Selective Routing of Spatial Information Flow from Input to Output in Hippocampal Granule Cells

[Analysis of nerve excitability in the dentate gyrus of the hippocampus in cerebral ischaemia-reperfusion mice]

Ischemic stroke often leads to cognitive dysfunction, which delays the recovery process of patients. However, its pathogenesis is not yet clear. In this study, the cerebral ischemia-reperfusion model was built as the experimental object, and the hippocampal dentate gyrus (DG) was the target brain area. TTC staining was used to evaluate the degree of cerebral infarction, and nerve cell membrane potentials and local field potentials (LFPs) signals were collected to explore the mechanism of cognitive impairment in ischemia-reperfusion mice. The results showed that the infarcted area on the right side of the brain of the mice in the model group was white. The resting membrane potential, the number of action potential discharges, the post-hyperpolarization potential and the maximum ascending slope of the hippocampal DG nerve cells in the model mice were significantly lower than those in the control group ( P < 0.01); the peak time, half-wave width, threshold and maximum descending slope of the action potential were significantly higher than those in the control group ( P < 0.01). The time-frequency energy values of LFPs signals in the θ and γ bands of mice in the ischemia and reperfusion groups were significantly reduced ( P < 0.01), and the time-frequency energy values in the reperfusion group were increased compared with the ischemia group ( P < 0.01). The signal complexity of LFPs in the ischemia and reperfusion group was significantly reduced ( P < 0.05), and the signal complexity in the reperfusion group was increased compared with the ischemia group ( P < 0.05). In summary, cerebral ischemia-reperfusion reduced the excitability of nerve cells in the DG area of the mouse hippocampus; cerebral ischemia reduced the discharge activity and signal complexity of nerve cells, and the electrophysiological indicators recovered after reperfusion, but it failed to reach the healthy state during the experiment period.

Ion-channel degeneracy and heterogeneities in the emergence of signature physiological characteristics of dentate gyrus granule cells

Complex systems are neither fully determined nor completely random. Biological complex systems, including single neurons, manifest intermediate regimes of randomness that recruit integration of specific combinations of functionally specialized subsystems. Such emergence of biological function provides the substrate for the expression of degeneracy, the ability of disparate combinations of subsystems to yield similar function. Here, we present evidence for the expression of degeneracy in morphologically realistic models of dentate gyrus granule cells (GCs) through functional integration of disparate ion-channel combinations. We performed a 45-parameter randomized search spanning 16 active and passive ion channels, each biophysically constrained by their gating kinetics and localization profiles, to search for valid GC models. Valid models were those that satisfied 17 sub- and suprathreshold cellular-scale electrophysiological measurements from rat GCs. A vast majority (>99%) of the 15,000 random models were not electrophysiologically valid, demonstrating that arbitrarily random ion-channel combinations would not yield GC functions. The 141 valid models (0.94% of 15,000) manifested heterogeneities in and cross-dependencies across local and propagating electrophysiological measurements, which matched with their respective biological counterparts. Importantly, these valid models were widespread throughout the parametric space and manifested weak cross-dependencies across different parameters. These observations together showed that GC physiology could neither be obtained by entirely random ion-channel combinations nor is there an entirely determined single parametric combination that satisfied all constraints. The complexity, the heterogeneities in measurement and parametric spaces, and degeneracy associated with GC physiology should be rigorously accounted for while assessing GCs and their robustness under physiological and pathological conditions.NEW & NOTEWORTHY A recent study from our laboratory had demonstrated pronounced heterogeneities in a set of 17 electrophysiological measurements obtained from a large population of rat hippocampal granule cells. Here, we demonstrate the manifestation of ion-channel degeneracy in a heterogeneous population of morphologically realistic conductance-based granule cell models that were validated against these measurements and their cross-dependencies. Our analyses show that single neurons are complex entities whose functions emerge through intricate interactions among several functionally specialized subsystems.

