The pyramidal neuron of the cerebral cortex: morphological and chemical characteristics of the synaptic inputs

Serotonergic neuromodulation of synaptic plasticity

Synaptic plasticity constitutes a fundamental process in the reorganization of neural networks that underlie memory, cognition, emotional responses, and behavioral planning. At the core of this phenomenon lie Hebbian mechanisms, wherein frequent synaptic stimulation induces long-term potentiation (LTP), while less activation leads to long-term depression (LTD). The synaptic reorganization of neuronal networks is regulated by serotonin (5-HT), a neuromodulator capable of modify synaptic plasticity to appropriately respond to mental and behavioral states, such as alertness, attention, concentration, motivation, and mood. Lately, understanding the serotonergic Neuromodulation of synaptic plasticity has become imperative for unraveling its impact on cognitive, emotional, and behavioral functions. Through a comparative analysis across three main forebrain structures-the hippocampus, amygdala, and prefrontal cortex, this review discusses the actions of 5-HT on synaptic plasticity, offering insights into its role as a neuromodulator involved in emotional and cognitive functions. By distinguishing between plastic and metaplastic effects, we provide a comprehensive overview about the mechanisms of 5-HT neuromodulation of synaptic plasticity and associated functions across different brain regions.

Implications of altered pyramidal cell morphology on clinical symptoms of neurodevelopmental disorders

The prevalence of pyramidal cells (PCs) in the mammalian cerebral cortex underscore their value as they play a crucial role in various brain functions, ranging from cognition, sensory processing, to motor output. PC morphology significantly influences brain connectivity and plays a critical role in maintaining normal brain function. Pathological alterations to PC morphology are thought to contribute to the aetiology of neurodevelopmental disorders such as autism spectrum disorder (ASD) and schizophrenia. This review explores the relationship between abnormalities in PC morphology in key cortical areas and the clinical manifestations in schizophrenia and ASD. We focus largely on human postmortem studies and provide evidence that dendritic segment length, complexity and spine density are differentially affected in these disorders. These morphological alterations can lead to disruptions in cortical connectivity, potentially contributing to the cognitive and behavioural deficits observed in these disorders. Furthermore, we highlight the importance of investigating the functional and structural characteristics of PCs in these disorders to illuminate the underlying pathogenesis and stimulate further research in this area.

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.

The plasticity of pyramidal neurons in the behaving brain

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

Pre- and postsynaptic signatures in the prelimbic cortex associated with "alcohol use disorder" in the rat

The transition to alcohol use disorder (AUD) involves persistent neuroadaptations in executive control functions primarily regulated by the medial prefrontal cortex. However, the neurophysiological correlates to behavioral manifestations of AUD are not fully defined. The association between cortical neuroadaptations and behavioral manifestations of addiction was studied using a multi-symptomatic operant model based on the DSM-5 diagnostic criteria for AUD. This model aimed to characterize an AUD-vulnerable and AUD-resistant subpopulation of outbred male Wistar rats and was combined with electrophysiological measurements in the prelimbic cortex (PL). Mirroring clinical observations, rats exhibited individual variability in their vulnerability to develop AUD-like behavior, including motivation to seek for alcohol (crit 1), increased effort to obtain the substance (crit 2), and continued drinking despite negative consequences (crit 3). Only a small subset of rats met all the aforementioned AUD criteria (3 crit, AUD-vulnerable), while a larger fraction was considered AUD-resilient (0 crit). The development of AUD-like behavior was characterized by disruptions in glutamatergic synaptic activity, involving decreased frequency of spontaneous excitatory postsynaptic currents (sEPSCs) and heightened intrinsic excitability in layers 2/3 PL pyramidal neurons. These alterations were concomitant with a significant impairment in the ability of mGlu2/3 receptors to negatively regulate glutamate release in the PL but not in downstream regions like the basolateral amygdala or nucleus accumbens core. In conclusion alterations in PL synaptic activity were strongly associated with individual addiction scores, indicating their role as potential markers of the behavioral manifestations linked to AUD psychopathology.

Key morphological features of human pyramidal neurons

The basic building block of the cerebral cortex, the pyramidal cell, has been shown to be characterized by a markedly different dendritic structure among layers, cortical areas, and species. Functionally, differences in the structure of their dendrites and axons are critical in determining how neurons integrate information. However, within the human cortex, these neurons have not been quantified in detail. In the present work, we performed intracellular injections of Lucifer Yellow and 3D reconstructed over 200 pyramidal neurons, including apical and basal dendritic and local axonal arbors and dendritic spines, from human occipital primary visual area and associative temporal cortex. We found that human pyramidal neurons from temporal cortex were larger, displayed more complex apical and basal structural organization, and had more spines compared to those in primary sensory cortex. Moreover, these human neocortical neurons displayed specific shared and distinct characteristics in comparison to previously published human hippocampal pyramidal neurons. Additionally, we identified distinct morphological features in human neurons that set them apart from mouse neurons. Lastly, we observed certain consistent organizational patterns shared across species. This study emphasizes the existing diversity within pyramidal cell structures across different cortical areas and species, suggesting substantial species-specific variations in their computational properties.

Neuroanatomical frameworks for volitional control of breathing and orofacial behaviors

Breathing is the only vital function that can be volitionally controlled. However, a detailed understanding how volitional (cortical) motor commands can transform vital breathing activity into adaptive breathing patterns that accommodate orofacial behaviors such as swallowing, vocalization or sniffing remains to be developed. Recent neuroanatomical tract tracing studies have identified patterns and origins of descending forebrain projections that target brain nuclei involved in laryngeal adductor function which is critically involved in orofacial behavior. These nuclei include the midbrain periaqueductal gray and nuclei of the respiratory rhythm and pattern generating network in the brainstem, specifically including the pontine Kölliker-Fuse nucleus and the pre-Bötzinger complex in the medulla oblongata. This review discusses the functional implications of the forebrain-brainstem anatomical connectivity that could underlie the volitional control and coordination of orofacial behaviors with breathing.

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

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

Mechanistic stoichiometric relationship between the rates of neurotransmission and neuronal glucose oxidation: Reevaluation of and alternatives to the pseudo-malate-aspartate shuttle model

The ~1:1 stoichiometry between the rates of neuronal glucose oxidation (CMRglc-ox-N) and glutamate (Glu)/γ-aminobutyric acid (GABA)-glutamine (Gln) neurotransmitter (NT) cycling between neurons and astrocytes (VNTcycle) has been firmly established. However, the mechanistic basis for this relationship is not fully understood, and this knowledge is critical for the interpretation of metabolic and brain imaging studies in normal and diseased brain. The pseudo-malate-aspartate shuttle (pseudo-MAS) model established the requirement for glycolytic metabolism in cultured glutamatergic neurons to produce NADH that is shuttled into mitochondria to support conversion of extracellular Gln (i.e., astrocyte-derived Gln in vivo) into vesicular neurotransmitter Glu. The evaluation of this model revealed that it could explain half of the 1:1 stoichiometry and it has limitations. Modifications of the pseudo-MAS model were, therefore, devised to address major knowledge gaps, that is, submitochondrial glutaminase location, identities of mitochondrial carriers for Gln and other model components, alternative mechanisms to transaminate α-ketoglutarate to form Glu and shuttle glutamine-derived ammonia while maintaining mass balance. All modified models had a similar 0.5 to 1.0 predicted mechanistic stoichiometry between VNTcycle and the rate of glucose oxidation. Based on studies of brain β-hydroxybutyrate oxidation, about half of CMRglc-ox-N may be linked to glutamatergic neurotransmission and localized in pre-synaptic structures that use pseudo-MAS type mechanisms for Glu-Gln cycling. In contrast, neuronal compartments that do not participate in transmitter cycling may use the MAS to sustain glucose oxidation. The evaluation of subcellular compartmentation of neuronal glucose metabolism in vivo is a critically important topic for future studies to understand glutamatergic and GABAergic neurotransmission.

