Types Of Neurons Research Articles

LIU Zhishun's clinical experience of electroacupuncture for pediatric neurogenic bladder of lower motor neuron type in children

Professor LIU Zhishun's clinical experience of electroacupuncture (EA) for pediatric neurogenic bladder of lower motor neuron type in children is summarized. Considering the unique physiological and pathological characteristics of children, with the strategy of combining "disease-symptom-location" in the selection of acupoints, professor LIU Zhishun proposes that the main disease location is the bladder and kidney, with the involvement of the conception vessel, governor vessel, kidney meridian of foot-shaoyin and the bladder meridian of foot-taiyang. The primary acupoint prescription-1 (bilateral Zhongliao [BL 33], Ciliao [BL 32] and Huiyang [BL 35]) and primary acupoint prescription-2 (Guanyuan [CV 4], Zhongji [CV 3] and bilateral Sanyinjiao [SP 6]) are selected to promote the yang of the governor vessel, stimulate the yin of the conception vessel, and invigorate the bladder's qi transformation. Before acupuncture, the four-step method is applied to precisely locate Ciliao (BL 32) and Zhongliao (BL 33). During acupuncture, the importance of achieving deqi is emphasized, with deep insertion in the sacral area to reach the disease location. Based on the tolerance characteristics of children, low-frequency EA and gentle moxibustion treatment are applied.

Deciphering the genetic code of neuronal type connectivity through bilinear modeling.

Understanding how different neuronal types connect and communicate is critical to interpreting brain function and behavior. However, it has remained a formidable challenge to decipher the genetic underpinnings that dictate the specific connections formed between neuronal types. To address this, we propose a novel bilinear modeling approach that leverages the architecture similar to that of recommendation systems. Our model transforms the gene expressions of presynaptic and postsynaptic neuronal types, obtained from single-cell transcriptomics, into a covariance matrix. The objective is to construct this covariance matrix that closely mirrors a connectivity matrix, derived from connectomic data, reflecting the known anatomical connections between these neuronal types. When tested on a dataset of Caenorhabditis elegans, our model achieved a performance comparable to, if slightly better than, the previously proposed spatial connectome model (SCM) in reconstructing electrical synaptic connectivity based on gene expressions. Through a comparative analysis, our model not only captured all genetic interactions identified by the SCM but also inferred additional ones. Applied to a mouse retinal neuronal dataset, the bilinear model successfully recapitulated recognized connectivity motifs between bipolar cells and retinal ganglion cells, and provided interpretable insights into genetic interactions shaping the connectivity. Specifically, it identified unique genetic signatures associated with different connectivity motifs, including genes important to cell-cell adhesion and synapse formation, highlighting their role in orchestrating specific synaptic connections between these neurons. Our work establishes an innovative computational strategy for decoding the genetic programming of neuronal type connectivity. It not only sets a new benchmark for single-cell transcriptomic analysis of synaptic connections but also paves the way for mechanistic studies of neural circuit assembly and genetic manipulation of circuit wiring.

Deciphering the genetic code of neuronal type connectivity through bilinear modeling

Understanding how different neuronal types connect and communicate is critical to interpreting brain function and behavior. However, it has remained a formidable challenge to decipher the genetic underpinnings that dictate the specific connections formed between neuronal types. To address this, we propose a novel bilinear modeling approach that leverages the architecture similar to that of recommendation systems. Our model transforms the gene expressions of presynaptic and postsynaptic neuronal types, obtained from single-cell transcriptomics, into a covariance matrix. The objective is to construct this covariance matrix that closely mirrors a connectivity matrix, derived from connectomic data, reflecting the known anatomical connections between these neuronal types. When tested on a dataset of Caenorhabditis elegans, our model achieved a performance comparable to, if slightly better than, the previously proposed spatial connectome model (SCM) in reconstructing electrical synaptic connectivity based on gene expressions. Through a comparative analysis, our model not only captured all genetic interactions identified by the SCM but also inferred additional ones. Applied to a mouse retinal neuronal dataset, the bilinear model successfully recapitulated recognized connectivity motifs between bipolar cells and retinal ganglion cells, and provided interpretable insights into genetic interactions shaping the connectivity. Specifically, it identified unique genetic signatures associated with different connectivity motifs, including genes important to cell-cell adhesion and synapse formation, highlighting their role in orchestrating specific synaptic connections between these neurons. Our work establishes an innovative computational strategy for decoding the genetic programming of neuronal type connectivity. It not only sets a new benchmark for single-cell transcriptomic analysis of synaptic connections but also paves the way for mechanistic studies of neural circuit assembly and genetic manipulation of circuit wiring.