Hippocampal-dependent navigation in head-fixed mice using a floating real-world environment

Head-fixation of mice enables high-resolution monitoring of neuronal activity coupled with precise control of environmental stimuli. Virtual reality can be used to emulate the visual experience of movement during head fixation, but a low inertia floating real-world environment (mobile homecage, MHC) has the potential to engage more sensory modalities and provide a richer experimental environment for complex behavioral tasks. However, it is not known whether mice react to this adapted environment in a similar manner to real environments, or whether the MHC can be used to implement validated, maze-based behavioral tasks. Here, we show that hippocampal place cell representations are intact in the MHC and that the system allows relatively long (20 min) whole-cell patch clamp recordings from dorsal CA1 pyramidal neurons, revealing sub-threshold membrane potential dynamics. Furthermore, mice learn the location of a liquid reward within an adapted T-maze guided by 2-dimensional spatial navigation cues and relearn the location when spatial contingencies are reversed. Bilateral infusions of scopolamine show that this learning is hippocampus-dependent and requires intact cholinergic signalling. Therefore, we characterize the MHC system as an experimental tool to study sub-threshold membrane potential dynamics that underpin complex navigation behaviors.

Structure, biophysics, and circuit function of a "giant" cortical presynaptic terminal

The hippocampal mossy fiber synapse, formed between axons of dentate gyrus granule cells and dendrites of CA3 pyramidal neurons, is a key synapse in the trisynaptic circuitry of the hippocampus. Because of its comparatively large size, this synapse is accessible to direct presynaptic recording, allowing a rigorous investigation of the biophysical mechanisms of synaptic transmission and plasticity. Furthermore, because of its placement in the very center of the hippocampal memory circuit, this synapse seems to be critically involved in several higher network functions, such as learning, memory, pattern separation, and pattern completion. Recent work based on new technologies in both nanoanatomy and nanophysiology, including presynaptic patch-clamp recording, paired recording, super-resolution light microscopy, and freeze-fracture and "flash-and-freeze" electron microscopy, has provided new insights into the structure, biophysics, and network function of this intriguing synapse. This brings us one step closer to answering a fundamental question in neuroscience: how basic synaptic properties shape higher network computations.

Regulation of specific abnormal calcium signals in the hippocampal CA1 and primary cortex M1 alleviates the progression of temporal lobe epilepsy

Temporal lobe epilepsy is a multifactorial neurological dysfunction syndrome that is refractory, resistant to antiepileptic drugs, and has a high recurrence rate. The pathogenesis of temporal lobe epilepsy is complex and is not fully understood. Intracellular calcium dynamics have been implicated in temporal lobe epilepsy. However, the effect of fluctuating calcium activity in CA1 pyramidal neurons on temporal lobe epilepsy is unknown, and no longitudinal studies have investigated calcium activity in pyramidal neurons in the hippocampal CA1 and primary motor cortex M1 of freely moving mice. In this study, we used a multi-channel fiber photometry system to continuously record calcium signals in CA1 and M1 during the temporal lobe epilepsy process. We found that calcium signals varied according to the grade of temporal lobe epilepsy episodes. In particular, cortical spreading depression, which has recently been frequently used to represent the continuously and substantially increased calcium signals, was found to correspond to complex and severe behavioral characteristics of temporal lobe epilepsy ranging from grade II to grade V. However, vigorous calcium oscillations and highly synchronized calcium signals in CA1 and M1 were strongly related to convulsive motor seizures. Chemogenetic inhibition of pyramidal neurons in CA1 significantly attenuated the amplitudes of the calcium signals corresponding to grade I episodes. In addition, the latency of cortical spreading depression was prolonged, and the above-mentioned abnormal calcium signals in CA1 and M1 were also significantly reduced. Intriguingly, it was possible to rescue the altered intracellular calcium dynamics. Via simultaneous analysis of calcium signals and epileptic behaviors, we found that the progression of temporal lobe epilepsy was alleviated when specific calcium signals were reduced, and that the end-point behaviors of temporal lobe epilepsy were improved. Our results indicate that the calcium dynamic between CA1 and M1 may reflect specific epileptic behaviors corresponding to different grades. Furthermore, the selective regulation of abnormal calcium signals in CA1 pyramidal neurons appears to effectively alleviate temporal lobe epilepsy, thereby providing a potential molecular mechanism for a new temporal lobe epilepsy diagnosis and treatment strategy.