NEURD: automated proofreading and feature extraction for connectomics

We are now in the era of millimeter-scale electron microscopy (EM) volumes collected at nanometer resolution (Shapson-Coe et al., 2021; Consortium et al., 2021). Dense reconstruction of cellular compartments in these EM volumes has been enabled by recent advances in Machine Learning (ML) (Lee et al., 2017; Wu et al., 2021; Lu et al., 2021; Macrina et al., 2021). Automated segmentation methods can now yield exceptionally accurate reconstructions of cells, but despite this accuracy, laborious post-hoc proofreading is still required to generate large connectomes free of merge and split errors. The elaborate 3-D meshes of neurons produced by these segmentations contain detailed morphological information, from the diameter, shape, and branching patterns of axons and dendrites, down to the fine-scale structure of dendritic spines. However, extracting information about these features can require substantial effort to piece together existing tools into custom workflows. Building on existing open-source software for mesh manipulation, here we present "NEURD", a software package that decomposes each meshed neuron into a compact and extensively-annotated graph representation. With these feature-rich graphs, we implement workflows to automate a variety of tasks that would otherwise require extensive manual effort, such as state of the art automated post-hoc proofreading of merge errors, cell classification, spine detection, axon-dendritic proximities, and computation of other features. These features enable many downstream analyses of neural morphology and connectivity, making these new massive and complex datasets more accessible to neuroscience researchers focused on a variety of scientific questions.

Unambiguous identification of asymmetric and symmetric synapses using volume electron microscopy

The brain contains thousands of millions of synapses, exhibiting diverse structural, molecular, and functional characteristics. However, synapses can be classified into two primary morphological types: Gray's type I and type II, corresponding to Colonnier's asymmetric (AS) and symmetric (SS) synapses, respectively. AS and SS have a thick and thin postsynaptic density, respectively. In the cerebral cortex, since most AS are excitatory (glutamatergic), and SS are inhibitory (GABAergic), determining the distribution, size, density, and proportion of the two major cortical types of synapses is critical, not only to better understand synaptic organization in terms of connectivity, but also from a functional perspective. However, several technical challenges complicate the study of synapses. Potassium ferrocyanide has been utilized in recent volume electron microscope studies to enhance electron density in cellular membranes. However, identifying synaptic junctions, especially SS, becomes more challenging as the postsynaptic densities become thinner with increasing concentrations of potassium ferrocyanide. Here we describe a protocol employing Focused Ion Beam Milling and Scanning Electron Microscopy for studying brain tissue. The focus is on the unequivocal identification of AS and SS types. To validate SS observed using this protocol as GABAergic, experiments with immunocytochemistry for the vesicular GABA transporter were conducted on fixed mouse brain tissue sections. This material was processed with different concentrations of potassium ferrocyanide, aiming to determine its optimal concentration. We demonstrate that using a low concentration of potassium ferrocyanide (0.1%) improves membrane visualization while allowing unequivocal identification of synapses as AS or SS.

Data-driven multiscale computational models of cortical and subcortical regions

Data-driven computational models of neurons, synapses, microcircuits, and mesocircuits have become essential tools in modern brain research. The goal of these multiscale models is to integrate and synthesize information from different levels of brain organization, from cellular properties, dendritic excitability, and synaptic dynamics to microcircuits, mesocircuits, and ultimately behavior. This article surveys recent advances in the genesis of data-driven computational models of mammalian neural networks in cortical and subcortical areas. I discuss the challenges and opportunities in developing data-driven multiscale models, including the need for interdisciplinary collaborations, the importance of model validation and comparison, and the potential impact on basic and translational neuroscience research. Finally, I highlight future directions and emerging technologies that will enable more comprehensive and predictive data-driven models of brain function and dysfunction.

Ultrasound pulse repetition frequency preferentially activates different neuron populations independent of cell type

Transcranial ultrasound activates mechanosensitive cellular signaling and modulates neural dynamics. Given that intrinsic neuronal activity is limited to a couple hundred hertz and often exhibits frequency preference, we examined whether pulsing ultrasound at physiologic pulse repetition frequencies (PRFs) could selectively influence neuronal activity in the mammalian brain. We performed calcium imaging of individual motor cortex neurons, while delivering 0.35 MHz ultrasound at PRFs of 10, 40, and 140 Hz in awake mice. We found that most neurons were preferentially activated by only one of the three PRFs, highlighting unique cellular effects of physiologic PRFs. Further, ultrasound evoked responses were similar between excitatory neurons and parvalbumin positive interneurons regardless of PRFs, indicating that individual cell sensitivity dominates ultrasound-evoked effects, consistent with the heterogeneous mechanosensitive channel expression we found across single neurons in mice and humans. These results highlight the feasibility of tuning ultrasound neuromodulation effects through varying PRFs.

Heterosynaptic plasticity of the visuo-auditory projection requires cholecystokinin released from entorhinal cortex afferents

The entorhinal cortex is involved in establishing enduring visuo-auditory associative memory in the neocortex. Here we explored the mechanisms underlying this synaptic plasticity related to projections from the visual and entorhinal cortices to the auditory cortex in mice using optogenetics of dual pathways. High-frequency laser stimulation (HFS laser) of the visuo-auditory projection did not induce long-term potentiation. However, after pairing with sound stimulus, the visuo-auditory inputs were potentiated following either infusion of cholecystokinin (CCK) or HFS laser of the entorhino-auditory CCK-expressing projection. Combining retrograde tracing and RNAscope in situ hybridization, we show that Cck expression is higher in entorhinal cortex neurons projecting to the auditory cortex than in those originating from the visual cortex. In the presence of CCK, potentiation in the neocortex occurred when the presynaptic input arrived 200 ms before postsynaptic firing, even after just five trials of pairing. Behaviorally, inactivation of the CCK+ projection from the entorhinal cortex to the auditory cortex blocked the formation of visuo-auditory associative memory. Our results indicate that neocortical visuo-auditory association is formed through heterosynaptic plasticity, which depends on release of CCK in the neocortex mostly from entorhinal afferents.

