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Behavioural time scale plasticity (BTSP) is non-Hebbian plasticity induced by integrating presynaptic and postsynaptic components separated by a behaviourally relevant time scale (seconds)1. BTSP in hippocampal CA1 neurons underlies place cell formation. However, the molecular mechanisms that enable synapse-specific plasticity on a behavioural time scale are unknown. Here we show that BTSP can be induced in a single dendritic spine using two-photon glutamate uncaging paired with postsynaptic current injection temporally separated by a behavioural time scale. Using an improved Ca2+/calmodulin-dependent kinase II (CaMKII) sensor, we did not detect CaMKII activation during this BTSP induction. Instead, we observed dendritic, delayed and stochastic CaMKII activation (DDSC) associated with Ca2+ influx and plateau potentials 10–100 s after BTSP induction. DDSC required both presynaptic and postsynaptic activity, which suggests that CaMKII can integrate these two signals. Also, optogenetically blocking CaMKII 15–30 s after the BTSP protocol inhibited synaptic potentiation, which indicated that DDSC is an essential mechanism of BTSP. IP3-dependent intracellular Ca2+ release facilitated both DDSC and BTSP. Thus, our study suggests that non-synapse-specific CaMKII activation provides an instructive signal with an extensive time window over tens of seconds during BTSP.Induction of behavioural time scale plasticity leads to dendritic, delayed and stochastic Ca2+/calmodulin-dependent kinase II activation, findings that clarify the mechanisms that underlie place cell formation. [ABSTRACT FROM AUTHOR]

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, it has been challenging to integrate information obtained from diverse experimental approaches. To address this challenge, we present a community-based, full-scale in silico model of the rat CA1 that integrates a broad range of experimental data, from synapse to network, including the reconstruction of its principal afferents, the Schaffer collaterals, and a model of the effects that acetylcholine has on the system. We tested and validated each model component and the final network model, and made input data, assumptions, and strategies explicit and transparent. The unique flexibility of the model allows scientists to potentially address a range of scientific questions. In this article, we describe the methods used to set up simulations to reproduce in vitro and in vivo experiments. Among several applications in the article, we focus on theta rhythm, a prominent hippocampal oscillation associated with various behavioral correlates and use our computer model to reproduce experimental findings. Finally, we make data, code, and model available through the hippocampushub.eu portal, which also provides an extensive set of analyses of the model and a user-friendly interface to facilitate adoption and usage. This community-based model represents a valuable tool for integrating diverse experimental data and provides a foundation for further research into the complex workings of the hippocampal CA1 region. Integrating data from different experimental approaches into one model is challenging. This study presents a community-based, full-scale in silico model of the rat hippocampal CA1 region that integrates diverse experimental data from synapse to network. [ABSTRACT FROM AUTHOR]

Inhibitory interneurons are pivotal components of cortical circuits. Beyond providing inhibition, they have been proposed to coordinate the firing of excitatory neurons within cell assemblies. While the roles of specific interneuron subtypes have been extensively studied, their influence on pyramidal cell synchrony in vivo remains elusive. Employing an all-optical approach in mice, we simultaneously recorded hippocampal interneurons and pyramidal cells and probed the network influence of individual interneurons using optogenetics. We demonstrate that CA1 interneurons form a functionally interconnected network that promotes synchrony through disinhibition during awake immobility, while preserving endogenous cell assemblies. Our network model underscores the importance of both cell assemblies and dense, unspecific interneuron connectivity in explaining our experimental findings, suggesting that interneurons may operate not only via division of labor but also through concerted activity. Interneurons control the timing of activation of excitatory neurons, but how single interneurons affect synchrony in vivo is unclear. This study shows that CA1 hippocampus interneurons form a functionally connected network that promotes synchrony between pyramidal cells at the single neuron level. [ABSTRACT FROM AUTHOR]

In calcium imaging studies, Ca2+ transients are commonly interpreted as neuronal action potentials (APs). However, our findings demonstrate that robust optical Ca2+ transients primarily stem from complex "AP-Plateaus", while simple APs lacking underlying depolarization envelopes produce much weaker photonic signatures. Under challenging in vivo conditions, these "AP-Plateaus" are likely to surpass noise levels, thus dominating the Ca2+ recordings. In spontaneously active neuronal culture, optical Ca2+ transients (OGB1-AM, GCaMP6f) exhibited approximately tenfold greater amplitude and twofold longer half-width compared to optical voltage transients (ArcLightD). The amplitude of the ArcLightD signal exhibited a strong correlation with the duration of the underlying membrane depolarization, and a weaker correlation with the presence of a fast sodium AP. Specifically, ArcLightD exhibited robust responsiveness to the slow "foot" but not the fast "trunk" of the neuronal AP. Particularly potent stimulators of optical signals in both Ca2+ and voltage imaging modalities were APs combined with plateau potentials (AP-Plateaus), resembling dendritic Ca2+ spikes or "UP states" in pyramidal neurons. Interestingly, even the spikeless plateaus (amplitude > 10 mV, duration > 200 ms) could generate conspicuous Ca2+ optical signals in neurons. Therefore, in certain circumstances, Ca2+ transients should not be interpreted solely as indicators of neuronal AP firing. [ABSTRACT FROM AUTHOR]

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

Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions, report an advancing gradient of dendritic theta phase along the basal-tuft axis, and describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find that spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states. Neurons receive their input in three dimensions via their dendrites, but how electrical activity in dendrites is organized is unknown. Here, the authors work out the distinct rules that govern activity across this 3D structure in different brain states. [ABSTRACT FROM AUTHOR]

