Nonrandom local circuits in the dentate gyrus

Field EPSPs of Dentate Gyrus Granule Cells Studied by Selective Optogenetic Activation of Hilar Mossy Cells in Hippocampal Slices

Glutamatergic dentate gyrus (DG) mossy cells (MCs) innervate the primary DG cell type, granule cells (GCs). Numerous MC synapses are on GC proximal dendrites in the inner molecular layer (IML). However, field recordings of the GC excitatory postsynaptic potential (fEPSPs) have not been used to study this pathway selectively. Here we describe methods to selectively activate MC axons in the IML using mice with Cre recombinase expressed in MCs. Slices were made after injecting adeno-associated virus (AAV) encoding channelrhodopsin (ChR2) in the DG. In these slices, we show that fEPSPs could be recorded reliably in the IML in response to optogenetic stimulation of MC axons. Furthermore, fEPSPs were widespread across the septotemporal axis. However, fEPSPs were relatively weak because they were small in amplitude and did not elicit a significant population spike in GCs. They also showed little paired pulse facilitation. We confirmed the extracellular findings with patch clamp recordings of GCs despite different recording chambers and other differences in methods. Together the results provide a simple method for studying MC activation of GCs and add to the evidence that this input is normally weak but widespread across the GC population.

Field EPSPs of dentate gyrus granule cells studied by selective optogenetic activation of hilar mossy cells in hippocampal slices

Glutamatergic dentate gyrus (DG) mossy cells (MCs) innervate the primary DG cell type, granule cells (GCs). Numerous MC synapses are on GC proximal dendrites in the inner molecular layer (IML). However, field recordings of the GC excitatory postsynaptic potential (fEPSPs) have not been used to study this pathway selectively. Here we describe methods to selectively activate MC axons in the IML using mice with Cre recombinase expressed in MCs. Slices were made after injecting adeno-associated virus (AAV) encoding channelrhodopsin (ChR2) in the DG. In these slices, we show that fEPSPs could be recorded reliably in the IML in response to optogenetic stimulation of MC axons. Furthermore, fEPSPs were widespread across the septotemporal axis. However, fEPSPs were relatively weak because they were small in amplitude and did not elicit a significant population spike in GCs. They also showed little paired pulse facilitation. We confirmed the extracellular findings with patch clamp recordings of GCs despite different recording chambers and other differences in methods. Together the results provide a simple method for studying MC activation of GCs and add to the evidence that this input is normally weak but widespread across the GC population.

KEY POINTS

We describe a method to activate the MC input to GCs selectively using optogenetics in hippocampal slicesMC excitation is weakly excitatory but so common among GCs that a field EPSP is generated at the site of MC synapses on GCsMC excitation of GCs is consistent across the septotemporal axis and contralaterallyUsing the characteristics of optogenetically-evoked fEPSPs, electrical stimulation of the MC input to GCs can be optimized.

Neurobehavioral Impairments Predict Specific Cerebral Damage in Rat Model of Subarachnoid Hemorrhage

Subarachnoid hemorrhage (SAH) is a severe form of stroke that can cause unpredictable and diffuse cerebral damage, which is difficult to detect until it becomes irreversible. Therefore, there is a need for a reliable method to identify dysfunctional regions and initiate treatment before permanent damage occurs. Neurobehavioral assessments have been suggested as a possible tool to detect and approximately localize dysfunctional cerebral regions. In this study, we hypothesized that a neurobehavioral assessment battery could be a sensitive and specific method for detecting damage in discrete cerebral regions following SAH. To test this hypothesis, a behavioral battery was employed at multiple time points after SAH induced via an endovascular perforation, and brain damage was confirmed via postmortem histopathological analysis. Our results demonstrate that impairment of sensorimotor function accurately predict damage in the cerebral cortex (AUC 0.905; sensitivity 81.8%; specificity 90.9%) and striatum (AUC 0.913; sensitivity 90.1%; specificity 100%), while impaired novel object recognition is a more accurate indicator of damage to the hippocampus (AUC 0.902; sensitivity 74.1%; specificity 83.3%) than impaired reference memory (AUC 0.746; sensitivity 72.2%; specificity 58.0%). Tests for anxiety-like and depression-like behaviors predict damage to the amygdala (AUC 0.900; sensitivity 77.0%; specificity 81.7%) and thalamus (AUC 0.963; sensitivity 86.3%; specificity 87.8%), respectively. This study suggests that recurring behavioral testing can accurately predict damage in specific brain regions, which could be developed into a clinical battery for early detection of SAH damage in humans, potentially improving early treatment and outcomes.

Effect of adult-born immature granule cells on pattern separation in the hippocampal dentate gyrus

Young immature granule cells (imGCs) appear via adult neurogenesis in the hippocampal dentate gyrus (DG). In comparison to mature GCs (mGCs) (born during development), the imGCs exhibit two competing distinct properties such as high excitability (increasing activation degree) and low excitatory innervation (reducing activation degree). We develop a spiking neural network for the DG, incorporating both the mGCs and the imGCs. The mGCs are well known to perform "pattern separation" (i.e., a process of transforming similar input patterns into less similar output patterns) to facilitate pattern storage in the hippocampal CA3. In this paper, we investigate the effect of the young imGCs on pattern separation of the mGCs. The pattern separation efficacy (PSE) of the mGCs is found to vary through competition between high excitability and low excitatory innervation of the imGCs. Their PSE becomes enhanced (worsened) when the effect of high excitability is higher (lower) than the effect of low excitatory innervation. In contrast to the mGCs, the imGCs are found to perform "pattern integration" (i.e., making association between dissimilar patterns). Finally, we speculate that memory resolution in the hippocampal CA3 might be optimally maximized via mixed cooperative encoding through pattern separation and pattern integration.

Is the Papez circuit the location of the elusive episodic memory engram?

All of the brain structures and white matter that make up Papez' circuit, as well as the circuit as a whole, are implicated in the literature in episodic memory formation and recall. This paper shows that Papez' circuit has the detailed structure and connectivity that is evidently required to support the episodic memory engram, and that identifying Papez' circuit as the location of the engram answers a number of long-standing questions regarding the role of medial temporal lobe structures in episodic memory. The paper then shows that the process by which the episodic memory engram may be formed is a network-wide Hebbian potentiation termed "racetrack potentiation", whose frequency corresponds to that observed in vivo in humans for memory functions. Further, by considering the microcircuits observed in the medial temporal lobe structures forming Papez' circuit, the paper establishes the neural mechanisms behind the required functions of sensory information storage and recall, pattern completion, pattern separation, and memory consolidation. The paper shows that Papez' circuit has the necessary connectivity to gather the various elements of an episodic memory occurring within Pöppel's experienced time or "quantum of experience". Finally, the paper shows how the memory engram located in Papez' circuit might be central to the formation of a duplicate engram in the cortex enabling consolidation and long-term storage of episodic memories.

Increased excitability of dentate gyrus mossy cells occurs early in life in the Tg2576 model of Alzheimer's disease

INTRODUCTION

Hyperexcitability in Alzheimer's disease (AD) emerge early and contribute to disease progression. The dentate gyrus (DG) is implicated in hyperexcitability in AD. We hypothesized that mossy cells (MCs), regulators of DG excitability, contribute to early hyperexcitability in AD. Indeed, MCs generate hyperexcitability in epilepsy.

METHODS

Using the Tg2576 model and WT mice (∼1month-old), we compared MCs electrophysiologically, assessed c-Fos activity marker, Aβ expression and mice performance in a hippocampal-dependent memory task.

RESULTS

Tg2576 MCs exhibit increased spontaneous excitatory events and decreased inhibitory currents, increasing the charge transfer excitation/inhibition ratio. Tg2576 MC intrinsic excitability was enhanced, and showed higher c-Fos, intracellular Aβ expression, and axon sprouting. Granule cells only showed changes in synaptic properties, without intrinsic changes. The effects occurred before a memory task is affected.

DISCUSSION

Early electrophysiological and morphological alterations in Tg2576 MCs are consistent with enhanced excitability, suggesting an early role in DG hyperexcitability and AD pathophysiology.

HIGHLIGHTS

∘ MCs from 1 month-old Tg2576 mice had increased spontaneous excitatory synaptic input. ∘ Tg2576 MCs had reduced spontaneous inhibitory synaptic input. ∘ Several intrinsic properties were abnormal in Tg2576 MCs. ∘ Tg2576 GCs had enhanced synaptic excitation but no changes in intrinsic properties. ∘ Tg2576 MCs exhibited high c-Fos expression, soluble Aβ and axonal sprouting.

