Axo-axonic synapses: Diversity in neural circuit function

Role of Neural Circuits in Cognitive Impairment

Cognitive impairment refers to abnormalities in learning, memory and cognitive judgment, mainly manifested as symptoms such as decreased memory, impaired orientation and reduced computational ability. As the fundamental unit of information processing in the brain, neural circuits have recently attracted great attention due to their functions in regulating pain, emotion and behavior. Furthermore, a growing number of studies have suggested that neural circuits play an important role in cognitive impairment. Neural circuits can affect perception, attention and decision-making, they can also regulate language skill, thinking and memory. Pathological conditions crucially affecting the integrity and preservation of neural circuits and their connectivity will heavily impact cognitive abilities. Nowadays, technological developments have led to many novel methods for studying neural circuits, such as brain imaging, optogenetic techniques, and chemical genetics approaches. Therefore, neural circuits show great promise as a potential target in mitigating cognitive impairment. In this review we discuss the pathogenesis of cognitive impairment and the regulation and detection of neural circuits, thus highlighting the role of neural circuits in cognitive impairment. Hence, therapeutic agents against cognitive impairment may be developed that target neural circuits important in cognition.

A Concept-Value Network as a Brain Model

This paper suggests a statistical framework for describing the relations between the physical and conceptual entities of a brain-like model. Features and concept instances are put into context, where the paper suggests that features may be the electrical wiring; although, chemical connections are also possible. With this idea, the actual length of the connection is important, because it is related to firing rates and neuron synchronization, but the signal type is less important. The paper then suggests that concepts are neuron groups that link feature sets and concept instances are determined by chemical signals from those groups. Therefore, features become the static horizontal framework of the neural system and concepts are vertically interconnected combinations of these. With regards to functionality, the neuron is then considered to be functional, and the more horizontal memory structures can even be glial. This would also suggest that features can be distributed entities and not concentrated to a single area. Another aspect could be signal 'breaks' that compartmentalise a pattern and may help with neural binding.

Distinct 5-HT receptor subtypes regulate claustrum excitability by serotonin and the psychedelic, DOI

Recent evidence indicates that neuronal activity within the claustrum (CLA) may be central to cellular and behavioral responses to psychedelic hallucinogens. The CLA prominently innervates many cortical targets and displays exceptionally high levels of serotonin (5-HT) binding. However, the influence of serotonin receptors, prime targets of psychedelic drug action, on CLA activity remains unexplored. We characterize the CLA expression of all known 5-HT subtypes and contrast the effects of 5-HT and the psychedelic hallucinogen, 2,5-dimethoxy-4-iodoamphetamine (DOI), on excitability of cortical-projecting CLA neurons. We find that the CLA is particularly enriched with 5-HT2C receptors, expressed predominantly on glutamatergic neurons. Electrophysiological recordings from CLA neurons that project to the anterior cingulate cortex (ACC) indicate that application of 5-HT inhibits glutamate receptor-mediated excitatory postsynaptic currents (EPSCs). In contrast, application of DOI stimulates EPSCs. We find that the opposite effects of 5-HT and DOI on synaptic signaling can both be reversed by inhibition of the 5-HT2C, but not 5-HT2A, receptors. We identify specific 5-HT receptor subtypes as serotonergic regulators of the CLA excitability and argue against the canonical role of 5-HT2A in glutamatergic synapse response to psychedelics within the CLA-ACC circuit.

Activity-Dependent Remodeling of Corticostriatal Axonal Boutons During Motor Learning

Motor skill learning induces long-lasting synaptic plasticity at not only the inputs, such as dendritic spines1-4, but also at the outputs to the striatum of motor cortical neurons5,6. However, very little is known about the activity and structural plasticity of corticostriatal axons during learning in the adult brain. Here, we used longitudinal in vivo two-photon imaging to monitor the activity and structure of thousands of corticostriatal axonal boutons in the dorsolateral striatum in awake mice. We found that learning a new motor skill induces dynamic regulation of axonal boutons. The activities of motor corticostriatal axonal boutons exhibited selectivity for rewarded movements (RM) and un-rewarded movements (UM). Strikingly, boutons on the same axonal branches showed diverse responses during behavior. Motor learning significantly increased the fraction of RM boutons and reduced the heterogeneity of bouton activities. Moreover, motor learning-induced profound structural dynamism in boutons. By combining structural and functional imaging, we identified that newly formed axonal boutons are more likely to exhibit selectivity for RM and are stabilized during motor learning, while UM boutons are selectively eliminated. Our results highlight a novel form of plasticity at corticostriatal axons induced by motor learning, indicating that motor corticostriatal axonal boutons undergo dynamic reorganization that facilitates the acquisition and execution of motor skills.