Robust and consistent measures of pattern separation based on information theory and demonstrated in the dentate gyrus

Pattern separation is a valuable computational function performed by neuronal circuits, such as the dentate gyrus, where dissimilarity between inputs is increased, reducing noise and increasing the storage capacity of downstream networks. Pattern separation is studied from both in vivo experimental and computational perspectives and, a number of different measures (such as orthogonalisation, decorrelation, or spike train distance) have been applied to quantify the process of pattern separation. However, these are known to give conclusions that can differ qualitatively depending on the choice of measure and the parameters used to calculate it. We here demonstrate that arbitrarily increasing sparsity, a noticeable feature of dentate granule cell firing and one that is believed to be key to pattern separation, typically leads to improved classical measures for pattern separation even, inappropriately, up to the point where almost all information about the inputs is lost. Standard measures therefore both cannot differentiate between pattern separation and pattern destruction, and give results that may depend on arbitrary parameter choices. We propose that techniques from information theory, in particular mutual information, transfer entropy, and redundancy, should be applied to penalise the potential for lost information (often due to increased sparsity) that is neglected by existing measures. We compare five commonly-used measures of pattern separation with three novel techniques based on information theory, showing that the latter can be applied in a principled way and provide a robust and reliable measure for comparing the pattern separation performance of different neurons and networks. We demonstrate our new measures on detailed compartmental models of individual dentate granule cells and a dentate microcircuit, and show how structural changes associated with epilepsy affect pattern separation performance. We also demonstrate how our measures of pattern separation can predict pattern completion accuracy. Overall, our measures solve a widely acknowledged problem in assessing the pattern separation of neural circuits such as the dentate gyrus, as well as the cerebellum and mushroom body. Finally we provide a publicly available toolbox allowing for easy analysis of pattern separation in spike train ensembles.

Fear memory recall involves hippocampal somatostatin interneurons

Fear-related memory traces are encoded by sparse populations of hippocampal principal neurons that are recruited based on their inhibitory-excitatory balance during memory formation. Later, the reactivation of the same principal neurons can recall the memory. The details of this mechanism are still unclear. Here, we investigated whether disinhibition could play a major role in this process. Using optogenetic behavioral experiments, we found that when fear was associated with the inhibition of mouse hippocampal somatostatin positive interneurons, the re-inhibition of the same interneurons could recall fear memory. Pontine nucleus incertus neurons selectively inhibit hippocampal somatostatin cells. We also found that when fear was associated with the activity of these incertus neurons or fibers, the reactivation of the same incertus neurons or fibers could also recall fear memory. These incertus neurons showed correlated activity with hippocampal principal neurons during memory recall and were strongly innervated by memory-related neocortical centers, from which the inputs could also control hippocampal disinhibition in vivo. Nonselective inhibition of these mouse hippocampal somatostatin or incertus neurons impaired memory recall. Our data suggest a novel disinhibition-based memory mechanism in the hippocampus that is supported by local somatostatin interneurons and their pontine brainstem inputs.

Burst firing is required for induction of Hebbian LTP at lateral perforant path to hippocampal granule cell synapses

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 (F_init) 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 F_init 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 F_init 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.