The hippocampus is critical for memory and spatial navigation. The ability to map novel environments, as well as more abstract conceptual relationships, is fundamental to the cognitive flexibility that humans and other animals require to survive in a dynamic world. In this review, we survey recent advances in our understanding of how this flexibility is implemented anatomically and functionally by hippocampal circuitry, during both active exploration (online) and rest (offline). We discuss the advantages and limitations of spike timing–dependent plasticity and the more recently discovered behavioral timescale synaptic plasticity in supporting distinct learning modes in the hippocampus. Finally, we suggest complementary roles for these plasticity types in explaining many-shot and single-shot learning in the hippocampus and discuss how these rules could work together to support the learning of cognitive maps. [ABSTRACT FROM AUTHOR]

Hippocampal representations that underlie spatial memory undergo continuous refinement following formation1. Here, to track the spatial tuning of neurons dynamically during offline states, we used a new Bayesian learning approach based on the spike-triggered average decoded position in ensemble recordings from freely moving rats. Measuring these tunings, we found spatial representations within hippocampal sharp-wave ripples that were stable for hours during sleep and were strongly aligned with place fields initially observed during maze exploration. These representations were explained by a combination of factors that included preconfigured structure before maze exposure and representations that emerged during θ-oscillations and awake sharp-wave ripples while on the maze, revealing the contribution of these events in forming ensembles. Strikingly, the ripple representations during sleep predicted the future place fields of neurons during re-exposure to the maze, even when those fields deviated from previous place preferences. By contrast, we observed tunings with poor alignment to maze place fields during sleep and rest before maze exposure and in the later stages of sleep. In sum, the new decoding approach allowed us to infer and characterize the stability and retuning of place fields during offline periods, revealing the rapid emergence of representations following new exploration and the role of sleep in the representational dynamics of the hippocampus.Using a Bayesian learning approach, a study tracks the spatial representations by individual hippocampal cells over time in freely moving rats, and provides insights into how ensemble patterns form and reconfigure during sleep. [ABSTRACT FROM AUTHOR]

We present computer simulations illustrating how the plastic integration of spatially stable inputs could contribute to the dynamic character of hippocampal spatial representations. In novel environments of slightly larger size than typical apparatus, the emergence of well-defined place fields in real place cells seems to rely on inputs from normally functioning grid cells. Theoretically, the grid-to-place transformation is possible if a place cell is able to respond selectively to a combination of suitably aligned grids. We previously identified the functional characteristics that allow a synaptic plasticity rule to accomplish this selection by synaptic competition during rat foraging behavior. Here, we show that the synaptic competition can outlast the formation of place fields, contributing to their spatial reorganization over time, when the model is run in larger environments and the topographical/modular organization of grid inputs is taken into account. Co-simulated cells that differ only by their randomly assigned grid inputs display different degrees and kinds of spatial reorganization—ranging from place-field remapping to more subtle in-field changes or lapses in firing. The model predicts a greater number of place fields and propensity for remapping in place cells recorded from more septal regions of the hippocampus and/or in larger environments, motivating future experimental standardization across studies and animal models. In sum, spontaneous remapping could arise from rapid synaptic learning involving inputs that are functionally homogeneous, spatially stable, and minimally stochastic. [ABSTRACT FROM AUTHOR]

This study aimed to investigate structural synaptic plasticity in the medial prefrontal cortex of rats under treadmill exercise pretreatment or naive conditions in a vascular dementia model, followed by recognition memory performance in a novel object recognition task. In this study, 24 Sprague–Dawley rats were obtained and randomly assigned into 4 groups as follows: control group (Con group, n = 6), vascular dementia (VD group, n = 6), exercise and vascular dementia group (Exe + VD group, n = 6), and exercise group (Exe group, n = 6). Initially, 4 weeks of treadmill exercise intervention was administered to the rats in the Exe + VD and Exe groups. Then, to establish the vascular dementia model, the rats both in the VD and Exe + VD groups were subjected to bilateral common carotids arteries surgery. One week later, open-field task and novel recognition memory task were adopted to evaluate anxiety-like behavior and recognition memory in each group. Then, immunofluorescence and Golgi staining were used to evaluate neuronal number and spine density in the rat medial prefrontal cortex. Transmission electron microscopy was used to observe the synaptic ultrastructure. Finally, microdialysis coupled with high-performance liquid chromatography was used to assess the levels of 5-HT and dopamine in the medial prefrontal cortex. The behavior results showed that 4 weeks of treadmill exercise pretreatment significantly alleviated recognition memory impairment and anxiety-like behavior in VD rats (P < 0.01), while the rats in VD group exhibited impaired recognition memory and anxiety-like behavior when compared with the Con group (P < 0.001). Additionally, NeuN immunostaining results revealed a significant decrease of NeuN-marked neuron in the VD group compared to Con group (P < 0.01), but a significantly increase in this molecular marker was found in the Exe + VD group compared to the Con group (P < 0.01). Golgi staining results showed that the medial prefrontal cortex neurons in the VD group displayed fewer dendritic spines than those in the Con group (P < 0.01), and there were more spines on the dendrites of medial prefrontal cortex cells in Exe + VD rats than in VD rats (P < 0.01). Transmission electron microscopy further revealed that there was a significant reduction of synapses intensity in the medial prefrontal cortex of rats in the VD group when compared with the Con group(P < 0.01), but physical exercise was found to significantly increased synapses intensity in the VD model (P < 0.01). Lastly, the levels of dopamine and 5-HT in the medial prefrontal cortex of rats in the VD group was significantly lower compared to the Con group (P < 0.01), and treadmill exercise was shown to significantly increased the levels of dopamine and 5-HT in the VD rats (P < 0.05). Treadmill exercise pretreatment ameliorated structural synaptic plasticity impairments of medial prefrontal cortex in VD rat and improved recognition memory. [ABSTRACT FROM AUTHOR]

