Subgroups Of Neurons Research Articles

Prolonged Differentiation of Neuron-Astrocyte Co-Cultures Results in Emergence of Dopaminergic Neurons.

Dopamine is present in a subgroup of neurons that are vital for normal brain functioning. Disruption of the dopaminergic system, e.g., by chemical compounds, contributes to the development of Parkinson's disease and potentially some neurodevelopmental disorders. Current test guidelines for chemical safety assessment do not include specific endpoints for dopamine disruption. Therefore, there is a need for the human-relevant assessment of (developmental) neurotoxicity related to dopamine disruption. The aim of this study was to determine the biological domain related to dopaminergic neurons of a human stem cell-based in vitro test, the human neural progenitor test (hNPT). Neural progenitor cells were differentiated in a neuron-astrocyte co-culture for 70 days, and dopamine-related gene and protein expression was investigated. Expression of genes specific for dopaminergic differentiation and functioning, such as LMX1B, NURR1, TH, SLC6A3, and KCNJ6, were increasing by day 14. From day 42, a network of neurons expressing the catecholamine marker TH and the dopaminergic markers VMAT2 and DAT was present. These results confirm stable gene and protein expression of dopaminergic markers in hNPT. Further characterization and chemical testing are needed to investigate if the model might be relevant in a testing strategy to test the neurotoxicity of the dopaminergic system.

Three-dimensional highly porous hydrogel scaffold for neural circuit dissection and modulation.

Biomimetic brain structures and artificial neural networks have provided a simplified strategy for quantitatively investigating the complex structural and functional characteristics of highly interconnected neural networks. To achieve this, three-dimensional (3D) cell culture approaches have attracted much attention, which can mimic cell-cell interactions at the organism level and help better understand the function of specific neurons and neuronal networks than traditional two-dimensional cell culture methods. However, 3D scaffolds similar to the natural extracellular matrix to support the culturing, recording, and manipulation of neurons have long been an unresolved challenge. To resolve this, 3D hydrogel scaffolds can be fabricated via an innovative thermal treatment followed by an esterification process. A highly porous microstructure was formed within the bulk hydrogel scaffold, which showed a high porosity of 91% and a low Young's modulus of 6.11 kPa. Due to the merits of the fabricated hydrogel scaffolds, we constructed 3D neural networks and detected spontaneous action potentials in vitro. We successfully induced seizure-like waveforms in 3D cultured neurons and suppressed hyperactivated discharges by selectively activating γ-aminobutyric acid-ergic (GABAergic) interneurons. These results prove the advantages of our hydrogel scaffolds and demonstrate their application potential in the accurate dissection of neural circuits, which may help develop effective treatments for various neurological disorders. STATEMENT OF SIGNIFICANCE: While 3D cell culture approaches have attracted much attention and offer more advantages than two-dimensional cell culture methods, 3D scaffolds similar to the natural extracellular matrix to support the culturing, recording, and manipulation of neurons have long been an unresolved challenge. Herein, we developed a simplified and low-cost strategy for fabricating highly porous and cytocompatible hydrogel scaffolds for the construction of three-dimensional (3D) neural networks in vitro. The cultured 3D neural networks can mimic the in vivo connection among different neuron subgroups and help accurately dissect and manipulate the structure and function of specific neural circuits.

Nutraceuticals and phytotherapeutics for holistic management of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis" (ALS) is a progressive neuronal disorder that affects sensory neurons in the brain and spinal cord, causing loss of muscle control. Moreover, additional neuronal subgroups as well as glial cells such as microglia, astrocytes, and oligodendrocytes are also thought to play a role in the aetiology. The disease affects upper motor neurons and lowers motor neurons and leads to that either lead to muscle weakness and wasting in the arms, legs, trunk and periventricular area. Oxidative stress, excitotoxicity, programmed cell death, altered neurofilament activity, anomalies in neurotransmission, abnormal protein processing and deterioration, increased inflammation, and mitochondrial dysfunction may all play a role in the progression of ALS. There are presently hardly FDA-approved drugs used to treat ALS, and they are only beneficial in slowing the progression of the disease and enhancing functions in certain individuals with ALS, not really in curing or preventing the illness. These days, researchers focus on understanding the pathogenesis of the disease by targeting several mechanisms aiming to develop successful treatments for ALS. This review discusses the epidemiology, risk factors, diagnosis, clinical features, pathophysiology, and disease management. The compilation focuses on alternative methods for the management of symptoms of ALS with nutraceuticals and phytotherapeutics.