Global remapping in granule cells and mossy cells of the mouse dentate gyrus

Hippocampal place cells exhibit spatially modulated firing, or place fields, which can remap to encode changes in the environment or other variables. Unique among hippocampal subregions, the dentate gyrus (DG) has two excitatory populations of place cells, granule cells and mossy cells, which are among the least and most active spatially modulated cells in the hippocampus, respectively. Previous studies of remapping in the DG have drawn different conclusions about whether granule cells exhibit global remapping and contribute to the encoding of context specificity. By recording granule cells and mossy cells as mice foraged in different environments, we found that by most measures, both granule cells and mossy cells remapped robustly but through different mechanisms that are consistent with firing properties of each cell type. Our results resolve the ambiguity surrounding remapping in the DG and suggest that most spatially modulated granule cells contribute to orthogonal representations of distinct spatial contexts.

Circadian regulation of dentate gyrus excitability mediated by G-protein signaling

The central circadian regulator within the suprachiasmatic nucleus transmits time of day information by a diurnal spiking rhythm driven by molecular clock genes controlling membrane excitability. Most brain regions, including the hippocampus, harbor similar intrinsic circadian transcriptional machinery, but whether these molecular programs generate oscillations of membrane properties is unclear. Here, we show that intrinsic excitability of mouse dentate granule neurons exhibits a 24-h oscillation that controls spiking probability. Diurnal changes in excitability are mediated by antiphase G-protein regulation of potassium and sodium currents that reduce excitability during the Light phase. Disruption of the circadian transcriptional machinery by conditional deletion of Bmal1 enhances excitability selectively during the Light phase by removing G-protein regulation. These results reveal that circadian transcriptional machinery regulates intrinsic excitability by coordinated regulation of ion channels by G-protein signaling, highlighting a potential novel mechanism of cell-autonomous oscillations.

Adult-born dentate granule cells promote hippocampal population sparsity

The dentate gyrus (DG) gates neocortical information flow to the hippocampus. Intriguingly, the DG also produces adult-born dentate granule cells (abDGCs) throughout the lifespan, but their contribution to downstream firing dynamics remains unclear. Here, we show that abDGCs promote sparser hippocampal population spiking during mnemonic processing of novel stimuli. By combining triple-(DG-CA3-CA1) ensemble recordings and optogenetic interventions in behaving mice, we show that abDGCs constitute a subset of high-firing-rate neurons with enhanced activity responses to novelty and strong modulation by theta oscillations. Selectively activating abDGCs in their 4-7-week post-birth period increases sparsity of hippocampal population patterns, whereas suppressing abDGCs reduces this sparsity, increases principal cell firing rates and impairs novel object recognition with reduced dimensionality of the network firing structure, without affecting single-neuron spatial representations. We propose that adult-born granule cells transiently support sparser hippocampal population activity structure for higher-dimensional responses relevant to effective mnemonic information processing.

A synaptic signal for novelty processing in the hippocampus

Episodic memory formation and recall are complementary processes that rely on opposing neuronal computations in the hippocampus. How this conflict is resolved in hippocampal circuits is unclear. To address this question, we obtained in vivo whole-cell patch-clamp recordings from dentate gyrus granule cells in head-fixed mice trained to explore and distinguish between familiar and novel virtual environments. We find that granule cells consistently show a small transient depolarisation upon transition to a novel environment. This synaptic novelty signal is sensitive to local application of atropine, indicating that it depends on metabotropic acetylcholine receptors. A computational model suggests that the synaptic response to novelty may bias granule cell population activity, which can drive downstream attractor networks to a new state, favouring the switch from recall to new memory formation when faced with novelty. Such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.

Memory formation and recall are complementary processes within the hippocampus. Here the authors demonstrate a synaptic signal of novelty in the hippocampus and provide a computational framework for how such a novelty-driven switch may enable flexible encoding of new memories while preserving stable retrieval of familiar ones.

