyramidals, indicative of compartment-specific alterations. A significant positive correlation between spatial memory acquisition and extent of complexity of CA1 pyramidals was found. Taken together, we provide first evidence of significant disruptions in hippocampal CA1 neuronal dendritic architecture and physiology, driven by Gpr158 deficiency. Importantly, the hippocampal neuronal morphology deficits appear to support the impairments in spatial memory acquisition observed in Gpr158 KO mice.

The Opening of Connexin 43 Hemichannels Alters Hippocampal Astrocyte Function and Neuronal Survival in Prenatally LPS-Exposed Adult Offspring

Clinical evidence has revealed that children born from mothers exposed to viral and bacterial pathogens during pregnancy are more likely to suffer various neurological disorders including schizophrenia, autism bipolar disorder, major depression, epilepsy, and cerebral palsy. Despite that most research has centered on the impact of prenatal inflammation in neurons and microglia, the potential modifications of astrocytes and neuron-astrocyte communication have received less scrutiny. Here, we evaluated whether prenatally LPS-exposed offspring display alterations in the opening of astrocyte hemichannels and pannexons in the hippocampus, together with changes in neuroinflammation, intracellular Ca²⁺ and nitric oxide (NO) signaling, gliotransmitter release, cell arborization, and neuronal survival. Ethidium uptake recordings revealed that prenatal LPS exposure enhances the opening of astrocyte Cx43 hemichannels and Panx1 channels in the hippocampus of adult offspring mice. This enhanced channel activity occurred by a mechanism involving a microglia-dependent production of IL-1β/TNF-α and the stimulation of p38 MAP kinase/iNOS/[Ca²⁺]_i-mediated signaling and purinergic/glutamatergic pathways. Noteworthy, the activity of Cx43 hemichannels affected the release of glutamate, [Ca²⁺]_i handling, and morphology of astrocytes, whereas also disturbed neuronal function, including the dendritic arbor and spine density, as well as survival. We speculate that excitotoxic levels of glutamate triggered by the activation of Cx43 hemichannels may contribute to hippocampal neurotoxicity and damage in prenatally LPS-exposed offspring. Therefore, the understanding of how astrocyte-neuron crosstalk is an auspicious avenue toward the development of broad treatments for several neurological disorders observed in children born to women who had a severe infection during gestation.

NeuroMorphoVis: a collaborative framework for analysis and visualization of neuronal morphology skeletons reconstructed from microscopy stacks

Motivation

From image stacks to computational models, processing digital representations of neuronal morphologies is essential to neuroscientific research. Workflows involve various techniques and tools, leading in certain cases to convoluted and fragmented pipelines. The existence of an integrated, extensible and free framework for processing, analysis and visualization of those morphologies is a challenge that is still largely unfulfilled.

Results

We present NeuroMorphoVis, an interactive, extensible and cross-platform framework for building, visualizing and analyzing digital reconstructions of neuronal morphology skeletons extracted from microscopy stacks. Our framework is capable of detecting and repairing tracing artifacts, allowing the generation of high fidelity surface meshes and high resolution volumetric models for simulation and in silico imaging studies. The applicability of NeuroMorphoVis is demonstrated with two case studies. The first simulates the construction of three-dimensional profiles of neuronal somata and the other highlights how the framework is leveraged to create volumetric models of neuronal circuits for simulating different types of in vitro imaging experiments.

Availability and implementation

The source code and documentation are freely available on https://github.com/BlueBrain/NeuroMorphoVis under the GNU public license. The morphological analysis, visualization and surface meshing are implemented as an extensible Python API (Application Programming Interface) based on Blender, and the volume reconstruction and analysis code is written in C++ and parallelized using OpenMP. The framework features are accessible from a user-friendly GUI (Graphical User Interface) and a rich CLI (Command Line Interface).

Supplementary information

Supplementary data are available at Bioinformatics online.