A theory of hippocampal theta correlations accounting for extrinsic and intrinsic sequences

Hippocampal place cell sequences have been hypothesized to serve as diverse purposes as the induction of synaptic plasticity, formation and consolidation of long-term memories, or navigation and planning. During spatial behaviors of rodents, sequential firing of place cells at the theta timescale (known as theta sequences) encodes running trajectories, which can be considered as one-dimensional behavioral sequences of traversed locations. In a two-dimensional space, however, each single location can be visited along arbitrary one-dimensional running trajectories. Thus, a place cell will generally take part in multiple different theta sequences, raising questions about how this two-dimensional topology can be reconciled with the idea of hippocampal sequences underlying memory of (one-dimensional) episodes. Here, we propose a computational model of cornu ammonis 3 (CA3) and dentate gyrus (DG), where sensorimotor input drives the direction-dependent (extrinsic) theta sequences within CA3 reflecting the two-dimensional spatial topology, whereas the intrahippocampal CA3-DG projections concurrently produce intrinsic sequences that are independent of the specific running trajectory. Consistent with experimental data, intrinsic theta sequences are less prominent, but can nevertheless be detected during theta activity, thereby serving as running-direction independent landmark cues. We hypothesize that the intrinsic sequences largely reflect replay and preplay activity during non-theta states.

Adaptive spike threshold dynamics associated with sparse spiking of hilar mossy cells are captured by a simple model

Hilar mossy cells (hMCs) in the dentate gyrus (DG) receive inputs from DG granule cells (GCs), CA3 pyramidal cells and inhibitory interneurons, and provide feedback input to GCs. Behavioural and in vivo recording experiments implicate hMCs in pattern separation, navigation and spatial learning. Our experiments link hMC intrinsic excitability to their synaptically evoked in vivo spiking outputs. We performed electrophysiological recordings from DG neurons and found that hMCs displayed an adaptative spike threshold that increased both in proportion to the intensity of injected currents, and in response to spiking itself, returning to baseline over a long time scale, thereby instantaneously limiting their firing rate responses. The hMC activity is additionally limited by a prominent medium after-hyperpolarizing potential (AHP) generated by small conductance K+ channels. We hypothesize that these intrinsic hMC properties are responsible for their low in vivo firing rates. Our findings extend previous studies that compare hMCs, CA3 pyramidal cells and hilar inhibitory cells and provide novel quantitative data that contrast the intrinsic properties of these cell types. We developed a phenomenological exponential integrate-and-fire model that closely reproduces the hMC adaptive threshold nonlinearities with respect to their threshold dependence on input current intensity, evoked spike latency and long-lasting spike-induced increase in spike threshold. Our robust and computationally efficient model is amenable to incorporation into large network models of the DG that will deepen our understanding of the neural bases of pattern separation, spatial navigation and learning. KEY POINTS: Previous studies have shown that hilar mossy cells (hMCs) are implicated in pattern separation and the formation of spatial memory, but how their intrinsic properties relate to their in vivo spiking patterns is still unknown. Here we show that the hMCs display electrophysiological properties that distinguish them from the other hilar cell types including a highly adaptive spike threshold that decays slowly. The spike-dependent increase in threshold combined with an after-hyperpolarizing potential mediated by a slow K+ conductance is hypothesized to be responsible for the low-firing rate of the hMC observed in vivo. The hMC's features are well captured by a modified stochastic exponential integrate-and-fire model that has the unique feature of a threshold intrinsically dependant on both the stimulus intensity and the spiking history. This computational model will allow future work to study how the hMCs can contribute to spatial memory formation and navigation.

Neurobehavioral impairments predict specific cerebral damage in rat model of subarachnoid hemorrhage

Subarachnoid hemorrhage (SAH) is a severe form of stroke that can cause unpredictable and diffuse cerebral damage, which is difficult to detect until it becomes irreversible. Therefore, there is a need for a reliable method to identify dysfunctional regions and initiate treatment before permanent damage occurs. Neurobehavioral assessments have been suggested as a possible tool to detect and approximately localize dysfunctional cerebral regions. In this study, we hypothesized that a neurobehavioral assessment battery could be a sensitive and specific early warning for damage in discrete cerebral regions following SAH. To test this hypothesis, a behavioral battery was employed at multiple time points after SAH induced via an endovascular perforation, and brain damage was confirmed via postmortem histopathological analysis. Our results demonstrate that impairment of sensorimotor function accurately predict damage in the cerebral cortex (AUC: 0.905; sensitivity: 81.8%; specificity: 90.9%) and striatum (AUC: 0.913; sensitivity: 90.1%; specificity: 100%), while impaired novel object recognition is a more accurate indicator of damage to the hippocampus (AUC: 0.902; sensitivity: 74.1%; specificity: 83.3%) than impaired reference memory (AUC: 0.746; sensitivity: 72.2%; specificity: 58.0%). Tests for anxiety-like and depression-like behaviors predict damage to the amygdala (AUC: 0.900; sensitivity: 77.0%; specificity: 81.7%) and thalamus (AUC: 0.963; sensitivity: 86.3%; specificity: 87.8%), respectively. This study suggests that recurring behavioral testing can accurately predict damage in specific brain regions, which could be developed into a clinical battery for early detection of SAH damage in humans, potentially improving early treatment and outcomes.

Dopamine D2 receptors in mossy cells reduce excitatory transmission and are essential for hippocampal function

Hilar mossy cells (MCs) are principal excitatory neurons of the dentate gyrus (DG) that play critical roles in hippocampal function and have been implicated in brain disorders such as anxiety and epilepsy. However, the mechanisms by which MCs contribute to DG function and disease are poorly understood. Expression from the dopamine D2 receptor (D2R) gene (Drd2) promoter is a defining feature of MCs, and previous work indicates a key role for dopaminergic signaling in the DG. Additionally, the involvement of D2R signaling in cognition and neuropsychiatric conditions is well-known. Surprisingly, though, the function of MC D2Rs remain largely unexplored. In this study, we show that selective and conditional removal of Drd2 from MCs of adult mice impaired spatial memory, promoted anxiety-like behavior and was proconvulsant. To determine the subcellular expression of D2Rs in MCs, we used a D2R knockin mouse which revealed that D2Rs are enriched in the inner molecular layer of the DG, where MCs establish synaptic contacts with granule cells. D2R activation by exogenous and endogenous dopamine reduced MC to dentate granule cells (GC) synaptic transmission, most likely by a presynaptic mechanism. In contrast, removing Drd2 from MCs had no significant impact on MC excitatory inputs and passive and active properties. Our findings support that MC D2Rs are essential for proper DG function by reducing MC excitatory drive onto GCs. Lastly, impairment of MC D2R signaling could promote anxiety and epilepsy, therefore highlighting a potential therapeutic target.

Target cell-specific plasticity rules of NMDA receptor-mediated synaptic transmission in the hippocampus

Long-term potentiation and depression of NMDA receptor-mediated synaptic transmission (NMDAR LTP/LTD) can significantly impact synapse function and information transfer in several brain areas. However, the mechanisms that determine the direction of NMDAR plasticity are poorly understood. Here, using physiologically relevant patterns of presynaptic and postsynaptic burst activities, whole-cell patch clamp recordings, 2-photon laser calcium imaging in acute rat hippocampal slices and immunoelectron microscopy, we tested whether distinct calcium dynamics and group I metabotropic glutamate receptor (I-mGluR) subtypes control the sign of NMDAR plasticity. We found that postsynaptic calcium transients (CaTs) in response to hippocampal MF stimulation were significantly larger during the induction of NMDAR-LTP compared to NMDAR-LTD at the MF-to-CA3 pyramidal cell (MF-CA3) synapse. This difference was abolished by pharmacological blockade of mGluR5 and was significantly reduced by depletion of intracellular calcium stores, whereas blocking mGluR1 had no effect on these CaTs. In addition, we discovered that MF to hilar mossy cell (MF-MC) synapses, which share several structural and functional commonalities with MF-CA3 synapses, also undergoes NMDAR plasticity. To our surprise, however, we found that the postsynaptic distribution of I-mGluR subtypes at these two synapses differ, and the same induction protocol that induces NMDAR-LTD at MF-CA3 synapses, only triggered NMDAR-LTP at MF-MC synapses, despite a comparable calcium dynamics. Thus, postsynaptic calcium dynamics alone cannot predict the sign of NMDAR plasticity, indicating that both postsynaptic calcium rise and the relative contribution of I-mGluR subtypes likely determine the learning rules of NMDAR plasticity.