Layer 5 pyramidal neurons of sensory cortices project “corticofugal” axons to myriad sub-cortical targets, thereby broadcasting high-level signals important for perception and learning. Recent studies suggest dendritic Ca2+ spikes as key biophysical mechanisms supporting corticofugal neuron function: these long-lasting events drive burst firing, thereby initiating uniquely powerful signals to modulate sub-cortical representations and trigger learning-related plasticity. However, the behavioral relevance of corticofugal dendritic spikes is poorly understood. We shed light on this issue using 2-photon Ca2+ imaging of auditory corticofugal dendrites as mice of either sex engage in a GO/NO-GO sound-discrimination task. Unexpectedly, only a minority of dendritic spikes were triggered by behaviorally relevant sounds under our conditions. Task related dendritic activity instead mostly followed sound cue termination and co-occurred with mice’s instrumental licking during the answer period of behavioral trials, irrespective of reward consumption. Temporally selective, optogenetic silencing of corticofugal neurons during the trial answer period impaired auditory discrimination learning. Thus, auditory corticofugal systems’ contribution to learning and plasticity may be partially nonsensory in nature. [ABSTRACT FROM AUTHOR]

It is widely believed that memory storage depends on activity-dependent synaptic modifications. Classical studies of learning and memory in neural networks describe synaptic efficacy either as continuous or discrete. However, recent results suggest an intermediate scenario in which synaptic efficacy can be described by a continuous variable, but whose distribution is peaked around a small set of discrete values. Motivated by these results, we explored a model in which each synapse is described by a continuous variable that evolves in a potential with multiple minima. External inputs to the network can switch synapses from one potential well to another. Our analytical and numerical results show that this model can interpolate between models with discrete synapses which correspond to the deep potential limit, and models in which synapses evolve in a single quadratic potential. We find that the storage capacity of the network with double well synapses exhibits a power law dependence on the network size, rather than the logarithmic dependence observed in models with single well synapses. In addition, synapses with deeper potential wells lead to more robust information storage in the presence of noise. When memories are sparsely encoded, the scaling of the capacity with network size is similar to previously studied network models in the sparse coding limit. Author summary: A long-lasting question in neuroscience is whether synaptic efficacies should be described as continuous variable or discrete variables. Recent experiments indicate that it is a combination of both: synaptic efficacy changes continuously, but its distribution peaks at several discrete values. In this study, we introduce a synapse model described by a double well potential, and investigate the memory properties of networks of neurons connected with such synapses. Our results show in networks with a bimodal weight distribution, the storage capacity depends on network size as a power law. In addition, we demonstrate that networks with such synapses store information more robustly in the presence of noise, compared to networks with synapses with a single well potential. [ABSTRACT FROM AUTHOR]

Evidence shows that the dendritic polarization induced by weak electrical field (EF) can affect the neuronal input–output function via modulating dendritic integration of AMPA synapses, indicating that the supralinear dendritic integration of NMDA synapses can also be influenced by dendritic polarization. However, it remains unknown how dendritic polarization affects NMDA-type dendritic integration, and then contributes to neuronal input–output relationship. Here, we used a computational model of pyramidal neuron with inhomogeneous extracellular potentials to characterize the relationship among EF, dendritic integration, and somatic output. Basing on singular perturbation we analyzed the subthreshold dynamics of membrane potentials in response to NMDA synapses, and found that the equilibrium mapping of a fast subsystem can characterize the asymptotic subthreshold input–output (sI/O) relationship for EF-regulated supralinear dendritic integration, allowing us to predict the tendency of EF-regulated dendritic integration by showing the variation of equilibrium mapping under EF stimulation. EF-induced depolarization at distal dendrites receiving synapses plays a crucial role in shifting the steep change of sI/O left by facilitating dendritic NMDA spike generation and in decreasing the plateau of sI/O via reducing driving force. And more effective EF modulation appears at sparsely activated NMDA receptors compared with clustered synaptic inputs. During the action potential (AP) generation, the respective contribution of EF-regulated dendritic integration and EF-induced somatic polarization was identified to show their synergetic or antagonistic effect on AP generation, depending on neuronal excitability. These results provided insight in understanding the modulation effect of EF on neuronal computation, which is important for optimizing noninvasive brain stimulation. [ABSTRACT FROM AUTHOR]

Microelectrodes serve as a fundamental tool in electrophysiology research throughout the nervous system, providing a means of exploring neural function with a high resolution of neural firing information. We constructed a hybrid computational model using the finite element method and multicompartment cable models to explore factors that contribute to extracellular voltage waveforms that are produced by sensory pseudounipolar neurons, specifically smaller A-type neurons, and that are recorded by microelectrodes in dorsal root ganglia. The finite element method model included a dorsal root ganglion, surrounding tissues, and a planar microelectrode array. We built a multicompartment neuron model with multiple trajectories of the glomerular initial segment found in many A-type sensory neurons. Our model replicated both the somatic intracellular voltage profile of Ad lowthreshold mechanoreceptor neurons and the unique extracellular voltage waveform shapes that are observed in experimental settings. Results from this model indicated that tortuous glomerular initial segment geometries can introduce distinct multiphasic properties into a neuron's recorded waveform. Our model also demonstrated how recording location relative to specific microanatomical components of these neurons, and recording distance from these components, can contribute to additional changes in the multiphasic characteristics and peak-to-peak voltage amplitude of the waveform. This knowledge may provide context for research employing microelectrode recordings of pseudounipolar neurons in sensory ganglia, including functional mapping and closed-loop neuromodulation. Furthermore, our simulations gave insight into the neurophysiology of pseudounipolar neurons by demonstrating how the glomerular initial segment aids in increasing the resistance of the stem axon and mitigating rebounding somatic action potentials. [ABSTRACT FROM AUTHOR]