A multi-class logistic regression algorithm to reliably infer network connectivity from cell membrane potentials

In neuroscience, the structural connectivity matrix of synaptic weights between neurons is one of the critical factors that determine the overall function of a network of neurons. The mechanisms of signal transduction have been intensively studied at different time and spatial scales and both the cellular and molecular levels. While a better understanding and knowledge of some basic processes of information handling by neurons has been achieved, little is known about the organization and function of complex neuronal networks. Experimental methods are now available to simultaneously monitor the electrical activity of a large number of neurons in real time. The analysis of the data related to the activities of individual neurons can become a very valuable tool for the study of the dynamics and architecture of neural networks. In particular, advances in optical imaging techniques allow us to record up to thousands of neurons nowadays. However, most of the efforts have been focused on calcium signals, that lack relevant aspects of cell activity. In recent years, progresses in the field of genetically encoded voltage indicators have shown that imaging signals could be well suited to record spiking and synaptic events from a large population of neurons. Here, we present a methodology to infer the connectivity of a population of neurons from their voltage traces. At first, putative synaptic events were detected. Then, a multi-class logistic regression was used to fit the putative events to the spiking activities and a penalization term was allowed to regulate the sparseness of the inferred network. The proposed Multi-Class Logistic Regression with L1 penalization (MCLRL) was benchmarked against data obtained from in silico network simulations. MCLRL properly inferred the connectivity of all tested networks, as indicated by the Matthew correlation coefficient (MCC). Importantly, MCLRL was accomplished to reconstruct the connectivity among subgroups of neurons sampled from the network. The robustness of MCLRL to noise was also assessed and the performances remained high (MCC>0.95) even in extremely high noise conditions (>95% noisy events). Finally, we devised a procedure to determine the optimal MCLRL regularization term, which allows us to envision its application to experimental data.

Unbiased analysis of the dorsal root ganglion after peripheral nerve injury: no neuronal loss, no gliosis, but satellite glial cell plasticity.

Pain syndromes are often accompanied by complex molecular and cellular changes in dorsal root ganglia (DRG). However, the evaluation of cellular plasticity in the DRG is often performed by heuristic manual analysis of a small number of representative microscopy image fields. In this study, we introduce a deep learning-based strategy for objective and unbiased analysis of neurons and satellite glial cells (SGCs) in the DRG. To validate the approach experimentally, we examined serial sections of the rat DRG after spared nerve injury (SNI) or sham surgery. Sections were stained for neurofilament, glial fibrillary acidic protein (GFAP), and glutamine synthetase (GS) and imaged using high-resolution large-field (tile) microscopy. After training of deep learning models on consensus information of different experts, thousands of image features in DRG sections were analyzed. We used known (GFAP upregulation), controversial (neuronal loss), and novel (SGC phenotype switch) changes to evaluate the method. In our data, the number of DRG neurons was similar 14 d after SNI vs sham. In GFAP-positive subareas, the percentage of neurons in proximity to GFAP-positive cells increased after SNI. In contrast, GS-positive signals, and the percentage of neurons in proximity to GS-positive SGCs decreased after SNI. Changes in GS and GFAP levels could be linked to specific DRG neuron subgroups of different size. Hence, we could not detect gliosis but plasticity changes in the SGC marker expression. Our objective analysis of DRG tissue after peripheral nerve injury shows cellular plasticity responses of SGCs in the whole DRG but neither injury-induced neuronal death nor gliosis.