Oscillations in the dentate gyrus as a tool for the performance of the hippocampal functions: Healthy and epileptic brain

The dentate gyrus (DG) is part of the hippocampal formation and is essential for important cognitive processes such as navigation and memory. The oscillatory activity of the DG network is believed to play a critical role in cognition. DG circuits generate theta, beta, and gamma rhythms, which participate in the specific information processing performed by DG neurons. In the temporal lobe epilepsy (TLE), cognitive abilities are impaired, which may be due to drastic alterations in the DG structure and network activity during epileptogenesis. The theta rhythm and theta coherence are especially vulnerable in dentate circuits; disturbances in DG theta oscillations and their coherence may be responsible for general cognitive impairments observed during epileptogenesis. Some researchers suggested that the vulnerability of DG mossy cells is a key factor in the genesis of TLE, but others did not support this hypothesis. The aim of the review is not only to present the current state of the art in this field of research but to help pave the way for future investigations by highlighting the gaps in our knowledge to completely appreciate the role of DG rhythms in brain functions. Disturbances in oscillatory activity of the DG during TLE development may be a diagnostic marker in the treatment of this disease.

Similar Presynaptic Action Potential-Calcium Influx Coupling in Two Types of Large Mossy Fiber Terminals Innervating CA3 Pyramidal Cells and Hilar Mossy Cells

Morphologically similar axon boutons form synaptic contacts with diverse types of postsynaptic cells. However, it is less known to what extent the local axonal excitability, presynaptic action potentials (APs), and AP-evoked calcium influx contribute to the functional diversity of synapses and neuronal activity. This is particularly interesting in synapses that contact cell types that show only subtle cellular differences but fulfill completely different physiological functions. Here, we tested these questions in two synapses that are formed by rat hippocampal granule cells (GCs) onto hilar mossy cells (MCs) and CA3 pyramidal cells, which albeit share several morphologic and synaptic properties but contribute to distinct physiological functions. We were interested in the deterministic steps of the action potential-calcium ion influx coupling as these complex modules may underlie the functional segregation between and within the two cell types. Our systematic comparison using direct axonal recordings showed that AP shapes, Ca²⁺ currents and their plasticity are indistinguishable in synapses onto these two cell types. These suggest that the complete module that couples granule cell activity to synaptic release is shared by hilar mossy cells and CA3 pyramidal cells. Thus, our findings present an outstanding example for the modular composition of distinct cell types, by which cells employ different components only for those functions that are deterministic for their specialized functions, while many of their main properties are shared.

Disynaptic effect of hilar cells on pattern separation in a spiking neural network of hippocampal dentate gyrus

We study the disynaptic effect of the hilar cells on pattern separation in a spiking neural network of the hippocampal dentate gyrus (DG). The principal granule cells (GCs) in the DG perform pattern separation, transforming similar input patterns into less-similar output patterns. In our DG network, the hilus consists of excitatory mossy cells (MCs) and inhibitory HIPP (hilar perforant path-associated) cells. Here, we consider the disynaptic effects of the MCs and the HIPP cells on the GCs, mediated by the inhibitory basket cells (BCs) in the granular layer; MC → BC → GC and HIPP → BC → GC. The MCs provide disynaptic inhibitory input (mediated by the intermediate BCs) to the GCs, which decreases the firing activity of the GCs. On the other hand, the HIPP cells disinhibit the intermediate BCs, which leads to increasing the firing activity of the GCs. In this way, the disynaptic effects of the MCs and the HIPP cells are opposite. We investigate change in the pattern separation efficacy by varying the synaptic strength K ( BC , X ) [from the pre-synaptic X (= MC or HIPP) to the post-synaptic BC]. Thus, sparsity for the firing activity of the GCs is found to improve the efficacy of pattern separation, and hence the disynaptic effects of the MCs and the HIPP cells on the pattern separation become opposite ones. In the combined case when simultaneously changing both K ( BC , MC ) and K ( BC , HIPP ) , as a result of balance between the two competing disynaptic effects of the MCs and the HIPP cells, the efficacy of pattern separation is found to become the highest at their original default values where the activation degree of the GCs is the lowest. We also note that, while the GCs perform pattern separation, sparsely synchronized rhythm is found to appear in the population of the GCs. Hence, we examine quantitative association between population and individual firing behaviors in the sparsely synchronized rhythm and pattern separation. They are found to be strongly correlated. Consequently, the better the population and individual firing behaviors in the sparsely synchronized rhythm are, the more pattern separation efficacy becomes enhanced.

Connectivity and synaptic features of hilar mossy cells and their effects on granule cell activity along the hippocampal longitudinal axis

The hippocampus is an elongated brain structure which runs along a ventral-to-dorsal axis in rodents, corresponding to the anterior-to-posterior axis in humans. A glutamatergic cell type in the dentate gyrus (DG), the mossy cells (MCs), establishes extensive excitatory collateral connections with the DG principal cells, the granule cells (GCs), and inhibitory interneurons in both hippocampal hemispheres along the longitudinal axis. Although coupling of two physically separated GC populations via long-axis projecting MCs is instrumental for information processing, the connectivity and synaptic features of MCs along the longitudinal axis are poorly defined. Here, using channelrhodopsin-2 assisted circuit mapping, we showed that MC excitation results in a low synaptic excitation-inhibition (E/I) balance in the intralamellar (local) GCs, but a high synaptic E/I balance in the translamellar (distant) ones. In agreement with the differential E/I balance along the ventrodorsal axis, activation of MCs either enhances or suppresses the local GC response to the cortical input, but primarily promotes the distant GC activation. Moreover, activation of MCs enhances the spike timing precision of the local GCs, but not that of the distant ones. Collectively, these findings suggest that MCs differentially regulate the local and distant GC activity through distinct synaptic mechanisms. KEY POINTS: Hippocampal mossy cell (MC) pathways differentially regulate granule cell (GC) activity along the longitudinal axis. MCs mediate a low excitation-inhibition balance in intralamellar (local) GCs, but a high excitation-inhibition balance in translamellar (distant) GCs. MCs enhance the spiking precision of local GCs, but not distant GCs. MCs either promote or suppress local GC activity, but primarily promote distant GC activation.

Population and individual firing behaviors in sparsely synchronized rhythms in the hippocampal dentate gyrus

We investigate population and individual firing behaviors in sparsely synchronized rhythms (SSRs) in a spiking neural network of the hippocampal dentate gyrus (DG). The main encoding granule cells (GCs) are grouped into lamellar clusters. In each GC cluster, there is one inhibitory (I) basket cell (BC) along with excitatory (E) GCs, and they form the E-I loop. Winner-take-all competition, leading to sparse activation of the GCs, occurs in each GC cluster. Such sparsity has been thought to enhance pattern separation performed in the DG. During the winner-take-all competition, SSRs are found to appear in each population of the GCs and the BCs through interaction of excitation of the GCs with inhibition of the BCs. Sparsely synchronized spiking stripes appear successively with the population frequencyf p ( = 13.1 Hz) in the raster plots of spikes. We also note that excitatory hilar mossy cells (MCs) control the firing activity of the GC-BC loop by providing excitation to both the GCs and the BCs. SSR also appears in the population of MCs via interaction with the GCs (i.e., GC-MC loop). Population behaviors in the SSRs are quantitatively characterized in terms of the synchronization measures. In addition, we investigate individual firing activity of GCs, BCs, and MCs in the SSRs. Individual GCs exhibit random spike skipping, leading to a multi-peaked inter-spike-interval histogram, which is well characterized in terms of the random phase-locking degree. In this case, population-averaged mean-firing-rate (MFR) < f i ( GC ) > is less than the population frequency f p . On the other hand, both BCs and MCs show "intrastripe" burstings within stripes, together with random spike skipping. Thus, the population-averaged MFR ⟨ f i ( X ) ⟩ ( X = MC and BC) is larger than f p , in contrast to the case of the GCs. MC loss may occur during epileptogenesis. With decreasing the fraction of the MCs, changes in the population and individual firings in the SSRs are also studied. Finally, quantitative association between the population/individual firing behaviors in the SSRs and the winner-take-all competition is discussed.

Activin A regulates the excitability of hippocampal mossy cells

Mossy cells (MCs) in the hilus of the dentate gyrus (DG) receive increasing attention as a major player controlling information processing in the DG network. Furthermore, disturbed MC activity has been implicated in widespread neuropsychiatric disorders such as epilepsy and major depression. Using whole-cell patch-clamp recordings from MCs in acute hippocampal slices from wild type and transgenic mice, we demonstrate that activin, a member of the transforming growth factor-β (TGF-β) family, has a strong neuromodulatory effect on MC activity. Disruption of activin receptor signaling reduced MC firing, dampened their excitatory input and augmented their inhibitory input. By contrast, acute application of recombinant activin A strongly increased MC activity and promoted excitatory synaptic drive. Notably, similar changes of MC activity have been observed in a rodent model of depression and after antidepressant drug therapy, respectively. Given that a rise in activin signaling particularly in the DG has been proposed as a mechanism of antidepressant action, our data suggest that the effect of activin on MC excitability might make a considerable contribution in this regard.