Neural circuits for the adaptive regulation of fear and extinction memory

The regulation of fear memories is critical for adaptive behaviors and dysregulation of these processes is implicated in trauma- and stress-related disorders. Treatments for these disorders include pharmacological interventions as well as exposure-based therapies, which rely upon extinction learning. Considerable attention has been directed toward elucidating the neural mechanisms underlying fear and extinction learning. In this review, we will discuss historic discoveries and emerging evidence on the neural mechanisms of the adaptive regulation of fear and extinction memories. We will focus on neural circuits regulating the acquisition and extinction of Pavlovian fear conditioning in rodent models, particularly the role of the medial prefrontal cortex and hippocampus in the contextual control of extinguished fear memories. We will also consider new work revealing an important role for the thalamic nucleus reuniens in the modulation of prefrontal-hippocampal interactions in extinction learning and memory. Finally, we will explore the effects of stress on this circuit and the clinical implications of these findings.

Excitatory subtypes of the lateral amygdala neurons are differentially involved in regulation of synaptic plasticity and excitation/inhibition balance in aversive learning in mice

The amygdala plays a crucial role in aversive learning. In Pavlovian fear conditioning, sensory information about an emotionally neutral conditioned stimulus (CS) and an innately aversive unconditioned stimulus is associated with the lateral amygdala (LA), and the CS acquires the ability to elicit conditioned responses. Aversive learning induces synaptic plasticity in LA excitatory neurons from CS pathways, such as the medial geniculate nucleus (MGN) of the thalamus. Although LA excitatory cells have traditionally been classified based on their firing patterns, the relationship between the subtypes and functional properties remains largely unknown. In this study, we classified excitatory cells into two subtypes based on whether the after-depolarized potential (ADP) amplitude is expressed in non-ADP cells and ADP cells. Their electrophysiological properties were significantly different. We examined subtype-specific synaptic plasticity in the MGN-LA pathway following aversive learning using optogenetics and found significant experience-dependent plasticity in feed-forward inhibitory responses in fear-conditioned mice compared with control mice. Following aversive learning, the inhibition/excitation (I/E) balance in ADP cells drastically changed, whereas that in non-ADP cells tended to change in the reverse direction. These results suggest that the two LA subtypes are differentially regulated in relation to synaptic plasticity and I/E balance during aversive learning.

Sialyltransferase Mutations Alter the Expression of Calcium-Binding Interneurons in Mice Neocortex, Hippocampus and Striatum

Gangliosides are major glycans on vertebrate nerve cells, and their metabolic disruption results in congenital disorders with marked cognitive and motor deficits. The sialyltransferase gene St3gal2 is responsible for terminal sialylation of two prominent brain gangliosides in mammals, GD1a and GT1b. In this study, we analyzed the expression of calcium-binding interneurons in primary sensory (somatic, visual, and auditory) and motor areas of the neocortex, hippocampus, and striatum of St3gal2-null mice as well as St3gal3-null and St3gal2/3-double null. Immunohistochemistry with highly specific primary antibodies for GABA, parvalbumin, calretinin, and calbindin were used for interneuron detection. St3gal2-null mice had decreased expression of all three analyzed types of calcium-binding interneurons in all analyzed regions of the neocortex. These results implicate gangliosides GD1a and GT1b in the process of interneuron migration and maturation.

Modeling apical and basal tree contribution to orientation selectivity in a mouse primary visual cortex layer 2/3 pyramidal cell

Pyramidal neurons, a mainstay of cortical regions, receive a plethora of inputs from various areas onto their morphologically distinct apical and basal trees. Both trees differentially contribute to the somatic response, defining distinct anatomical and possibly functional sub-units. To elucidate the contribution of each tree to the encoding of visual stimuli at the somatic level, we modeled the response pattern of a mouse L2/3 V1 pyramidal neuron to orientation tuned synaptic input. Towards this goal, we used a morphologically detailed computational model of a single cell that replicates electrophysiological and two-photon imaging data. Our simulations predict a synergistic effect of apical and basal trees on somatic action potential generation: basal tree activity, in the form of either depolarization or dendritic spiking, is necessary for producing somatic activity, despite the fact that most somatic spikes are heavily driven by apical dendritic spikes. This model provides evidence for synergistic computations taking place in the basal and apical trees of the L2/3 V1 neuron along with mechanistic explanations for tree-specific contributions and emphasizes the potential role of predictive and attentional feedback input in these cells.

STED microscopy reveals dendrite-specificity of spines in turtle cortex

Dendritic spines are key structures for neural communication, learning and memory. Spine size and shape probably reflect synaptic strength and learning. Imaging with superresolution STED microscopy the detailed shape of the majority of the spines of individual neurons in turtle cortex (Trachemys scripta elegans) revealed several distinguishable shape classes. Dendritic spines of a given class were not distributed randomly, but rather decorated significantly more often some dendrites than others. The individuality of dendrites was corroborated by significant inter-dendrite differences in other parameters such as spine density and length. In addition, many spines were branched or possessed spinules. These findings may have implications for the role of individual dendrites in this cortex.

Layer 1 of somatosensory cortex: an important site for input to a tiny cortical compartment

Neocortical layer 1 has been proposed to be at the center for top-down and bottom-up integration. It is a locus for interactions between long-range inputs, layer 1 interneurons, and apical tuft dendrites of pyramidal neurons. While input to layer 1 has been studied intensively, the level and effect of input to this layer has still not been completely characterized. Here we examined the input to layer 1 of mouse somatosensory cortex with retrograde tracing and optogenetics. Our assays reveal that local input to layer 1 is predominantly from layers 2/3 and 5 pyramidal neurons and interneurons, and that subtypes of local layers 5 and 6b neurons project to layer 1 with different probabilities. Long-range input from sensory-motor cortices to layer 1 of somatosensory cortex arose predominantly from layers 2/3 neurons. Our optogenetic experiments showed that intra-telencephalic layer 5 pyramidal neurons drive layer 1 interneurons but have no effect locally on layer 5 apical tuft dendrites. Dual retrograde tracing revealed that a fraction of local and long-range neurons was both presynaptic to layer 5 neurons and projected to layer 1. Our work highlights the prominent role of local inputs to layer 1 and shows the potential for complex interactions between long-range and local inputs, which are both in position to modify the output of somatosensory cortex.

Neurocomputational modeling of speech motor development

This review describes a computational approach for modeling the development of speech motor control in infants. We address the development of two levels of control: articulation of individual speech sounds (defined here as phonemes, syllables, or words for which there is an optimized motor program) and production of sound sequences such as phrases or sentences. We describe the DIVA model of speech motor control and its application to the problem of learning individual sounds in the infant's native language. Then we describe the GODIVA model, an extension of DIVA, and how chunking of frequently produced phoneme sequences is implemented within it.