The hippocampus is the brain's center for episodic memories. Its subregions, the dentate gyrus and CA1-3, are differentially involved in memory encoding and recall. Hippocampal principal cells represent episodic features like movement, space, and context, but less is known about GABAergic interneurons. Here, we performed two-photon calcium imaging of parvalbumin- and somatostatin-expressing interneurons in the dentate gyrus and CA1-3 of male mice exploring virtual environments. Parvalbumin-interneurons increased activity with running-speed and reduced it in novel environments. Somatostatin-interneurons in CA1-3 behaved similar to parvalbumin-expressing cells, but their dentate gyrus counterparts increased activity during rest and in novel environments. Congruently, chemogenetic silencing of dentate parvalbumin-interneurons had prominent effects in familiar contexts, while silencing somatostatin-expressing cells increased similarity of granule cell representations between novel and familiar environments. Our data indicate unique roles for parvalbumin- and somatostatin-positive interneurons in the dentate gyrus that are distinct from those in CA1-3 and may support routing of novel information. Hippocampal GABAergic neurons are thought to play a role in processing memories. Here, the authors show that functions of parvalbumin and somatostatin expressing interneurons in mice depend on novelty and differ between hippocampal subfields. [ABSTRACT FROM AUTHOR]

The medial entorhinal cortex (MEC) hosts many of the brain’s circuit elements for spatial navigation and episodic memory, operations that require neural activity to be organized across long durations of experience1. Whereas location is known to be encoded by spatially tuned cell types in this brain region2,3, little is known about how the activity of entorhinal cells is tied together over time at behaviourally relevant time scales, in the second-to-minute regime. Here we show that MEC neuronal activity has the capacity to be organized into ultraslow oscillations, with periods ranging from tens of seconds to minutes. During these oscillations, the activity is further organized into periodic sequences. Oscillatory sequences manifested while mice ran at free pace on a rotating wheel in darkness, with no change in location or running direction and no scheduled rewards. The sequences involved nearly the entire cell population, and transcended epochs of immobility. Similar sequences were not observed in neighbouring parasubiculum or in visual cortex. Ultraslow oscillatory sequences in MEC may have the potential to couple neurons and circuits across extended time scales and serve as a template for new sequence formation during navigation and episodic memory formation.Neural population activity in the medial entorhinal cortex of mice can be organized into ultraslow oscillatory sequences, with periods extending up to the minute range. [ABSTRACT FROM AUTHOR]

It is widely believed the brain-inspired spiking neural networks have the capability of processing temporal information owing to their dynamic attributes. However, how to understand what kind of mechanisms contributing to the learning ability and exploit the rich dynamic properties of spiking neural networks to satisfactorily solve complex temporal computing tasks in practice still remains to be explored. In this article, we identify the importance of capturing the multi-timescale components, based on which a multi-compartment spiking neural model with temporal dendritic heterogeneity, is proposed. The model enables multi-timescale dynamics by automatically learning heterogeneous timing factors on different dendritic branches. Two breakthroughs are made through extensive experiments: the working mechanism of the proposed model is revealed via an elaborated temporal spiking XOR problem to analyze the temporal feature integration at different levels; comprehensive performance benefits of the model over ordinary spiking neural networks are achieved on several temporal computing benchmarks for speech recognition, visual recognition, electroencephalogram signal recognition, and robot place recognition, which shows the best-reported accuracy and model compactness, promising robustness and generalization, and high execution efficiency on neuromorphic hardware. This work moves neuromorphic computing a significant step toward real-world applications by appropriately exploiting biological observations.Brain-inspired spiking neural networks have shown their capability for effective learning, however current models may not consider realistic heterogeneities present in the brain. The authors propose a neuron model with temporal dendritic heterogeneity for improved neuromorphic computing applications. [ABSTRACT FROM AUTHOR]

The consolidation of recent memories depends on memory replays, also called ripples, generated within the hippocampus during slow-wave sleep, and whose inactivation leads to memory impairment. For now, the mobilisation, localisation and importance of synaptic plasticity events associated to ripples are largely unknown. To tackle this question, we used cell surface AMPAR immobilisation to block post-synaptic LTP within the hippocampal region of male mice during a spatial memory task, and show that: 1- hippocampal synaptic plasticity is engaged during consolidation, but is dispensable during encoding or retrieval. 2- Plasticity blockade during sleep results in apparent forgetting of the encoded rule. 3- In vivo ripple recordings show a strong effect of AMPAR immobilisation when a rule has been recently encoded. 4- In situ investigation suggests that plasticity at CA3-CA3 recurrent synapses supports ripple generation. We thus propose that post-synaptic AMPAR mobility at CA3 recurrent synapses is necessary for ripple-dependent rule consolidation. Memory consolidation requires hippocampal ripples. Here the authors show that AMPA receptor mobilisation at CA3 recurrent synapses is required for ripple-dependent rule consolidation. [ABSTRACT FROM AUTHOR]