Interneuron diversity in the rat dentate gyrus: An unbiased in vitro classification

Information processing in cortical circuits, including the hippocampus, relies on the dynamic control of neuronal activity by GABAergic interneurons (INs). INs form a heterogenous population with defined types displaying distinct morphological, molecular, and physiological characteristics. In the major input region of the hippocampus, the dentate gyrus (DG), a number of IN types have been described which provide synaptic inhibition to distinct compartments of excitatory principal cells (PrCs) and other INs. In this study, we perform an unbiased classification of GABAergic INs in the DG by combining in vitro whole-cell patch-clamp recordings, intracellular labeling, morphological analysis, and supervised cluster analysis to better define IN type diversity in this region. This analysis reveals that DG INs divide into at least 13 distinct morpho-physiological types which reflect the complexity of the local IN network and serve as a basis for further network analyses.

Dynamical origin for winner-take-all competition in a biological network of the hippocampal dentate gyrus

We consider a biological network of the hippocampal dentate gyrus (DG). Computational models suggest that the DG would be a preprocessor for pattern separation (i.e., a process transforming a set of similar input patterns into distinct nonoverlapping output patterns) which could facilitate pattern storage and retrieval in the CA3 area of the hippocampus. The main encoding cells in the DG are the granule cells (GCs) which receive the input from the entorhinal cortex (EC) and send their output to the CA3. We note that the activation degree of GCs is very low (∼5%). This sparsity has been thought to enhance the pattern separation. We investigate the dynamical origin for winner-take-all (WTA) competition which leads to sparse activation of the GCs. The whole GCs are grouped into lamellar clusters. In each cluster, there is one inhibitory (I) basket cell (BC) along with excitatory (E) GCs. There are three kinds of external inputs into the GCs: the direct excitatory EC input; the indirect feedforward inhibitory EC input, mediated by the HIPP (hilar perforant path-associated) cells; and the excitatory input from the hilar mossy cells (MCs). The firing activities of the GCs are determined via competition between the external E and I inputs. The E-I conductance ratio R_{E-I}^{(con)}^{*} (given by the time average of the ratio of the external E to I conductances) may represent well the degree of such external E-I input competition. It is thus found that GCs become active when their R_{E-I}^{(con)}^{*} is larger than a threshold R_{th}^{*}, and then the mean firing rates of the active GCs are strongly correlated with R_{E-I}^{(con)}^{*}. In each cluster, the feedback inhibition from the BC may select the winner GCs. GCs with larger R_{E-I}^{(con)}^{*} than the threshold R_{th}^{*} survive, and they become winners; all the other GCs with smaller R_{E-I}^{(con)}^{*} become silent. In this way, WTA competition occurs via competition between the firing activity of the GCs and the feedback inhibition from the BC in each cluster. Finally, we also study the effects of MC death and adult-born immature GCs on the WTA competition.

Direct synaptic excitation between hilar mossy cells revealed with a targeted voltage sensor

The dentate gyrus not only gates the flow of information into the hippocampus, it also integrates and processes this information. Mossy cells (MCs) are a major type of excitatory neuron strategically located in the hilus of the dentate gyrus where they can contribute to this processing through networks of synapses with inhibitory neurons and dentate granule cells. Some prior work has suggested that MCs can form excitatory synapses with other MCs, but the role of these synapses in the network activity of the dentate gyrus has received little attention. Here, we investigated synaptic inputs to MCs in mouse hippocampal slices using a genetically encoded hybrid voltage sensor (hVOS) targeted to MCs by Cre-lox technology. This enabled optical recording of voltage changes from multiple MCs simultaneously. Stimulating granule cells and CA3 pyramidal cells activated well-established inputs to MCs and elicited synaptic responses as expected. However, the weak blockade of MC responses to granule cell layer stimulation by DCG-IV raised the possibility of another source of excitation. To evaluate synapses between MCs as this source, single MCs were stimulated focally. Stimulation of one MC above its action potential threshold evoked depolarizing responses in neighboring MCs that depended on glutamate receptors. Short latency responses of MCs to other MCs did not depend on release from granule cell axons. However, granule cells did contribute to the longer latency responses of MCs to stimulation of other MCs. Thus, MCs transmit their activity to other MCs both through direct synaptic coupling and through polysynaptic coupling with dentate granule cells. MC-MC synapses can redistribute information entering the dentate gyrus and thus shape and modulate the electrical activity underlying hippocampal functions such as navigation and memory, as well as excessive excitation during seizures.

Multiple cannabinoid signaling cascades powerfully suppress recurrent excitation in the hippocampus

Recurrent excitatory neural networks are unstable. In the hippocampus, excitatory mossy cells (MCs) receive strong excitatory inputs from dentate granule cells (GCs) and project back onto the proximal dendrites of GCs. By targeting the ipsi- and contralateral dentate gyrus (DG) along the dorsoventral axis of the hippocampus, MCs form an extensive recurrent excitatory circuit (GC-MC-GC) whose dysregulation can promote epilepsy. We recently reported that a physiologically relevant pattern of MC activity induces a robust form of presynaptic long-term potentiation (LTP) of MC-GC transmission which enhances GC output. Left unchecked, this LTP may interfere with DG-dependent learning, like pattern separation-which relies on sparse GC firing-and may even facilitate epileptic activity. Intriguingly, MC axons display uniquely high expression levels of type-1 cannabinoid receptors (CB1Rs), but their role at MC-GC synapses is poorly understood. Using rodent hippocampal slices, we report that constitutively active CB1Rs, presumably via βγ subunits, selectively inhibited MC inputs onto GCs but not MC inputs onto inhibitory interneurons or CB1R-sensitive inhibitory inputs onto GCs. Tonic CB1R activity also inhibited LTP and GC output. Furthermore, brief endocannabinoid release from GCs dampened MC-GC LTP in two mechanistically distinct ways: during induction via βγ signaling and before induction via α_i/o signaling in a form of presynaptic metaplasticity. Lastly, a single in vivo exposure to exogenous cannabinoids was sufficient to induce this presynaptic metaplasticity. By dampening excitatory transmission and plasticity, tonic and phasic CB1R activity at MC axon terminals may preserve the sparse nature of the DG and protect against runaway excitation.

Hippocampal Somatostatin Interneurons, Long-Term Synaptic Plasticity and Memory

A distinctive feature of the hippocampal structure is the diversity of inhibitory interneurons. These complex inhibitory interconnections largely contribute to the tight modulation of hippocampal circuitry, as well as to the formation and coordination of neuronal assemblies underlying learning and memory. Inhibitory interneurons provide more than a simple transitory inhibition of hippocampal principal cells (PCs). The synaptic plasticity of inhibitory neurons provides long-lasting changes in the hippocampal network and is a key component of memory formation. The dendrite targeting interneurons expressing the peptide somatostatin (SOM) are particularly interesting in this regard because they display unique long-lasting synaptic changes leading to metaplastic regulation of hippocampal networks. In this article, we examine the actions of the neuropeptide SOM on hippocampal cells, synaptic plasticity, learning, and memory. We address the different subtypes of hippocampal SOM interneurons. We describe the long-term synaptic plasticity that takes place at the excitatory synapses of SOM interneurons, its singular induction and expression mechanisms, as well as the consequences of these changes on the hippocampal network, learning, and memory. We also review evidence that astrocytes provide cell-specific dynamic regulation of inhibition of PC dendrites by SOM interneurons. Finally, we cover how, in mouse models of Alzheimer’s disease (AD), dysfunction of plasticity of SOM interneuron excitatory synapses may also contribute to cognitive impairments in brain disorders.

Neurophotonics Approaches for the Study of Pattern Separation

Successful memory involves not only remembering over time but also keeping memories distinct. Computational models suggest that pattern separation appears as a highly efficient process to discriminate between overlapping memories. Furthermore, lesion studies have shown that the dentate gyrus (DG) participates in pattern separation. However, these manipulations did not allow identifying the neuronal mechanism underlying pattern separation. The development of different neurophotonics techniques, together with other genetic tools, has been useful for the study of the microcircuit involved in this process. It has been shown that less-overlapped information would generate distinct neuronal representations within the granule cells (GCs). However, because glutamatergic or GABAergic cells in the DG are not functionally or structurally homogeneous, identifying the specific role of the different subpopulations remains elusive. Then, understanding pattern separation requires the ability to manipulate a temporal and spatially specific subset of cells in the DG and ideally to analyze DG cells activity in individuals performing a pattern separation dependent behavioral task. Thus, neurophotonics and calcium imaging techniques in conjunction with activity-dependent promoters and high-resolution microscopy appear as important tools for this endeavor. In this work, we review how different neurophotonics techniques have been implemented in the elucidation of a neuronal network that supports pattern separation alone or in combination with traditional techniques. We discuss the limitation of these techniques and how other neurophotonic techniques could be used to complement the advances presented up to this date.