Organization of an ascending circuit that conveys flight motor state in Drosophila

Natural behaviors are a coordinated symphony of motor acts that drive reafferent (self-induced) sensory activation. Individual sensors cannot disambiguate exafferent (externally induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to carry out adaptive behaviors through corollary discharge circuits (CDCs), which provide predictive motor signals from motor pathways to sensory processing and other motor pathways. Yet, how CDCs comprehensively integrate into the nervous system remains unexplored. Here, we use connectomics, neuroanatomical, physiological, and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs) in Drosophila, which function as a predictive CDC in other insects. Both AHN pairs receive input primarily from a partially overlapping population of descending neurons, especially from DNg02, which controls wing motor output. Using Ca2+ imaging and behavioral recordings, we show that AHN activation is correlated to flight behavior and precedes wing motion. Optogenetic activation of DNg02 is sufficient to activate AHNs, indicating that AHNs are activated by descending commands in advance of behavior and not as a consequence of sensory input. Downstream, each AHN pair targets predominantly non-overlapping networks, including those that process visual, auditory, and mechanosensory information, as well as networks controlling wing, haltere, and leg sensorimotor control. These results support the conclusion that the AHNs provide a predictive motor signal about wing motor state to mostly non-overlapping sensory and motor networks. Future work will determine how AHN signaling is driven by other descending neurons and interpreted by AHN downstream targets to maintain adaptive sensorimotor performance.

Mechanosensitive enteric neurons in the guinea pig gastric fundus and antrum

BACKGROUND

Coping with the ingested food, the gastric regions of fundus, corpus, and antrum display different motility patterns. Intrinsic components of such patterns involving mechanosensitive enteric neurons (MEN) have been described in the guinea pig gastric corpus but are poorly understood in the fundus and antrum.

METHODS

To elucidate mechanosensitive properties of myenteric neurons in the gastric fundus and antrum, membrane potential imaging using Di-8-ANEPPS was applied. A small-volume injection led to neuronal compression. We analyzed the number of MEN and their firing frequency in addition to the involvement of selected mechanoreceptors. To characterize the neurochemical phenotype of MEN, we performed immunohistochemistry.

KEY RESULTS

In the gastric fundus, 16% of the neurons reproducibly responded to mechanical stimulation and thus were MEN. Of those, 83% were cholinergic and 19% nitrergic. In the antrum, 6% of the neurons responded to the compression stimulus, equally distributed among cholinergic and nitrergic MEN. Defunctionalizing the sensory extrinsic afferents led to a significant drop in the number of MEN in both regions.

CONCLUSION

We provided evidence for MEN in the gastric fundus and antrum and further investigated mechanoreceptors. However, the proportions of the chemical phenotypes of the MEN differed significantly between both regions. Further investigations of synaptic connections of MEN are crucial to understand the hardwired neuronal circuits in the stomach.

Attentional effects on local V1 microcircuits explain selective V1-V4 communication

Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modelled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing.

Distinctive features of the central synaptic organization of Drosophila larval proprioceptors

Proprioceptive feedback is critically needed for locomotor control, but how this information is incorporated into central proprioceptive processing circuits remains poorly understood. Circuit organization emerges from the spatial distribution of synaptic connections between neurons. This distribution is difficult to discern in model systems where only a few cells can be probed simultaneously. Therefore, we turned to a relatively simple and accessible nervous system to ask: how are proprioceptors' input and output synapses organized in space, and what principles underlie this organization? Using the Drosophila larval connectome, we generated a map of the input and output synapses of 34 proprioceptors in several adjacent body segments (5-6 left-right pairs per segment). We characterized the spatial organization of these synapses, and compared this organization to that of other somatosensory neurons' synapses. We found three distinguishing features of larval proprioceptor synapses: (1) Generally, individual proprioceptor types display segmental somatotopy. (2) Proprioceptor output synapses both converge and diverge in space; they are organized into six spatial domains, each containing a unique set of one or more proprioceptors. Proprioceptors form output synapses along the proximal axonal entry pathway into the neuropil. (3) Proprioceptors receive few inhibitory input synapses. Further, we find that these three features do not apply to other larval somatosensory neurons. Thus, we have generated the most comprehensive map to date of how proprioceptor synapses are centrally organized. This map documents previously undescribed features of proprioceptors, raises questions about underlying developmental mechanisms, and has implications for downstream proprioceptive processing circuits.

