Local Neurons Research Articles

Spontaneous slow wave oscillations in extracellular field potential recordings reflect the alternating dominance of excitation and inhibition.

In the resting state, cortical neurons can fire action potentials spontaneously but synchronously (Up state), followed by a quiescent period (Down state) before the cycle repeats. Extracellular recordings in the infragranular layer of cortex with a micro-electrode display a negative deflection (depth-negative) during Up states and a positive deflection (depth-positive) during Down states. The resulting slow wave oscillation (SWO) has been studied extensively during sleep and under anaesthesia. However, recent research on the balanced nature of synaptic excitation and inhibition has highlighted our limited understanding of its genesis. Specifically, are excitation and inhibition balanced during SWOs? We analyse spontaneous local field potentials (LFPs) during SWOs recorded from anaesthetised rats via a multi-channel laminar micro-electrode and show that the Down state consists of two distinct synaptic states: a Dynamic Down state associated with depth-positive LFPs and a prominent dipole in the extracellular field, and a Static Down state with negligible ( ) LFPs and a lack of dipoles extracellularly. We demonstrate that depth-negative and -positive LFPs are generated by a shift in the balance of synaptic excitation and inhibition from excitation dominance (depth-negative) to inhibition dominance (depth-positive) in the infragranular layer neurons. Thus, although excitation and inhibition co-tune overall, differences in their timing lead to an alternation of dominance, manifesting as SWOs. We further show that Up state initiation is significantly faster if the preceding Down state is dynamic rather than static. Our findings provide a coherent picture of the dependence of SWOs on synaptic activity. KEY POINTS: Cortical neurons can exhibit repeated cycles of spontaneous activity interleaved with periods of relative silence, a phenomenon known as 'slow wave oscillation' (SWO). During SWOs, recordings of local field potentials (LFPs) in the neocortex show depth-negative deflection during the active period (Up state) and depth-positive deflection during the silent period (Down state). Here we further classified the Down state into a dynamic phase and a static phase based on a novel method of classification and revealed non-random, stereotypical sequences of the three states occurring with significantly different transitional kinetics. Our results suggest that the positive and negative deflections in the LFP reflect the shift of the instantaneous balance between excitatory and inhibitory synaptic activity of the local cortical neurons. The differences in transitional kinetics may imply distinct synaptic mechanisms for Up state initiation. The study may provide a new approach for investigating spontaneous brain rhythms.

High-resolution tracking of unconfined zebrafish behavior reveals stimulatory and anxiolytic effects of psilocybin

Serotonergic psychedelics are emerging therapeutics for psychiatric disorders, yet their underlying mechanisms of action in the brain remain largely elusive. Here, we developed a wide-field behavioral tracking system for larval zebrafish and investigated the effects of psilocybin, a psychedelic serotonin receptor agonist. Machine learning analyses of precise body kinematics identified latent behavioral states reflecting spontaneous exploration, visually-driven rapid swimming, and irregular swim patterns following stress exposure. Using this method, we found that acute psilocybin treatment has two behavioral effects: [i] facilitation of spontaneous exploration (“stimulatory”) and [ii] prevention of irregular swim patterns following stress exposure (“anxiolytic”). These effects differed from the effect of acute SSRI treatment and were rather similar to the effect of ketamine treatment. Neural activity imaging in the dorsal raphe nucleus suggested that psilocybin inhibits serotonergic neurons by activating local GABAergic neurons, consistent with psychedelic-induced suppression of serotonergic neurons in mammals. These findings pave the way for using larval zebrafish to elucidate neural mechanisms underlying the behavioral effects of serotonergic psychedelics.

Silencing long-descending inter-enlargement propriospinal neurons improves hindlimb stepping after contusive spinal cord injuries.

Spinal locomotor circuitry is comprised of rhythm generating centers, one for each limb, that are interconnected by local and long-distance propriospinal neurons thought to carry temporal information necessary for interlimb coordination and gait control. We showed previously that conditional silencing of the long ascending propriospinal neurons (LAPNs) that project from the lumbar to the cervical rhythmogenic centers (L1/L2 to C6), disrupts right-left alternation of both the forelimbs and hindlimbs without significantly disrupting other fundamental aspects of interlimb and speed-dependent coordination (Pocratsky et al., 2020). Subsequently, we showed that silencing the LAPNs after a moderate thoracic contusive spinal cord injury (SCI) resulted in better recovered locomotor function (Shepard et al., 2021). In this research advance, we focus on the descending equivalent to the LAPNs, the long descending propriospinal neurons (LDPNs) that have cell bodies at C6 and terminals at L2. We found that conditional silencing of the LDPNs in the intact adult rat resulted in a disrupted alternation of each limb pair (forelimbs and hindlimbs) and after a thoracic contusion SCI significantly improved locomotor function. These observations lead us to speculate that the LAPNs and LDPNs have similar roles in the exchange of temporal information between the cervical and lumbar rhythm generating centers, but that the partial disruption of the pathway after SCI limits the independent function of the lumbar circuitry. Silencing the LAPNs or LDPNs effectively permits or frees-up the lumbar circuitry to function independently.