A comprehensive knowledge base of synaptic electrophysiology in the rodent hippocampal formation

The cellular and synaptic architecture of the rodent hippocampus has been described in thousands of peer-reviewed publications. However, no human- or machine-readable public catalog of synaptic electrophysiology data exists for this or any other neural system. Harnessing state-of-the-art information technology, we have developed a cloud-based toolset for identifying empirical evidence from the scientific literature pertaining to synaptic electrophysiology, for extracting the experimental data of interest, and for linking each entry to relevant text or figure excerpts. Mining more than 1,200 published journal articles, we have identified eight different signal modalities quantified by 90 different methods to measure synaptic amplitude, kinetics, and plasticity in hippocampal neurons. We have designed a data structure that both reflects the differences and maintains the existing relations among experimental modalities. Moreover, we mapped every annotated experiment to identified potential connections, that is, specific pairs of presynaptic and postsynaptic neuron types. To this aim, we leveraged Hippocampome.org, an open-access knowledge base of morphologically, electrophysiologically, and molecularly characterized neuron types in the rodent hippocampal formation. Specifically, we have implemented a computational pipeline to systematically translate neuron type properties into formal queries in order to find all compatible potential connections. With this system, we have collected nearly 40,000 synaptic data entities covering 88% of the 3,120 potential connections in Hippocampome.org. Correcting membrane potentials with respect to liquid junction potentials significantly reduced the difference between theoretical and experimental reversal potentials, thereby enabling the accurate conversion of all synaptic amplitudes to conductance. This data set allows for large-scale hypothesis testing of the general rules governing synaptic signals. To illustrate these applications, we confirmed several expected correlations between synaptic measurements and their covariates while suggesting previously unreported ones. We release all data open-source at Hippocampome.org in order to further research across disciplines.

Effect of interpopulation spike-timing-dependent plasticity on synchronized rhythms in neuronal networks with inhibitory and excitatory populations

We consider a two-population network consisting of both inhibitory (I) interneurons and excitatory (E) pyramidal cells. This I-E neuronal network has adaptive dynamic I to E and E to I interpopulation synaptic strengths, governed by interpopulation spike-timing-dependent plasticity (STDP). In previous works without STDPs, fast sparsely synchronized rhythms, related to diverse cognitive functions, were found to appear in a range of noise intensity D for static synaptic strengths. Here, by varying D, we investigate the effect of interpopulation STDPs on fast sparsely synchronized rhythms that emerge in both the I- and the E-populations. Depending on values of D, long-term potentiation (LTP) and long-term depression (LTD) for population-averaged values of saturated interpopulation synaptic strengths are found to occur. Then, the degree of fast sparse synchronization varies due to effects of LTP and LTD. In a broad region of intermediate D, the degree of good synchronization (with higher synchronization degree) becomes decreased, while in a region of large D, the degree of bad synchronization (with lower synchronization degree) gets increased. Consequently, in each I- or E-population, the synchronization degree becomes nearly the same in a wide range of D (including both the intermediate and the large D regions). This kind of "equalization effect" is found to occur via cooperative interplay between the average occupation and pacing degrees of spikes (i.e., the average fraction of firing neurons and the average degree of phase coherence between spikes in each synchronized stripe of spikes in the raster plot of spikes) in fast sparsely synchronized rhythms. Finally, emergences of LTP and LTD of interpopulation synaptic strengths (leading to occurrence of equalization effect) are intensively investigated via a microscopic method based on the distributions of time delays between the pre- and the post-synaptic spike times.

Quantitative properties of a feedback circuit predict frequency-dependent pattern separation

Feedback inhibitory motifs are thought to be important for pattern separation across species. How feedback circuits may implement pattern separation of biologically plausible, temporally structured input in mammals is, however, poorly understood. We have quantitatively determined key properties of netfeedback inhibition in the mouse dentate gyrus, a region critically involved in pattern separation. Feedback inhibition is recruited steeply with a low dynamic range (0% to 4% of active GCs), and with a non-uniform spatial profile. Additionally, net feedback inhibition shows frequency-dependent facilitation, driven by strongly facilitating mossy fiber inputs. Computational analyses show a significant contribution of the feedback circuit to pattern separation of theta modulated inputs, even within individual theta cycles. Moreover, pattern separation was selectively boosted at gamma frequencies, in particular for highly similar inputs. This effect was highly robust, suggesting that frequency-dependent pattern separation is a key feature of the feedback inhibitory microcircuit.

You can probably recall where you left your car this morning without too much trouble. But assuming you use the same busy parking lot every day, can you remember which space you parked in yesterday? Or the day before that? Most people find this difficult not because they cannot remember what happened two or three days ago, but because it requires distinguishing between very similar memories. The car, the parking lot, and the time of day were the same on each occasion. So how do you remember where you parked this morning?

This ability to distinguish between memories of similar events depends on a brain region called the hippocampus. A subregion of the hippocampus called the dentate gyrus generates different patterns of activity in response to events that are similar but distinct. This process is called pattern separation, and it helps ensure that you do not look for your car in yesterday’s parking space.

Pattern separation in the dentate gyrus is thought to involve a form of negative feedback called feedback inhibition, a phenomenon where the output of a process acts to limit or stop the same process. To test this idea, Braganza et al. studied feedback inhibition in the dentate gyrus of mice, before building a computer model simulating the inhibition process and supplying the model with two types of realistic input. The first consisted of low-frequency theta brainwaves, which occur, for instance, in the dentate gyrus when animals explore their environment. The second consisted of higher frequency gamma brainwaves, which occur, for example, when animals experience something new.

Testing the model showed that feedback inhibition contributes to pattern separation with both theta and gamma inputs. However, pattern separation is stronger with gamma input. This suggests that high frequency brainwaves in the hippocampus could help animals distinguish new events from old ones by promoting pattern separation.

Various brain disorders, including Alzheimer’s disease, schizophrenia and epilepsy, involve changes in the dentate gyrus and altered brain rhythms. The current findings could help reveal how these changes contribute to memory impairments and to a reduced ability to distinguish similar experiences.

Dentate gyrus circuits for encoding, retrieval and discrimination of episodic memories

The dentate gyrus (DG) has a key role in hippocampal memory formation. Intriguingly, DG lesions impair many, but not all, hippocampus-dependent mnemonic functions, indicating that the rest of the hippocampus (CA1-CA3) can operate autonomously under certain conditions. An extensive body of theoretical work has proposed how the architectural elements and various cell types of the DG may underlie its function in cognition. Recent studies recorded and manipulated the activity of different neuron types in the DG during memory tasks and have provided exciting new insights into the mechanisms of DG computational processes, particularly for the encoding, retrieval and discrimination of similar memories. Here, we review these DG-dependent mnemonic functions in light of the new findings and explore mechanistic links between the cellular and network properties of, and the computations performed by, the DG.

Sonic Hedgehog is expressed by hilar mossy cells and regulates cellular survival and neurogenesis in the adult hippocampus

Sonic hedgehog (Shh) is a multifunctional signaling protein governing pattern formation, proliferation and cell survival during embryogenesis. In the adult brain, Shh has neurotrophic function and is implicated in hippocampal neurogenesis but the cellular source of Shh in the hippocampus remains ill defined. Here, we utilize a gene expression tracer allele of Shh (Shh-nlacZ) which allowed the identification of a subpopulation of hilar neurons known as mossy cells (MCs) as a prominent and dynamic source of Shh within the dentate gyrus. AAV-Cre mediated ablation of Shh in the adult dentate gyrus led to a marked degeneration of MCs. Conversely, chemical stimulation of hippocampal neurons using the epileptogenic agent kainic acid (KA) increased the number of Shh+ MCs indicating that the expression of Shh by MCs confers a survival advantage during the response to excitotoxic insults. In addition, ablation of Shh in the adult dentate gyrus led to increased neural precursor cell proliferation and their migration into the subgranular cell layer demonstrating that MCs-generated Shh is a key modulator of hippocampal neurogenesis.