Structural Organization of Perisomatic Inhibition in the Mouse Medial Prefrontal Cortex

Perisomatic inhibition profoundly controls neural function. However, the structural organization of inhibitory circuits giving rise to the perisomatic inhibition in the higher-order cortices is not completely known. Here, we performed a comprehensive analysis of those GABAergic cells in the medial prefrontal cortex (mPFC) that provide inputs onto the somata and proximal dendrites of pyramidal neurons. Our results show that most GABAergic axonal varicosities contacting the perisomatic region of superficial (layer 2/3) and deep (layer 5) pyramidal cells express parvalbumin (PV) or cannabinoid receptor type 1 (CB1). Further, we found that the ratio of PV/CB1 GABAergic inputs is larger on the somatic membrane surface of pyramidal tract neurons in comparison with those projecting to the contralateral hemisphere. Our morphologic analysis of in vitro labeled PV+ basket cells (PVBC) and CCK/CB1+ basket cells (CCKBC) revealed differences in many features. PVBC dendrites and axons arborized preferentially within the layer where their soma was located. In contrast, the axons of CCKBCs expanded throughout layers, although their dendrites were found preferentially either in superficial or deep layers. Finally, using anterograde trans-synaptic tracing we observed that PVBCs are preferentially innervated by thalamic and basal amygdala afferents in layers 5a and 5b, respectively. Thus, our results suggest that PVBCs can control the local circuit operation in a layer-specific manner via their characteristic arborization, whereas CCKBCs rather provide cross-layer inhibition in the mPFC.SIGNIFICANCE STATEMENT Inhibitory cells in cortical circuits are crucial for the precise control of local network activity. Nevertheless, in higher-order cortical areas that are involved in cognitive functions like decision-making, working memory, and cognitive flexibility, the structural organization of inhibitory cell circuits is not completely understood. In this study we show that perisomatic inhibitory control of excitatory cells in the medial prefrontal cortex is performed by two types of basket cells endowed with different morphologic properties that provide inhibitory inputs with distinct layer specificity on cells projecting to disparate areas. Revealing this difference in innervation strategy of the two basket cell types is a key step toward understanding how they fulfill their distinct roles in cortical network operations.

3D synaptic organization of layer III of the human anterior cingulate and temporopolar cortex

The human anterior cingulate and temporopolar cortices have been proposed as highly connected nodes involved in high-order cognitive functions, but their synaptic organization is still basically unknown due to the difficulties involved in studying the human brain. Using Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM) to study the synaptic organization of the human brain obtained with a short post-mortem delay allows excellent results to be obtained. We have used this technology to analyze layer III of the anterior cingulate cortex (Brodmann area 24) and the temporopolar cortex, including the temporal pole (Brodmann area 38 ventral and dorsal) and anterior middle temporal gyrus (Brodmann area 21). Our results, based on 6695 synaptic junctions fully reconstructed in 3D, revealed that Brodmann areas 24, 21 and ventral area 38 showed similar synaptic density and synaptic size, whereas dorsal area 38 displayed the highest synaptic density and the smallest synaptic size. However, the proportion of the different types of synapses (excitatory and inhibitory), the postsynaptic targets, and the shapes of excitatory and inhibitory synapses were similar, regardless of the region examined. These observations indicate that certain aspects of the synaptic organization are rather homogeneous, whereas others show specific variations across cortical regions.

Strength of Excitatory Inputs to Layer 3 Pyramidal Neurons During Synaptic Pruning in the Monkey Prefrontal Cortex: Relevance for the Pathogenesis of Schizophrenia

BACKGROUND

In schizophrenia, layer 3 pyramidal neurons (L3PNs) of the dorsolateral prefrontal cortex exhibit deficits in markers of excitatory synaptic inputs that are thought to disrupt the patterns of neural network activity essential for cognitive function. These deficits are usually interpreted under Irwin Feinberg's hypothesis of altered synaptic pruning, which postulates that normal periadolescent pruning, thought to preferentially eliminate weak/immature synapses, is altered in schizophrenia. However, it remains unknown whether periadolescent pruning on L3PNs in the primate dorsolateral prefrontal cortex selectively eliminates weak excitatory synapses or uniformly eliminates excitatory synapses across the full distribution of synaptic strengths.

METHODS

To distinguish between these alternative models of synaptic pruning, we assessed the densities of dendritic spines, the site of most excitatory inputs to L3PNs, and the distributions of excitatory synaptic strengths in dorsolateral prefrontal cortex L3PNs from male and female monkeys across the periadolescent period of synaptic pruning. We used patch-clamp methods in acute brain slices to record miniature excitatory synaptic currents and intracellular filling with biocytin to quantify dendritic spines.

RESULTS

On L3PNs, dendritic spines exhibited the expected age-related decline in density, but mean synaptic strength and the shape of synaptic strength distributions remained stable with age.

CONCLUSIONS

The absence of age-related differences in mean synaptic strength and synaptic strength distributions supports the model of a uniform pattern of synaptic pruning across the full range of synaptic strengths. The implications of these findings for the pathogenesis and functional consequences of dendritic spine deficits in schizophrenia are discussed.

Parvalbumin - Positive Neurons in the Neocortex: A Review

The calcium binding protein parvalbumin (PV) in the mammalian neocortex is expressed in a subpopulation of cortical GABAergic inhibitory interneurons. PV - producing interneurons represent the largest subpopulation of neocortical inhibitory cells, exhibit mutual chemical and electrical synaptic contacts and are well known to generate gamma oscillation. This review summarizes basic data of the distribution, afferent and efferent connections and physiological properties of parvalbumin expressing neurons in the neocortex. Basic data about participation of PV-positive neurons in cortical microcircuits are presented. Autaptic connections, metabolism and perineuronal nets (PNN) of PV positive neurons are also discussed.

Distinctive properties of biological neural networks and recent advances in bottom-up approaches toward a better biologically plausible neural network

Although it may appear infeasible and impractical, building artificial intelligence (AI) using a bottom-up approach based on the understanding of neuroscience is straightforward. The lack of a generalized governing principle for biological neural networks (BNNs) forces us to address this problem by converting piecemeal information on the diverse features of neurons, synapses, and neural circuits into AI. In this review, we described recent attempts to build a biologically plausible neural network by following neuroscientifically similar strategies of neural network optimization or by implanting the outcome of the optimization, such as the properties of single computational units and the characteristics of the network architecture. In addition, we proposed a formalism of the relationship between the set of objectives that neural networks attempt to achieve, and neural network classes categorized by how closely their architectural features resemble those of BNN. This formalism is expected to define the potential roles of top-down and bottom-up approaches for building a biologically plausible neural network and offer a map helping the navigation of the gap between neuroscience and AI engineering.

Chronic H3R activation reduces L-Dopa-induced dyskinesia, normalizes cortical GABA and glutamate levels, and increases striatal dopamine D1R mRNA expression in 6-hydroxydopamine-lesioned male rats

RATIONALE

Dyskinesias induced by L-3,4-dihydroxyphenylalanine, L-Dopa (LIDs), are the major complication in the pharmacological treatment of Parkinson's disease. LIDs induce overactivity of the glutamatergic cortico-striatal projections, and drugs that reduce glutamatergic overactivity exert antidyskinetic actions. Chronic administration of immepip, agonist at histamine H₃ receptors (H₃R), reduces LIDs and diminishes GABA and glutamate content in striatal dialysates (Avila-Luna et al., Psychopharmacology 236: 1937-1948, 2019).