Programming of neural progenitors of the adult subependymal zone towards a glutamatergic neuron lineage by neurogenin 2

Although adult subependymal zone (SEZ) neural stem cells mostly generate GABAergic interneurons, a small progenitor population expresses the proneural gene Neurog2 and produces glutamatergic neurons. Here, we determined whether Neurog2 could respecify SEZ neural stem cells and their progeny toward a glutamatergic fate. Retrovirus-mediated expression of Neurog2 induced the glutamatergic lineage markers TBR2 and TBR1 in cultured SEZ progenitors, which differentiated into functional glutamatergic neurons. Likewise, Neurog2-transduced SEZ progenitors acquired glutamatergic neuron hallmarks invivo. Intriguingly, they failed to migrate toward the olfactory bulb and instead differentiated within the SEZ or the adjacent striatum, where they received connections from local neurons, as indicated by rabies virus-mediated monosynaptic tracing. In contrast, lentivirus-mediated expression of Neurog2 failed to reprogram early SEZ neurons, which maintained GABAergic identity and migrated to the olfactory bulb. Our data show that NEUROG2 can program SEZ progenitors toward a glutamatergic identity but fails to reprogram their neuronal progeny.

High-Density Exploration of Activity States in a Multi-Area Brain Model

To simulate whole brain dynamics with only a few equations, biophysical, mesoscopic models of local neuron populations can be connected using empirical tractography data. The development of mesoscopic mean-field models of neural populations, in particular, the Adaptive Exponential (AdEx mean-field model), has successfully summarized neuron-scale phenomena leading to the emergence of global brain dynamics associated with conscious (asynchronous and rapid dynamics) and unconscious (synchronized slow-waves, with Up-and-Down state dynamics) brain states, based on biophysical mechanisms operating at cellular scales (e.g. neuromodulatory regulation of spike-frequency adaptation during sleep-wake cycles or anesthetics). Using the Virtual Brain (TVB) environment to connect mean-field AdEx models, we have previously simulated the general properties of brain states, playing on spike-frequency adaptation, but have not yet performed detailed analyses of other parameters possibly also regulating transitions in brain-scale dynamics between different brain states. We performed a dense grid parameter exploration of the TVB-AdEx model, making use of High Performance Computing. We report a remarkable robustness of the effect of adaptation to induce synchronized slow-wave activity. Moreover, the occurrence of slow waves is often paralleled with a closer relation between functional and structural connectivity. We find that hyperpolarization can also generate unconscious-like synchronized Up and Down states, which may be a mechanism underlying the action of anesthetics. We conclude that the TVB-AdEx model reveals large-scale properties identified experimentally in sleep and anesthesia.

Topographic axonal projection at single-cell precision supports local retinotopy in the mouse superior colliculus

Retinotopy, like all long-range projections, can arise from the axons themselves or their targets. The underlying connectivity pattern, however, remains elusive at the fine scale in the mammalian brain. To address this question, we functionally mapped the spatial organization of the input axons and target neurons in the female mouse retinocollicular pathway at single-cell resolution using in vivo two-photon calcium imaging. We found a near-perfect retinotopic tiling of retinal ganglion cell axon terminals, with an average error below 30 μm or 2° of visual angle. The precision of retinotopy was relatively lower for local neurons in the superior colliculus. Subsequent data-driven modeling ascribed it to a low input convergence, on average 5.5 retinal ganglion cell inputs per postsynaptic cell in the superior colliculus. These results indicate that retinotopy arises largely from topographically precise input from presynaptic cells, rather than elaborating local circuitry to reconstruct the topography by postsynaptic cells.