Although cortical feedback signals are essential for modulating feedforward processing, no feedback error signal across hierarchical cortical areas has been reported. Here, we observed such a signal in the auditory cortex of awake common marmoset during an oddball paradigm to induce auditory duration mismatch negativity. Prediction errors to a deviant tone presentation were generated as offset calcium responses of layer 2/3 neurons in the rostral parabelt (RPB) of higher-order auditory cortex, while responses to non-deviant tones were strongly suppressed. Within several hundred milliseconds, the error signals propagated broadly into layer 1 of the primary auditory cortex (A1) and accumulated locally on top of incoming auditory signals. Blockade of RPB activity prevented deviance detection in A1. Optogenetic activation of RPB following tone presentation nonlinearly enhanced A1 tone response. Thus, the feedback error signal is critical for automatic detection of unpredicted stimuli in physiological auditory processing and may serve as backpropagation-like learning.The brain can quickly detect sounds that are not predicted. Here, the authors show that propagation of prediction error signals from higher-order auditory cortex to primary auditory cortex is critical for the change detection in the non-human primates. [ABSTRACT FROM AUTHOR]

Background: Subarachnoid hemorrhage (SAH) causes significant long-term neurocognitive dysfunction, which is associated with hippocampal neuroinflammation. Growing evidences have shown that astrocytes played a significant role in mediating neuroinflammation. Recently, in vivo reprogramming of astrocytes to neurons by NeuroD1 or PTBP1 administration has generated a lot of interests and controversies. While the debates centered on the source of neurogenesis, no attention has been paid to the changes of the astrocytes-mediated neuroinflammation and its impact on endogenous neurogenesis after NeuroD1 administration. Methods: 80 adult male C57BL/6 mice were used in this study. SAH was established by pre-chiasmatic injection of 100 μl blood. AAV–NeuroD1–GFP virus was injected to the hippocampus 3 day post-SAH. Neurocognitive function, brain water content, in vivo electrophysiology, Golgi staining, western blot and immunofluorescent staining were assessed at day 14 post-virus injection. Results: NeuroD1 administration markedly attenuated reactive astrocytes-mediated neuroinflammation by reversing neurotoxic A1 astrocytes transformation, decreasing the secretion of neuroinflammatory cytokines, and reducing the activation of harmful microglia. NeuroD1 treatment significantly reversed the brain–blood barrier impairment and promoted the release of neurotrophic factors pleiotrophin (PTN), all of which contributed to the improvement of cellular microenvironment and made it more suitable for neurogenesis. Interestingly, besides neurogenesis in the hippocampus from cells transfected with NeuroD1 at the early phase of SAH, NeuroD1 administration significantly boosted the endogenous neurogenesis at the late phase of SAH, which likely benefited from the improvement of the neuroinflammatory microenvironment. Functionally, NeuroD1 treatment significantly alleviated neurocognitive dysfunction impaired by SAH. Conclusions: NeuroD1 significantly promoted neurofunctional recovery by attenuating reactive astrocytes-mediated neuroinflammation and boosting neurogenesis decimated by SAH. Specifically, NeuroD1 efficiently converted transfected cells, most likely astrocytes, to neurons at the early phase of SAH, suppressed astrocytes-mediated neuroinflammation and boosted endogenous neurogenesis at the late phase of SAH. [ABSTRACT FROM AUTHOR]

Many neurons exhibit regular firing that is limited to the duration and intensity of depolarizing stimuli. However, some neurons exhibit all-or-nothing plateau potentials that, once elicited, can lead to prolonged activity that is independent of stimulus intensity or duration. To better understand this diversity of information processing, we compared the voltage-gated and Ca2+-gated currents of three identified neurons from hermaphroditic Aplysia californica. Two of these neurons, B51 and B64, generated plateau potentials and a third neuron, B8, exhibited regular firing and was incapable of generating a plateau potential. With the exception of the Ca2+-gated potassium current (IKCa), all three neuron types expressed a similar array of outward and inward currents, but with distinct voltage-dependent properties for each neuron type. Inhibiting voltage-gated Ca2+ channels with Ni+ prolonged the plateau potential, indicating IKCa is important for plateau potential termination. In contrast, inhibiting persistent Na+ (INaP) blocked plateau potentials, empirically and in simulations. Surprisingly, the properties and level of expression of INaP were similar in all three neurons, indicating that the presence of INaP does not distinguish between regular-firing neurons and neurons capable of generating plateau potentials. Rather, the key distinguishing factor is the relationship between INaP and outward currents such as the delayed outward current (ID), and IKCa. We then demonstrated a technique for predicting complex physiological properties such as plateau duration, plateau amplitude, and action potential duration as a function of parameter values, by fitting a curve in parameter space and projecting the curve beyond the tested values. [ABSTRACT FROM AUTHOR]

Ectopic pregnancy (EP) is associated with high maternal morbidity and mortality. Ultrasonography is the only dependable diagnostic tool for confirming an ectopic pregnancy. In view of inadequate early detection methods, women suffer from a high-life risk due to the severity of EP. Early detection of EP using pathological/molecular markers will possibly improve clinical diagnosis and patient management. Salivary proteins contain potential biomarkers for diagnosing and detecting various physiological and/or pathological conditions. Therefore, the present investigation was designed to explore the salivary proteome with special reference to EP. Gel-based protein separation was performed on saliva, followed by identification of proteins using Liquid Chromatography-Tandem Mass Spectrometry (LC–MS/MS). Totally, 326 proteins were identified in the salivary samples, among which 101 were found to be specific for ruptured ectopic pregnancy (EPR). Reactome analysis revealed innate immune system, neutrophil degranulation, cell surface interactions at the vascular wall, and FCERI-mediated NF-kB activation as the major pathways to which the salivary proteins identified during EPR are associated. Glutathione-S-transferase omega-1 (GSTO1) is specific for EPR and has been reported as a candidate biomarker in the serum of EPR patients. Therefore, saliva would be a potential source of diagnostic non-invasive protein biomarker(s) for EP. Intensive investigation on the salivary proteins specific to EP can potentially lead to setting up of a panel of candidate biomarkers and developing a non-invasive protein-based diagnostic kit. [ABSTRACT FROM AUTHOR]