OBJECTIVES AND METHODS

In rats unilaterally lesioned with 6-hydroxydopamine in the substantia nigra pars compacta (SNc), we examined whether the chronic administration of immepip and their withdrawal modify LIDs, the effect of L-Dopa on glutamate and GABA content, and mRNA levels of dopamine D₁ receptors (D₁Rs) and H₃Rs in the cerebral cortex and striatum.

RESULTS

The administration of L-Dopa for 21 days induced LIDs. This effect was accompanied by increased GABA and glutamate levels in the cerebral cortex ipsi and contralateral to the lesioned SNc, and immepip administration prevented (GABA) or reduced (glutamate) these actions. In the striatum, GABA content increased in the ipsilateral nucleus, an effect prevented by immepip. L-Dopa administration had no significant effects on striatal glutamate levels. In lesioned and L-Dopa-treated animals, D₁R mRNA decreased in the ipsilateral striatum, an effect prevented by immepip administration.

CONCLUSIONS

Our results indicate that chronic H₃R activation reduces LIDs and the overactivity of glutamatergic cortico-striatal projections, providing further evidence for an interaction between D₁Rs and H₃Rs in the cortex and striatum under normal and pathological conditions.

Mechanisms regulating the properties of inhibition-based gamma oscillations in primate prefrontal and parietal cortices

In primates, the dorsolateral prefrontal (DLPFC) and posterior parietal (PPC) cortices are key nodes in the working memory network. The working memory-related gamma oscillations induced in these areas, predominantly in layer 3, exhibit higher frequency in DLPFC. Although these regional differences in oscillation frequency are likely essential for information transfer between DLPFC and PPC, the mechanisms underlying these differences remain poorly understood. We investigated, in rhesus monkey, the DLPFC and PPC layer 3 pyramidal neuron (L3PN) properties that might regulate oscillation frequency and assessed the effects of these properties simulating oscillations in computational models. We found that GABAAR-mediated synaptic inhibition synchronizes L3PNs in both areas, but analysis of GABAAR mRNA levels and inhibitory synaptic currents suggested similar mechanisms of inhibition-mediated synchrony in DLPFC and PPC. Basal dendrite spine density and AMPAR/NMDAR mRNA levels were higher in DLPFC L3PNs, whereas excitatory synaptic currents were similar between areas. Therefore, synaptically evoked excitation might be stronger in DLPFC L3PNs due to a greater quantity of synapses in basal dendrites, a main target of recurrent excitation. Simulations in computational networks showed that oscillation frequency and power increased with increasing recurrent excitation, suggesting a mechanism by which the DLPFC–PPC differences in oscillation properties are generated.

Direct activation of microglia by β-glucosylceramide causes phagocytosis of neurons that exacerbates Gaucher disease

Gaucher disease (GD) is the most common lysosomal storage disease caused by recessive mutations in the degrading enzyme of β-glucosylceramide (β-GlcCer). However, it remains unclear how β-GlcCer causes severe neuronopathic symptoms, which are not fully treated by current therapies. We herein found that β-GlcCer accumulating in GD activated microglia through macrophage-inducible C-type lectin (Mincle) to induce phagocytosis of living neurons, which exacerbated Gaucher symptoms. This process was augmented by tumor necrosis factor (TNF) secreted from activated microglia that sensitized neurons for phagocytosis. This characteristic pathology was also observed in human neuronopathic GD. Blockade of these pathways in mice with a combination of FDA-approved drugs, minocycline (microglia activation inhibitor) and etanercept (TNF blocker), effectively protected neurons and ameliorated neuronopathic symptoms. In this study, we propose that limiting unrestrained microglia activation using drug repurposing provides a quickly applicable therapeutic option for fatal neuronopathic GD.

Morphological changes of large layer V pyramidal neurons in cortical motor-related areas after spinal cord injury in macaque monkeys

In primates, neurons giving rise to the corticospinal tract (CST) are distributed in several motor-related areas of the frontal lobe, such as the primary motor cortex (M1), the supplementary motor area (SMA), and the dorsal and ventral divisions of the premotor cortex (PMd, PMv). Recently, we have shown in macaque monkeys that the morphology of basal dendrites of CST neurons, i.e., large layer V pyramidal neurons, varies among the digit regions of the motor-related areas. Here, we investigated the alterations in basal dendrite morphology of CST neurons after spinal cord injury (SCI). In our monkey model, both the complexity and the spine density of basal dendrites were highly decreased throughout the areas. Notably, these events were less prominent for the PMd than for the M1, SMA, and PMv. In analyzing the density changes post-SCI of the filopodia-, thin-, stubby-, and mushroom-type spines, it was found that the density of filopodia-type spines was increased for all areas, whereas the other types of spines exhibited density decreases. Such spine density reductions were so limited for the PMd as compared to the other areas. The observed plastic changes of CST neurons may contribute to the recovery from impaired motor functions caused by SCI.

Angular gyrus: an anatomical case study for association cortex

The angular gyrus is associated with a spectrum of higher order cognitive functions. This mini-review undertakes a broad survey of putative neuroanatomical substrates, guided by the premise that area-specific specializations derive from a combination of extrinsic connections and intrinsic area properties. Three levels of spatial resolution are discussed: cellular, supracellular connectivity, and synaptic micro-scale, with examples necessarily drawn mainly from experimental work with nonhuman primates. A significant factor in the functional specialization of the human parietal cortex is the pronounced enlargement. In addition to "more" cells, synapses, and connections, however, the heterogeneity itself can be considered an important property. Multiple anatomical features support the idea of overlapping and temporally dynamic membership in several brain wide subnetworks, but how these features operate in the context of higher cognitive functions remains for continued investigations.

Axonal transport deficits in neuropsychiatric disorders

Axonal transport is a major cellular process that mediates bidirectional signaling between the soma and synapse, enabling both intracellular and intercellular communications. Cellular materials, such as proteins, RNAs, and organelles, are transported by molecular motor proteins along cytoskeletal highways in a highly regulated manner. Several studies have demonstrated that axonal transport is central to normal neuronal function, plasticity, and memory storage. Importantly, disruptions in axonal transport result in neuronal dysfunction and are associated with several neurodegenerative disorders. However, we do not know much about axonal transport deficits in neuropsychiatric disorders. Here, we briefly discuss our current understanding of the role of axonal transport in schizophrenia, bipolar and autism.

Functional network antagonism and consciousness

Spontaneous brain activity changes across states of consciousness. A particular consciousness-mediated configuration is the anticorrelations between the default mode network and other brain regions. What this antagonistic organization implies about consciousness to date remains inconclusive. In this Perspective Article, we propose that anticorrelations are the physiological expression of the concept of segregation, namely the brain's capacity to show selectivity in the way areas will be functionally connected. We postulate that this effect is mediated by the process of neural inhibition, by regulating global and local inhibitory activity. While recognizing that this effect can also result from other mechanisms, neural inhibition helps the understanding of how network metastability is affected after disrupting local and global neural balance. In combination with relevant theories of consciousness, we suggest that anticorrelations are a physiological prior that can work as a marker of preserved consciousness. We predict that if the brain is not in a state to host anticorrelations, then most likely the individual does not entertain subjective experience. We believe that this link between anticorrelations and the underlying physiology will help not only to comprehend how consciousness happens, but also conceptualize effective interventions for treating consciousness disorders in which anticorrelations seem particularly affected.