CHEX-seq detects single-cell genomic single-stranded DNA with catalytical potential

Genomic DNA (gDNA) undergoes structural interconversion between single- and double-stranded states during transcription, DNA repair and replication, which is critical for cellular homeostasis. We describe “CHEX-seq” which identifies the single-stranded DNA (ssDNA) in situ in individual cells. CHEX-seq uses 3’-terminal blocked, light-activatable probes to prime the copying of ssDNA into complementary DNA that is sequenced, thereby reporting the genome-wide single-stranded chromatin landscape. CHEX-seq is benchmarked in human K562 cells, and its utilities are demonstrated in cultures of mouse and human brain cells as well as immunostained spatially localized neurons in brain sections. The amount of ssDNA is dynamically regulated in response to perturbation. CHEX-seq also identifies single-stranded regions of mitochondrial DNA in single cells. Surprisingly, CHEX-seq identifies single-stranded loci in mouse and human gDNA that catalyze porphyrin metalation in vitro, suggesting a catalytic activity for genomic ssDNA. We posit that endogenous DNA enzymatic activity is a function of genomic ssDNA.

CNSC-19. HYPOXIA-INDUCED NEURONAL ACTIVITY IN GLIOMA PATIENTS POLARIZES MICROGLIA BY POTENTIATING RNA M6A DEMETHYLATION

Abstract Neuronal activity in the brain has been reported to promote the malignant progression of glioma cells via nonsynaptic paracrine and electrical synaptic integration mechanisms. However, the interaction between neuronal activity and the immune microenvironment in glioblastoma (GBM) remains largely unclear. In this study, by applying chemogenetic techniques, we enhanced and inhibited neuronal activity in vitro and in a mouse model to study how neuronal activity regulates microglial polarization and affects GBM progression. Here, we demonstrate that hypoxia induces glioma stem cells (GSCs) to produce glutamate, which activates local neurons. The hypoxia-induced neuronal activity promotes GBM progression by facilitating microglial M2 polarization. We found that when microglia were co-cultured with activated neurons, the level of RNA m6A methylation in microglia was impaired, which subsequently induced microglial M2 polarization. In the mouse model, cortical neuronal activation promoted regional microglial M2 polarization while cortical neuronal inhibition decreased regional microglial M2 polarization in GBM xenografts. Together, these findings indicate that hypoxic GSC-induced neuronal activation promotes GBM progression by polarizing microglia via decreasing their m6A methylation levels.

Selective plasticity of fast and slow excitatory synapses on somatostatin interneurons in adult visual cortex

Somatostatin-positive (SOM) interneurons are integral for shaping cortical processing and their dynamic recruitment is likely necessary for adaptation to sensory experience and contextual information. We found that excitatory synapses on SOMs in layer 2/3 (L2/3) of primary visual cortex (V1) of mice can be categorized into fast (F)- and slow (S)-Types based on the kinetics of the AMPA receptor-mediated current. Each SOM contains both types of synapses in varying proportions. The majority of local pyramidal neurons (PCs) make unitary connections with SOMs using both types, followed by those utilizing only S-Type, and a minority with only F-Type. Sensory experience differentially regulates synapses on SOMs, such that local F-Type synapses change with visual deprivation and S-Type synapses undergo plasticity with crossmodal auditory deprivation. Our results demonstrate that the two types of excitatory synapses add richness to the SOM circuit recruitment and undergo selective plasticity enabling dynamic adaptation of the adult V1.

Hypoxia-Induced Neuronal Activity in Glioma Patients Polarizes Microglia by Potentiating RNA m6A Demethylation.

Neuronal activity in the brain has been reported to promote the malignant progression of glioma cells via nonsynaptic paracrine and electrical synaptic integration mechanisms. However, the interaction between neuronal activity and the immune microenvironment in glioblastoma (GBM) remains largely unclear. By applying chemogenetic techniques, we enhanced and inhibited neuronal activity in vitro and in a mouse model to study how neuronal activity regulates microglial polarization and affects GBM progression. We demonstrate that hypoxia drove glioma stem cells (GSC) to produce higher levels of glutamate, which activated local neurons. Neuronal activity promoted GBM progression by facilitating microglial M2 polarization through enriching miR-200c-3p in neuron-derived exosomes, which decreased the expression of the m6A writer zinc finger CCCH-type containing 13 (ZC3H13) in microglia, impairing methylation of dual specificity phosphatase 9 (DUSP9) mRNA. Downregulation of DUSP9 promoted ERK pathway activation, which subsequently induced microglial M2 polarization. In the mouse model, cortical neuronal activation promoted microglial M2 polarization whereas cortical neuronal inhibition decreased microglial M2 polarization in GBM xenografts. miR-200c-3p knockdown in cortical neurons impaired microglial M2 polarization and GBM xenograft growth, even when cortical neurons were activated. Treatment with the anti-seizure medication levetiracetam impaired neuronal activation and subsequently reduced neuron-mediated microglial M2 polarization. These findings indicated that hypoxic GSC-induced neuron activation promotes GBM progression by polarizing microglia via the exosomal miR-200c-3p/ZC3H13/DUSP9/p-ERK pathway. Levetiracetam, an antiepileptic drug, blocks the abnormal activation of neurons in GBM and impairs activity-dependent GBM progression. See related commentary by Cui et al., p. 1073.