Group I mGluR-Mediated Activation of Martinotti Cells Inhibits Local Cortical Circuitry in Human Cortex

Group I metabotropic glutamate receptors (mGluRs) mediate a range of signaling and plasticity processes in the brain and are of growing importance as potential therapeutic targets in clinical trials for neuropsychiatric and neurodevelopmental disorders (NDDs). Fundamental knowledge regarding the functional effects of mGluRs upon pyramidal neurons and interneurons is derived largely from rodent brain, and their effects upon human neurons are predominantly untested. We therefore addressed how group I mGluRs affect microcircuits in human neocortex. We show that activation of group I mGluRs elicits action potential firing in Martinotti cells, which leads to increased synaptic inhibition onto neighboring neurons. Some other interneurons, including fast-spiking interneurons, are depolarized but do not fire action potentials in response to group I mGluR activation. Furthermore, we confirm the existence of group I mGluR-mediated depression of excitatory synapses in human pyramidal neurons. We propose that the strong increase in inhibition and depression of excitatory synapses onto layer 2/3 pyramidal neurons upon group I mGluR activation likely results in a shift in the balance between excitation and inhibition in the human cortical network.

Segmentation, Tracing, and Quantification of Microglial Cells from 3D Image Stacks

Microglia play a central role in modulating synaptic structure and physiology, learning and memory processes. They exhibit morphological changes to perform these roles, therefore the morphological study of microglia can help to understand their functionality. Many promising methods are proposed to automatically segment the blood vessels or reconstruct the neuronal morphology. However, they often fail to accurately capture microglia organizations due to the striking structural differences. This requires a more sophisticated approach of reconstruction taking into account the varying nature of branch structures and soma sizes. To this end, we propose an automated method to reconstruct microglia, and quantify their features from 2D/3D image datasets. We first employ multilevel thresholding to segment soma volumes(3D)/areas(2D) and recognize foreground voxels/pixels. Seed points sampled from the foreground, are connected to form the skeleton of the branches via the tracing process. The reconstructed data is quantified and written in SWC standard file format. We have applied our method to 3D image datasets of microglia, then evaluated the results using ground truth data, and compared them to those achieved via the state-of-the-art methods. Our method outperforms the others both in accuracy and computational time.

Loss of EPAC2 alters dendritic spine morphology and inhibitory synapse density

EPAC2 is a guanine nucleotide exchange factor that regulates GTPase activity of the small GTPase Rap and Ras and is highly enriched at synapses. Activation of EPAC2 has been shown to induce dendritic spine shrinkage and increase spine motility, effects that are necessary for synaptic plasticity. These morphological effects are dysregulated by rare mutations of Epac2 associated with autism spectrum disorders. In addition, EPAC2 destabilizes synapses through the removal of synaptic GluA2/3-containing AMPA receptors. Previous work has shown that Epac2 knockout mice (Epac2^−/−) display abnormal social interactions, as well as gross disorganization of the frontal cortex and abnormal spine motility in vivo. In this study we sought to further understand the cellular consequences of knocking out Epac2 on the development of neuronal and synaptic structure and organization of cortical neurons. Using primary cortical neurons generated from Epac2^+/+ or Epac2^−/− mice, we confirm that EPAC2 is required for cAMP-dependent spine shrinkage. Neurons from Epac2^−/− mice also displayed increased synaptic expression of GluA2/3-containing AMPA receptors, as well as of the adhesion protein N-cadherin. Intriguingly, analysis of excitatory and inhibitory synaptic proteins revealed that loss of EPAC2 resulted in altered expression of vesicular GABA transporter (VGAT) but not vesicular glutamate transporter 1 (VGluT1), indicating an altered ratio of excitatory and inhibitory synapses onto neurons. Finally, examination of cortical neurons located within the anterior cingulate cortex further revealed subtle deficits in the establishment of dendritic arborization in vivo. These data provide evidence that loss of EPAC2 enhances the stability of excitatory synapses and increases the number of inhibitory inputs.

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EPAC2 is required for cAMP-dependent spine remodeling.

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Loss of EPAC2 results in over-stabilized excitatory synapses.

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Loss of EPAC2 results in an increase in inhibitory input onto neurons.

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EPAC2 is required for correct dendritic arborization and spine formation in vivo.

DeepBouton: Automated Identification of Single-Neuron Axonal Boutons at the Brain-Wide Scale

Fine morphological reconstruction of individual neurons across the entire brain is essential for mapping brain circuits. Inference of presynaptic axonal boutons, as a key part of single-neuron fine reconstruction, is critical for interpreting the patterns of neural circuit wiring schemes. However, automated bouton identification remains challenging for current neuron reconstruction tools, as they focus mainly on neurite skeleton drawing and have difficulties accurately quantifying bouton morphology. Here, we developed an automated method for recognizing single-neuron axonal boutons in whole-brain fluorescence microscopy datasets. The method is based on deep convolutional neural networks and density-peak clustering. High-dimensional feature representations of bouton morphology can be learned adaptively through convolutional networks and used for bouton recognition and subtype classification. We demonstrate that the approach is effective for detecting single-neuron boutons at the brain-wide scale for both long-range pyramidal projection neurons and local interneurons.