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

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

Spiking networks that efficiently process dynamic sensory features explain receptor information mixing in somatosensory cortex.

How do biological neural systems efficiently encode, transform and propagate information between the sensory periphery and the sensory cortex about sensory features evolving at different time scales? Are these computations efficient in normative information processing terms? While previous work has suggested that biologically plausible models of of such neural information processing may be implemented efficiently within a single processing layer, how such computations extend across several processing layers is less clear. Here, we model propagation of multiple time-varying sensory features across a sensory pathway, by extending the theory of efficient coding with spikes to efficient encoding, transformation and transmission of sensory signals. These computations are optimally realized by a multilayer spiking network with feedforward networks of spiking neurons (receptor layer) and recurrent excitatory-inhibitory networks of generalized leaky integrate-and-fire neurons (recurrent layers). Our model efficiently realizes a broad class of feature transformations, including positive and negative interaction across features, through specific and biologically plausible structures of feedforward connectivity. We find that mixing of sensory features in the activity of single neurons is beneficial because it lowers the metabolic cost at the network level. We apply the model to the somatosensory pathway by constraining it with parameters measured empirically and include in its last node, analogous to the primary somatosensory cortex (S1), two types of inhibitory neurons: parvalbumin-positive neurons realizing lateral inhibition, and somatostatin-positive neurons realizing winner-take-all inhibition. By implementing a negative interaction across stimulus features, this model captures several intriguing empirical observations from the somatosensory system of the mouse, including a decrease of sustained responses from subcortical networks to S1, a non-linear effect of the knock-out of receptor neuron types on the activity in S1, and amplification of weak signals from sensory neurons across the pathway.

Noradrenergic current responses of neurons in rat oculomotor neural integrators.

The prepositus hypoglossi nucleus (PHN) and the interstitial nucleus of Cajal (INC) are involved in the control of horizontal and vertical gaze, respectively. A previous study showed that PHN neurons exhibit depolarized or hyperpolarized responses to noradrenaline (NA). However, the adrenoceptor types that participate in NA-induced responses and the effects of NA on INC neurons have not yet been investigated. Furthermore, the relationship between NA-induced responses and neuron types defined by neurotransmitter phenotypes has not been determined. In this study, we investigated NA-induced current responses in PHN and INC neurons and the relationships between these responses and neuron types using whole cell recordings in wild-type and transgenic rat brainstem slices. Local application of NA to the cell soma induced slow inward (SI) and slow outward (SO) currents that were mainly mediated by α1 and α2 adrenoceptors, respectively. These current responses were observed in both PHN and INC neurons, although the proportion of INC neurons that responded to NA was low. Analyses of the distributions of the current responses revealed that in the PHN, all fluorescently identified inhibitory neurons exhibited SI currents, whereas glutamatergic and cholinergic neurons exhibited both SI and SO currents. In the INC, glutamatergic and inhibitory neurons preferentially exhibited SI and SO currents, respectively. When the PHN and INC neurons were characterized by their firing pattern, we found that the proportions of the currents depended on their firing pattern. These results suggest that various modes of noradrenergic modulation in horizontal and vertical neural integrators are dependent on neuron type.NEW & NOTEWORTHY Noradrenergic modulation of oculomotor neural integrators involved in gaze control has not been elucidated. Here, we report that noradrenaline (NA)-induced slow inward (SI) and outward (SO) currents are mediated mainly by α1 and α2 adrenoceptors in neurons that participate in horizontal and vertical gaze control. The NA-induced current responses differed depending on the neurotransmitter phenotype and firing pattern. These results suggest various modes of noradrenergic modulation in horizontal and vertical integrator neurons.