Dominant role of adult neurogenesis-induced structural heterogeneities in driving plasticity heterogeneity in dentate gyrus granule cells

Neurons and synapses manifest pronounced variability in the amount of plasticity induced by identical activity patterns. The mechanisms underlying such plasticity heterogeneity, which have been implicated in context‐specific resource allocation during encoding, have remained unexplored. Here, we employed a systematic physiologically constrained parametric search to identify the cellular mechanisms behind plasticity heterogeneity in dentate gyrus granule cells. We used heterogeneous model populations to ensure that our conclusions were not biased by parametric choices in a single hand‐tuned model. We found that each of intrinsic, synaptic, and structural heterogeneities independently yielded heterogeneities in synaptic plasticity profiles obtained with two different induction protocols. However, among the disparate forms of neural‐circuit heterogeneities, our analyses demonstrated the dominance of neurogenesis‐induced structural heterogeneities in driving plasticity heterogeneity in granule cells. We found that strong relationships between neuronal intrinsic excitability and plasticity emerged only when adult neurogenesis‐induced heterogeneities in neural structure were accounted for. Importantly, our analyses showed that it was not imperative that the manifestation of neural‐circuit heterogeneities must translate to heterogeneities in plasticity profiles. Specifically, despite the expression of heterogeneities in structural, synaptic, and intrinsic neuronal properties, similar plasticity profiles were attainable across all models through synergistic interactions among these heterogeneities. We assessed the parametric combinations required for the manifestation of such degeneracy in the expression of plasticity profiles. We found that immature cells showed physiological plasticity profiles despite receiving afferent inputs with weak synaptic strengths. Thus, the high intrinsic excitability of immature granule cells was sufficient to counterbalance their low excitatory drive in the expression of plasticity profile degeneracy. Together, our analyses demonstrate that disparate forms of neural‐circuit heterogeneities could mechanistically drive plasticity heterogeneity, but also caution against treating neural‐circuit heterogeneities as proxies for plasticity heterogeneity. Our study emphasizes the need for quantitatively characterizing the relationship between neural‐circuit and plasticity heterogeneities across brain regions.

Excitatory selective LTP of supramammillary glutamatergic/GABAergic cotransmission potentiates dentate granule cell firing

It is now established that many neurons can release multiple transmitters. Recent studies revealed that fast-acting neurotransmitters, glutamate and GABA, are coreleased from the same presynaptic terminals in some adult brain regions. The dentate gyrus (DG) granule cells (GCs) are innervated by the hypothalamic supramammillary nucleus (SuM) afferents that corelease glutamate and GABA. However, how these functionally opposing neurotransmitters contribute to DG information processing remains unclear. We show that glutamatergic, but not GABAergic, cotransmission exhibits long-term potentiation (LTP) at SuM-GC synapses. By the excitatory selective LTP, the excitation/inhibition balance of SuM inputs increases, and GC firing is enhanced. This study provides evidence that glutamatergic/GABAergic cotransmission balance is rapidly changed in an activity-dependent manner, and such plasticity may modulate DG activity.

Emerging evidence indicates that the functionally opposing neurotransmitters, glutamate and GABA, are coreleased from the same presynaptic terminals in some adult brain regions. The supramammillary nucleus (SuM) is one region that coreleases glutamate and GABA in the dentate gyrus (DG) through its afferents. Although the SuM-DG pathway has been implicated in various brain functions, little is known about the functional roles of the peculiar features of glutamate/GABA corelease. Here, we show that depolarization of granule cells (GCs) triggers postsynaptic long-term potentiation (LTP) of glutamatergic, but not GABAergic, cotransmission at SuM-GC synapses. Moreover, the burst activity of perforant-path inputs heterosynaptically induces LTP at excitatory SuM-GC synapses. This non-Hebbian LTP requires postsynaptic Ca²⁺ influx, Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) activity, and exocytosis of AMPA receptors. Glutamatergic transmission-selective expression of LTP increases the excitatory drive such that SuM inputs become sufficient to discharge GCs. Our results highlight a form of LTP, which dynamically and rapidly changes the glutamatergic/GABAergic cotransmission balance and contributes to DG network activity.