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.

Sound processing in the cricket brain: evidence for a pulse duration filter.

The auditory system of female crickets allows them to specifically recognize and approach the species-specific male calling song, defined by sound pulses and silent intervals. Auditory brain neurons form a delay-line and coincidence detector network tuned to the pulse period of the male song. We analyzed the impact of changes in pulse duration on the behavior and the responses of the auditory neurons and the network. We confirm that the ascending neuron AN1 and the local neuron LN2 copy the temporal structure of the song. During ongoing long sound pulses, the delay-line neuron LN5 shows additional rebound responses and the coincidence detector neuron LN3 can generate additional bursts of activity, indicating that these may be driven by intrinsic oscillations of the network. Moreover, the response of the feature detector neuron LN4 is shaped by a combination of inhibitory and excitatory synaptic inputs, and LN4 responds even to long sound pulses with a short depolarization and burst of spikes, like to a sound pulse of natural duration. This response property of LN4 indicates a selective auditory pulse duration filter mechanism of the pattern recognition network, which is tuned to the duration of natural pulses. Comparing the tuning of the phonotactic behavior with the tuning of the local auditory brain neurons to the same test patterns, we find no evidence that a modulation of the phonotactic behavior is reflected at the level of the feature detector neurons. This rather suggests that steering to nonattractive pulse patterns is organized at the thoracic level.NEW & NOTEWORTHY Pulse period selectivity has been reported for the cricket delay-line and coincidence detector network, whereas pulse duration selectivity is evident from behavioral tests. Pulses of increasing duration elicit responses in the pattern recognition neurons, which do not parallel the behavioral responses and indicate additional processing mechanisms. Long sound pulses elicit rhythmic rebound activity and additional bursts, whereas the feature detector neuron reveals a pulse duration filter, expanding our understanding of the pattern recognition process.

Metal-organic framework materials promote neural differentiation of dental pulp stem cells in spinal cord injury

Spinal cord injury (SCI) is accompanied by loss of Zn2+, which is an important cause of glutamate excitotoxicity and death of local neurons as well as transplanted stem cells. Dental pulp stem cells (DPSCs) have the potential for neural differentiation and play an immunomodulatory role in the microenvironment, making them an ideal cell source for the repair of central nerve injury, including SCI. The zeolitic imidazolate framework 8 (ZIF-8) is usually used as a drug and gene delivery carrier, which can release Zn2+ sustainedly in acidic environment. However, the roles of ZIF-8 on neural differentiation of DPSCs and the effect of combined treatment on SCI have not been explored. ZIF-8-introduced DPSCs were loaded into gelatin methacryloyl (GelMA) hydrogel and in situ injected into the injured site of SCI rats. Under the effect of ZIF-8, axon number and axon length of DPSCs-differentiated neuro-like cells were significantly increased. In addition, ZIF-8 protected transplanted DPSCs from apoptosis in the damaged microenvironment. ZIF-8 promotes neural differentiation and angiogenesis of DPSCs by activating the Mitogen-activated protein kinase (MAPK) signaling pathway, which is a promising transport nanomaterial for nerve repair.

Structural and functional changes of deep layer pyramidal neurons surrounding microelectrode arrays implanted in rat motor cortex.

