Connectomic comparison of mouse and human cortex

Sleep deprivation modulates pain sensitivity through alterations in lncRNA and mRNA expression in the nucleus accumbens and ventral midbrain

Sleep deprivation (SD) is a growing public health concern with implications for pain sensitivity and well-being. Although the relationship between sleep and pain is well understood, the underlying mechanisms remain largely unknown. This study investigates how SD influences pain sensitivity by modulating gene expression in the nucleus accumbens (NAc) and ventral tegmental area (VTA) of mice. Using the CPW sleep deprivation model, mice were deprived of sleep for three days, simulating preoperative conditions. Behavioral tests revealed heightened mechanical and thermal hypersensitivity post-SD. Brain MRI, immunofluorescence, and RNA sequencing analyses showed significant changes in the expression of non-coding RNAs (ncRNAs) and mRNAs in NAc and VTA, implicating several pain-related genes. Functional enrichment analysis highlighted pathways associated with neurotransmission, inflammation, and stress response. The study identified Hcrt and Apoe as critical modulators of SD-induced hyperalgesia, with potential therapeutic implications for managing pain associated with SD. Findings suggest that overlapping pathways exist between sleep and pain sensitivity, offering insights into the molecular mechanisms that connect sleep disorders with heightened pain responses.

Emergence of a synergistic scaffold in the brains of human infants

The human brain is a complex organ comprising billions of interconnected neurons, which enables interaction with both physical and social environments. Neural dynamics of the whole brain go far beyond just the sum of its individual elements; a property known as "synergy". Previously it has been shown that synergy is crucial for many complex brain functions and cognition, however, it remains unknown how and when the large number of discrete neurons evolve into the unified system able to support synergistic interactions. Here we analyzed high-density electroencephalography data from the late fetal period to one month after term age. We found that the human brain transitions from a redundancy-dominated to a synergy-dominated system around birth. Frontal regions lead the emergence of a synergistic scaffold comprised of overlapping subsystems, while the integration of sensory areas developed gradually, from occipital to central regions. Strikingly, early developmental trajectories of brain synergy were modulated by environmental enrichment associated with enhanced mother-infant interactions, and the level of synergy near term equivalent age was associated with later neurocognitive development.

Light-microscopy-based connectomic reconstruction of mammalian brain tissue

The information-processing capability of the brain's cellular network depends on the physical wiring pattern between neurons and their molecular and functional characteristics. Mapping neurons and resolving their individual synaptic connections can be achieved by volumetric imaging at nanoscale resolution1,2 with dense cellular labelling. Light microscopy is uniquely positioned to visualize specific molecules, but dense, synapse-level circuit reconstruction by light microscopy has been out of reach, owing to limitations in resolution, contrast and volumetric imaging capability. Here we describe light-microscopy-based connectomics (LICONN). We integrated specifically engineered hydrogel embedding and expansion with comprehensive deep-learning-based segmentation and analysis of connectivity, thereby directly incorporating molecular information into synapse-level reconstructions of brain tissue. LICONN will allow synapse-level phenotyping of brain tissue in biological experiments in a readily adoptable manner.

Development of GABAergic Interneurons in the Human Cerebral Cortex

GABAergic interneurons are critical regulators of information processing in the cerebral cortex. They constitute a heterogeneous group of neurons with unique spatial and temporal capabilities to control information flow and influence neural network dynamics through inhibitory and disinhibitory mechanisms. Interneuron diversity is largely conserved between rodents and primates, which indicates that the addition of new types of GABAergic neurons is not the most critical innovation of the primate cortex. In contrast, interneurons are much more abundant and seem more widely interconnected in the cerebral cortex of primates than in rodents, suggesting selective evolutionary pressure in the mechanisms regulating the generation, survival and maturation of cortical interneurons. Recent studies are beginning to shed light on the cellular and molecular mechanisms controlling the development of cortical interneurons in humans, from their generation in the embryonic telencephalon to their early integration in cortical networks. These studies identified many features in the development of human cortical interneurons that are shared with other mammals, along with distinctive features that seem characteristic of the primate brain, such as a previously unrecognised protracted period of neurogenesis and migration that extends the earliest stages of interneuron development into the first months of postnatal life in humans.

Accelerated signal propagation speed in human neocortical dendrites

Human-specific cognitive abilities depend on information processing in the cerebral cortex, where the neurons are significantly larger and their processes longer and sparser compared to rodents. We found that, in synaptically connected layer 2/3 pyramidal cells (L2/3 PCs), the delay in signal propagation from soma to soma is similar in humans and rodents. To compensate for the longer processes of neurons, membrane potential changes in human axons and/or dendrites must propagate faster. Axonal and dendritic recordings show that the propagation speed of action potentials (APs) is similar in human and rat axons, but the forward propagation of excitatory postsynaptic potentials (EPSPs) and the backward propagation of APs are 26 and 47% faster in human dendrites, respectively. Experimentally-based detailed biophysical models have shown that the key factor responsible for the accelerated EPSP propagation in human cortical dendrites is the large conductance load imposed at the soma by the large basal dendritic tree. Additionally, larger dendritic diameters and differences in cable and ion channel properties in humans contribute to enhanced signal propagation. Our integrative experimental and modeling study provides new insights into the scaling rules that help maintain information processing speed albeit the large and sparse neurons in the human cortex.

Cross-Species Multi-Omics Analysis Reveals Myeloid-Driven Endothelial Oxidative Stress in Ischemic Stroke

BACKGROUND

Ischemic stroke is a leading cause of mortality and disability worldwide, yet the interplay between peripheral and central immune responses is still only partially understood. Emerging evidence suggests that myeloid cells, when activated in the periphery, infiltrate the ischemic brain and contribute to the disruption of the blood-brain barrier (BBB) through both inflammatory and metabolic mechanisms.

METHODS

In this study, we integrated bulk RNA-sequencing (RNA-seq), single-cell RNA-seq (scRNA-seq), spatial transcriptomics, and flow cytometry data from human and mouse models of ischemic stroke. Mouse stroke models were induced by transient middle cerebral artery occlusion (tMCAO), and brain tissues were later collected at specified time points for analysis. We examined time-dependent transcriptional changes in the peripheral blood, delineated cell-type-specific responses by single-cell profiling, and validated myeloid infiltration into the ischemic brain. We also investigated endothelial metabolic reprogramming and oxidative stress by combining scMetabolism analyses (a computational R package for inferring metabolic pathway activity at the single-cell level) with in vitro oxygen-glucose deprivation/reperfusion (OGD/R) experiments.