The peripheral nervous system (PNS) of mammals and nervous systems of lower organisms possess significant regenerative potential. In contrast, although neural plasticity can provide some compensation, the central nervous system (CNS) neurons and nerves of adult mammals generally fail to regenerate after an injury or damage. However, use of diverse electrical, electromagnetic and sonographic energy waves are illuminating novel ways to stimulate neuronal differentiation, proliferation, neurite growth, and axonal elongation/regeneration leading to various levels of functional recovery in animals and humans afflicted with disorders of the CNS, PNS, retina, and optic nerve. Tools such as acupuncture, electroacupuncture, electroshock therapy, electrical stimulation, transcranial magnetic stimulation, red light therapy, and low-intensity pulsed ultrasound therapy are demonstrating efficacy in treating many different maladies. These include wound healing, partial recovery from motor dysfunctions, recovery from ischemic/reperfusion insults and CNS and ocular remyelination, retinal ganglion cell (RGC) rejuvenation, and RGC axonal regeneration. Neural rejuvenation and axonal growth/regeneration processes involve activation or intensifying of the intrinsic bioelectric waves (action potentials) that exist in every neuronal circuit of the body. In addition, reparative factors released at the nerve terminals and via neuronal dendrites (transmitter substances), extracellular vesicles containing microRNAs and neurotrophins, and intercellular communication occurring via nanotubes aid in reestablishing lost or damaged connections between the traumatized tissues and the PNS and CNS. Many other beneficial effects of the aforementioned treatment paradigms are mediated via gene expression alterations such as downregulation of inflammatory and death-signal genes and upregulation of neuroprotective and cytoprotective genes. These varied techniques and technologies will be described and discussed covering cell-based and animal model-based studies. Data from clinical applications and linkage to human ocular diseases will also be discussed where relevant translational research has been reported. [ABSTRACT FROM AUTHOR]

Place cells are hippocampal neurons encoding the position of an animal in space. Studies of place cells are essential to understanding the processing of information by neural networks of the brain. An important characteristic of place cell spike trains is phase precession. When an animal is running through the place field, the discharges of the place cells shift from the ascending phase of the theta rhythm through the minimum to the descending phase. The role of excitatory inputs to pyramidal neurons along the Schaffer collaterals and the perforant pathway in phase precession is described, but the role of local interneurons is poorly understood. Our goal is estimating of the contribution of field CA1 interneurons to the phase precession of place cells using mathematical methods. The CA1 field is chosen because it provides the largest set of experimental data required to build and verify the model. Our simulations discover optimal parameters of the excitatory and inhibitory inputs to the pyramidal neuron so that it generates a spike train with the effect of phase precession. The uniform inhibition of pyramidal neurons best explains the effect of phase precession. Among interneurons, axo-axonal neurons make the greatest contribution to the inhibition of pyramidal cells. [ABSTRACT FROM AUTHOR]

Thyrotropin-releasing hormone (TRH) and TRH-like peptides carry a therapeutic potential for neurological conditions. Nanoparticles (NP) made of the biodegradable polymer, Poly(Sebacic Anhydride) (PSA), have been developed to carry TRH, intended for intranasal administration to patients. There is limited information on the safety of biodegradable polymers when given intranasally, and therefore, we have performed two preclinical safety and toxicity studies in cynomolgus monkeys and rats using TRH-PSA nanoparticles. The rats and monkeys were dosed intranasally for 42 days or 28 days, respectively, and several animals were followed for additional 14 days. Animals received either placebo, vehicle (PSA), or different concentrations of TRH-PSA. No systemic adverse effects were seen. Changes in T3 or T4 concentrations were observed in some TRH-PSA-treated animals, which did not have clinical or microscopic correlates. No effect was seen on TSH or prolactin concentrations. In the monkey study, microscopic changes in the nasal turbinates were observed, which were attributed to incidental mechanical trauma caused during administration. Taken together, the TRH-loaded PSA NPs have proven to be safe, with no local or systemic adverse effects attributed to the drug loaded nanoparticles. These findings provide additional support to the growing evidence of the safety of peptide-loaded NPs for intranasal delivery and pave the way for future clinical trials in humans. [ABSTRACT FROM AUTHOR]

Memory deficits are a debilitating symptom of epilepsy, but little is known about mechanisms underlying cognitive deficits. Here, we describe a Na+ channel-dependent mechanism underlying altered hippocampal dendritic integration, degraded place coding, and deficits in spatial memory. Two-photon glutamate uncaging experiments revealed a marked increase in the fraction of hippocampal 1st order CA1 pyramidal cell dendrites capable of generating dendritic spikes in the kainate model of chronic epilepsy. Moreover, in epileptic mice dendritic spikes were generated with lower input synchrony inputs, and with a lower threshold. The Nav1.3/1.1 selective Na+ channel blocker ICA-121431 reversed dendritic hyperexcitability in epileptic mice, while the Nav1.2/1.6 preferring anticonvulsant S-Lic did not. We used in-vivo two-photon imaging to determine if aberrant dendritic excitability is associated with altered place-related firing of CA1 neurons. We show that ICA-121431 improves degraded hippocampal spatial representations in epileptic mice. Finally, behavioural experiments show that reversing aberrant dendritic excitability with ICA-121431 reverses hippocampal memory deficits. Thus, a dendritic channelopathy may underlie cognitive deficits in epilepsy and targeting it pharmacologically may constitute a new avenue to enhance cognition. [ABSTRACT FROM AUTHOR]