Supramammillary Nucleus Afferents to the Dentate Gyrus Co-release Glutamate and GABA and Potentiate Granule Cell Output

The supramammillary nucleus (SuM) of the hypothalamus projects to the dentate gyrus (DG) and the CA2 region of the hippocampus. Although the SuM-to-hippocampus circuits have been implicated in spatial and emotional memory formation, little is known about precise neural connections between the SuM and hippocampus. Here, we report that axons of SuM neurons make monosynaptic connections to granule cells (GCs) and GABAergic interneurons, but not to hilar mossy cells, in the DG and co-release glutamate and γ-aminobutyric acid (GABA) at these synapses. Although inputs from the SuM can excite some interneurons, the inputs alone fail to generate spikes in GCs. However, despite the insufficient excitatory drive and GABAergic co-transmission, SuM inputs have net excitatory effects on GCs and can potentiate GC firing when temporally associated with perforant path inputs. Our results indicate that the SuM influences DG information processing by modulating GC outputs.

Involvement of Mossy Cells in Sharp Wave-Ripple Activity In Vitro

The role of mossy cells (MCs) of the hippocampal dentate area has long remained mysterious. Recent research has begun to unveil their significance in spatial computation of the hippocampus. Here, we used an in vitro model of sharp wave-ripple complexes (SWRs), which contribute to hippocampal memory formation, to investigate MC involvement in this fundamental population activity. We find that a significant fraction of MCs (∼47%) is recruited into the active neuronal network during SWRs in the CA3 area. Moreover, MCs receive pronounced, ripple-coherent, excitatory and inhibitory synaptic input. Finally, we find evidence for SWR-related synaptic activity in granule cells that is mediated by MCs. Given the widespread connectivity of MCs within and between hippocampi, our data suggest a role for MCs as a hub functionally coupling the CA3 and the DG during ripple-associated computations.

Functional Specialization of Interneuron Dendrites: Identification of Action Potential Initiation Zone in Axonless Olfactory Bulb Granule Cells

Principal cells in the olfactory bulb (OB), mitral and tufted cells, play key roles in processing and then relaying sensory information to downstream cortical regions. How OB local circuits facilitate odor-specific responses during odor discrimination is not known but involves GABAergic inhibition mediated by axonless granule cells (GCs), the most abundant interneuron in the OB. Most previous work on GCs has focused on defining properties of distal apical dendrites where these interneurons form reciprocal dendrodendritic connections with principal cells. Less is known about the function of the proximal dendritic compartments. In the present study, we identified the likely action potentials (AP) initiation zone by comparing electrophysiological properties of rat (either sex) GCs with apical dendrites severed at different locations. We find that truncated GCs with long apical dendrites had active properties that were indistinguishable from intact GCs, generating full-height APs and short-latency low-threshold Ca²⁺ spikes. We then confirmed the presumed site of AP and low-threshold Ca²⁺ spike initiation in the proximal apical dendrite using two-photon Ca²⁺ photometry and focal TTX application. These results suggest that GCs incorporate two separate pathways for processing synaptic inputs: an already established dendrodendritic input to the distal apical dendrite and a novel pathway in which the cell body integrates proximal synaptic inputs, leading to spike generation in the proximal apical dendrite. Spikes generated by the proximal pathway likely enables GCs to regulate lateral inhibition by defining time windows when lateral inhibition is functional.SIGNIFICANCE STATEMENT The olfactory bulb plays a central role in processing sensory input transduced by receptor neurons. How local circuits in the bulb function to facilitate sensory processing during odor discrimination is not known but appears to involve inhibition mediated by granule cells, axonless GABAergic interneurons. Little is known about the active conductances in granule cells including where action potentials originate. Using a variety of experimental approaches, we find the Na⁺-based action potentials originate in the proximal apical dendrite, a region targeted by cortical feedback afferents. We also find evidence for high expression of low-voltage activated Ca²⁺ channels in the same region, intrinsic currents that enable GCs to spike rapidly in response to sensory input during each sniff cycle.

Hippocampal Mossy Cells Provide a Fate Switch for Adult Neural Stem Cells

The pathways that convert neural stem cells (NSCs) into functional neurons in the adult hippocampus are tightly regulated. In this issue of Neuron, Yeh et al. (2018) demonstrate that the activity of dentate mossy cells determines the balance between quiescence and activation of NSCs.

Cluster burst synchronization in a scale-free network of inhibitory bursting neurons

We consider a scale-free network of inhibitory Hindmarsh-Rose (HR) bursting neurons, and make a computational study on coupling-induced cluster burst synchronization by varying the average coupling strength J 0 . For sufficiently small J 0 , non-cluster desynchronized states exist. However, when passing a critical point J c ∗ ( ≃ 0.16 ) , the whole population is segregated into 3 clusters via a constructive role of synaptic inhibition to stimulate dynamical clustering between individual burstings, and thus 3-cluster desynchronized states appear. As J 0 is further increased and passes a lower threshold J l ∗ ( ≃ 0.78 ) , a transition to 3-cluster burst synchronization occurs due to another constructive role of synaptic inhibition to favor population synchronization. In this case, HR neurons in each cluster make burstings every 3rd cycle of the instantaneous burst rate R w ( t ) of the whole population, and exhibit burst synchronization. However, as J 0 passes an intermediate threshold J m ∗ ( ≃ 5.2 ) , HR neurons fire burstings intermittently at a 4th cycle of R w ( t ) via burst skipping rather than at its 3rd cycle, and hence they begin to make intermittent hoppings between the 3 clusters. Due to such intermittent intercluster hoppings via burst skippings, the 3 clusters become broken up (i.e., the 3 clusters are integrated into a single one). However, in spite of such break-up (i.e., disappearance) of the 3-cluster states, (non-cluster) burst synchronization persists in the whole population, which is well visualized in the raster plot of burst onset times where bursting stripes (composed of burst onset times and indicating burst synchronization) appear successively. With further increase in J 0 , intercluster hoppings are intensified, and bursting stripes also become dispersed more and more due to a destructive role of synaptic inhibition to spoil the burst synchronization. Eventually, when passing a higher threshold J h ∗ ( ≃ 17.8 ) a transition to desynchronization occurs via complete overlap between the bursting stripes. Finally, we also investigate the effects of stochastic noise on both 3-cluster burst synchronization and intercluster hoppings.

Dentate granule and mossy cells exhibit distinct spatiotemporal responses to local change in a one-dimensional landscape of visual-tactile cues

The dentate gyrus (DG) is critical for detecting changes in environments; however, how granule cells (GCs) and mossy cells (MCs), the two excitatory cell types of the DG, respond to small changes in the object layout is unclear. Here, we recorded GCs and MCs, identified by spike feature and optogenetic tagging, as mice ran on a treadmill belt enriched with visual-tactile cues. We observed that fixing a new cue on the belt induced a reconfiguration of GC and MC spatial representations via the emergence, extinction and rate alteration of firing fields. For both GCs and MCs, the response was maximal near the cue and spread over the entire belt. However, compared to the GC response, the MC response was stronger and more immediate, peaked at a slightly earlier belt position, and exhibited a transient component reminiscent of neuromodulatory activity. A competitive neural network model reproduced the GC response contingent on both the introduction of new object-vector inputs and the reconfiguration of MC activity, the former being critical for spreading the GC response in locations distant from the cue. These findings suggest that GCs operate as a competitive network and that MCs precede GCs in detecting changes and help expand the range of GC pattern separation.

Pattern separation of spiketrains in hippocampal neurons

Pattern separation is a process that minimizes overlap between patterns of neuronal activity representing similar experiences. Theoretical work suggests that the dentate gyrus (DG) performs this role for memory processing but a direct demonstration is lacking. One limitation is the difficulty to measure DG inputs and outputs simultaneously. To rigorously assess pattern separation by DG circuitry, we used mouse brain slices to stimulate DG afferents and simultaneously record DG granule cells (GCs) and interneurons. Output spiketrains of GCs are more dissimilar than their input spiketrains, demonstrating for the first time temporal pattern separation at the level of single neurons in the DG. Pattern separation is larger in GCs than in fast-spiking interneurons and hilar mossy cells, and is amplified in CA3 pyramidal cells. Analysis of the neural noise and computational modelling suggest that this form of pattern separation is not explained by simple randomness and arises from specific presynaptic dynamics. Overall, by reframing the concept of pattern separation in dynamic terms and by connecting it to the physiology of different types of neurons, our study offers a new window of understanding in how hippocampal networks might support episodic memory.