Neuronal cell populations in circumoral nerve ring of sea cucumber Apostichopus japonicus: Ultrastructure and transcriptional profile

The echinoderm nervous system has been studied as a model for understanding the evolution of the chordate nervous system. Neuronal cells are essential groups that release a ‘cocktail’ of messenger molecules providing a spectrum of biological actions in the nervous system. Among echinoderms, most evidence on neuronal cell types has been obtained from starfish and sea urchin. In sea cucumbers, most research has focused on the location of neuronal cells, whereas their transcriptional features have rarely been investigated. Here, we observed the ultrastructure of neuronal cells in the sea cucumber, Apostichopus japonicus. The transcriptional profile of neuronal cells from the circumoral nerve ring (CNR) was investigated using single-cell RNA sequencing (scRNA-seq), and a total of six neuronal cell types were identified. 26 neuropeptide precursor genes (NPPs) and 28 G-protein-coupled receptors (GPCR) were expressed in the six neuronal cell types, comprising five NPP/NP-GPCR pairs. Unsupervised pseudotime analysis of neuronal cells showed their different differentiation status. We also located the neuronal cells in the CNR by immunofluorescence (IF) and identified the potential hub genes of key cell populations. This broad resource serves as a valuable support in the development of cell-specific markers for accurate cell-type identification in sea cucumbers. It also contributes to facilitating comparison across species, providing a deeper understanding of the evolutionary processes of neuronal cells.

Cell-type-specific effects of age and sex on human cortical neurons

Altered transcriptional and epigenetic regulation of brain cell types may contribute to cognitive changes withadvanced age. Using single-nucleus multi-omic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex from young adult and aged donors, we found widespread age- and sex-related variation in specific neuron types. The proportion of inhibitory SST- and VIP-expressing neurons was reduced in aged donors. Excitatory neurons had more profound age-related changes in their gene expression and DNA methylation than inhibitory cells. Hundreds of genes involved in synaptic activity, including EGR1, were less expressed in aged adults. Genes located in subtelomeric regions increased their expression with age and correlated with reduced telomere length. We further mapped cell-type-specific sex differences in gene expression and X-inactivation escape genes. Multi-omic single-nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.

Experimental study on treatment of retinitis pigmentosa by inducing Müller cell reprogramming with Lycii Fructus and Salviae Miltiorrhizae Radix et Rhizoma

This study aims to explore the effect of Lycii Fructus and Salviae Miltiorrhizae Radix et Rhizoma(LFSMR), a drug pair possesses the function of nourishing Yin, promoting blood circulation, and brightening the eyes, in treating retinitis pigmentosa(RP)by inhibiting the gliosis of Müller cells(MCs) and inducing their reprogramming and differentiation into various types of retinal nerve cells. Twelve C57 mice were used as the normal control group, and 48 transgenic RP(rd10) mice were randomly divided into the model group, positive control group, and low and high dose LFSMR groups, with 12 mice in each group. HE staining was used to detect pathological changes in the retina, and an electroretinogram was used to detect retinal function. Retinal optical coherence tomography was used to detect retinal thickness and perform fundus photography, and laser speckle perfusion imaging was used to detect local retinal blood flow. Digital PCR was used to detect gene expression related to retinal nerve cells, and immunofluorescence was used to detect protein expression related to retinal nerve cells. LFSMR could significantly improve the pathological changes, increase the amplitude of a and b waves, increase the retinal thickness, restore retinal damage, and increase retinal blood flow in mice with RP lesions. LFSMR could also significantly inhibit the m RNA expression of the glial fibrillary acidic protein( GFAP) during the pathogenesis of RP and upregulate m RNA expression of sex determining region Y box protein 2(SOX2), paired box protein 6(Pax6),rhodopsin, protein kinase C-α(PKCα), syntaxin, and thymic cell antigen 1. 1(Thy1. 1). LFSMR could significantly inhibit GFAP protein expression and enhance protein expression of SOX2, Pax6, rhodopsin, PKCα, syntaxin, and Thy1. 1. It could also reverse the pathological changes in the retina of rd10 mice, improve retinal function and fundus performance, increase retinal thickness, enhance local retinal blood flow, and exert therapeutic effects on RP. The mechanism of action of LFSMR may be related to inhibiting the gliosis of MCs and promoting their reprogramming and differentiation into various types of retinal nerve cells.