Devices capable of recording or stimulating neuronal signals have created new opportunities to understand normal physiology and treat sources of pathology in the brain. However, it is possible that the tissue response to implanted electrodes may influence the nature of the signals detected or stimulated. In this study, we characterized structural and functional changes in deep layer pyramidal neurons surrounding silicon or polyimide-based electrodes implanted in the motor cortex of rats. Devices were captured in 300µm-thick tissue slices collected at the 1 or 6 week time point post-implantation, and individual neurons were assessed using a combination of whole-cell electrophysiology and 2-photon imaging. We observed disrupted dendritic arbors and a significant reduction in spine densities in neurons surrounding devices. These effects were accompanied by a decrease in the frequency of spontaneous excitatory post-synaptic currents, a reduction in sag amplitude, an increase in spike frequency adaptation, and an increase in filopodia density. We hypothesize that the effects observed in this study may contribute to the signal loss and instability that often accompany chronically implanted electrodes. STATEMENT OF SIGNIFICANCE: Implanted electrodes in the brain can be used to treat sources of pathology and understand normal physiology by recording or stimulating electrical signals generated by local neurons. However, a foreign body response following implantation undermines the performance of these devices. While several studies have investigated the biological mechanisms of device-tissue interactions through histology, transcriptomics, and imaging, our study is the first to directly interrogate effects on the function of neurons surrounding electrodes using single-cell electrophysiology. Additionally, we provide new, detailed assessments of the impacts of electrodes on the dendritic structure and spine morphology of neurons, and we assess effects for both traditional (silicon) and newer polymer electrode materials. These results reveal new potential mechanisms of electrode-tissue interactions.

Neuroinflammation catching nanobubbles for microglia-neuron unit modulation against epilepsy

Epilepsy is a common neurological disease caused by synchronous firing of hyperexcitable neurons. Currently, patients with epilepsy are typically treated with antiseizure medicines that work by interrupting the hyperexcitability or hypersynchrony of localized neurons or by inhibiting excitatory neurotransmission. However, these drugs do not treat the underlying causes of epilepsy, and nearly one-third of patients have seizures that cannot be controlled by these medications. Animal and clinical evidence suggests that inflammation caused by neuronal and non-neuronal cells within the epilepsy lesion could play a central role in seizure disorders. Here we report a gas-filled nanobubble (NB) conjugated with diammonium glycyrrhizinate (DG) drugs and sphingosine-1-phosphate (S1P) molecules (S1P@DG–NBs) on the lipid shell for targeted therapy and real-time ultrasound visualization applications against neuroinflammatory injury. Affinity of S1P@DG-NBs for the S1P receptor endows these NBs with enhanced targeting capability to the neuroinflammatory microenvironment of epilepsy, where the DG drugs modulate endothelium-microglia-neuron inflammation by inhibiting high-mobility group box 1 molecules and downregulating the Toll-like receptor 4 signaling pathway, resulting in anti-inflammatory M2 microglia that exert anti-epilepsy effects. Our results show that this technology can enhance visualization of epileptic brain and deliver drugs with anti-inflammatory and immunomodulatory properties to ameliorate seizures symptoms.

Sex-dependent noradrenergic modulation of premotor cortex during decision making.

Rodent premotor cortex (M2) integrates information from sensory and cognitive networks for action planning during goal-directed decision making. M2 function is regulated by cortical inputs and ascending neuromodulators, including norepinephrine (NE) released from the locus coeruleus (LC). LC-NE has been shown to modulate the signal to noise ratio of neural representations in target cortical regions, increasing the salience of relevant stimuli. Using rats performing a two-alternative forced choice task after administration of a β noradrenergic antagonist (propranolol), we show that β noradrenergic signaling is necessary for effective action plan signals in anterior M2. Loss of β noradrenergic signaling results in failure to suppress irrelevant action plans in anterior M2 disrupting decoding of cue related information, delaying decision times, and increasing trial omissions, particularly in females. Furthermore, we identify a potential mechanism for the sex bias in behavioral and neural changes after propranolol administration via differential expression of β2 noradrenergic receptor RNA across sexes in anterior M2, particularly on local inhibitory neurons. Overall, we show a critical role for β noradrenergic signaling in anterior M2 during decision making by suppressing irrelevant information to enable efficient action planning and decision making.

Nanorobot-Mediated Synchronized Neuron Activation.

Interactions between active materials lead to collective behavior and even intelligence beyond the capability of individuals. Such behaviors are prevalent in nature and can be observed in animal colonies, providing these species with diverse capacities for communication and cooperation. In artificial systems, however, collective intelligence systems interacting with biological entities remains unexplored. Herein, we describe black (B)-TiO2@N/Au nanorobots interacting through photocatalytic pure water splitting-induced electrophoresis that exhibit periodic swarming oscillations under programmed near-infrared light. The periodic chemical-electric field generated by the oscillating B-TiO2@N/Au nanorobot swarm leads to local neuron activation in vitro. The field oscillations and neurotransmission from synchronized neurons further trigger the resonance oscillation of neuron populations without synaptic contact (about 2 mm spacing), in different ways from normal neuron oscillation requiring direct contact. We envision that the oscillating nanorobot swarm platforms will shed light on contactless communication of neurons and offer tools to explore interactions between neurons.