0193 Moving While Sleeping: On the Paradoxical Co-occurrence of Muscle Atonia and Twitching

Abstract Introduction During active (or REM) sleep, discreet, jerky movements called myoclonic twitches occur against a background of muscle atonia. The neural mechanisms that allow these two seemingly contradictory phenomena to co-occur remain unclear. One view holds that twitches are produced when a large descending motor signal overpowers the inhibition on spinal motor neurons. An alternative view is that atonia and twitching are coordinated by the same brainstem structures that produce and regulate active sleep. One such structure is the sublaterodorsal tegmental nucleus (SLD), which plays a key role in adult rats to the production of atonia, but whose contribution to twitching has not been examined. Here, we investigated the relationship of SLD neurons to atonia and twitching during a period in early development when twitching is abundant. Methods We recorded extracellular neural activity from the SLD in 8 12-day-old (P12) head-fixed rats as they cycled freely between sleep and wake. To assess the relationship between twitches and neural activity, we also recorded limb movements using high-speed video. Results Consistent with the adult literature, the majority of SLD neurons (35/56) were significantly more active during periods of sleep-related atonia. Interestingly, a subgroup of neurons (n=15) was inhibited at the onset of a burst of twitches, whereas another subgroup of neurons (n=26) was excited around the onset of a burst of twitches. Thus, together, the activity of 41 of 56 SLD neurons was modulated by twitches. Conclusion These results demonstrate that the activity of SLD neurons is associated with both atonia and twitching. This finding suggests that these two early-developing components of active sleep are coordinated within the brainstem. These initial findings open new avenues for further research into the neural mechanisms that coordinate the co-occurrence of twitching and atonia during active sleep. Support (If Any) This research was supported by R37-HD081168 awarded to M.S.B.

Decreasing dorsal cochlear nucleus activity ameliorates noise-induced tinnitus perception in mice

BackgroundThe dorsal cochlear nucleus (DCN) is a region known to integrate somatosensory and auditory inputs and is identified as a potential key structure in the generation of phantom sound perception, especially noise-induced tinnitus. Yet, how altered homeostatic plasticity of the DCN induces and maintains the sensation of tinnitus is not clear. Here, we chemogenetically decrease activity of a subgroup of DCN neurons, Ca2+/Calmodulin kinase 2 α (CaMKII α)-positive DCN neurons, using Gi-coupled human M4 Designer Receptors Exclusively Activated by Designer Drugs (hM4Di DREADDs), to investigate their role in noise-induced tinnitus.ResultsMice were exposed to loud noise (9–11kHz, 90dBSPL, 1h, followed by 2h of silence), and auditory brainstem responses (ABRs) and gap prepulse inhibition of acoustic startle (GPIAS) were recorded 2 days before and 2 weeks after noise exposure to identify animals with a significantly decreased inhibition of startle, indicating tinnitus but without permanent hearing loss. Neuronal activity of CaMKII α+ neurons expressing hM4Di in the DCN was lowered by administration of clozapine-N-oxide (CNO). We found that acutely decreasing firing rate of CaMKII α+ DCN units decrease tinnitus-like responses (p = 3e −3, n = 11 mice), compared to the control group that showed no improvement in GPIAS (control virus; CaMKII α-YFP + CNO, p = 0.696, n = 7 mice). Extracellular recordings confirmed CNO to decrease unit firing frequency of CaMKII α-hM4Di+ mice and alter best frequency and tuning width of response to sound. However, these effects were not seen if CNO had been previously administered during the noise exposure (n = 6 experimental and 6 control mice).ConclusionWe found that lowering DCN activity in mice displaying tinnitus-related behavior reduces tinnitus, but lowering DCN activity during noise exposure does not prevent noise-induced tinnitus. Our results suggest that CaMKII α-positive cells in the DCN are not crucial for tinnitus induction but play a significant role in maintaining tinnitus perception in mice.