Neuron type-specific optogenetic stimulation for differential stroke recovery in chronic capsular infarct

Cortical neuromodulation (CNM) is widely used to promote recovery after stroke. Despite the beneficial results of CNM, the roles played by different neuron types in the effects of current CNM techniques are unable to be differentiated. Our aim was to use selective optogenetic cortical stimulation to explore how different subpopulations of neuronal cells contribute to poststroke recovery. We transduced the sensory-parietal cortex (SPC) of rats with CamKII-ChR2 (pyramidal neurons), PV-ChR2 (parvalbumin-expressing inhibitory neurons), or hSyn-ChR2 (pan-neuronal population) before inducing photothrombotic capsular infarct lesions. We found that selective stimulation of inhibitory neurons resulted in significantly greater motor recovery than stimulation of excitatory neurons or the pan-neuronal population. Furthermore, 2-deoxy-2-[18F] fluoro-D-glucose microPET (FDG-microPET) imaging revealed a significant reduction in cortical diaschisis and activation of the corticostriatal neural circuit, which were correlated with behavioral recovery in the PV-ChR2 group. The spatial pattern of brain-derived neurotrophic factor (BDNF) expression was evident in the stimulated cortex and underlying cortico-subcortical circuit. Our results indicate that the plasticity of inhibitory neurons is crucial for functional recovery after capsular infarct. Modifying CNM parameters to potentiate the stimulation of inhibitory neurons could improve poststroke outcomes.

The influence of olfactory experience on the birthrates of olfactory sensory neurons with specific odorant receptor identities.

Olfactory sensory neurons (OSNs) are one of a few neuron types that are generated continuously throughout life in mammals. The persistence of olfactory sensory neurogenesis beyond early development has long been thought to function simply to replace neurons that are lost or damaged through exposure to environmental insults. The possibility that olfactory sensory neurogenesis may also serve an adaptive function has received relatively little consideration, largely due to the assumption that the generation of new OSNs is stochastic with respect to OSN subtype, as defined by the single odorant receptor gene that each neural precursor stochastically chooses for expression out of hundreds of possibilities. Accordingly, the relative birthrates of different OSN subtypes are predicted to be constant and impervious to olfactory experience. This assumption has been called into question, however, by evidence that the birthrates of specific OSN subtypes can be selectively altered by manipulating olfactory experience through olfactory deprivation, enrichment, and conditioning paradigms. Moreover, studies of recovery of the OSN population following injury provide further evidence that olfactory sensory neurogenesis may not be strictly stochastic with respect to subtype. Here we review this evidence and consider mechanistic and functional implications of the prospect that specific olfactory experiences can regulate olfactory sensory neurogenesis rates in a subtype-selective manner.

Connectome-driven neural inventory of a complete visual system.

Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brain's volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the fly's visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the ~53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.

A Continuous Attractor Model with Realistic Neural and Synaptic Properties Quantitatively Reproduces Grid Cell Physiology.