RESULTS

Cross-species bulk RNA-seq revealed a modest early immune shift at 3 h post-stroke, escalating significantly by 24 h, with robust myeloid-centric gene signatures conserved in humans and mice. Single-cell analyses confirmed a pronounced expansion of neutrophils, monocytes, and megakaryocytes in peripheral blood, coupled with a decrease in T and B lymphocytes. Spatial transcriptomics and flow cytometry demonstrated substantial infiltration of CD11b+ myeloid cells into the infarct core, which showed extensive interaction with endothelial cells. Endothelial scRNA-seq data showed reductions in the oxidative phosphorylation, glutathione, and nicotinate metabolic pathways, together with elevated pentose phosphate pathway activity, suggestive of oxidative stress and compromised antioxidant capacity. Functional scoring further indicated diminished endothelial inflammation/repair potential, while in vitro OGD/R experiments revealed morphological disruption, CD31 downregulation, and increased 4-hydroxynonenal (4-HNE), underscoring the importance of endothelial oxidative damage in BBB breakdown.

CONCLUSIONS

These multi-omics findings highlight the existence of a coordinated peripheral-central immune axis in ischemic stroke, wherein myeloid cell recruitment and endothelial metabolic vulnerability jointly exacerbate inflammation and oxidative stress. The targeting of endothelial oxidative injury and myeloid-endothelial crosstalk may represent a promising strategy to mitigate secondary brain injury in ischemic stroke.

HYPOTHESIS: Lipid-protecting disulfide bridges are the missing molecular link between ApoE4 and sporadic Alzheimer's disease in humans

As the principal lipid transporter in the human brain, apolipoprotein E (ApoE) is tasked with transport and protection of highly vulnerable lipids that are required to support and remodel neuronal membranes, in a process that is dependent on ApoE receptors. APOE allele variants that encode proteins differing only in the number of cysteine (Cys)-to-arginine (Arg) exchanges (ApoE2 [2 Cys], ApoE3 [1 Cys], ApoE4 [0 Cys]) comprise the strongest genetic risk factor for sporadic Alzheimer's disease (AD); however, the specific molecular feature(s) and resultant mechanisms that underlie these isoform-dependent effects are unknown. One signature feature of Cys is the capacity to form disulfide (Cys-Cys) bridges, which are required to form disulfide-linked dimers and multimers. Here we propose the overarching hypothesis that super-ability (for ApoE2), intermediate ability (for ApoE3) or inability (for ApoE4) to form lipid-protecting intermolecular disulfide bridges, is the central molecular determinant accounting for the disparate effects of APOE alleles on AD risk and amyloid-β and Tau pathologies in humans. We posit that presence and abundance of Cys in human ApoE3 and ApoE2 respectively, conceal and protect vulnerable lipids transported by ApoE from peroxidation by enabling formation of disulfide-linked homo- and heteromeric ApoE complexes. We thus propose that inability to form intermolecular disulfide bridges makes ApoE4-containing lipoproteins uniquely vulnerable to peroxidation and its downstream consequences. Consistent with our model, we found that brain-enriched polyunsaturated fatty acid-containing phospholipids induce disulfide-dependent dimerization and multimerization of ApoE3 and ApoE2 (but not ApoE4). By contrast, incubation with the peroxidation-resistant lipid DMPC or cholesterol alone had minimal effects on dimerization. These novel concepts and findings are integrated into our unifying model implicating peroxidation of ApoE-containing lipoproteins, with consequent ApoE receptor-ligand disruption, as initiating molecular events that ultimately lead to AD in humans.

Large brains: Big unknowns in cellular neuroscience

Contemporary cellular neuroscience is strong on small but weak on large brains. Large brains have lower neuronal densities than smaller brains. We outline opposing functional interpretations of this result. Analysis of human brains supports the idea that dendritic complexity matters and might even correlate with intellectual ability. Cortical connectomics revealed an elaboration of disinhibitory motifs in human brains. There is disagreement as to whether glia-to-neuron ratios differ between small and large brains. The elaborate myeloarchitecture of the human brain has long been recognized and novel evidence indicates myelin might play nonconventional structural functions in larger brains. Three-dimensional body-part models in the cortex of tactile specialists point to the significance of the three-dimensional structure of cortical networks. The comparative assessment of brain performance remains one of the biggest challenges in neurobiology. Understanding cellular differences between small and large brains is a neglected, yet fundamental issue for neuroscience and translation.

Synapses mediate the effects of different types of stress on working memory: a brain-inspired spiking neural network study

Acute stress results from sudden short-term events, and individuals need to quickly adjust their physiological and psychological to re-establish balance. Chronic stress, on the other hand, results in long-term physiological and psychological burdens due to the continued existence of stressors, making it difficult for individuals to recover and prone to pathological symptoms. Both types of stress can affect working memory and change cognitive function. In this study, we explored the impact of acute and chronic stress on synaptic modulation using a biologically inspired, data-driven rodent prefrontal neural network model. The model consists of a specific number of excitatory and inhibitory neurons that are connected through AMPA, NMDA, and GABA synapses. The study used a short-term recall to simulate working memory tasks and assess the ability of neuronal populations to maintain information over time. The results showed that acute stress can enhance working memory information retention by enhancing AMPA and NMDA synaptic currents. In contrast, chronic stress reduces dendritic spine density and weakens the regulatory effect of GABA currents on working memory tasks. In addition, this structural damage can be complemented by strong connections between excitatory neurons with the same selectivity. These findings provide a reference scheme for understanding the neural basis of working memory under different stress conditions.

Sample Processing and Benchmarking for Multibeam Optical Scanning Transmission Electron Microscopy

Electron microscopy (EM) is an indispensable technique to visualize biological ultrastructure in health and disease. High-throughput EM further enables larger scales and volumes to be recorded within feasible timeframes. Multibeam optical scanning transmission EM (OSTEM) utilizes multiple beamlets and optical separation of the transmitted electrons to increase imaging throughput with transmission-based imaging. However, the compatibility of multibeam OSTEM with routine sample preparation protocols and the effect of machine settings on image quality remain largely unknown. Here, we show multibeam OSTEM to be an order of magnitude faster than (scanning) transmission EM while yielding comparable high-quality images of tissue processed with standard high-contrast staining protocols. Multibeam OSTEM benefits from embedding approaches that introduce high contrast but is flexible in the type of stain used. Optimal results are obtained using an acceleration voltage of 5 kV, where section thickness and pixel dwell time require a balance between throughput and image quality. Our results show high-throughput EM with imaging quality comparable with commonly used transmission-based modalities, enabling biological ultrastructure analysis across larger scales and volumes.