Organization of an Ascending Circuit that Conveys Flight Motor State

Natural behaviors are a coordinated symphony of motor acts which drive self-induced or reafferent sensory activation. Single sensors only signal presence and magnitude of a sensory cue; they cannot disambiguate exafferent (externally-induced) from reafferent sources. Nevertheless, animals readily differentiate between these sources of sensory signals to make appropriate decisions and initiate adaptive behavioral outcomes. This is mediated by predictive motor signaling mechanisms, which emanate from motor control pathways to sensory processing pathways, but how predictive motor signaling circuits function at the cellular and synaptic level is poorly understood. We use a variety of techniques, including connectomics from both male and female electron microscopy volumes, transcriptomics, neuroanatomical, physiological and behavioral approaches to resolve the network architecture of two pairs of ascending histaminergic neurons (AHNs), which putatively provide predictive motor signals to several sensory and motor neuropil. Both AHN pairs receive input primarily from an overlapping population of descending neurons, many of which drive wing motor output. The two AHN pairs target almost exclusively non-overlapping downstream neural networks including those that process visual, auditory and mechanosensory information as well as networks coordinating wing, haltere, and leg motor output. These results support the conclusion that the AHN pairs multi-task, integrating a large amount of common input, then tile their output in the brain, providing predictive motor signals to non-overlapping sensory networks affecting motor control both directly and indirectly.

The connectome of an insect brain

Brains contain networks of interconnected neurons and so knowing the network architecture is essential for understanding brain function. We therefore mapped the synaptic-resolution connectome of an entire insect brain (Drosophila larva) with rich behavior, including learning, value computation, and action selection, comprising 3016 neurons and 548,000 synapses. We characterized neuron types, hubs, feedforward and feedback pathways, as well as cross-hemisphere and brain-nerve cord interactions. We found pervasive multisensory and interhemispheric integration, highly recurrent architecture, abundant feedback from descending neurons, and multiple novel circuit motifs. The brain's most recurrent circuits comprised the input and output neurons of the learning center. Some structural features, including multilayer shortcuts and nested recurrent loops, resembled state-of-the-art deep learning architectures. The identified brain architecture provides a basis for future experimental and theoretical studies of neural circuits.

Deep learning-based synapse counting and synaptic ultrastructure analysis of electron microscopy images

BACKGROUND

Synapses are the connections between neurons in the central nervous system (CNS) or between neurons and other excitable cells in the peripheral nervous system (PNS), where electrical or chemical signals rapidly travel through one cell to another with high spatial precision. Synaptic analysis, based on synapse numbers and fine morphology, is the basis for understanding neurological functions and diseases. Manual analysis of synaptic structures in electron microscopy (EM) images is often limited by low efficiency and subjective bias.

NEW METHOD

We developed a multifunctional synaptic analysis system based on several advanced deep learning (DL) models. The system achieved synapse counting in low-magnification EM images and synaptic ultrastructure analysis in high-magnification EM images.

RESULTS

The synapse counting system based on ResNet18 and a Faster R-CNN model had a mean average precision (mAP) of 92.55%. For synaptic ultrastructure analysis, the Faster R-CNN model based on ResNet50 achieved a mAP of 91.60%, the DeepLab v3 + model based on ResNet50 enabled high performance in presynaptic and postsynaptic membrane segmentation with a global accuracy of 0.9811, and the Faster R-CNN model based on ResNet18 achieved a mAP of 91.41% for synaptic vesicle detection.

CONCLUSIONS

The proposed multifunctional synaptic analysis system may help to overcome the experimental bias inherent in manual analysis, thereby facilitating EM image-based synaptic function studies.