Parvalbumin+ interneurons obey unique connectivity rules and establish a powerful lateral-inhibition microcircuit in dentate gyrus

Parvalbumin-positive (PV⁺) GABAergic interneurons in hippocampal microcircuits are thought to play a key role in several higher network functions, such as feedforward and feedback inhibition, network oscillations, and pattern separation. Fast lateral inhibition mediated by GABAergic interneurons may implement a winner-takes-all mechanism in the hippocampal input layer. However, it is not clear whether the functional connectivity rules of granule cells (GCs) and interneurons in the dentate gyrus are consistent with such a mechanism. Using simultaneous patch-clamp recordings from up to seven GCs and up to four PV⁺ interneurons in the dentate gyrus, we find that connectivity is structured in space, synapse-specific, and enriched in specific disynaptic motifs. In contrast to the neocortex, lateral inhibition in the dentate gyrus (in which a GC inhibits neighboring GCs via a PV⁺ interneuron) is ~ 10-times more abundant than recurrent inhibition (in which a GC inhibits itself). Thus, unique connectivity rules may enable the dentate gyrus to perform specific higher-order computations.

GABAergic interneurons are known to provide inhibition to allow computational function of neuronal network. Here, Espinoza and colleagues show that connectivity of granule cells and interneurons in the dentate gyrus of mouse hippocampus are consistent with the circuit architecture capable of performing a winners-take-all mechanism.

Burst synchronization in a scale-free neuronal network with inhibitory spike-timing-dependent plasticity

We are concerned about burst synchronization (BS), related to neural information processes in health and disease, in the Barabási-Albert scale-free network (SFN) composed of inhibitory bursting Hindmarsh-Rose neurons. This inhibitory neuronal population has adaptive dynamic synaptic strengths governed by the inhibitory spike-timing-dependent plasticity (iSTDP). In previous works without considering iSTDP, BS was found to appear in a range of noise intensities for fixed synaptic inhibition strengths. In contrast, in our present work, we take into consideration iSTDP and investigate its effect on BS by varying the noise intensity. Our new main result is to find occurrence of a Matthew effect in inhibitory synaptic plasticity: good BS gets better via LTD, while bad BS get worse via LTP. This kind of Matthew effect in inhibitory synaptic plasticity is in contrast to that in excitatory synaptic plasticity where good (bad) synchronization gets better (worse) via LTP (LTD). We note that, due to inhibition, the roles of LTD and LTP in inhibitory synaptic plasticity are reversed in comparison with those in excitatory synaptic plasticity. Moreover, emergences of LTD and LTP of synaptic inhibition strengths are intensively investigated via a microscopic method based on the distributions of time delays between the pre- and the post-synaptic burst onset times. Finally, in the presence of iSTDP we investigate the effects of network architecture on BS by varying the symmetric attachment degree l ∗ and the asymmetry parameter Δ l in the SFN.

Advances in understanding hilar mossy cells of the dentate gyrus

Hilar mossy cells (MCs) of the dentate gyrus (DG) distinguish the DG from other hippocampal subfields (CA1-3) because there are two glutamatergic cell types in the DG rather than one. Thus, in the DG, the main cell types include glutamatergic granule cells (GCs) and MCs, whereas in CA1-3, the only glutamatergic cell type is the pyramidal cell. In contrast to GCs, MCs are different in morphology, intrinsic electrophysiological properties, afferent input and axonal projections, so their function is likely to be very different from GCs. Why are MCs necessary to the DG? In past studies, the answer has been unclear because MCs not only excite GCs directly but also inhibit them disynaptically, by exciting GABAergic neurons that project to GCs. Results of new studies are discussed that shed light on this issue. These studies take advantage of recently available transgenic mice with Cre recombinase expression mostly in MCs and techniques such as optogenetics and DREADDs (designer receptors exclusively activated by designer drugs). The recent studies also address in vivo behavioral functions of MCs. Some of the results support past hypotheses whereas others suggest new conceptualizations of how the MCs contribute to DG circuitry and function. While substantial progess has been made, additional research is still needed to clarify the characteristics and functions of these unique cells.

Effect of inhibitory spike-timing-dependent plasticity on fast sparsely synchronized rhythms in a small-world neuronal network

We consider the Watts-Strogatz small-world network (SWN) consisting of inhibitory fast spiking Izhikevich interneurons. This inhibitory neuronal population has adaptive dynamic synaptic strengths governed by the inhibitory spike-timing-dependent plasticity (iSTDP). In previous works without iSTDP, fast sparsely synchronized rhythms, associated with diverse cognitive functions, were found to appear in a range of large noise intensities for fixed strong synaptic inhibition strengths. Here, we investigate the effect of iSTDP on fast sparse synchronization (FSS) by varying the noise intensity D. We employ an asymmetric anti-Hebbian time window for the iSTDP update rule [which is in contrast to the Hebbian time window for the excitatory STDP (eSTDP)]. Depending on values of D, population-averaged values of saturated synaptic inhibition strengths are potentiated [long-term potentiation (LTP)] or depressed [long-term depression (LTD)] in comparison with the initial mean value, and dispersions from the mean values of LTP/LTD are much increased when compared with the initial dispersion, independently of D. In most cases of LTD where the effect of mean LTD is dominant in comparison with the effect of dispersion, good synchronization (with higher spiking measure) is found to get better via LTD, while bad synchronization (with lower spiking measure) is found to get worse via LTP. This kind of Matthew effect in inhibitory synaptic plasticity is in contrast to that in excitatory synaptic plasticity where good (bad) synchronization gets better (worse) via LTP (LTD). Emergences of LTD and LTP of synaptic inhibition strengths are intensively investigated via a microscopic method based on the distributions of time delays between the pre- and the post-synaptic spike times. Furthermore, we also investigate the effects of network architecture on FSS by changing the rewiring probability p of the SWN in the presence of iSTDP.

Morphological Diversity Strongly Constrains Synaptic Connectivity and Plasticity

Synaptic connectivity between neurons is naturally constrained by the anatomical overlap of neuronal arbors, the space on the axon available for synapses, and by physiological mechanisms that form synapses at a subset of potential synapse locations. What is not known is how these constraints impact emergent connectivity in a circuit with diverse morphologies. We investigated the role of morphological diversity within and across neuronal types on emergent connectivity in a model of neocortical microcircuitry. We found that the average overlap between the dendritic and axonal arbors of different types of neurons determines neuron-type specific patterns of distance-dependent connectivity, severely constraining the space of possible connectomes. However, higher order connectivity motifs depend on the diverse branching patterns of individual arbors of neurons belonging to the same type. Morphological diversity across neuronal types, therefore, imposes a specific structure on first order connectivity, and morphological diversity within neuronal types imposes a higher order structure of connectivity. We estimate that the morphological constraints resulting from diversity within and across neuron types together lead to a 10-fold reduction of the entropy of possible connectivity configurations, revealing an upper bound on the space explored by structural plasticity.

Pattern separation in the hippocampus: distinct circuits under different conditions

Pattern separation is a fundamental hippocampal process thought to be critical for distinguishing similar episodic memories, and has long been recognized as a natural function of the dentate gyrus (DG), supporting autoassociative learning in CA3. Understanding how neural circuits within the DG-CA3 network mediate this process has received much interest, yet the exact mechanisms behind remain elusive. Here, we argue for the case that sparse coding is necessary but not sufficient to ensure efficient separation and, alternatively, propose a possible interaction of distinct circuits which, nevertheless, act in synergy to produce a unitary function of pattern separation. The proposed circuits involve different functional granule-cell populations, a primary population mediates sparsification and provides recurrent excitation to the other populations which are related to additional pattern separation mechanisms with higher degrees of robustness against interference in CA3. A variety of top-down and bottom-up factors, such as motivation, emotion, and pattern similarity, control the selection of circuitry depending on circumstances. According to this framework, a computational model is implemented and tested against model variants in a series of numerical simulations and biological experiments. The results demonstrate that the model combines fast learning, robust pattern separation and high storage capacity. It also accounts for the controversy around the involvement of the DG during memory recall, explains other puzzling findings, and makes predictions that can inform future investigations.