Absolute Number of Three Populations of Interneurons and All GABAergic Synapses in the Human Hippocampus

The human hippocampus, essential for learning and memory, is implicated in numerous neurological and psychiatric disorders, each linked to specific neuronal subpopulations. Advancing our understanding of hippocampal function requires computational models grounded in precise quantitative neuronal data. While extensive data exist on the neuronal composition and synaptic architecture of the rodent hippocampus, analogous quantitative data for the human hippocampus remain very limited. Given the critical role of local GABAergic interneurons in modulating hippocampal functions, we employed unbiased stereological techniques to estimate the density and total number of three major GABAergic cell types in the male and female human hippocampus: parvalbumin (PV)-expressing, somatostatin (SOM)-positive, and calretinin (CR)-positive interneurons. Our findings reveal an estimated 49,400 PV-positive, 141,500 SOM-positive, and 250,600 CR-positive interneurons per hippocampal hemisphere. Notably, CR-positive interneurons, which are primarily interneuron-selective in rodents, were present in humans at a higher proportion. Additionally, using three-dimensional electron microscopy, we estimated ∼25 billion GABAergic synapses per hippocampal hemisphere, with PV-positive boutons comprising ∼3.5 billion synapses, or 14% of the total GABAergic synapses. These findings contribute crucial quantitative insights for modeling human hippocampal circuits and understanding its complex regulatory dynamics.

Augmenting flexibility: mutual inhibition between inhibitory neurons expands functional diversity

Recent advances in microcircuit analysis of nervous systems have revealed a plethora of mutual connections between inhibitory interneurons across many different species and brain regions. The abundance of these mutual connections has not been fully explained. Strikingly, we show that neural circuits with mutually inhibitory connections are able to rapidly and flexibly switch between distinct functions. That is, multiple functions coexist for a single set of synaptic weights. Here, we develop a theoretical framework to explain how inhibitory recurrent circuits give rise to this flexibility and show that mutual inhibition doubles the number of cusp bifurcations in small neural circuits. As a concrete example, we study a class of functional motifs we call coupled recurrent inhibitory and recurrent excitatory loops (CRIRELs). These CRIRELs have the advantage of being both multi-functional and controllable, performing a plethora of functions, including decisions, memory, toggle, and so forth. Finally, we demonstrate how mutual inhibition maximizes storage capacity for larger networks.

Mapping Alzheimer's Molecular Pathologies in Large-Scale Connectomics Data: A Publicly Accessible Correlative Microscopy Resource

Connectomics using volume-electron-microscopy enables mapping and analysis of neuronal networks, revealing insights into neural circuit function and dysfunction. In Alzheimer's disease (AD), where amyloid-β (Aβ) and hyperphosphorylated-Tau (pTau) are implicated, connectomics offers an approach to unravel how these molecules contribute to circuit alterations by enabling the study of these molecules within the context of the complete local neuronal and glial milieu. We present a volumetric-correlated-light-and-electron microscopy (vCLEM) protocol using fluorescent nanobodies to localize Aβ and pTau within a large-scale connectomics dataset from the hippocampus of the 3xTg AD mouse model. A key outcome of this work is a publicly accessible vCLEM dataset, featuring fluorescent labeling of Aβ and pTau in the ultrastructural context with segmented neurons, glia, and synapses. This dataset provides a unique resource for exploring AD pathology in the context of connectomics and fosters collaborative opportunities in neurodegenerative disease research. As a proof-of-principle, we uncovered new localizations of Aβ and pTau, including pTau-positive spine-like protrusions at the axon initial segment and changes in the number and size of synapses near Aβ plaques. Our vCLEM approach facilitates the discovery of both molecular and structural alterations within large-scale EM data, advancing connectomics research in Alzheimer's and other neurodegenerative diseases.

Human brain tissue cultures: a unique ex vivo model to unravel the pathogenesis of neurotropic arboviruses

Arboviruses are transmitted by arthropods, and their spread from endemic to nonendemic regions has been accelerated by deforestation, climate change, and global mobility. Arbovirus infection in human results in symptoms ranging from mild to life-threatening, with the impairment of central nervous system functions being reported in severe cases. Despite its clinical relevance, the mechanisms by which arboviruses led to neural dysfunction are still poorly understood. The lack of a widespread human central nervous system model to study the virus-host interaction challenges the advance of our knowledge on these mechanisms. In this context, human brain-derived ex vivo models have the advantage of preserving cellular diversity, cell connections, and tissue cytoarchitecture found in human brain, raising them as a powerful strategy to elucidate the cellular-molecular alterations underlying brain diseases. Here, we review recent advances in the field of neurotropic arboviruses obtained using ex vivo human brain tissue as the experimental model.

Volume electron microscopy reveals unique laminar synaptic characteristics in the human entorhinal cortex

The entorhinal cortex (EC) plays a pivotal role in memory function and spatial navigation, connecting the hippocampus with the neocortex. The EC integrates a wide range of cortical and subcortical inputs, but its synaptic organization in the human brain is largely unknown. We used volume electron microscopy to perform a 3D analysis of the microanatomical features of synapses in all layers of the medial EC (MEC) from the human brain. Using this technology, 12,974 synapses were fully 3D reconstructed at the ultrastructural level. The MEC presented a distinct set of synaptic features, differentiating this region from other human cortical areas. Furthermore, ultrastructural synaptic characteristics within the MEC was predominantly similar, although layers I and VI exhibited several synaptic characteristics that were distinct from other layers. The present study constitutes an extensive description of the synaptic characteristics of the neuropil of all layers of the EC, a crucial step to better understand the connectivity of this cortical region, in both health and disease.

Human hippocampal CA3 uses specific functional connectivity rules for efficient associative memory

Our brain has remarkable computational power, generating sophisticated behaviors, storing memories over an individual's lifetime, and producing higher cognitive functions. However, little of our neuroscience knowledge covers the human brain. Is this organ truly unique, or is it a scaled version of the extensively studied rodent brain? Combining multicellular patch-clamp recording with expansion-based superresolution microscopy and full-scale modeling, we determined the cellular and microcircuit properties of the human hippocampal CA3 region, a fundamental circuit for memory storage. In contrast to neocortical networks, human hippocampal CA3 displayed sparse connectivity, providing a circuit architecture that maximizes associational power. Human synapses showed unique reliability, high precision, and long integration times, exhibiting both species- and circuit-specific properties. Together with expanded neuronal numbers, these circuit characteristics greatly enhanced the memory storage capacity of CA3. Our results reveal distinct microcircuit properties of the human hippocampus and begin to unravel the inner workings of our most complex organ.