Computational models reveal how chloride dynamics determine the optimal distribution of inhibitory synapses to minimise dendritic excitability

Many neurons in the mammalian central nervous system have complex dendritic arborisations and active dendritic conductances that enable these cells to perform sophisticated computations. How dendritically targeted inhibition affects local dendritic excitability is not fully understood. Here we use computational models of branched dendrites to investigate where GABAergic synapses should be placed to minimise dendritic excitability over time. To do so, we formulate a metric we term the “Inhibitory Level” (IL), which quantifies the effectiveness of synaptic inhibition for reducing the depolarising effect of nearby excitatory input. GABAergic synaptic inhibition is dependent on the reversal potential for GABA_A receptors (EGABA), which is primarily set by the transmembrane chloride ion (Cl^-) concentration gradient. We, therefore, investigated how variable EGABA and dynamic chloride affects dendritic inhibition. We found that the inhibitory effectiveness of dendritic GABAergic synapses combines at an encircled branch junction. The extent of this inhibitory accumulation is dependent on the number of branches and location of synapses but is independent of EGABA. This inhibitory accumulation occurs even for very distally placed inhibitory synapses when they are hyperpolarising–but not when they are shunting. When accounting for Cl^- fluxes and dynamics in Cl^- concentration, we observed that Cl^- loading is detrimental to inhibitory effectiveness. This enabled us to determine the most inhibitory distribution of GABAergic synapses which is close to–but not at–a shared branch junction. This distribution balances a trade-off between a stronger combined inhibitory influence when synapses closely encircle a branch junction with the deleterious effects of increased Cl^- by loading that occurs when inhibitory synapses are co-located.

Dendritic branches allow for a rich repertoire of computational capabilities for neurons within the brain. Inhibitory synaptic inputs, which utilise the neurotransmitter GABA, refine and enhance dendritic computations. They are traditionally viewed with regards to their inhibitory effect on action potential generation at the neuronal cell body. Here, we studied the local effects of inhibitory synapses on excitability in dendrites. We also considered the dynamic nature of inhibition that deteriorates the longer it is active due to intracellular chloride ion loading. The central goal of our investigation was to find the best locations for multiple inhibitory synapses to maximise their combined inhibitory effectiveness on nearby excitation in the dendritic tree. We found that the optimal distribution is when inhibitory synapses closely encircle a branch junction, without being co-located at the junction itself. This maximises how their inhibitory influence combines whilst minimising the deleterious effects of chloride loading.

Quantitative analysis of the GABAergic innervation of the soma and axon initial segment of pyramidal cells in the human and mouse neocortex

Perisomatic GABAergic innervation in the cerebral cortex is carried out mostly by basket and chandelier cells, which differentially participate in the control of pyramidal cell action potential output and synchronization. These cells establish multiple synapses with the cell body (and proximal dendrites) and the axon initial segment (AIS) of pyramidal neurons, respectively. Using multiple immunofluorescence, confocal microscopy and 3D quantification techniques, we have estimated the number and density of GABAergic boutons on the cell body and AIS of pyramidal neurons located through cortical layers of the human and mouse neocortex. The results revealed, in both species, that there is clear variability across layers regarding the density and number of perisomatic GABAergic boutons. We found a positive linear correlation between the surface area of the soma, or the AIS, and the number of GABAergic terminals in apposition to these 2 neuronal domains. Furthermore, the density of perisomatic GABAergic boutons was higher in the human cortex than in the mouse. These results suggest a selectivity for the GABAergic innervation of the cell body and AIS that might be related to the different functional attributes of the microcircuits in which neurons from different layers are involved in both human and mouse.

Synaptic spinules are reliable indicators of excitatory presynaptic bouton size and strength and are ubiquitous components of excitatory synapses in CA1 hippocampus

Synaptic spinules are thin, finger-like projections from one neuron that become embedded within the presynaptic or postsynaptic compartments of another neuron. While spinules are conserved features of synapses across the animal kingdom, their specific function(s) remain unknown. Recent focused ion beam scanning electron microscopy (FIB-SEM) image volume analyses have demonstrated that spinules are embedded within ∼25% of excitatory boutons in primary visual cortex, yet the diversity of spinule sizes, origins, and ultrastructural relationships to their boutons remained unclear. To begin to uncover the function of synaptic spinules, we sought to determine the abundance, origins, and 3D ultrastructure of spinules within excitatory presynaptic spinule-bearing boutons (SBBs) in mammalian CA1 hippocampus and compare them with presynaptic boutons bereft of spinules (non-SBBs). Accordingly, we performed a comprehensive 3D analysis of every excitatory presynaptic bouton, their embedded spinules, and postsynaptic densities, within a 5 nm isotropic FIB-SEM image volume from CA1 hippocampus of an adult male rat. Surprisingly, we found that ∼74% of excitatory presynaptic boutons in this volume contained at least one spinule, suggesting they are fundamental components of excitatory synapses in CA1. In addition, we found that SBBs are 2.5-times larger and have 60% larger postsynaptic densities (PSDs) than non-SBBs. Moreover, synaptic spinules within SBBs are clearly differentiated into two groups: small clathrin-coated spinules, and 29-times larger spinules without clathrin. Together, these findings suggest that the presence of a spinule is a marker for stronger and more stable presynaptic boutons in CA1, and that synaptic spinules serve at least two separable and distinct functions.

Multi-Stimuli-Responsive Synapse Based on Vertical van der Waals Heterostructures

Brain-inspired intelligent systems demand diverse neuromorphic devices beyond simple functionalities. Merging biomimetic sensing with weight-updating capabilities in artificial synaptic devices represents one of the key research focuses. Here, we report a multiresponsive synapse device that integrates synaptic and optical-sensing functions. The device adopts vertically stacked graphene/h-BN/WSe₂ heterostructures, including an ultrahigh-mobility readout layer, a weight-control layer, and a dual-stimuli-responsive layer. The unique structure endows synapse devices with excellent synaptic plasticity, short response time (3 μs), and excellent optical responsivity (10⁵ A/W). To demonstrate the application in neuromorphic computing, handwritten digit recognition was simulated based on an unsupervised spiking neural network (SNN) with a precision of 90.89%, well comparable with the state-of-the-art results. Furthermore, multiterminal neuromorphic devices are demonstrated to mimic dendritic integration and photoswitching logic. Different from other synaptic devices, the research work validates multifunctional integration in synaptic devices, supporting the potential fusion of sensing and self-learning in neuromorphic networks.