Leucine-rich repeats containing 4 protein (LRRC4) in memory, psychoneurosis, and glioblastoma

ABSTRACT

Leucine-rich repeats containing 4 ( LRRC4 , also named netrin-G ligand 2 [NGL-2]) is a member of the NetrinGs ligands (NGLs) family. As a gene with relatively high and specific expression in brain, it is a member of the leucine-rich repeat superfamily and has been proven to be a suppressor gene for gliomas, thus being involved in gliomagenesis. LRRC4 is the core of microRNA-dependent multi-phase regulatory loops that inhibit the proliferation and invasion of glioblastoma (GB) cells, including LRRC4/NGL2-activator protein 2 (AP2)-microRNA (miR) 182-LRRC4 and LRRC4-miR185-DNA methyltransferase 1 (DNMT1)-LRRC4/specific protein 1 (SP1)-DNMT1-LRRC4. In this review, we demonstrated LRRC4 as a new member of the partitioning-defective protein (PAR) polarity complex that promotes axon differentiation, mediates the formation and plasticity of synapses, and assists information input to the hippocampus and storage of memory. As an important synapse regulator, aberrant expression of LRRC4 has been detected in autism, spinal injury and GBs. LRRC4 is a candidate susceptibility gene for autism and a neuro-protective factor in spinal nerve damage. In GBs, LRRC4 is a novel inhibitor of autophagy, and an inhibitor of protein-protein interactions involving in temozolomide resistance, tumor immune microenvironment, and formation of circular RNA.

Dynamic proteomic and phosphoproteomic atlas of corticostriatal axons in neurodevelopment

Mammalian axonal development begins in embryonic stages and continues postnatally. After birth, axonal proteomic landscape changes rapidly, coordinated by transcription, protein turnover, and post-translational modifications. Comprehensive profiling of axonal proteomes across neurodevelopment is limited, with most studies lacking cell-type and neural circuit specificity, resulting in substantial information loss. We create a Cre-dependent APEX2 reporter mouse line and map cell-type-specific proteome of corticostriatal projections across postnatal development. We synthesize analysis frameworks to define temporal patterns of axonal proteome and phosphoproteome, identifying co-regulated proteins and phosphorylations associated with genetic risk for human brain disorders. We discover proline-directed kinases as major developmental regulators. APEX2 transgenic reporter proximity labeling offers flexible strategies for subcellular proteomics with cell type specificity in early neurodevelopment, a critical period for neuropsychiatric disease.

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.

Dopamine and Dopamine-Related Ligands Can Bind Not Only to Dopamine Receptors

The dopaminergic system is one of the most important neurotransmitter systems in the central nervous system (CNS). It acts mainly by activation of the D₁-like receptor family at the target cell. Additionally, fine-tuning of the signal is achieved via pre-synaptic modulation by the D₂-like receptor family. Some dopamine drugs (both agonists and antagonists) bind in addition to DRs also to α₂-ARs and 5-HT receptors. Unfortunately, these compounds are often considered subtype(s) specific. Thus, it is important to consider the presence of these receptor subtypes in specific CNS areas as the function virtually elicited by one receptor type could be an effect of other—or the co-effect of multiple receptors. However, there are enough molecules with adequate specificity. In this review, we want to give an overview of the most common off-targets for established dopamine receptor ligands. To give an overall picture, we included a discussion on subtype selectivity. Molecules used as antipsychotic drugs are reviewed too. Therefore, we will summarize reported affinities and give an outline of molecules sufficiently specific for one or more subtypes (i.e., for subfamily), the presence of DR, α₂-ARs, and 5-HT receptors in CNS areas, which could help avoid ambiguous results.