Memory consolidation involves discrete patterns of transcriptional events in the hippocampus. Despite the emergence of single-cell transcriptomic profiling techniques, mapping the transcriptomic signature across subregions of the hippocampus has remained challenging. Here, we utilized unbiased spatial sequencing to delineate transcriptome-wide gene expression changes across subregions of the dorsal hippocampus of male mice following learning. We find that each subregion of the hippocampus exhibits distinct yet overlapping transcriptomic signatures. The CA1 region exhibited increased expression of genes related to transcriptional regulation, while the DG showed upregulation of genes associated with protein folding. Importantly, our approach enabled us to define the transcriptomic signature of learning within two less-defined hippocampal subregions, CA1 stratum radiatum, and oriens. We demonstrated that CA1 subregion-specific expression of a transcription factor subfamily has a critical functional role in the consolidation of long-term memory. This work demonstrates the power of spatial molecular approaches to reveal simultaneous transcriptional events across the hippocampus during memory consolidation.Transcriptional events are critical for hippocampus-dependent long-term memory storage. Here, the authors utilize spatial transcriptomics to elucidate localized gene expression patterns across hippocampal subregions during memory consolidation. [ABSTRACT FROM AUTHOR]

High frequency burst firing is critical in summation of back-propagating action potentials (APs) in dendrites, which may greatly depolarize dendritic membrane potential. The physiological significance of burst firings of hippocampal dentate GCs in synaptic plasticity remains unknown. We found that GCs with low input resistance could be categorized into regular-spiking (RS) and burst-spiking (BS) cells based on their initial firing frequency (Finit) upon somatic rheobase current injection, and investigated how two types of GCs differ in long-term potentiation (LTP) induced by high-frequency lateral perforant pathway (LPP) inputs. Induction of Hebbian LTP at LPP synapses required at least three postsynaptic APs at Finit higher than 100 Hz, which was met in BS but not in RS cells. The synaptically evoked burst firing was critically dependent on persistent Na+ current, which was larger in BS than RS cells. The Ca2+ source for Hebbian LTP at LPP synapses was primarily provided by L-type calcium channels. In contrast, Hebbian LTP at medial PP synapses was mediated by T-type calcium channels, and could be induced regardless of cell types or Finit of postsynaptic APs. These results suggest that intrinsic firing properties affect synaptically driven firing patterns, and that bursting behavior differentially affects Hebbian LTP mechanisms depending on the synaptic input pathway. [ABSTRACT FROM AUTHOR]

Representing past, present and future locations is key for spatial navigation. Indeed, within each cycle of the theta oscillation, the population of hippocampal place cells appears to represent trajectories starting behind the current position of the animal and sweeping ahead of it. In particular, we reported recently that the position represented by CA1 place cells at a given theta phase corresponds to the location where animals were or will be located at a fixed time interval into the past or future assuming the animal ran at its typical, not the current, speed through that part of the environment. This coding scheme leads to longer theta trajectories, larger place fields and shallower phase precession in areas where animals typically run faster. Here we present a mechanistic computational model that accounts for these experimental observations. The model consists of a continuous attractor network with short-term synaptic facilitation and depression that internally generates theta sequences that advance at a fixed pace. Spatial locations are then mapped onto the active units via modified Hebbian plasticity. As a result, neighboring units become associated with spatial locations further apart where animals run faster, reproducing our earlier experimental results. The model also accounts for the higher density of place fields generally observed where animals slow down, such as around rewards. Furthermore, our modeling results reveal that an artifact of the decoding analysis might be partly responsible for the observation that theta trajectories start behind the animal's current position. Overall, our results shed light on how the hippocampal code might arise from the interplay between behavior, sensory input and predefined network dynamics. Author summary: To navigate in space we need to know where we are, but also where we are going and, possibly, where we are coming from. In mammals, including humans, this might rely on the hippocampal theta phase code, where in each cycle of the theta oscillation, spatial representations appear to start behind the animal's location and then sweep forward. Previously, we showed that these sweeps extend to the locations that were or will be reached at fixed time intervals in the past or future, but assuming the animal ran at its typical speed through each portion of the environment. Here, we present a computational model that can account for these effects, as well as for the over-representation of reward zones in the hippocampal code. The model uses preconfigured neural sequences in the hippocampus to learn sequences of spatial inputs, a mechanism which is supported by experimental findings. Similar mechanisms have been proposed to underlie the encoding of episodic memories. Our work might therefore help reconcile the prominence of spatial representations in the hippocampus with its well-known function in episodic memory. [ABSTRACT FROM AUTHOR]

On-going, large-scale neuroimaging initiatives can aid in uncovering neurobiological causes and correlates of poor mental health, disease pathology, and many other important conditions. As projects grow in scale with hundreds, even thousands, of individual participants and scans collected, quantification of brain structures by automated algorithms is becoming the only truly tractable approach. Here, we assessed the spatial and numerical reliability for newly deployed automated segmentation of hippocampal subfields and amygdala nuclei in FreeSurfer 7. In a sample of participants with repeated structural imaging scans (N = 928), we found numerical reliability (as assessed by intraclass correlations, ICCs) was reasonable. Approximately 95% of hippocampal subfields had "excellent" numerical reliability (ICCs ≥ 0.90), while only 67% of amygdala subnuclei met this same threshold. In terms of spatial reliability, 58% of hippocampal subfields and 44% of amygdala subnuclei had Dice coefficients ≥ 0.70. Notably, multiple regions had poor numerical and/or spatial reliability. We also examined correlations between spatial reliability and person-level factors (e.g., participant age; T1 image quality). Both sex and image scan quality were related to variations in spatial reliability metrics. Examined collectively, our work suggests caution should be exercised for a few hippocampal subfields and amygdala nuclei with more variable reliability. [ABSTRACT FROM AUTHOR]