Lipid-protecting disulfide bridges are the missing molecular link between ApoE4 and sporadic Alzheimer's disease in humans

As the principal lipid transporter in the human brain, apolipoprotein E (ApoE) is tasked with the transport and protection of highly vulnerable lipids required to support and remodel neuronal membranes, in a process that is dependent on ApoE receptors. Human APOE allele variants that encode proteins differing only in the number of cysteine (Cys)-to-arginine (Arg) exchanges (ApoE2 [2 Cys], ApoE3 [1 Cys], ApoE4 [0 Cys]) comprise the strongest genetic risk factor for sporadic Alzheimer's disease (AD); however, the specific molecular feature(s) and resultant mechanisms that underlie these isoform-dependent effects are unknown. One signature feature of Cys is the capacity to form disulfide (Cys-Cys) bridges, which are required to form disulfide bridge-linked dimers and multimers. Here we propose the overarching hypothesis that the super-ability (for ApoE2), intermediate ability (for ApoE3) or inability (for ApoE4) to form lipid-protecting intermolecular disulfide bridges, is the central molecular determinant accounting for the disparate effects of APOE alleles on AD risk and amyloid-β and Tau pathologies in humans. We posit that presence and abundance of Cys in human ApoE3 and ApoE2 respectively, conceal and protect vulnerable lipids transported by ApoE from peroxidation by enabling formation of ApoE homo-dimers/multimers and heteromeric ApoE complexes such as ApoE-ApoJ and ApoE-ApoD. We thus propose that the inability to form intermolecular disulfide bridges makes ApoE4-containing lipoproteins uniquely vulnerable to peroxidation and its downstream consequences. Consistent with our model, we found that brain-enriched polyunsaturated fatty acid-containing phospholipids induce disulfide-dependent dimerization and multimerization of ApoE3 and ApoE2 (but not ApoE4). By contrast, incubation with the peroxidation-resistant lipid DMPC or cholesterol alone had minimal effects on dimerization. These novel concepts and findings are integrated into our unifying model implicating peroxidation of ApoE-containing lipoproteins, with consequent ApoE receptor-ligand disruption, as the initiating molecular events that ultimately lead to AD in humans.

Data-driven synapse classification reveals a logic of glutamate receptor diversity

The rich diversity of synapses facilitates the capacity of neural circuits to transmit, process and store information. We used multiplex super-resolution proteometric imaging through array tomography to define features of single synapses in mouse neocortex. We find that glutamatergic synapses cluster into subclasses that parallel the distinct biochemical and functional categories of receptor subunits: GluA1/4, GluA2/3 and GluN1/GluN2B. Two of these subclasses align with physiological expectations based on synaptic plasticity: large AMPAR-rich synapses may represent potentiated synapses, whereas small NMDAR-rich synapses suggest "silent" synapses. The NMDA receptor content of large synapses correlates with spine neck diameter, and thus the potential for coupling to the parent dendrite. Overall, ultrastructural features predict receptor content of synapses better than parent neuron identity does, suggesting synapse subclasses act as fundamental elements of neuronal circuits. No barriers prevent future generalization of this approach to other species, or to study of human disorders and therapeutics.

Cancer Neuroscience of Brain Tumors: From Multicellular Networks to Neuroscience-Instructed Cancer Therapies

Deepening our understanding of neuro-cancer interactions can innovate brain tumor treatment. This mini review unfolds the most relevant and recent insights into the neural mechanisms contributing to brain tumor initiation, progression, and resistance, including synaptic connections between neurons and cancer cells, paracrine neuro-cancer signaling, and cancer cells' intrinsic neural properties. We explain the basic and clinical-translational relevance of these findings, identify unresolved questions and particularly interesting future research avenues, such as central nervous system neuro-immunooncology, and discuss the potential transferability to extracranial cancers. Lastly, we conceptualize ways toward clinical trials and develop a roadmap toward neuroscience-instructed brain tumor therapies. Significance: Neural influences on brain tumors drive their growth and invasion. Herein, we develop a roadmap to use these fundamentally new insights into brain tumor biology for improved outcomes.

Exploring Cortical Interneurons in Substance Use Disorder: From Mechanisms to Therapeutic Perspectives

Interneurons (INs) play a crucial role in the regulation of neural activity within the medial prefrontal cortex (mPFC), a brain region critically involved in executive functions and behavioral control. In recent preclinical studies, dysregulation of INs in the mPFC has been implicated in the pathophysiology of substance use disorder, characterized by vulnerability to chronic drug use. Here, we explore the diversity of mPFC INs and their connectivity and roles in vulnerability to addiction. We also discuss how these INs change over time with drug exposure. Finally, we focus on noninvasive brain stimulation as a therapeutic approach for targeting INs in substance use disorder, highlighting its potential to restore neural circuits.

Spike reliability is cell type specific and shapes excitation and inhibition in the cortex

Neurons encode information in the highly variable spiking activity of neuronal populations, so that different repetitions of the same stimulus can generate action potentials that vary significantly in terms of the count and timing. How does spiking variability originate, and does it have a functional purpose? Leveraging large-scale intracellular electrophysiological data, we relate the spiking reliability of cortical neurons in-vitro during the intracellular injection of current resembling synaptic inputs to their morphologic, electrophysiologic, and transcriptomic classes. Our findings demonstrate that parvalbumin+ (PV) interneurons, a subclass of inhibitory neurons, show high reliability compared to other neuronal subclasses, particularly excitatory neurons. Through computational modeling, we predict that the high reliability of PV interneurons allows for strong and precise inhibition in downstream neurons, while the lower reliability of excitatory neurons allows for integrating multiple synaptic inputs leading to a spiking rate code. These findings illuminate how spiking variability in different neuronal classes affect information propagation in the brain, leading to precise inhibition and spiking rate codes.

Understanding GABAergic synapse diversity and its implications for GABAergic pharmacotherapy

Despite the substantial contribution of disruptions in GABAergic inhibitory neurotransmission to the etiology of psychiatric, neurodevelopmental, and neurodegenerative disorders, surprisingly few drugs targeting the GABAergic system are currently available, partly due to insufficient understanding of circuit-specific GABAergic synapse biology. In addition to GABA receptors, GABAergic synapses contain an elaborate organizational protein machinery that regulates the properties of synaptic transmission. Until recently, this machinery remained largely unexplored, but key methodological advances have now led to the identification of a wealth of new GABAergic organizer proteins. Notably, many of these proteins appear to function only at specific subsets of GABAergic synapses, creating a diversity of organizer complexes that may serve as circuit-specific targets for pharmacotherapies. The present review aims to summarize the methodological developments that underlie this newfound knowledge and provide a current overview of synapse-specific GABAergic organizer complexes, as well as outlining future avenues and challenges in translating this knowledge into clinical applications.

Ultrastructural membrane dynamics of mouse and human cortical synapses

Live human brain tissues provide unique opportunities for understanding the physiology and pathophysiology of synaptic transmission. Investigations have been limited to anatomy, electrophysiology, and protein localization-while crucial parameters such as synaptic vesicle dynamics were not visualized. Here we utilize zap-and-freeze time-resolved electron microscopy to overcome this hurdle. First we validate the approach with acute mouse brain slices to demonstrate that axons parallel to the electrical field can be stimulated to produce calcium signaling. Next we show that ultrafast endocytosis is induced and can be captured in both mouse and human brain slices. Crucially, in both species a protein essential for ultrafast endocytosis Dynamin 1xA (Dyn1xA) localizes to the region peripheral to the active zone, the putative endocytic zone, indicating a likely mechanism conservation between mouse and human. This approach has the potential to reveal dynamic, high-resolution information about synaptic membrane trafficking in intact human brain slices.