Molecular self-avoidance in synaptic neurexin complexes

Synapses are thought to be organized by interactions of presynaptic neurexins with postsynaptic ligands, particularly with neuroligins and cerebellins. However, when a neuron forms adjacent pre- and postsynaptic specializations, as in dendrodendritic or axo-axonic synapses, nonfunctional cis neurexin/ligand interactions would be energetically favored. Here, we reveal an organizational principle for preventing synaptic cis interactions (“self-avoidance”). Using dendrodendritic synapses between mitral and granule cells in the olfactory bulb as a paradigm, we show that, owing to its higher binding affinity, cerebellin-1 blocks the cis interaction of neurexins with neuroligins, thereby enabling trans neurexin/neuroligin interaction. In mitral cells, ablating either cerebellin-1 or neuroligins severely impaired granule cell➔mitral cell synapses, as did overexpression of wild-type neurexins but not of mutant neurexins unable to bind to neuroligins. Our data uncover a molecular interaction network that organizes the self-avoidance of nonfunctional neurexin/ligand cis interactions, thus allowing assembly of physiological trans interactions.

Perigenual and Subgenual Anterior Cingulate Afferents Converge on Common Pyramidal Cells in Amygdala Subregions of the Macaque

The subgenual (sgACC) and perigenual (pgACC) anterior cingulate are important afferents of the amygdala, with different cytoarchitecture, connectivity, and function. The sgACC is associated with arousal mechanisms linked to salient cues, whereas the pgACC is engaged in conflict decision-making, including in social contexts. After placing same-size, small volume tracer injections into sgACC and pgACC of the same hemisphere in male macaques, we examined anterogradely labeled fiber distribution to understand how these different functional systems communicate in the main amygdala nuclei at both mesocopic and cellular levels. The sgACC has broad-based termination patterns. In contrast, the pgACC has a more restricted pattern, which was always nested in sgACC terminals. Terminal overlap occurred in subregions of the accessory basal and basal nuclei, which we termed "hotspots." In triple-labeling confocal studies, the majority of randomly selected CaMKIIα-positive cells (putative amygdala glutamatergic neurons) in hotspots received dual contacts from the sgACC and pgACC. The ratio of dual contacts occurred over a surprisingly narrow range, suggesting a consistent, tight balance of afferent contacts on postsynaptic neurons. Large boutons, which are associated with greater synaptic strength, were ∼3 times more frequent on sgACC versus pgACC axon terminals in hotspots, consistent with a fast "driver" function. Together, the results reveal a nested interaction in which pgACC ("conflict/social monitoring") terminals converge with the broader sgACC ("salience") terminals at both the mesoscopic and cellular level. The presynaptic organization in hotspots suggests that shifts in arousal states can rapidly and flexibly influence decision-making functions in the amygdala.SIGNIFICANCE STATEMENT The subgenual (sgACC) and perigenual cingulate (pgACC) have distinct structural and functional characteristics and are important afferent modulators of the amygdala. The sgACC is critical for arousal, whereas the pgACC mediates conflict-monitoring, including in social contexts. Using dual tracer injections in the same monkey, we found that sgACC inputs broadly project in the main amygdala nuclei, whereas pgACC inputs were more restricted and nested in zones containing sgACC terminals (hotspots). The majority of CaMKIIα + (excitatory) amygdala neurons in hotspots received converging contacts, which were tightly balanced. pgACC and sgACC afferent streams are therefore highly interdependent in these specific amygdala subregions, permitting "internal arousal" states to rapidly shape responses of amygdala neurons involved in conflict and social monitoring networks.

Hugin + neurons provide a link between sleep homeostat and circadian clock neurons

Sleep is controlled by homeostatic mechanisms, which drive sleep after wakefulness, and a circadian clock, which confers the 24-h rhythm of sleep. These processes interact with each other to control the timing of sleep in a daily cycle as well as following sleep deprivation. However, the mechanisms by which they interact are poorly understood. We show here that hugin ⁺ neurons, previously identified as neurons that function downstream of the clock to regulate rhythms of locomotor activity, are also targets of the sleep homeostat. Sleep deprivation decreases activity of hugin ⁺ neurons, likely to suppress circadian-driven activity during recovery sleep, and ablation of hugin ⁺ neurons promotes sleep increases generated by activation of the homeostatic sleep locus, the dorsal fan-shaped body (dFB). Also, mutations in peptides produced by the hugin ⁺ locus increase recovery sleep following deprivation. Transsynaptic mapping reveals that hugin ⁺ neurons feed back onto central clock neurons, which also show decreased activity upon sleep loss, in a Hugin peptide-dependent fashion. We propose that hugin ⁺ neurons integrate circadian and sleep signals to modulate circadian circuitry and regulate the timing of sleep.