Lai et al showed that 33% of OAB patients reported pain, pressure or discomfort in the bladder, and hypothesized that OAB patients with pain resemble OAB-dry patients without UUI (Lai et al 2014). Aidin Abedi SP 9 sp , Kofi Agyeman SP 1 sp , Darrin J Lee SP 2 sp , Evgeniy Kreydin SP 3 sp , David Chapman SP 3 sp , Jonathan J Russin SP 4 sp , Wooseong Choi SP 5 sp , Hui Zhong SP 6 sp , V Reggie Edgerton SP 6 sp , Charles Y Liu SP 7 sp , Vassilios N Christopoulos SP 8 sp SP I 1 i sp I Department of i I Bioengineering, UC Riverside, USA i , SP I 2 i sp I Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; USC Neurorestoration Center, Keck School of Medicine of USC, Los Angeles, CA, USA i , SP I 3 i sp I University of Southern California, Institute of Urology, Keck School of Medicine, Los Angeles, CA i , SP I 4 i sp I Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA; USC Neurorestoration Center, Keck School of Medicine, University of Southern California i , SP I 5 i sp I Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA i , SP I 6 i sp I Department of Neurobiology, University of California, Los Angeles, CA i , SP I 7 i sp I USC Neurorestoration Center, Keck School of Medicine, University of Southern California, Los Angeles, CA; Department of Neurological Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA i , SP I 8 i sp I Department of Bioengineering, UC Riverside, Riverside, CA, USA i , SP I 9 i sp I USC Neurorestoration Center, Department of Neurological Surgery, Keck School of Medicine, University of Southern California i Presented By: Aidin Abedi, MD B Introduction b : Neurogenic bladder dysfunction is a debilitating sequela of various neurological disorders. [Extracted from the article]

The advent of comprehensive synaptic wiring diagrams of large neural circuits has created the field of connectomics and given rise to a number of open research questions. One such question is whether it is possible to reconstruct the information stored in a recurrent network of neurons, given its synaptic connectivity matrix. Here, we address this question by determining when solving such an inference problem is theoretically possible in specific attractor network models and by providing a practical algorithm to do so. The algorithm builds on ideas from statistical physics to perform approximate Bayesian inference and is amenable to exact analysis. We study its performance on three different models, compare the algorithm to standard algorithms such as PCA, and explore the limitations of reconstructing stored patterns from synaptic connectivity. Author summary: One of the central hypothesis of neuroscience is that memories are stored in synaptic connectivity. Theoretical models show how large numbers of memories can be stored in recurrent neural circuits thanks to synaptic plasticity mechanisms. Recent advances in serial block-face electron microscopy, and machine learning methods, are making it possible to fully reconstruct the synaptic connectivity of neuronal circuits of increasingly large volumes. Here, we ask the question to what extent it is possible to reconstruct memories stored in a neural circuit from the knowledge of its synaptic connectivity. We present an approximate Bayesian inference algorithm, and study its properties on specific attractor network models. [ABSTRACT FROM AUTHOR]

The expression of biosynthetic genes in bacterial hosts can enable access to high-value compounds, for which appropriate molecular genetic tools are essential. Therefore, we developed a toolbox of modular vectors, which facilitate chromosomal gene integration and expression in Pseudomonas putida KT2440. To this end, we designed an integrative sequence, allowing customisation regarding the modes of integration (random, at attTn7, or into the 16S rRNA gene), promoters, antibiotic resistance markers as well as fluorescent proteins and enzymes as transcription reporters. We thus established a toolbox of vectors carrying integrative sequences, designated as pYT series, of which we present 27 ready-to-use variants along with a set of strains equipped with unique 'landing pads' for directing a pYT interposon into one specific copy of the 16S rRNA gene. We used genes of the well-described violacein biosynthesis as reporter to showcase random Tn5-based chromosomal integration leading to constitutive expression and production of violacein and deoxyviolacein. Deoxyviolacein was likewise produced after gene integration into the 16S rRNA gene of rrn operons. Integration in the attTn7 site was used to characterise the suitability of different inducible promoters and successive strain development for the metabolically challenging production of mono-rhamnolipids. Finally, to establish arcyriaflavin A production in P. putida for the first time, we compared different integration and expression modes, revealing integration at attTn7 and expression with NagR/PnagAa to be most suitable. In summary, the new toolbox can be utilised for the rapid generation of various types of P. putida expression and production strains. [ABSTRACT FROM AUTHOR]

Background & Objective: Prediction of preterm delivery can reduce a large number of its complications. The present study aimed to compare vaginal and plasma fibronectin concentrations in the diagnosis of preterm delivery. Materials & Methods: Serum samples were obtained from 105 women at 24-36 weeks of gestation. However, only 40 women gave permission to collect vaginal samples. Fibronectin concentration was measured using the ELISA technique. Then, plasma and vaginal fibronectin levels were compared in term and preterm deliveries. Results: The mean plasma fibronectin level was 6226.43±7174.97 ng/mL among the mothers with term infants and 7724.01±1143.82 ng/mL among those with preterm infants (p=0.667). The mean fetal fibronectin level was 156.61±126.42 ng/mL among the mothers with term infants and 127.71±43.14 ng/mL among those with preterm infants (p=0.241). The cut-off point of plasma fibronectin level was 1750 ng/mL with a sensitivity of 80.25% and specificity of 85.17%. Additionally, the cut-off point of vaginal fibronectin level was 158.98 ng/mL with a sensitivity of 94.62% and specificity of 22.08%. Conclusion: Plasma fibronectin analysis had lower sensitivity and higher specificity compared to vaginal fibronectin analysis. This implies that plasma testing has lower false-positive cases and can identify a more significant number of true positive cases of preterm delivery. [ABSTRACT FROM AUTHOR]