Conjunctive changes in multiple ion channels mediate activity-dependent intrinsic plasticity in hippocampal granule cells

Plasticity in the brain is ubiquitous. How do neurons and networks encode new information and simultaneously maintain homeostasis in the face of such ubiquitous plasticity? Here, we unveil a form of neuronal plasticity in rat hippocampal granule cells, which is mediated by conjunctive changes in HCN, inward-rectifier potassium, and persistent sodium channels induced by theta-modulated burst firing, a behaviorally relevant activity pattern. Cooperation and competition among these simultaneous changes resulted in a unique physiological signature: sub-threshold excitability and temporal summation were reduced without significant changes in action potential firing, together indicating a concurrent enhancement of supra-threshold excitability. This form of intrinsic plasticity was dependent on calcium influx through L-type calcium channels and inositol trisphosphate receptors. These observations demonstrate that although brain plasticity is ubiquitous, strong systemic constraints govern simultaneous plasticity in multiple components-referred here as plasticity manifolds-thereby providing a cellular substrate for concomitant encoding and homeostasis in engram cells.

Juxtacellular opto-tagging of hippocampal CA1 neurons in freely moving mice

Neural circuits are made of a vast diversity of neuronal cell types. While immense progress has been made in classifying neurons based on morphological, molecular, and functional properties, understanding how this heterogeneity contributes to brain function during natural behavior has remained largely unresolved. In the present study, we combined the juxtacellular recording and labeling technique with optogenetics in freely moving mice. This allowed us to selectively target molecularly defined cell classes for in vivo single-cell recordings and morphological analysis. We validated this strategy in the CA1 region of the mouse hippocampus by restricting Channelrhodopsin expression to Calbindin-positive neurons. Directly versus indirectly light-activated neurons could be readily distinguished based on the latencies of light-evoked spikes, with juxtacellular labeling and post hoc histological analysis providing ‘ground-truth’ validation. Using these opto-juxtacellular procedures in freely moving mice, we found that Calbindin-positive CA1 pyramidal cells were weakly spatially modulated and conveyed less spatial information than Calbindin-negative neurons – pointing to pyramidal cell identity as a key determinant for neuronal recruitment into the hippocampal spatial map. Thus, our method complements current in vivo techniques by enabling optogenetic-assisted structure–function analysis of single neurons recorded during natural, unrestrained behavior.

How connectivity rules and synaptic properties shape the efficacy of pattern separation in the entorhinal cortex-dentate gyrus-CA3 network

Pattern separation is a fundamental brain computation that converts small differences in input patterns into large differences in output patterns. Several synaptic mechanisms of pattern separation have been proposed, including code expansion, inhibition and plasticity; however, which of these mechanisms play a role in the entorhinal cortex (EC)-dentate gyrus (DG)-CA3 circuit, a classical pattern separation circuit, remains unclear. Here we show that a biologically realistic, full-scale EC-DG-CA3 circuit model, including granule cells (GCs) and parvalbumin-positive inhibitory interneurons (PV+-INs) in the DG, is an efficient pattern separator. Both external gamma-modulated inhibition and internal lateral inhibition mediated by PV+-INs substantially contributed to pattern separation. Both local connectivity and fast signaling at GC-PV+-IN synapses were important for maximum effectiveness. Similarly, mossy fiber synapses with conditional detonator properties contributed to pattern separation. By contrast, perforant path synapses with Hebbian synaptic plasticity and direct EC-CA3 connection shifted the network towards pattern completion. Our results demonstrate that the specific properties of cells and synapses optimize higher-order computations in biological networks and might be useful to improve the deep learning capabilities of technical networks.