Topological Sholl descriptors for neuronal clustering and classification

Neuronal morphology is a fundamental factor influencing information processing within neurons and networks. Dendritic morphology in particular can widely vary among cell classes, brain regions, and animal species. Thus, accurate quantitative descriptions allowing classification of large sets of neurons is essential for their structural and functional characterization. Current robust and unbiased computational methods that characterize groups of neurons are scarce. In this work, we introduce a novel technique to study dendritic morphology, complementing and advancing many of the existing techniques. Our approach is to conceptualize the notion of a Sholl descriptor and associate, for each morphological feature, and to each neuron, a function of the radial distance from the soma, taking values in a metric space. Functional distances give rise to pseudo-metrics on sets of neurons which are then used to perform the two distinct tasks of clustering and classification. To illustrate the use of Sholl descriptors, four datasets were retrieved from the large public repository https://neuromorpho.org/ comprising neuronal reconstructions from different species and brain regions. Sholl descriptors were subsequently computed, and standard clustering methods enhanced with detection and metric learning algorithms were then used to objectively cluster and classify each dataset. Importantly, our descriptors outperformed conventional morphometric techniques (L-Measure metrics) in several of the tested datasets. Therefore, we offer a novel and effective approach to the analysis of diverse neuronal cell types, and provide a toolkit for researchers to cluster and classify neurons.

Looking for the origins of axons

Pyramidal neurons with axons that exit from dendrites rather than the cell body itself are relatively common in non-primates, but rare in monkeys and humans.

Computational Concepts for Reconstructing and Simulating Brain Tissue

It has previously been shown that it is possible to derive a new class of biophysically detailed brain tissue models when one computationally analyzes and exploits the interdependencies or the multi-modal and multi-scale organization of the brain. These reconstructions, sometimes referred to as digital twins, enable a spectrum of scientific investigations. Building such models has become possible because of increase in quantitative data but also advances in computational capabilities, algorithmic and methodological innovations. This chapter presents the computational science concepts that provide the foundation to the data-driven approach to reconstructing and simulating brain tissue as developed by the EPFL Blue Brain Project, which was originally applied to neocortical microcircuitry and extended to other brain regions. Accordingly, the chapter covers aspects such as a knowledge graph-based data organization and the importance of the concept of a dataset release. We illustrate algorithmic advances in finding suitable parameters for electrical models of neurons or how spatial constraints can be exploited for predicting synaptic connections. Furthermore, we explain how in silico experimentation with such models necessitates specific addressing schemes or requires strategies for an efficient simulation. The entire data-driven approach relies on the systematic validation of the model. We conclude by discussing complementary strategies that not only enable judging the fidelity of the model but also form the basis for its systematic refinements.

Emerging insights into synapse dysregulation in Alzheimer's disease

Alzheimer's disease is the leading cause of dementia and a growing worldwide problem, with its incidence expected to increase in the coming years. Since synapse loss is a major pathology and is correlated with symptoms in Alzheimer's disease, synapse dysfunction and loss may underlie pathophysiology. In this context, this review focuses on emerging insights into synaptic changes at the ultrastructural level. The three-dimensional electron microscopy technique unequivocally detects all types of synapses, including multi-synapses, which are indicators of synaptic connectivity between neurons. In recent years it has become feasible to perform sophisticated three-dimensional electron microscopy analyses on post-mortem human Alzheimer's disease brain as tissue preservation and electron microscopy techniques have improved. This ultrastructural analysis found that synapse loss does not always precede neuronal loss, as long believed. For instance, in the transentorhinal cortex and area CA1 of the hippocampus, synapse loss does not precede neuronal loss. However, in the entorhinal cortex, synapse loss precedes neuronal loss. Moreover, the ultrastructural analysis provides details about synapse morphology. For example, changes in excitatory synapses' post-synaptic densities, with fragmented postsynaptic densities increasing at the expense of perforated synapses, are seen in Alzheimer's disease brain. Further, multi-synapses also appear to be altered in Alzheimer's disease by doubling the abundance of multi-innervated spines in the transentorhinal cortex of Alzheimer's disease brain. Collectively, these recent ultrastructural analyses highlight distinct synaptic phenotypes in different Alzheimer's disease brain regions and broaden the understanding of synapse alterations, which may unravel some new therapeutic targets.

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

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

Abnormalities in Cortical GABAergic Interneurons of the Primary Motor Cortex Caused by Lis1 (Pafah1b1) Mutation Produce a Non-drastic Functional Phenotype

LIS1 (PAFAH1B1) plays a major role in the developing cerebral cortex, and haploinsufficient mutations cause human lissencephaly type 1. We have studied morphological and functional properties of the cerebral cortex of mutant mice harboring a deletion in the first exon of the mouse Lis1 (Pafah1b1) gene, which encodes for the LisH domain. The Lis1/sLis1 animals had an overall unaltered cortical structure but showed an abnormal distribution of cortical GABAergic interneurons (those expressing calbindin, calretinin, or parvalbumin), which mainly accumulated in the deep neocortical layers. Interestingly, the study of the oscillatory activity revealed an apparent inability of the cortical circuits to produce correct activity patterns. Moreover, the fast spiking (FS) inhibitory GABAergic interneurons exhibited several abnormalities regarding the size of the action potentials, the threshold for spike firing, the time course of the action potential after-hyperpolarization (AHP), the firing frequency, and the frequency and peak amplitude of spontaneous excitatory postsynaptic currents (sEPSC’s). These morphological and functional alterations in the cortical inhibitory system characterize the Lis1/sLis1 mouse as a model of mild lissencephaly, showing a phenotype less drastic than the typical phenotype attributed to classical lissencephaly. Therefore, the results described in the present manuscript corroborate the idea that mutations in some regions of the Lis1 gene can produce phenotypes more similar to those typically described in schizophrenic and autistic patients and animal models.

A Deep Learning-Based Workflow for Dendritic Spine Segmentation

The morphological analysis of dendritic spines is an important challenge for the neuroscientific community. Most state-of-the-art techniques rely on user-supervised algorithms to segment the spine surface, especially those designed for light microscopy images. Therefore, processing large dendritic branches is costly and time-consuming. Although deep learning (DL) models have become one of the most commonly used tools in image segmentation, they have not yet been successfully applied to this problem. In this article, we study the feasibility of using DL models to automatize spine segmentation from confocal microscopy images. Supervised learning is the most frequently used method for training DL models. This approach requires large data sets of high-quality segmented images (ground truth). As mentioned above, the segmentation of microscopy images is time-consuming and, therefore, in most cases, neuroanatomists only reconstruct relevant branches of the stack. Additionally, some parts of the dendritic shaft and spines are not segmented due to dyeing problems. In the context of this research, we tested the most successful architectures in the DL biomedical segmentation field. To build the ground truth, we used a large and high-quality data set, according to standards in the field. Nevertheless, this data set is not sufficient to train convolutional neural networks for accurate reconstructions. Therefore, we implemented an automatic preprocessing step and several training strategies to deal with the problems mentioned above. As shown by our results, our system produces a high-quality segmentation in most cases. Finally, we integrated several postprocessing user-supervised algorithms in a graphical user interface application to correct any possible artifacts.