Neural underpinnings of emotion regulation subgroups in remitted patients with recently diagnosed bipolar disorder

Neuroimaging studies of bipolar disorder (BD) generally involve comparison with healthy controls (HC), which may mask neurobiological variability within the disorder. This study aims to assess the neural underpinnings of potential subgroups of BD patients based on functional activity in the emotion regulation network and its relation to illness characteristics and relapse risk. Eighty-seven remitted patients with recently diagnosed BD and 66 HC underwent functional magnetic resonance imaging (fMRI) while performing an emotion regulation task. Patients were re-assessed with clinical interviews after 16 (±5) months. Data-driven hierarchical cluster analysis was employed to investigate ‘neuronal subgroups’ of patients based on their neuronal activity in a pre-defined emotion regulation network. Relations between neuronal subgroups and illness characteristics and relapse rates were examined. Patients were allocated into two subgroups. Subgroup 1 (n=62, 75%) was characterized by exaggerated bilateral amygdala reactivity but normal prefrontal and temporo-parietal activation. Subgroup 2 (n= 22, 25%) showed widespread hypo-activity within all emotion regulation regions. Both subgroups were less successful at down-regulating their emotions than HC (F(2,146)=5.33, p=.006, ηp2=.07). Patients in subgroup 2 had a history of more and longer mixed episodes (ps≤.01). Importantly, heightened amygdala activity across all patients was associated with increased risk of relapse during a 16-month follow-up period (β=3.36, 95% CI [1.49;550.35], N=60, p=.03). The identified neuronal subgroups of patients with either amygdala hyper-activity or broad network hypo-activity during emotion regulation points to neurobiological heterogeneity among remitted patients with BD. Heightened amygdala reactivity may be a neuronal target for personalized treatments to prevent relapse.

Different Approximation Methods for Calculation of Integrated Information Coefficient in the Brain during Instrumental Learning.

The amount of integrated information, , proposed in an integrated information theory (IIT) is useful to describe the degree of brain adaptation to the environment. However, its computation cannot be precisely performed for a reasonable time for time-series spike data collected from a large count of neurons.. Therefore, was only used to describe averaged activity of a big group of neurons, and the behavior of small non-brain systems. In this study, we reported on ways for fast and precise calculation using different approximation methods for Φ calculation in neural spike data, and checked the capability of to describe a degree of adaptation in brain neural networks. We show that during instrumental learning sessions, all applied approximation methods reflect temporal trends of in the rat hippocampus. The value of is positively correlated with the number of successful acts performed by a rat. We also show that only one subgroup of neurons modulates their Φ during learning. The obtained results pave the way for application of to investigate plasticity in the brain during the acquisition of new tasks.

Primate anterior insular cortex represents economic decision variables proposed by prospect theory

In humans, risk attitude is highly context-dependent, varying with wealth levels or for different potential outcomes, such as gains or losses. These behavioral effects have been modelled using prospect theory, with the key assumption that humans represent the value of each available option asymmetrically as a gain or loss relative to a reference point. It remains unknown how these computations are implemented at the neuronal level. Here we show that macaques, like humans, change their risk attitude across wealth levels and gain/loss contexts using a token gambling task. Neurons in the anterior insular cortex (AIC) encode the ‘reference point’ (i.e., the current wealth level of the monkey) and reflect ‘loss aversion’ (i.e., option value signals are more sensitive to change in the loss than in the gain context) as postulated by prospect theory. In addition, changes in the activity of a subgroup of AIC neurons correlate with the inter-trial fluctuations in choice and risk attitude. Taken together, we show that the primate AIC in risky decision-making may be involved in monitoring contextual information used to guide the animal’s willingness to accept risk.

FACS-Based Neuronal Cell Type-Specific RNA Isolation and Alternative Splicing Analysis.