The hippocampus converts dynamic entorhinal inputs into stable spatial maps

The medial entorhinal cortex (MEC)-hippocampal network plays a key role in the processing, storage, and recall of spatial information. However, how the spatial code provided by MEC inputs relates to spatial representations generated by principal cell assemblies within hippocampal subfields remains enigmatic. To investigate this coding relationship, we employed two-photon calcium imaging in mice navigating through dissimilar virtual environments. Imaging large MEC bouton populations revealed spatially tuned activity patterns. MEC inputs drastically changed their preferred spatial field locations between environments, whereas hippocampal cells showed lower levels of place field reconfiguration. Decoding analysis indicated that higher place field reliability and larger context-dependent activity-rate differences allow low numbers of principal cells, particularly in the DG and CA1, to provide information about location and context more accurately and rapidly than MEC inputs. Thus, conversion of dynamic MEC inputs into stable spatial hippocampal maps may enable fast encoding and efficient recall of spatio-contextual information.

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MEC inputs to the DG, CA3, and CA1 show different spatial coding properties

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MEC inputs remap even more strongly than hippocampal principal cells

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Hippocampal principal cell activity is more reliable and stable than their MEC inputs

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Hippocampal principal cells allow improved spatial and contextual readout

Gamma rhythm communication between entorhinal cortex and dentate gyrus neuronal assemblies

Gamma oscillations are thought to coordinate the spike timing of functionally specialized neuronal ensembles across brain regions. To test this hypothesis, we optogenetically perturbed gamma spike timing in the rat medial (MEC) and lateral (LEC) entorhinal cortices and found impairments in spatial and object learning tasks, respectively. MEC and LEC were synchronized with the hippocampal dentate gyrus through high- and low-gamma-frequency rhythms, respectively, and engaged either granule cells or mossy cells and CA3 pyramidal cells in a task-dependent manner. Gamma perturbation disrupted the learning-induced assembly organization of target neurons. Our findings imply that pathway-specific gamma oscillations route task-relevant information between distinct neuronal subpopulations in the entorhinal-hippocampal circuit. We hypothesize that interregional gamma-time-scale spike coordination is a mechanism of neuronal communication.

MOD: A novel machine-learning optimal-filtering method for accurate and efficient detection of subthreshold synaptic events in vivo

BACKGROUND

To understand information coding in single neurons, it is necessary to analyze subthreshold synaptic events, action potentials (APs), and their interrelation in different behavioral states. However, detecting excitatory postsynaptic potentials (EPSPs) or currents (EPSCs) in behaving animals remains challenging, because of unfavorable signal-to-noise ratio, high frequency, fluctuating amplitude, and variable time course of synaptic events.

NEW METHOD

We developed a method for synaptic event detection, termed MOD (Machine-learning Optimal-filtering Detection-procedure), which combines concepts of supervised machine learning and optimal Wiener filtering. Experts were asked to manually score short epochs of data. The algorithm was trained to obtain the optimal filter coefficients of a Wiener filter and the optimal detection threshold. Scored and unscored data were then processed with the optimal filter, and events were detected as peaks above threshold.

RESULTS

We challenged MOD with EPSP traces in vivo in mice during spatial navigation and EPSC traces in vitro in slices under conditions of enhanced transmitter release. The area under the curve (AUC) of the receiver operating characteristics (ROC) curve was, on average, 0.894 for in vivo and 0.969 for in vitro data sets, indicating high detection accuracy and efficiency.

COMPARISON WITH EXISTING METHODS

When benchmarked using a (1 - AUC)^-1 metric, MOD outperformed previous methods (template-fit, deconvolution, and Bayesian methods) by an average factor of 3.13 for in vivo data sets, but showed comparable (template-fit, deconvolution) or higher (Bayesian) computational efficacy.

CONCLUSIONS

MOD may become an important new tool for large-scale, real-time analysis of synaptic activity.