Computational simulations with data-driven physiological detail can foster a deeper understanding of the neural mechanisms involved in cognition. Here, we utilize the wealth of cellular properties from Hippocampome.org to study neural mechanisms of spatial coding with a spiking continuous attractor network model of medial entorhinal cortex circuit activity. The primary goal is to investigate if adding such realistic constraints could produce firing patterns similar to those measured in real neurons. Biological characteristics included in the work are excitability, connectivity, and synaptic signaling of neuron types defined primarily by their axonal and dendritic morphologies. We investigate the spiking dynamics in specific neuron types and the synaptic activities between groups of neurons. Modeling the rodent hippocampal formation keeps the simulations to a computationally reasonable scale while also anchoring the parameters and results to experimental measurements. Our model generates grid cell activity that well matches the spacing, size, and firing rates of grid fields recorded in live behaving animals from both published datasets and new experiments performed for this study. Our simulations also recreate different scales of those properties, e.g., small and large, as found along the dorsoventral axis of the medial entorhinal cortex. Computational exploration of neuronal and synaptic model parameters reveals that a broad range of neural properties produce grid fields in the simulation. These results demonstrate that the continuous attractor network model of grid cells is compatible with a spiking neural network implementation sourcing data-driven biophysical and anatomical parameters from Hippocampome.org. The software (version 1.0) is released as open source to enable broad community reuse and encourage novel applications.

Altered firing activity of intracardiac neurons isolated from mice carrying the Scn5a-1798insD mutation

Abstract Funding Acknowledgements None. Background Dysfunction of the cardiac sodium channel Nav1.5 (encoded by SCN5A) is associated with arrhythmias and sudden cardiac death, the mechanisms of which have been extensively studied in cardiomyocytes. However, patients carrying an SCN5A mutation often display clinical symptoms which are not readily explained solely by alterations in cardiomyocyte electrophysiology. For instance, carriers of the SCN5A-1795insD mutation, which is associated with features of Brugada syndrome and Long QT syndrome type 3 (LQT3), display severe bradycardia leading to excessive QT-prolongation and sudden death especially occurring at rest or during the night, suggesting autonomic triggers. Interestingly, SCN5A is not only present in cardiomyocytes, but also in intracardiac neurons (ICN). ICN modulate cardiac electrophysiological properties and their dysregulation may contribute to arrhythmogenesis. Purpose To explore whether ICN from mice carrying the Scn5a-1798insD mutation (the murine equivalent of SCN5A-1795insD) display electrophysiological alterations that may (in part) contribute to the arrhythmogenic phenotype. Methods and Results ICN were isolated by enzymatic dissociation from fat pads located in the pulmonary veins and sinoatrial node regions of the hearts of wild-type (WT) and Scn5a-1798insD mice. Immunodetection of the cholinergic marker ChAT confirmed the prominent cholinergic phenotype of ICN. In agreement with previous reports in other species, we also detected the presence of Nav1.5 in murine ICN. Nav1.5 expression was mainly observed in ChAT positive cells. To evoke repetitive action potential (AP) firing in single ICN, 500 ms-sustained depolarizing current pulses were applied of increasing amplitude (from 0 pA to 150 pA). Two types of neurons were identified on the basis of firing pattern characteristics: accommodating (neurons that discharged multiple APs decrementing in frequency during the pulse) and tonic (neurons that discharged multiple APs at a high frequency). APs firing frequency did not differ between WT and Scn5a-1798insD accommodating ICN, while it was significantly increased in Scn5a-1798insD tonic ICN as compared to WT (at 100 pA, AP count/500ms in WT CMs: 29.5±1.7, n=24; at 100 pA, AP count/500ms in Scn5a-1798insD: 36.2±2.0, n=18, p=0.02). Conclusions The impact of SCN5A mutations on ICN function are unexplored, but may play an essential role in arrhythmogenesis. The increased AP firing frequency observed in Scn5a-1798insD ICN may lead to increased release of neurotransmitters, such as acetylcholine, that in turn may contribute to the bradycardia observed in patients. Overall, further elucidation of the electrophysiological consequences of inherited Nav1.5 dysfunction in ICN might provide novel therapeutic targets to prevent lethal arrhythmias.