Alternative splicing of pre-mRNAs expands the coding abilities of genomes by generating distinct transcription variants from individual genes. It contributes to the marvelous complexity of the transcriptome in neurons. Given the differential expression of alternative splicing regulators and diversity in alternative splicing programs in neuronal subpopulations, it is urgent and necessary to develop methods to efficiently isolate diverse subgroups of neurons and analyze their transcriptomic diversity. Here, we describe a protocol to isolate RNA from specific neuronal types using a fluorescence-activated cell sorting (FACS)-based method to analyze alternative splicing events in a cell type-specific manner. The method is universally applicable to analyze alternative splicing in fluorescent protein-labeled neuronal types. It was optimized to preservethe transcription state and improve efficiency in cell suspension purification. With our protocol, fluorescent protein-labeled neurons could be efficiently purified. The transcription states suitable for gene expression and alternative splicing analysis could be well-preserved.

Axonal Projection Patterns of the Dorsal Interneuron Populations in the Embryonic Hindbrain.

Unraveling the inner workings of neural circuits entails understanding the cellular origin and axonal pathfinding of various neuronal groups during development. In the embryonic hindbrain, different subtypes of dorsal interneurons (dINs) evolve along the dorsal-ventral (DV) axis of rhombomeres and are imperative for the assembly of central brainstem circuits. dINs are divided into two classes, class A and class B, each containing four neuronal subgroups (dA1-4 and dB1-4) that are born in well-defined DV positions. While all interneurons belonging to class A express the transcription factor Olig3 and become excitatory, all class B interneurons express the transcription factor Lbx1 but are diverse in their excitatory or inhibitory fate. Moreover, within every class, each interneuron subtype displays its own specification genes and axonal projection patterns which are required to govern the stage-by-stage assembly of their connectivity toward their target sites. Remarkably, despite the similar genetic landmark of each dINs subgroup along the anterior-posterior (AP) axis of the hindbrain, genetic fate maps of some dA/dB neuronal subtypes uncovered their contribution to different nuclei centers in relation to their rhombomeric origin. Thus, DV and AP positional information has to be orchestrated in each dA/dB subpopulation to form distinct neuronal circuits in the hindbrain. Over the span of several decades, different axonal routes have been well-documented to dynamically emerge and grow throughout the hindbrain DV and AP positions. Yet, the genetic link between these distinct axonal bundles and their neuronal origin is not fully clear. In this study, we reviewed the available data regarding the association between the specification of early-born dorsal interneuron subpopulations in the hindbrain and their axonal circuitry development and fate, as well as the present existing knowledge on molecular effectors underlying the process of axonal growth.

The Mean Field Approach for Populations of Spiking Neurons.

Mean field theory is a device to analyze the collective behavior of a dynamical system comprising many interacting particles. The theory allows to reduce the behavior of the system to the properties of a handful of parameters. In neural circuits, these parameters are typically the firing rates of distinct, homogeneous subgroups of neurons. Knowledge of the firing rates under conditions of interest can reveal essential information on both the dynamics of neural circuits and the way they can subserve brain function. The goal of this chapter is to provide an elementary introduction to the mean field approach for populations of spiking neurons. We introduce the general idea in networks of binary neurons, starting from the most basic results and then generalizing to more relevant situations. This allows to derive the mean field equations in a simplified setting. We then derive the mean field equations for populations of integrate-and-fire neurons. An effort is made to derive the main equations of the theory using only elementary methods from calculus and probability theory. The chapter ends with a discussion of the assumptions of the theory and some of the consequences of violating those assumptions. This discussion includes an introduction to balanced and metastable networks and a brief catalogue of successful applications of the mean field approach to the study of neural circuits.

Stereotaxic Viral Injection and Gradient-Index Lens Implantation for Deep Brain In Vivo Calcium Imaging.