In Vivo Whole-Cell Patch-Clamp Methods: Recent Technical Progress and Future Perspectives

Brain functions are fundamental for the survival of organisms, and they are supported by neural circuits consisting of a variety of neurons. To investigate the function of neurons at the single-cell level, researchers often use whole-cell patch-clamp recording techniques. These techniques enable us to record membrane potentials (including action potentials) of individual neurons of not only anesthetized but also actively behaving animals. This whole-cell recording method enables us to reveal how neuronal activities support brain function at the single-cell level. In this review, we introduce previous studies using in vivo patch-clamp recording techniques and recent findings primarily regarding neuronal activities in the hippocampus for behavioral function. We further discuss how we can bridge the gap between electrophysiology and biochemistry.

The effects of Kctd12, an auxiliary subunit of GABAB receptor in dentate gyrus on behavioral response to chronic social defeat stress in mice

Adaptive responses to stress are critical to enhance physical and mental well-being, but excessive or prolonged stress may cause inadaptability and increase the risks of psychiatric disorders, such as depression. GABABR signaling is fundamental to brain function and has been identified in neuropsychiatric disorders. KCTD12 is a critical auxiliary subunit in GABABR signaling, but its role in mental disorders, such as depression is unclear. In the present study, we used a well-validated mice model, chronic social defeat stress (CSDS) to investigate behavioral responses to stress and explore the role of Kctd12 in stress response, as well as the relevant mechanisms. We found that CSDS increased the expression of Kctd12 in the dentate gyrus (DG), a subregion of hippocampus. Overexpression of Kctd12 in DG induced higher responsiveness to acute stress and increased vulnerability to social stress in mice, whereas knock-down of Kctd12 in DG prevented the social avoidance. Furthermore, an increased expression of GABAB receptor 2 (GB2) in the DG of CSDS-treated mice was observed, and CGP35348, an antagonist of GABABR, improved the stress-induced behavior responses along with suppressing the excess expression of Kctd12. In addition, Kctd12 regulated the excitability of granule cell in DG, and the stimulation of neuronal activity by silencing Kctd12 contributed to the antidepressant-like effect of fluoxetine. These findings identify that the Kctd12 in DG works as a critical mediator of stress responses, providing a promising therapeutic target in stress-related psychiatric disorders, including depression.

Differential Relation between Neuronal and Behavioral Discrimination during Hippocampal Memory Encoding

How are distinct memories formed and used for behavior? To relate neuronal and behavioral discrimination during memory formation, we use in vivo 2-photon Ca2+ imaging and whole-cell recordings from hippocampal subregions in head-fixed mice performing a spatial virtual reality task. We find that subthreshold activity as well as population codes of dentate gyrus neurons robustly discriminate across different spatial environments, whereas neuronal remapping in CA1 depends on the degree of difference between visual cues. Moreover, neuronal discrimination in CA1, but not in the dentate gyrus, reflects behavioral performance. Our results suggest that CA1 weights the decorrelated information from the dentate gyrus according to its relevance, producing a map of memory representations that can be used by downstream circuits to guide learning and behavior.

Integration of spatial and non-spatial information by heterogeneous dentate gyrus granule cells

The hippocampus is the key site for learning and memory and for processing of spatial information in the brain. It is divided into three main subregions: the dentate gyrus (DG), the CA3 area, and the CA1 region, which are linearly interconnected to form a so-called trisynaptic circuit. Thus, the DG sits in a strategic position to gate the flow of information from the neocortex into the hippocampal network. The granule cells (GCs), the main cell type in the DG, receive 'where' and 'what' information from the medial and lateral entorhinal cortex, respectively. How they process this mixed information remains enigmatic. By characterizing the spatial information encoded by the excitatory postsynaptic potentials (EPSPs) in GCs, we demonstrated that the majority of GCs received spatially tuned synaptic input. However, only a minority of GCs successfully converted spatially tuned input to spatially tuned output. Furthermore, we found that mature GCs were highly heterogeneous in terms of their dendritic morphology and intrinsic excitability, which contributes to the sparse and heterogeneous firing of GCs. Finally, we discuss the possible origin of this neural heterogeneity and its potential role in enlarging the computational power of the DG, facilitating pattern separation in this network.