What makes human cortical pyramidal neurons functionally complex

Humans exhibit unique cognitive abilities within the animal kingdom, but the neural mechanisms driving these advanced capabilities remain poorly understood. Human cortical neurons differ from those of other species, such as rodents, in both their morphological and physiological characteristics. Could the distinct properties of human cortical neurons help explain the superior cognitive capabilities of humans? Understanding this relationship requires a metric to quantify how neuronal properties contribute to the functional complexity of single neurons, yet no such standardized measure currently exists. Here, we propose the Functional Complexity Index (FCI), a generalized, deep learning-based framework to assess the input-output complexity of neurons. By comparing the FCI of cortical pyramidal neurons from different layers in rats and humans, we identified key morpho-electrical factors that underlie functional complexity. Human cortical pyramidal neurons were found to be significantly more functionally complex than their rat counterparts, primarily due to differences in dendritic membrane area and branching pattern, as well as density and nonlinearity of NMDA-mediated synaptic receptors. These findings reveal the structural-biophysical basis for the enhanced functional properties of human neurons.

Of mice and men: Dendritic architecture differentiates human from mice neuronal networks

The organizational principles that distinguish the human brain from other species have been a long-standing enigma in neuroscience. Focusing on the uniquely evolved human cortical layers 2 and 3, we computationally reconstruct the cortical architecture for mice and humans. We show that human pyramidal cells form highly complex networks, demonstrated by the increased number and simplex dimension compared to mice. This is surprising because human pyramidal cells are much sparser in the cortex. We show that the number and size of neurons fail to account for this increased network complexity, suggesting that another morphological property is a key determinant of network connectivity. Topological comparison of dendritic structure reveals much higher perisomatic (basal and oblique) branching density in human pyramidal cells. Using topological tools we quantitatively show that this neuronal structural property directly impacts network complexity, including the formation of a rich subnetwork structure. We conclude that greater dendritic complexity, a defining attribute of human L2 and 3 neurons, may provide the human cortex with enhanced computational capacity and cognitive flexibility.

Brain-like hardware, do we need it?

The brain's ability to perform efficient and fault-tolerant data processing is strongly related to its peculiar interconnected adaptive architecture, based on redundant neural circuits interacting at different scales. By emulating the brain's processing and learning mechanisms, computing technologies strive to achieve higher levels of energy efficiency and computational performance. Although efforts to address neuromorphic solutions through hardware based on top-down CMOS-based technologies have obtained interesting results in terms of energetic efficiency improvement, the replication of brain's self-assembled and redundant architectures is not considered in the roadmaps of data processing electronics. The exploration of solutions based on self-assembled elemental blocks to mimic biological networks' complexity is explored in the general frame of unconventional computing and it has not reached yet a maturity stage enabling a benchmark with standard electronic approaches in terms of performances, compatibility and scalability. Here we discuss some aspects related to advantages and disadvantages in the emulation of the brain for neuromorphic hardware. We also discuss possible directions in terms of hybrid hardware solutions where self-assembled substrates coexist and integrate with conventional electronics in view of neuromorphic architectures.

Single-Cell and Spatial Multi-Omics Analysis Reveal That Targeting JAG1 in Epithelial Cells Reduces Periodontal Inflammation and Alveolar Bone Loss

Mucosal immunity plays a critical role in the pathogenesis of inflammatory immune diseases. This study leverages single-cell RNA sequencing, spatial transcriptomics, and spatial proteomics to compare the cellular mechanisms involved in periodontitis between humans and mice, aiming to develop precise strategies to protect the gingival mucosal barrier. We identified key conserved and divergent features in cellular landscapes and transcriptional profiles across the two species, underscoring the complexity of inflammatory responses and immune dynamics in periodontitis. Additionally, we revealed a novel regulatory mechanism by which epithelial cells modulate macrophage behavior and inflammation through the JAG1-Notch pathway. Validation through animal experiments revealed that JAG1 inhibition reduces inflammation in epithelial cells, mitigating periodontitis. Our findings advance the understanding of periodontal disease pathogenesis and highlight the importance of integrating human and animal model data to develop treatments aligned with human physiology, offering potential therapeutic targets for controlling inflammation and enhancing tissue regeneration.

Renovating the Barnes maze for mouse models of Dementia with STARR FIELD: A 4-day protocol that probes learning rate, retention and cognitive flexibility

Land-based mazes that require spatial cues to identify the location of a hiding-place are a low-stress method to evaluate learning rate and memory retention in mice. One version, the Barnes maze, allows quantification of naturalistic exploratory behaviors not evident in water-based tasks. As the task relies on innate behaviors, it does not require overtraining, making it more feasible to examine early learning and non-memory executive functions that are characteristic of some non-amnestic dementias. However, because it is difficult to hide odor cues in the traditional version of the maze, learning rate during individual trials can be difficult to interpret. We designed and tested the use of 3D-printed escape shuttles that can be made in duplicate, as well as a docking tunnel that allows mice to self-exit the maze to improve reproducibility and limit experimenter influence. In combination with maze turning and escape tunnel caps, we show our shuttles mitigate the possibility of undesired cues. We then compare use of our 4-day protocol across several mouse models of cognitive impairment. We demonstrate an additional stage, the STARR protocol (Spatial Training and Rapid Reversal), to better challenge executive functions such as working memory and behavioral flexibility. We examine commonly used outcome measures across mice with and without access to spatial cues, as well as across mouse models of cognitive impairment to demonstrate the use of our 4-day protocol. Overall, this protocol provides detailed instructions to build and perform a robust spatial maze that can help expand the range of deficits identified. Our findings will aid in interpretation of traditional protocols, as well as provide an updated method to screen for both amnestic and non-amnestic cognitive changes.

A framework for translational therapy development in deep brain stimulation

Deep brain stimulation (DBS) is an established treatment for motor disorders like Parkinson's disease, but its mechanisms and effects on neurons and networks are not fully understood, limiting research-driven progress. This review presents a framework that combines neurophysiological insights and translational research to enhance DBS therapy, emphasizing biomarkers, device technology, and symptom-specific neuromodulation. It also examines the role of animal research in improving DBS, while acknowledging challenges in clinical translation.

Synchrony dynamics underlie irregular neocortical spiking

Cortical neurons are characterized by their variable spiking patterns. We challenge prevalent theories for the origin of spiking variability. We examine the specific hypothesis that cortical synchrony drives spiking variability in vivo . Using dynamic clamp, we demonstrate that intrinsic neuronal properties do not contribute substantially to spiking variability, but rather spiking variability emerges from weakly synchronous network drive. With large-scale electrophysiology we quantify the degree of synchrony and its time scale in cortical networks in vivo . We demonstrate that physiological levels of synchrony are sufficient to generate irregular responses found in vivo . Further, this synchrony shifts over timescales ranging from 25 to 200 ms, depending on the presence of external sensory input. Such shifts occur when the network moves from spontaneous to driven modes, leading naturally to a decline in response variability as observed across cortical areas. Finally, while individual neurons exhibit reliable responses to physiological drive, different neurons respond in a distinct fashion according to their intrinsic properties, contributing to stable synchrony across the neural network.