Dorsal and median raphe neuronal firing dynamics characterized by nonlinear measures.

The dorsal (DRN) and median (MRN) raphe are important nuclei involved in similar functions, including mood and sleep, but playing distinct roles. These nuclei have a different composition of neuronal types and set of neuronal connections, which among other factors, determine their neuronal dynamics. Most works characterize the neuronal dynamics using classic measures, such as using the average spiking frequency (FR), the coefficient of variation (CV), and action potential duration (APD). In the current study, to refine the characterization of neuronal firing profiles, we examined the neurons within the raphe nuclei. Through the utilization of nonlinear measures, our objective was to discern the redundancy and complementarity of these measures, particularly in comparison with classic methods. To do this, we analyzed the neuronal basal firing profile in both nuclei of urethane-anesthetized rats using the Shannon entropy (Bins Entropy) of the inter-spike intervals, permutation entropy of ordinal patterns (OP Entropy), and Permutation Lempel-Ziv Complexity (PLZC). Firstly, we found that classic (i.e., FR, CV, and APD) and nonlinear measures fail to distinguish between the dynamics of DRN and MRN neurons, except for the OP Entropy. We also found strong relationships between measures, including the CV with FR, CV with Bins entropy, and FR with PLZC, which imply redundant information. However, APD and OP Entropy have either a weak or no relationship with the rest of the measures tested, suggesting that they provide complementary information to the characterization of the neuronal firing profiles. Secondly, we studied how these measures are affected by the oscillatory properties of the firing patterns, including rhythmicity, bursting patterns, and clock-like behavior. We found that all measures are sensitive to rhythmicity, except for the OP Entropy. Overall, our work highlights OP Entropy as a powerful and useful quantity for the characterization of neuronal discharge patterns.

Nociceptor-immune interactomes reveal insult-specific immune signatures of pain

Inflammatory pain results from the heightened sensitivity and reduced threshold of nociceptor sensory neurons due to exposure to inflammatory mediators. However, the cellular and transcriptional diversity of immune cell and sensory neuron types makes it challenging to decipher the immune mechanisms underlying pain. Here we used single-cell transcriptomics to determine the immune gene signatures associated with pain development in three skin inflammatory pain models in mice: zymosan injection, skin incision and ultraviolet burn. We found that macrophage and neutrophil recruitment closely mirrored the kinetics of pain development and identified cell-type-specific transcriptional programs associated with pain and its resolution. Using a comprehensive list of potential interactions mediated by receptors, ligands, ion channels and metabolites to generate injury-specific neuroimmune interactomes, we also uncovered that thrombospondin-1 upregulated by immune cells upon injury inhibited nociceptor sensitization. This study lays the groundwork for identifying the neuroimmune axes that modulate pain in diverse disease contexts.

Whole-brain Mapping of Inputs and Outputs of Specific Orbitofrontal Cortical Neurons in Mice.

The orbitofrontal cortex (ORB), a region crucial for stimulus-reward association, decision-making, and flexible behaviors, extensively connects with other brain areas. However, brain-wide inputs to projection-defined ORB neurons and the distribution of inhibitory neurons postsynaptic to neurons in specific ORB subregions remain poorly characterized. Here we mapped the inputs of five types of projection-specific ORB neurons and ORB outputs to two types of inhibitory neurons. We found that different projection-defined ORB neurons received inputs from similar cortical and thalamic regions, albeit with quantitative variations, particularly in somatomotor areas and medial groups of the dorsal thalamus. By counting parvalbumin (PV) or somatostatin (SST) interneurons innervated by neurons in specific ORB subregions, we found a higher fraction of PV neurons in sensory cortices and a higher fraction of SST neurons in subcortical regions targeted by medial ORB neurons. These results provide insights into understanding and investigating the function of specific ORB neurons.

Thyrotropin-Releasing Hormone and Food Intake in Mammals: An Update.