Early postnatal development of pyramidal neurons across layers of the mouse medial prefrontal cortex

Mammalian neocortex is a highly layered structure. Each layer is populated by distinct subtypes of principal cells that are born at different times during development. While the differences between principal cells across layers have been extensively studied, it is not known how the developmental profiles of neurons in different layers compare. Here, we provide a detailed morphological and functional characterisation of pyramidal neurons in mouse mPFC during the first postnatal month, corresponding to known critical periods for synapse and neuron formation in mouse sensory neocortex. Our data demonstrate similar maturation profiles of dendritic morphology and intrinsic properties of pyramidal neurons in both deep and superficial layers. In contrast, the balance of synaptic excitation and inhibition differs in a layer-specific pattern from one to four postnatal weeks of age. Our characterisation of the early development and maturation of pyramidal neurons in mouse mPFC not only demonstrates a comparable time course of postnatal maturation to that in other neocortical circuits, but also implies that consideration of layer- and time-specific changes in pyramidal neurons may be relevant for studies in mouse models of neuropsychiatric and neurodevelopmental disorders.

Conserved regulation of neurodevelopmental processes and behavior by FoxP in Drosophila

FOXP proteins form a subfamily of evolutionarily conserved transcription factors involved in the development and functioning of several tissues, including the central nervous system. In humans, mutations in FOXP1 and FOXP2 have been implicated in cognitive deficits including intellectual disability and speech disorders. Drosophila exhibits a single ortholog, called FoxP, but due to a lack of characterized mutants, our understanding of the gene remains poor. Here we show that the dimerization property required for mammalian FOXP function is conserved in Drosophila. In flies, FoxP is enriched in the adult brain, showing strong expression in ~1000 neurons of cholinergic, glutamatergic and GABAergic nature. We generate Drosophila loss-of-function mutants and UAS-FoxP transgenic lines for ectopic expression, and use them to characterize FoxP function in the nervous system. At the cellular level, we demonstrate that Drosophila FoxP is required in larvae for synaptic morphogenesis at axonal terminals of the neuromuscular junction and for dendrite development of dorsal multidendritic sensory neurons. In the developing brain, we find that FoxP plays important roles in α-lobe mushroom body formation. Finally, at a behavioral level, we show that Drosophila FoxP is important for locomotion, habituation learning and social space behavior of adult flies. Our work shows that Drosophila FoxP is important for regulating several neurodevelopmental processes and behaviors that are related to human disease or vertebrate disease model phenotypes. This suggests a high degree of functional conservation with vertebrate FOXP orthologues and established flies as a model system for understanding FOXP related pathologies.

Iterative expert-in-the-loop classification of sleep PSG recordings using a hierarchical clustering

BACKGROUND

The classification of sleep signals is a subjective and time consuming task. A large number of automatic classifiers have been published in the past decade but a sleep community has no strong confidence to use them in clinical practice and still remains using a standard manual scoring according standardized rules.

NEW METHOD

We developed a semi-supervised data-driven approach for objective and efficient evaluation of polysomnographic (PSG) data. The proposed algorithm finds a representative set of signal segments that are subsequently scored by a sleep neurologist. The remaining part of the recording is then automatically classified using these templates.

RESULTS

The method was evaluated on 36 PSG recordings (18 chronic insomniacs, 18 healthy controls). We show a faster and objective evaluation of PSG data compared to the manual scoring that is over-performing automated classifiers (accuracy increases ∼14%). The classification results are comparable on both datasets.

COMPARISON WITH EXISTING METHOD(S)

The methodology that we propose has not yet been published in the area of sleep PSG data processing. The performance of our method is comparable to various published automated approaches (a typical published classification accuracy is ∼75-95%). The method allows the evaluation of PSG recordings in more general terms and across different recording devices and standards.

CONCLUSIONS

The proposed solution is not based on a single-purpose rules or heuristics and training model is not trained on other patient's sleep recordings. The method is applicable to wide range of similar tasks and various types of physiological signals.