Multi-scale spiking network model of human cerebral cortex

Although the structure of cortical networks provides the necessary substrate for their neuronal activity, the structure alone does not suffice to understand the activity. Leveraging the increasing availability of human data, we developed a multi-scale, spiking network model of human cortex to investigate the relationship between structure and dynamics. In this model, each area in one hemisphere of the Desikan-Killiany parcellation is represented by a $1\,\mathrm{mm^{2}}$ column with a layered structure. The model aggregates data across multiple modalities, including electron microscopy, electrophysiology, morphological reconstructions, and diffusion tensor imaging, into a coherent framework. It predicts activity on all scales from the single-neuron spiking activity to the area-level functional connectivity. We compared the model activity with human electrophysiological data and human resting-state functional magnetic resonance imaging (fMRI) data. This comparison reveals that the model can reproduce aspects of both spiking statistics and fMRI correlations if the inter-areal connections are sufficiently strong. Furthermore, we study the propagation of a single-spike perturbation and macroscopic fluctuations through the network. The open-source model serves as an integrative platform for further refinements and future in silico studies of human cortical structure, dynamics, and function.

Neuronal wiring diagram of an adult brain

Connections between neurons can be mapped by acquiring and analysing electron microscopic brain images. In recent years, this approach has been applied to chunks of brains to reconstruct local connectivity maps that are highly informative1-6, but nevertheless inadequate for understanding brain function more globally. Here we present a neuronal wiring diagram of a whole brain containing 5 × 107 chemical synapses7 between 139,255 neurons reconstructed from an adult female Drosophila melanogaster8,9. The resource also incorporates annotations of cell classes and types, nerves, hemilineages and predictions of neurotransmitter identities10-12. Data products are available for download, programmatic access and interactive browsing and have been made interoperable with other fly data resources. We derive a projectome-a map of projections between regions-from the connectome and report on tracing of synaptic pathways and the analysis of information flow from inputs (sensory and ascending neurons) to outputs (motor, endocrine and descending neurons) across both hemispheres and between the central brain and the optic lobes. Tracing from a subset of photoreceptors to descending motor pathways illustrates how structure can uncover putative circuit mechanisms underlying sensorimotor behaviours. The technologies and open ecosystem reported here set the stage for future large-scale connectome projects in other species.

Unique Transcriptomic Cell Types of the Granular Retrosplenial Cortex are Preserved Across Mice and Rats Despite Dramatic Changes in Key Marker Genes

The granular retrosplenial cortex (RSG) supports key functions ranging from memory consolidation to spatial navigation. The mouse RSG contains several cell types that are remarkably distinct from those found in other cortical regions. This includes the physiologically and transcriptomically unique low rheobase neuron that is the dominant cell-type in RSG layers 2/3 (L2/3 LR), as well as the similarly exclusive pyramidal cells that comprise much of RSG layer 5a (L5a RSG). While the functions of the RSG are extensively studied in both mice and rats, it remains unknown if the transcriptomically unique cell types of the mouse RSG are evolutionarily conserved in rats. Here, we show that mouse and rat RSG not only contain the same cell types, but key subtypes including the L2/3 LR and L5a RSG neurons are amplified in their representations in rats compared to mice. This preservation of cell types in male and female rats happens despite dramatic changes in key cell-type-specific marker genes, with the Scnn1a expression that selectively tags mouse L5a RSG neurons completely absent in rats. Important for Cre-driver line development, we identify alternative, cross-species genes that can be used to selectively target the cell types of the RSG in both mice and rats. Our results show that the unique cell types of the RSG are evolutionarily conserved across millions of years of evolution between mice and rats, but also emphasize stark species-specific differences in marker genes that need to be considered when making cell-type-specific transgenic lines of mice versus rats.

NeoCoMM: A neocortical neuroinspired computational model for the reconstruction and simulation of epileptiform events

BACKGROUND

Understanding the pathophysiological dynamics that underline Interictal Epileptiform Events (IEEs) such as epileptic spikes, spike-and-waves or High-Frequency Oscillations (HFOs) is of major importance in the context of neocortical refractory epilepsy, as it paves the way for the development of novel therapies. Typically, these events are detected in Local Field Potential (LFP) recordings obtained through depth electrodes during pre-surgical investigations. Although essential, the underlying pathophysiological mechanisms for the generation of these epileptic neuromarkers remain unclear. The aim of this paper is to propose a novel neurophysiologically relevant reconstruction of the neocortical microcircuitry in the context of epilepsy. This reconstruction intends to facilitate the analysis of a comprehensive set of parameters encompassing physiological, morphological, and biophysical aspects that directly impact the generation and recording of different IEEs.

METHOD

a novel microscale computational model of an epileptic neocortical column was introduced. This model incorporates the intricate multilayered structure of the cortex and allows for the simulation of realistic interictal epileptic signals. The proposed model was validated through comparisons with real IEEs recorded using intracranial stereo-electroencephalography (SEEG) signals from both humans and animals. Using the model, the user can recreate epileptiform patterns observed in different species (human, rodent, and mouse) and study the intracellular activity associated with these patterns.

RESULTS

Our model allowed us to unravel the relationship between glutamatergic and GABAergic synaptic transmission of the epileptic neural network and the type of generated IEE. Moreover, sensitivity analyses allowed for the exploration of the pathophysiological parameters responsible for the transitions between these events. Finally, the presented modeling framework also provides an Electrode Tissue Model (ETI) that adds realism to the simulated signals and offers the possibility of studying their sensitivity to the electrode characteristics.

CONCLUSION

The model (NeoCoMM) presented in this work can be of great use in different applications since it offers an in silico framework for sensitivity analysis and hypothesis testing. It can also be used as a starting point for more complex studies.

Circuit dynamics of superficial and deep CA1 pyramidal cells and inhibitory cells in freely moving macaques

Diverse neuron classes in hippocampal CA1 have been identified through the heterogeneity of their cellular/molecular composition. How these classes relate to hippocampal function and the network dynamics that support cognition in primates remains unclear. Here, we report inhibitory functional cell groups in CA1 of freely moving macaques whose diverse response profiles to network states and each other suggest distinct and specific roles in the functional microcircuit of CA1. In addition, pyramidal cells that were grouped by their superficial or deep layer position differed in firing rate, burstiness, and sharp-wave ripple-associated firing. They also showed strata-specific spike-timing interactions with inhibitory cell groups, suggestive of segregated neural populations. Furthermore, ensemble recordings revealed that cell assemblies were preferentially organized according to these strata. These results suggest that hippocampal CA1 in freely moving macaques bears a sublayer-specific circuit organization that may shape its role in cognition.