Normative and mechanistic model of an adaptive circuit for efficient encoding and feature extraction

One major question in neuroscience is how to relate connectomes to neural activity, circuit function, and learning. We offer an answer in the peripheral olfactory circuit of the Drosophila larva, composed of olfactory receptor neurons (ORNs) connected through feedback loops with interconnected inhibitory local neurons (LNs). We combine structural and activity data and, using a holistic normative framework based on similarity-matching, we formulate biologically plausible mechanistic models of the circuit. In particular, we consider a linear circuit model, for which we derive an exact theoretical solution, and a nonnegative circuit model, which we examine through simulations. The latter largely predicts the ORN [Formula: see text] LN synaptic weights found in the connectome and demonstrates that they reflect correlations in ORN activity patterns. Furthermore, this model accounts for the relationship between ORN [Formula: see text] LN and LN-LN synaptic counts and the emergence of different LN types. Functionally, we propose that LNs encode soft cluster memberships of ORN activity, and partially whiten and normalize the stimulus representations in ORNs through inhibitory feedback. Such a synaptic organization could, in principle, autonomously arise through Hebbian plasticity and would allow the circuit to adapt to different environments in an unsupervised manner. We thus uncover a general and potent circuit motif that can learn and extract significant input features and render stimulus representations more efficient. Finally, our study provides a unified framework for relating structure, activity, function, and learning in neural circuits and supports the conjecture that similarity-matching shapes the transformation of neural representations.

Phase relations of interneuronal activity relative to theta rhythm.

The theta rhythm plays a crucial role in synchronizing neural activity during attention and memory processes. However, the mechanisms behind the formation of neural activity during theta rhythm generation remain unknown. To address this, we propose a mathematical model that explains the distribution of interneurons in the CA1 field during the theta rhythm phase. Our model consists of a network of seven types of interneurons in the CA1 field that receive inputs from the CA3 field, entorhinal cortex, and local pyramidal neurons in the CA1 field. By adjusting the parameters of the connections in the model. We demonstrate that it is possible to replicate the experimentally observed phase relations between interneurons and the theta rhythm. Our model predicts that populations of interneurons receive unimodal excitation and inhibition with coinciding peaks, and that excitation dominates to determine the firing dynamics of interneurons.

Reduction of oxytocin-containing neurons and enhanced glymphatic activity in the hypothalamic paraventricular nucleus of patients with type 2 diabetes mellitus

Evidence from animal experiments has shown that the hypothalamic paraventricular nucleus (PVN) plays a key role in regulating body weight and blood glucose levels. However, it is unclear whether neuron populations in the human PVN are involved in the development of type 2 diabetes mellitus (T2DM). To address this, we investigated the neuronal and glial populations in the PVN of 26 T2DM patients and 20 matched controls. Our findings revealed a significant reduction in oxytocin (Oxt) neuron density in the PVN of T2DM patients compared to controls, while other neuronal populations remained unchanged. This suggests that Oxt neurons may play a specific role in the pathophysiology of T2DM. Interestingly, the reduction in Oxt neurons was accompanied by a decreased melanocortinergic input in to the PVN as reflected by a reduction in alpha-MSH immunoreactivity. We also analysed two glial cell populations, as they are important for maintaining a healthy neural microenvironment. We found that microglial density, phagocytic capacity, and their proximity to neurons were not altered in T2DM patients, indicating that the loss of Oxt neurons is independent of changes in microglial immunity. However, we did observe a reduction in the number of astrocytes, which are crucial for providing trophic support to local neurons. Moreover, a specific subpopulation of astrocytes characterized by aquaporin 4 expression was overrepresented in T2DM patients. Since this subset of astrocytes is linked to the glymphatic system, their overrepresentation might point to alterations in the hypothalamic waste clearance system in T2DM. Our study shows selective loss of Oxt neurons in the PVN of T2DM individuals in association with astrocytic reduction and gliovascular remodelling. Therefore, hypothalamic Oxt neurons may represent a potential target for T2DM treatment modalities.