A miniature fluorescence microscope (miniscope) is a potent tool for in vivo calcium imaging from freely behaving animals. It offers several advantages over conventional multi-photon calcium imaging systems: (1) compact; (2) light-weighted; (3) affordable; and (4) allows recording from freely behaving animals. This protocol describes brain surgeries for deep brain in vivo calcium imaging using a custom-developed miniscope recording system. The preparation procedure consists of three steps, including (1) stereotaxically injecting the virus at the desired brain region of a mouse brain to label a specific subgroup of neurons with genetically encoded calcium sensor; (2) implantation of gradient-index (GRIN) lens that can relay calcium image from deep brain region to the miniscope system; and (3) affixing the miniscope holder over the mouse skull where miniscope can be attached later. To perform in vivo calcium imaging, the miniscope is fastened onto the holder, and neuronal calcium images are collected along with simultaneous behavior recordings. The present surgery protocol is compatible with any commercial or custom-built single-photon and two-photon imaging systems for deep brain in vivo calcium imaging.

Stereotaxic Viral Injection and Gradient-Index Lens Implantation for Deep Brain <em>In Vivo</em> Calcium Imaging

A miniature fluorescence microscope (miniscope) is a potent tool for in vivo calcium imaging from freely behaving animals. It offers several advantages over conventional multi-photon calcium imaging systems: (1) compact; (2) light-weighted; (3) affordable; and (4) allows recording from freely behaving animals. This protocol describes brain surgeries for deep brain in vivo calcium imaging using a custom-developed miniscope recording system. The preparation procedure consists of three steps, including (1) stereotaxically injecting the virus at the desired brain region of a mouse brain to label a specific subgroup of neurons with genetically encoded calcium sensor; (2) implantation of gradient-index (GRIN) lens that can relay calcium image from deep brain region to the miniscope system; and (3) affixing the miniscope holder over the mouse skull where miniscope can be attached later. To perform in vivo calcium imaging, the miniscope is fastened onto the holder, and neuronal calcium images are collected along with simultaneous behavior recordings. The present surgery protocol is compatible with any commercial or custom-built single-photon and two-photon imaging systems for deep brain in vivo calcium imaging.

Narrative event segmentation in the cortical reservoir.

Recent research has revealed that during continuous perception of movies or stories, humans display cortical activity patterns that reveal hierarchical segmentation of event structure. Thus, sensory areas like auditory cortex display high frequency segmentation related to the stimulus, while semantic areas like posterior middle cortex display a lower frequency segmentation related to transitions between events. These hierarchical levels of segmentation are associated with different time constants for processing. Likewise, when two groups of participants heard the same sentence in a narrative, preceded by different contexts, neural responses for the groups were initially different and then gradually aligned. The time constant for alignment followed the segmentation hierarchy: sensory cortices aligned most quickly, followed by mid-level regions, while some higher-order cortical regions took more than 10 seconds to align. These hierarchical segmentation phenomena can be considered in the context of processing related to comprehension. In a recently described model of discourse comprehension word meanings are modeled by a language model pre-trained on a billion word corpus. During discourse comprehension, word meanings are continuously integrated in a recurrent cortical network. The model demonstrates novel discourse and inference processing, in part because of two fundamental characteristics: real-world event semantics are represented in the word embeddings, and these are integrated in a reservoir network which has an inherent gradient of functional time constants due to the recurrent connections. Here we demonstrate how this model displays hierarchical narrative event segmentation properties beyond the embeddings alone, or their linear integration. The reservoir produces activation patterns that are segmented by a hidden Markov model (HMM) in a manner that is comparable to that of humans. Context construction displays a continuum of time constants across reservoir neuron subsets, while context forgetting has a fixed time constant across these subsets. Importantly, virtual areas formed by subgroups of reservoir neurons with faster time constants segmented with shorter events, while those with longer time constants preferred longer events. This neurocomputational recurrent neural network simulates narrative event processing as revealed by the fMRI event segmentation algorithm provides a novel explanation of the asymmetry in narrative forgetting and construction. The model extends the characterization of online integration processes in discourse to more extended narrative, and demonstrates how reservoir computing provides a useful model of cortical processing of narrative structure.