Dimensionality reduction simplifies synaptic partner matching in an olfactory circuit

The distribution of postsynaptic partners in three-dimensional (3D) space presents complex choices for a navigating axon. Here, we discovered a dimensionality reduction principle in establishing the 3D glomerular map in the fly antennal lobe. Olfactory receptor neuron (ORN) axons first contact partner projection neuron (PN) dendrites at the 2D spherical surface of the antennal lobe during development, regardless of whether the adult glomeruli are at the surface or interior of the antennal lobe. Along the antennal lobe surface, axons of each ORN type take a specific 1D arc-shaped trajectory that precisely intersects with their partner PN dendrites. Altering axon trajectories compromises synaptic partner matching. Thus, a 3D search problem is reduced to 1D, which simplifies synaptic partner matching and may generalize to the wiring process of more complex brains.

Fast imaging of millimeter-scale areas with beam deflection transmission electron microscopy

Serial section transmission electron microscopy (TEM) has proven to be one of the leading methods for millimeter-scale 3D imaging of brain tissues at nanoscale resolution. It is important to further improve imaging efficiency to acquire larger and more brain volumes. We report here a threefold increase in the speed of TEM by using a beam deflecting mechanism to enable highly efficient acquisition of multiple image tiles (nine) for each motion of the mechanical stage. For millimeter-scale areas, the duty cycle of imaging doubles to more than 30%, yielding a net average imaging rate of 0.3 gigapixels per second. If fully utilized, an array of four beam deflection TEMs should be capable of imaging a dataset of cubic millimeter scale in five weeks.

Net synaptic drive of fast-spiking interneurons is inverted towards inhibition in human FCD I epilepsy

Focal cortical dysplasia type I (FCD I) is the most common cause of pharmaco-resistant epilepsy with the poorest prognosis. To understand the epileptogenic mechanisms of FCD I, we obtained tissue resected from patients with FCD I epilepsy, and from tumor patients as control. Using whole-cell patch clamp in acute human brain slices, we investigated the cellular properties of fast-spiking interneurons (FSINs) and pyramidal neurons (PNs) within the ictal onset zone. In FCD I epilepsy, FSINs exhibited lower firing rates from slower repolarization and action potential broadening, while PNs had increased firing. Importantly, excitatory synaptic drive of FSINs increased progressively with the scale of cortical activation as a general property across species, but this relationship was inverted towards net inhibition in FCD I epilepsy. Further comparison with intracranial electroencephalography (iEEG) from the same patients revealed that the spatial extent of pathological high-frequency oscillations (pHFO) was associated with synaptic events at FSINs.

The neuroanatomical organization of the hypothalamus is driven by spatial and topological efficiency

The hypothalamus in the mammalian brain is responsible for regulating functions associated with survival and reproduction representing a complex set of highly interconnected, yet anatomically and functionally distinct, sub-regions. It remains unclear what factors drive the spatial organization of sub-regions within the hypothalamus. One potential factor may be structural connectivity of the network that promotes efficient function with well-connected sub-regions placed closer together geometrically, i.e., the strongest axonal signal transferred through the shortest geometrical distance. To empirically test for such efficiency, we use hypothalamic data derived from the Allen Mouse Brain Connectivity Atlas, which provides a structural connectivity map of mouse brain regions derived from a series of viral tracing experiments. Using both cost function minimization and comparison with a weighted, sphere-packing ensemble, we demonstrate that the sum of the distances between hypothalamic sub-regions are not close to the minimum possible distance, consistent with prior whole brain studies. However, if such distances are weighted by the inverse of the magnitude of the connectivity, their sum is among the lowest possible values. Specifically, the hypothalamus appears within the top 94th percentile of neural efficiencies of randomly packed configurations and within one standard deviation of the median efficiency when packings are optimized for maximal neural efficiency. Our results, therefore, indicate that a combination of geometrical and topological constraints help govern the structure of the hypothalamus.

Flexible gating between subspaces in a neural network model of internally guided task switching

Behavioral flexibility relies on the brain's ability to switch rapidly between multiple tasks, even when the task rule is not explicitly cued but must be inferred through trial and error. The underlying neural circuit mechanism remains poorly understood. We investigated recurrent neural networks (RNNs) trained to perform an analog of the classic Wisconsin Card Sorting Test. The networks consist of two modules responsible for rule representation and sensorimotor mapping, respectively, where each module is comprised of a circuit with excitatory neurons and three major types of inhibitory neurons. We found that rule representation by self-sustained persistent activity across trials, error monitoring and gated sensorimotor mapping emerged from training. Systematic dissection of trained RNNs revealed a detailed circuit mechanism that is consistent across networks trained with different hyperparameters. The networks' dynamical trajectories for different rules resided in separate subspaces of population activity; the subspaces collapsed and performance was reduced to chance level when dendrite-targeting somatostatin-expressing interneurons were silenced, illustrating how a phenomenological description of representational subspaces is explained by a specific circuit mechanism.

Volume electron microscopy analysis of synapses in primary regions of the human cerebral cortex

Functional and structural studies investigating macroscopic connectivity in the human cerebral cortex suggest that high-order associative regions exhibit greater connectivity compared to primary ones. However, the synaptic organization of these brain regions remains unexplored. In the present work, we conducted volume electron microscopy to investigate the synaptic organization of the human brain obtained at autopsy. Specifically, we examined layer III of Brodmann areas 17, 3b, and 4, as representative areas of primary visual, somatosensorial, and motor cortex. Additionally, we conducted comparative analyses with our previous datasets of layer III from temporopolar and anterior cingulate associative cortical regions (Brodmann areas 24, 38, and 21). 9,690 synaptic junctions were 3D reconstructed, showing that certain synaptic characteristics are specific to particular regions. The number of synapses per volume, the proportion of the postsynaptic targets, and the synaptic size may distinguish one region from another, regardless of whether they are associative or primary cortex. By contrast, other synaptic characteristics were common to all analyzed regions, such as the proportion of excitatory and inhibitory synapses, their shapes, their spatial distribution, and a higher proportion of synapses located on dendritic spines. The present results provide further insights into the synaptic organization of the human cerebral cortex.

Modulation of large rhythmic depolarizations in human large basket cells by norepinephrine and acetylcholine

Rhythmic brain activity is critical to many brain functions and is sensitive to neuromodulation, but so far very few studies have investigated this activity on the cellular level in vitro in human brain tissue samples. This study reveals and characterizes a novel rhythmic network activity in the human neocortex. Using intracellular patch-clamp recordings of human cortical neurons, we identify large rhythmic depolarizations (LRDs) driven by glutamate release but not by GABA. These LRDs are intricate events made up of multiple depolarizing phases, occurring at ~0.3 Hz, have large amplitudes and long decay times. Unlike human tissue, rat neocortex layers 2/3 exhibit no such activity under identical conditions. LRDs are mainly observed in a subset of L2/3 interneurons that receive substantial excitatory inputs and are likely large basket cells based on their morphology. LRDs are highly sensitive to norepinephrine (NE) and acetylcholine (ACh), two neuromodulators that affect network dynamics. NE increases LRD frequency through β-adrenergic receptor activity while ACh decreases it via M4 muscarinic receptor activation. Multi-electrode array recordings show that NE enhances and synchronizes oscillatory network activity, whereas ACh causes desynchronization. Thus, NE and ACh distinctly modulate LRDs, exerting specific control over human neocortical activity.