Thyrotropin-releasing hormone (TRH; pGlu-His-Pro-NH2) is an intercellular signal produced mainly by neurons. Among the multiple pharmacological effects of TRH, that on food intake is not well understood. We review studies demonstrating that peripheral injection of TRH generally produces a transient anorexic effect, discuss the pathways that might initiate this effect, and explain its short half-life. In addition, central administration of TRH can produce anorexic or orexigenic effects, depending on the site of injection, that are likely due to interaction with TRH receptor 1. Anorexic effects are most notable when TRH is injected into the hypothalamus and the nucleus accumbens, while the orexigenic effect has only been detected by injection into the brain stem. Functional evidence points to TRH neurons that are prime candidate vectors for TRH action on food intake. These include the caudal raphe nuclei projecting to the dorsal motor nucleus of the vagus, and possibly TRH neurons from the tuberal lateral hypothalamus projecting to the tuberomammillary nuclei. For other TRH neurons, the anatomical or physiological context and impact of TRH in each synaptic domain are still poorly understood. The manipulation of TRH expression in well-defined neuron types will facilitate the discovery of its role in food intake control in each anatomical scene.

Effect of electroacupuncture stimulation of "Sibai"(ST2) and "Quanliao"(SI18) on excitatory neurons of sensorimotor cortex in mice.

To observe the activation state and neuronal types of somatosensory cortex and the primary motor cortex induced by electroacupuncture (EA) stimulation of "Sibai" (ST2) and "Quanliao" (SI18) acupoints in mice. Male C57BL/6J mice were randomly divided into blank control and EA groups, with 6 mice in each group. Rats of the EA group received EA stimulation (2 Hz, 0.6 mA) at ST2 and SI18 for 30 minutes. Samples were collected after EA intervention, and immunofluorescence staining was performed to quantify the expression of the c-Fos gene (proportion of c-Fos positive cells) in the somatosensory cortex and primary motor cortex. The co-labelled cells of calcium/calmodulin-dependent protein kinase Ⅱ (CaMKⅡ) and gamma-aminobutyric acid (GABA) in the somatosensory cortex and primary motor cortex were observed and counted by using microscope after immunofluorescence staining. Another 10 mice were used to detect the calcium activity of excitatory neurons in the somatosensory cortex and primary motor cortex by fiber photometry. In comparison with the blank control group, the number of c-Fos positive cells, and the proportion of c-Fos and CaMKⅡ co-labelled cells in both the somatosensory cortex and primary motor cortex were significantly increased after EA stimulation (P<0.05). No significant changes were found in the proportion of c-Fos and GABA co-labeled cells in both the somatosensory cortex and primary motor cortex after EA. Results of fiber optic calcium imaging technology showed that the spontaneous calcium activity of excitatory neurons in both somatosensory cortex and primary motor cortex were obviously increased during EA compared with that before EA (P<0.01), and strikingly reduced after cessation of EA compared with that during EA (P<0.05). Under physiological conditions, EA of ST2 and SI18 can effectively activate excitatory neurons in the somatosensory cortex and primary motor cortex.

Dendrite morphogenesis in Caenorhabditis elegans.

Since the days of Ramón y Cajal, the vast diversity of neuronal and particularly dendrite morphology has been used to catalog neurons into different classes. Dendrite morphology varies greatly and reflects the different functions performed by different types of neurons. Significant progress has been made in our understanding of how dendrites form and the molecular factors and forces that shape these often elaborately sculpted structures. Here, we review work in the nematode Caenorhabditis elegans that has shed light on the developmental mechanisms that mediate dendrite morphogenesis with a focus on studies investigating ciliated sensory neurons and the highly elaborated dendritic trees of somatosensory neurons. These studies, which combine time-lapse imaging, genetics, and biochemistry, reveal an intricate network of factors that function both intrinsically in dendrites and extrinsically from surrounding tissues. Therefore, dendrite morphogenesis is the result of multiple tissue interactions, which ultimately determine the shape of dendritic arbors.