Cochlear Synaptic Degeneration and Regeneration After Noise: Effects of Age and Neuronal Subgroup

In CBA/CaJ mice, confocal analysis has shown that acoustic overexposure can immediately destroy synapses between auditory-nerve fibers (ANFs) and their peripheral targets, the inner hair cells (IHCs), and that years later, a corresponding number of ANF cell bodies degenerate. In guinea pig, post-exposure disappearance of pre-synaptic ribbons can be equally dramatic, however, post-exposure recovery to near-baseline counts has been reported. Since confocal counts are confounded by thresholding issues, the fall and rise of synaptic ribbon counts could represent “regeneration,” i.e., terminal retraction, re-extension and synaptogenesis, or “recovery,” i.e., down- and subsequent up-regulation of synaptic markers. To clarify, we counted pre-synaptic ribbons, assessed their juxtaposition with post-synaptic receptors, measured the extension of ANF terminals, and quantified the spatial organization and size gradients of these synaptic elements around the hair cell. Present results in guinea pigs exposed as adults (14 months), along with prior results in juveniles (1 month), suggest there is post-exposure neural regeneration in the guinea pig, but not the CBA/CaJ mouse, and that this regenerative capacity extends into adulthood. The results also show, for the first time, that the acute synaptic loss is concentrated on the modiolar side of IHCs, consistent with a selective loss of the high-threshold ANFs with low spontaneous rates. The morphological similarities between the post-exposure neurite extension and synaptogenesis, seen spontaneously in the guinea pig, and in CBA/CaJ only with forced overexpression of neurotrophins, suggest that the key difference may be in the degree of sustained or injury-induced expression of these signaling molecules in the cochlea.

Deciphering an AgRP-serotoninergic neural circuit in distinct control of energy metabolism from feeding

Contrasting to the established role of the hypothalamic agouti-related protein (AgRP) neurons in feeding regulation, the neural circuit and signaling mechanisms by which they control energy expenditure remains unclear. Here, we report that energy expenditure is regulated by a subgroup of AgRP neurons that send non-collateral projections to neurons within the dorsal lateral part of dorsal raphe nucleus (dlDRN) expressing the melanocortin 4 receptor (MC4R), which in turn innervate nearby serotonergic (5-HT) neurons. Genetic manipulations reveal a bi-directional control of energy expenditure by this circuit without affecting food intake. Fiber photometry and electrophysiological results indicate that the thermo-sensing MC4RdlDRN neurons integrate pre-synaptic AgRP signaling, thereby modulating the post-synaptic serotonergic pathway. Specifically, the MC4RdlDRN signaling elicits profound, bi-directional, regulation of body weight mainly through sympathetic outflow that reprograms mitochondrial bioenergetics within brown and beige fat while feeding remains intact. Together, we suggest that this AgRP neural circuit plays a unique role in persistent control of energy expenditure and body weight, hinting next-generation therapeutic approaches for obesity and metabolic disorders.

P2Y 1 receptor modulation of Ih in the preBötzinger inspiratory rhythm generator may underlie the ATP‐mediated attenuation of the hypoxic respiratory depression