An estimation of the absolute number of axons indicates that human cortical areas are sparsely connected

The tracts between cortical areas are conceived as playing a central role in cortical information processing, but their actual numbers have never been determined in humans. Here, we estimate the absolute number of axons linking cortical areas from a whole-cortex diffusion MRI (dMRI) connectome, calibrated using the histologically measured callosal fiber density. Median connectivity is estimated as approximately 6,200 axons between cortical areas within hemisphere and approximately 1,300 axons interhemispherically, with axons connecting functionally related areas surprisingly sparse. For example, we estimate that <5% of the axons in the trunk of the arcuate and superior longitudinal fasciculi connect Wernicke's and Broca's areas. These results suggest that detailed information is transmitted between cortical areas either via linkage of the dense local connections or via rare, extraordinarily privileged long-range connections.

Looking at Developmental Neurotoxicity Testing from the Perspective of an Invertebrate Embryo

Developmental neurotoxicity (DNT) of chemical compounds disrupts the formation of a normal brain. There is impressive progress in the development of alternative testing methods for DNT potential in chemicals, some of which also incorporate invertebrate animals. This review briefly touches upon studies on the genetically tractable model organisms of Caenorhabditis elegans and Drosophila melanogaster about the action of specific developmental neurotoxicants. The formation of a functional nervous system requires precisely timed axonal pathfinding to the correct cellular targets. To address this complex key event, our lab developed an alternative assay using a serum-free culture of intact locust embryos. The first neural pathways in the leg of embryonic locusts are established by a pair of afferent pioneer neurons which use guidance cues from membrane-bound and diffusible semaphorin proteins. In a systematic approach according to recommendations for alternative testing, the embryo assay quantifies defects in pioneer navigation after exposure to a panel of recognized test compounds for DNT. The outcome indicates a high predictability for test-compound classification. Since the pyramidal neurons of the mammalian cortex also use a semaphorin gradient for neurite guidance, the assay is based on evolutionary conserved cellular mechanisms, supporting its relevance for cortical development.

Prefrontal Cortical Control of Anxiety: Recent Advances

Dysfunction in the prefrontal cortex is commonly implicated in anxiety disorders, but the mechanisms remain unclear. Approach-avoidance conflict tasks have been extensively used in animal research to better understand how changes in neural activity within the prefrontal cortex contribute to avoidance behaviors, which are believed to play a major role in the maintenance of anxiety disorders. In this article, we first review studies utilizing in vivo electrophysiology to reveal the relationship between changes in neural activity and avoidance behavior in rodents. We then review recent studies that take advantage of optical and genetic techniques to test the unique contribution of specific prefrontal cortex circuits and cell types to the control of anxiety-related avoidance behaviors. This new body of work reveals that behavior during approach-avoidance conflict is dynamically modulated by individual cell types, distinct neural pathways, and specific oscillatory frequencies. The integration of these different pathways, particularly as mediated by interactions between excitatory and inhibitory neurons, represents an exciting opportunity for the future of understanding anxiety.

Mechanisms underlying dorsolateral prefrontal cortex contributions to cognitive dysfunction in schizophrenia

Kraepelin, in his early descriptions of schizophrenia (SZ), characterized the illness as having "an orchestra without a conductor." Kraepelin further speculated that this "conductor" was situated in the frontal lobes. Findings from multiple studies over the following decades have clearly implicated pathology of the dorsolateral prefrontal cortex (DLPFC) as playing a central role in the pathophysiology of SZ, particularly with regard to key cognitive features such as deficits in working memory and cognitive control. Following an overview of the cognitive mechanisms associated with DLPFC function and how they are altered in SZ, we review evidence from an array of neuroscientific approaches addressing how these cognitive impairments may reflect the underlying pathophysiology of the illness. Specifically, we present evidence suggesting that alterations of the DLPFC in SZ are evident across a range of spatial and temporal resolutions: from its cellular and molecular architecture, to its gross structural and functional integrity, and from millisecond to longer timescales. We then present an integrative model based upon how microscale changes in neuronal signaling in the DLPFC can influence synchronized patterns of neural activity to produce macrocircuit-level alterations in DLPFC activation that ultimately influence cognition and behavior. We conclude with a discussion of initial efforts aimed at targeting DLPFC function in SZ, the clinical implications of those efforts, and potential avenues for future development.

Analysis of P2X7-Induced Neuronal Branching

P2X7 receptors regulate different aspects of neuronal development, including neurogenesis, dendritic outgrowth, and axonal elongation. Primary neuronal culture is a widely used model system in neuroscience as it enables to study molecular and cellular events caused by the activation of different ion channels, receptors, and transporters under controlled conditions. Primary neuronal cultures derived from normal and genetically modified mouse models can be used with a wide array of molecular biological, anatomical, and functional techniques such as RNA sequencing, western blots, immunostaining, Ca²⁺ imaging, and electrophysiology. In addition, they can also be genetically manipulated relatively easily. Moreover, cells can survive for multiple weeks if they are properly maintained and thus the development and maturation of individual neurons and their morphological properties can be studied under different conditions. Here, we present a protocol for the isolation and culturing of primary hippocampal cells from embryonic mouse hippocampal tissue (embryonic days 17.5-18.5). The neurons are plated in poly-L-lysine/laminin coated coverslips, where astroglia proliferation is controlled for the proper study of individual primary neurons. To investigate the development of dendrites and axons, as a good correlate of neuron morphology, we present a transfection protocol, which allows us to fill the whole neuron with a fluorescent protein. Subsequently, we perform tracing and analysis of dendritic branching by Sholl analysis using Neurolucida tracing Software (MBF Bioscience).

The Developmental Changes in Intrinsic and Synaptic Properties of Prefrontal Neurons Enhance Local Network Activity from the Second to the Third Postnatal Weeks in Mice

The prefrontal cortex (PFC) is characterized by protracted maturation. The cellular mechanisms controlling the early development of prefrontal circuits are still largely unknown. Our study delineates the developmental cellular processes in the mouse medial PFC (mPFC) during the second and the third postnatal weeks and characterizes their contribution to the changes in network activity. We show that spontaneous inhibitory postsynaptic currents (sIPSC) are increased, whereas spontaneous excitatory postsynaptic currents (sEPSC) are reduced from the second to the third postnatal week. Drug application suggested that the increased sEPSC frequency in mPFC at postnatal day 10 (P10) is due to depolarizing γ-aminobutyric acid (GABA) type A receptor function. To further validate this, perforated patch-clamp recordings were obtained and the expression levels of K-Cl cotransporter 2 (KCC2) protein were examined. The reversal potential of IPSCs in response to current stimulation was significantly more depolarized at P10 than P20 while KCC2 expression is decreased. Moreover, the number of parvalbumin-expressing GABAergic interneurons increases and their intrinsic electrophysiological properties significantly mature in the mPFC from P10 to P20. Using computational modeling, we show that the developmental changes in synaptic and intrinsic properties of mPFC neurons contribute to the enhanced network activity in the juvenile compared with neonatal mPFC.