Tracing nerve fibers with volume electron microscopy to quantitatively analyze brain connectivity

The highly complex structure of the brain requires an approach that can unravel its connectivity. Using volume electron microscopy and a dedicated software we can trace and measure all nerve fibers present within different samples of brain tissue. With this software tool, individual dendrites and axons are traced, obtaining a simplified "skeleton" of each fiber, which is linked to its corresponding synaptic contacts. The result is an intricate meshwork of axons and dendrites interconnected by a cloud of synaptic junctions. To test this methodology, we apply it to the stratum radiatum of the hippocampus and layers 1 and 3 of the somatosensory cortex of the mouse. We find that nerve fibers are densely packed in the neuropil, reaching up to 9 kilometers per cubic mm. We obtain the number of synapses, the number and lengths of dendrites and axons, the linear densities of synapses established by dendrites and axons, and their location on dendritic spines and shafts. The quantitative data obtained through this method enable us to identify subtle traits and differences in the synaptic organization of the samples, which might have been overlooked in a qualitative analysis.

Protocol to analyze 3D neurodegenerative vacuoles in Drosophila melanogaster

Vacuole formation is a key hallmark of age-dependent neurodegeneration in the Drosophila brain. Here, we present a protocol to analyze 3D neurodegenerative vacuoles in the whole-mount Drosophila melanogaster brain. We describe steps for whole-brain dissection, staining, 3D imaging, and z-stack image processing using Fiji ImageJ. We then detail procedures for annotating and 3D-reconstructing neurodegenerative vacuoles with WEBKNOSSOS and Python, and performing statistical analysis in Python. This protocol enables measurement of parameters such as the number and volume of each vacuole. For complete details on the use and execution of this protocol, please refer to Elguero et al.1.

Ultrastructural differences impact cilia shape and external exposure across cell classes in the visual cortex

A primary cilium is a membrane-bound extension from the cell surface that contains receptors for perceiving and transmitting signals that modulate cell state and activity. Primary cilia in the brain are less accessible than cilia on cultured cells or epithelial tissues because in the brain they protrude into a deep, dense network of glial and neuronal processes. Here, we investigated cilia frequency, internal structure, shape, and position in large, high-resolution transmission electron microscopy volumes of mouse primary visual cortex. Cilia extended from the cell bodies of nearly all excitatory and inhibitory neurons, astrocytes, and oligodendrocyte precursor cells (OPCs) but were absent from oligodendrocytes and microglia. Ultrastructural comparisons revealed that the base of the cilium and the microtubule organization differed between neurons and glia. Investigating cilia-proximal features revealed that many cilia were directly adjacent to synapses, suggesting that cilia are poised to encounter locally released signaling molecules. Our analysis indicated that synapse proximity is likely due to random encounters in the neuropil, with no evidence that cilia modulate synapse activity as would be expected in tetrapartite synapses. The observed cell class differences in proximity to synapses were largely due to differences in external cilia length. Many key structural features that differed between neuronal and glial cilia influenced both cilium placement and shape and, thus, exposure to processes and synapses outside the cilium. Together, the ultrastructure both within and around neuronal and glial cilia suggest differences in cilia formation and function across cell types in the brain.

A molecular and cellular perspective on human brain evolution and tempo

The evolution of the modern human brain was accompanied by distinct molecular and cellular specializations, which underpin our diverse cognitive abilities but also increase our susceptibility to neurological diseases. These features, some specific to humans and others shared with related species, manifest during different stages of brain development. In this multi-stage process, neural stem cells proliferate to produce a large and diverse progenitor pool, giving rise to excitatory or inhibitory neurons that integrate into circuits during further maturation. This process unfolds over varying time scales across species and has progressively become slower in the human lineage, with differences in tempo correlating with differences in brain size, cell number and diversity, and connectivity. Here we introduce the terms 'bradychrony' and 'tachycrony' to describe slowed and accelerated developmental tempos, respectively. We review how recent technical advances across disciplines, including advanced engineering of in vitro models, functional comparative genetics and high-throughput single-cell profiling, are leading to a deeper understanding of how specializations of the human brain arise during bradychronic neurodevelopment. Emerging insights point to a central role for genetics, gene-regulatory networks, cellular innovations and developmental tempo, which together contribute to the establishment of human specializations during various stages of neurodevelopment and at different points in evolution.

Diffusion-based deep learning method for augmenting ultrastructural imaging and volume electron microscopy

Electron microscopy (EM) revolutionized the way to visualize cellular ultrastructure. Volume EM (vEM) has further broadened its three-dimensional nanoscale imaging capacity. However, intrinsic trade-offs between imaging speed and quality of EM restrict the attainable imaging area and volume. Isotropic imaging with vEM for large biological volumes remains unachievable. Here, we developed EMDiffuse, a suite of algorithms designed to enhance EM and vEM capabilities, leveraging the cutting-edge image generation diffusion model. EMDiffuse generates realistic predictions with high resolution ultrastructural details and exhibits robust transferability by taking only one pair of images of 3 megapixels to fine-tune in denoising and super-resolution tasks. EMDiffuse also demonstrated proficiency in the isotropic vEM reconstruction task, generating isotropic volume even in the absence of isotropic training data. We demonstrated the robustness of EMDiffuse by generating isotropic volumes from seven public datasets obtained from different vEM techniques and instruments. The generated isotropic volume enables accurate three-dimensional nanoscale ultrastructure analysis. EMDiffuse also features self-assessment functionalities on predictions' reliability. We envision EMDiffuse to pave the way for investigations of the intricate subcellular nanoscale ultrastructure within large volumes of biological systems.

Layer 1 NDNF interneurons are specialized top-down master regulators of cortical circuits

Diverse types of inhibitory interneurons (INs) impart computational power and flexibility to neocortical circuits. Whereas markers for different IN types in cortical layers 2-6 (L2-L6) have been instrumental for generating a wealth of functional insights, only the recent identification of a selective marker (neuron-derived neurotrophic factor [NDNF]) has opened comparable opportunities for INs in L1 (L1INs). However, at present we know very little about the connectivity of NDNF L1INs with other IN types, their input-output conversion, and the existence of potential NDNF L1IN subtypes. Here, we report pervasive inhibition of L2/3 INs (including parvalbumin INs and vasoactive intestinal peptide INs) by NDNF L1INs. Intersectional genetics revealed similar physiology and connectivity in the NDNF L1IN subpopulation co-expressing neuropeptide Y. Finally, NDNF L1INs prominently and selectively engage in persistent firing, a physiological hallmark disconnecting their output from the current input. Collectively, our work therefore identifies NDNF L1INs as specialized master regulators of superficial neocortex according to their pervasive top-down afferents.