Premature infants often stop breathing briefly (apnea) because the brainstem respiratory network is still immature (apnea of prematurity, AOP). During these apneas, oxygen levels fall (hypoxia) triggering a biphasic hypoxic ventilatory response comprising an initial increase in ventilation followed by a centrally mediated secondary depression that can be life-threatening. Caffeine is used to stimulate breathing in AOP. However, ~20% of these infants do not respond to caffeine. Thus, alternate therapies are needed. Recent data suggest that during hypoxia, ATP is released in the preBötzinger Complex (preBötC, inspiratory rhythm generator) where it acts via P2Y1 receptors (Rs) to excite inspiratory neurons, increase ventilation and attenuate the secondary hypoxic depression. A mechanistic understanding of this P2Y1R excitation is lacking. Preliminary whole-cell analysis of inspiratory preBötC neurons in vitro revealed P2Y1R currents that reverse near -40 mV and increase in amplitude with neuron hyperpolarization. Based on these data, we tested the hypotheses that the increase in inspiratory frequency evoked by ATP in the preBötC in vitro and the ATP-mediated increase in ventilation during hypoxia in vivo reflects P2Y1R potentiation of the hyperpolarization-activated inward current, Ih (carried by cyclic nucleotide–gated, HCN, channels). Application of MRS2365 (P2Y1R agonist, 100 µM) to Ih-expressing inspiratory preBötC neurons in rhythmic brainstem slices from neonatal rat potentiated Ih by 32±6% (at -100 mV, n=18) and depolarized voltage-dependence of Ih activation by ~10 mV. The MRS2365 inward current and its potentiation of Ih were blocked by the Ih blocker, ZD7288 (100 μM). ZD7288 also attenuated the MRS2365-evoked frequency increase by 60-90%. Ih currents in preBötC neurons were sensitive to ZD7288 (100 µM) but not ivabradine (30 µM), suggesting HCN2 but not HCN1,4 subunit involvement. In paralyzed, anesthetized, vagotomized ventilated adult rats, bilateral microinfusion of ZD7288 (250 µM, but not 100 µM) into the preBötC increased the secondary hypoxic (10% O2) depression by 68±23% (n=6) compared to rats that received aCSF microinfusion (n=4). This effect was regionally specific. If the bilateral microinfusions of ZD7288 were not both in the preBötC (e.g., 1 in preBötC and the other in BötC or rVRG), ZD7288 had no effect on the hypoxic ventilatory response. Finally, in anesthetized, vagotomized, spontaneously-breathing adult rats, unilateral reverse microdialysis of ZD7288 (100 µM) in the preBötC area (n=13) increased the hypoxic frequency depression by 20±6% (compared to aCSF, n=6). These data suggest that the P2Y1R excitation of the preBötC network is produced, in part, via potentiation of Ih in a subgroup of inspiratory neurons, and that potentiation of Ih in the preBötC attenuates the hypoxic ventilatory depression in adult rats. Data also identify the HCN2 subunit as a potential target for new strategies to counteract respiratory depression in AOP.

Weekend Light Shifts Evoke Persistent Drosophila Circadian Neural Network Desynchrony.

We developed a method for single-cell resolution longitudinal bioluminescence imaging of PERIOD (PER) protein and TIMELESS (TIM) oscillations in cultured male adult Drosophila brains that captures circadian circuit-wide cycling under simulated day/night cycles. Light input analysis confirms that CRYPTOCHROME (CRY) is the primary circadian photoreceptor and mediates clock disruption by constant light (LL), and that eye light input is redundant to CRY; 3-h light phase delays (Friday) followed by 3-h light phase advances (Monday morning) simulate the common practice of staying up later at night on weekends, sleeping in later on weekend days then returning to standard schedule Monday morning [weekend light shift (WLS)]. PER and TIM oscillations are highly synchronous across all major circadian neuronal subgroups in unshifted light schedules for 11 d. In contrast, WLS significantly dampens PER oscillator synchrony and rhythmicity in most circadian neurons during and after exposure. Lateral ventral neuron (LNv) oscillations are the first to desynchronize in WLS and the last to resynchronize in WLS. Surprisingly, the dorsal neuron group-3 (DN3s) increase their within-group synchrony in response to WLS. In vivo, WLS induces transient defects in sleep stability, learning, and memory that temporally coincide with circuit desynchrony. Our findings suggest that WLS schedules disrupt circuit-wide circadian neuronal oscillator synchrony for much of the week, thus leading to observed behavioral defects in sleep, learning, and memory.