Effect of spike-timing-dependent plasticity on stochastic burst synchronization in a scale-free neuronal network

We consider an excitatory population of subthreshold Izhikevich neurons which cannot fire spontaneously without noise. As the coupling strength passes a threshold, individual neurons exhibit noise-induced burstings. This neuronal population has adaptive dynamic synaptic strengths governed by the spike-timing-dependent plasticity (STDP). However, STDP was not considered in previous works on stochastic burst synchronization (SBS) between noise-induced burstings of sub-threshold neurons. Here, we study the effect of additive STDP on SBS by varying the noise intensity D in the Barabási-Albert scale-free network (SFN). One of our main findings is a Matthew effect in synaptic plasticity which occurs due to a positive feedback process. Good burst synchronization (with higher bursting measure) gets better via long-term potentiation (LTP) of synaptic strengths, while bad burst synchronization (with lower bursting measure) gets worse via long-term depression (LTD). Consequently, a step-like rapid transition to SBS occurs by changing D, in contrast to a relatively smooth transition in the absence of STDP. We also investigate the effects of network architecture on SBS by varying the symmetric attachment degree [Formula: see text] and the asymmetry parameter [Formula: see text] in the SFN, and Matthew effects are also found to occur by varying [Formula: see text] and [Formula: see text]. Furthermore, emergences of LTP and LTD of synaptic strengths are investigated in details via our own microscopic methods based on both the distributions of time delays between the burst onset times of the pre- and the post-synaptic neurons and the pair-correlations between the pre- and the post-synaptic instantaneous individual burst rates (IIBRs). Finally, a multiplicative STDP case (depending on states) with soft bounds is also investigated in comparison with the additive STDP case (independent of states) with hard bounds. Due to the soft bounds, a Matthew effect with some quantitative differences is also found to occur for the case of multiplicative STDP.

Excitatory Synaptic Input to Hilar Mossy Cells under Basal and Hyperexcitable Conditions

Hilar mossy cells (HMCs) in the hippocampus receive glutamatergic input from dentate granule cells (DGCs) via mossy fibers (MFs) and back-projections from CA3 pyramidal neuron collateral axons. Many fundamental features of these excitatory synapses have not been characterized in detail despite their potential relevance to hippocampal cognitive processing and epilepsy-induced adaptations in circuit excitability. In this study, we compared pre- and postsynaptic parameters between MF and CA3 inputs to HMCs in young and adult mice of either sex and determined the relative contributions of the respective excitatory inputs during in vitro and in vivo models of hippocampal hyperexcitability. The two types of excitatory synapses both exhibited a modest degree of short-term plasticity, with MF inputs to HMCs exhibiting lower paired-pulse (PP) and frequency facilitation than was described previously for MF–CA3 pyramidal cell synapses. MF–HMC synapses exhibited unitary excitatory synaptic currents (EPSCs) of larger amplitude, contained postsynaptic kainate receptors, and had a lower NMDA/AMPA receptor ratio compared to CA3–HMC synapses. Pharmacological induction of hippocampal hyperexcitability in vitro transformed the abundant but relatively weak CA3–HMC connections to very large amplitude spontaneous bursts of compound EPSCs (cEPSCs) in young mice (∼P20) and, to a lesser degree, in adult mice (∼P70). CA3–HMC cEPSCs were also observed in slices prepared from mice with spontaneous seizures several weeks after intrahippocampal kainate injection. Strong excitation of HMCs during synchronous CA3 activity represents an avenue of significant excitatory network generation back to DGCs and might be important in generating epileptic networks.

Brain Injury-Induced Synaptic Reorganization in Hilar Inhibitory Neurons Is Differentially Suppressed by Rapamycin

Following traumatic brain injury (TBI), treatment with rapamycin suppresses mammalian (mechanistic) target of rapamycin (mTOR) activity and specific components of hippocampal synaptic reorganization associated with altered cortical excitability and seizure susceptibility. Reemergence of seizures after cessation of rapamycin treatment suggests, however, an incomplete suppression of epileptogenesis. Hilar inhibitory interneurons regulate dentate granule cell (DGC) activity, and de novo synaptic input from both DGCs and CA3 pyramidal cells after TBI increases their excitability but effects of rapamycin treatment on the injury-induced plasticity of interneurons is only partially described. Using transgenic mice in which enhanced green fluorescent protein (eGFP) is expressed in the somatostatinergic subset of hilar inhibitory interneurons, we tested the effect of daily systemic rapamycin treatment (3 mg/kg) on the excitability of hilar inhibitory interneurons after controlled cortical impact (CCI)-induced focal brain injury. Rapamycin treatment reduced, but did not normalize, the injury-induced increase in excitability of surviving eGFP+ hilar interneurons. The injury-induced increase in response to selective glutamate photostimulation of DGCs was reduced to normal levels after mTOR inhibition, but the postinjury increase in synaptic excitation arising from CA3 pyramidal cell activity was unaffected by rapamycin treatment. The incomplete suppression of synaptic reorganization in inhibitory circuits after brain injury could contribute to hippocampal hyperexcitability and the eventual reemergence of the epileptogenic process upon cessation of mTOR inhibition. Further, the cell-selective effect of mTOR inhibition on synaptic reorganization after CCI suggests possible mechanisms by which rapamycin treatment modifies epileptogenesis in some models but not others.

Spatial Structure of Synchronized Inhibition in the Olfactory Bulb

Olfactory sensory input is detected by receptor neurons in the nose, which then send information to the olfactory bulb (OB), the first brain region for processing olfactory information. Within the OB, many local circuit interneurons, including axonless granule cells, function to facilitate fine odor discrimination. How interneurons interact with principal cells to affect bulbar processing is not known, but the mechanism is likely to be different from that in sensory cortical regions because the OB lacks an obvious topographical organization. Neighboring glomerular columns, representing inputs from different receptor neuron subtypes, typically have different odor tuning. Determining the spatial scale over which interneurons such as granule cells can affect principal cells is a critical step toward understanding how the OB operates. We addressed this question by assaying inhibitory synchrony using intracellular recordings from pairs of principal cells with different intersomatic spacing. We found, in acute rat OB slices from both sexes, that inhibitory synchrony is evident in the spontaneous synaptic input in mitral cells (MCs) separated up to 220 μm (300 μm with elevated K⁺). At all intersomatic spacing assayed, inhibitory synchrony was dependent on Na⁺ channels, suggesting that action potentials in granule cells function to coordinate GABA release at relatively distant dendrodendritic synapses formed throughout the dendritic arbor. Our results suggest that individual granule cells are able to influence relatively large groups of MCs and tufted cells belonging to clusters of at least 15 glomerular modules, providing a potential mechanism to integrate signals reflecting a wide variety of odorants.SIGNIFICANCE STATEMENT Inhibitory circuits in the olfactory bulb (OB) play a major role in odor processing, especially during fine odor discrimination. However, how inhibitory networks enhance olfactory function, and over what spatial scale they operate, is not known. Interneurons are potentially able to function on both a highly localized, synapse-specific level and on a larger, spatial scale that encompasses many different glomerular channels. Although recent indirect evidence has suggested a relatively localized functional role for most inhibition in the OB, in the present study, we used paired intracellular recordings to demonstrate directly that inhibitory local circuits operate over large spatial scales by using fast action potentials to link GABA release at many different synaptic contacts formed with principal cells.

LTP at Hilar Mossy Cell-Dentate Granule Cell Synapses Modulates Dentate Gyrus Output by Increasing Excitation/Inhibition Balance

Excitatory hilar mossy cells (MCs) in the dentate gyrus receive inputs from dentate granule cells (GCs) and project back to GCs locally, contralaterally, and along the longitudinal axis of the hippocampus, thereby establishing an associative positive-feedback loop and connecting functionally diverse hippocampal areas. MCs also synapse with GABAergic interneurons that mediate feed-forward inhibition onto GCs. Surprisingly, although these circuits have been implicated in both memory formation (e.g., pattern separation) and temporal lobe epilepsy, little is known about activity-dependent plasticity of their synaptic connections. Here, we report that MC-GC synapses undergo a presynaptic, NMDA-receptor-independent form of long-term potentiation (LTP) that requires postsynaptic brain-derived neurotrophic factor (BDNF)/TrkB and presynaptic cyclic AMP (cAMP)/PKA signaling. This LTP is input specific and selectively expressed at MC-GC synapses, but not at the disynaptic inhibitory loop. By increasing the excitation/inhibition balance, MC-GC LTP enhances GC output at the associative MC-GC recurrent circuit and may contribute to dentate-dependent forms of learning and epilepsy.

Mechanisms of Persistent Activity in Cortical Circuits: Possible Neural Substrates for Working Memory

A commonly observed neural correlate of working memory is firing that persists after the triggering stimulus disappears. Substantial effort has been devoted to understanding the many potential mechanisms that may underlie memory-associated persistent activity. These rely either on the intrinsic properties of individual neurons or on the connectivity within neural circuits to maintain the persistent activity. Nevertheless, it remains unclear which mechanisms are at play in the many brain areas involved in working memory. Herein, we first summarize the palette of different mechanisms that can generate persistent activity. We then discuss recent work that asks which mechanisms underlie persistent activity in different brain areas. Finally, we discuss future studies that might tackle this question further. Our goal is to bridge between the communities of researchers who study either single-neuron biophysical, or neural circuit, mechanisms that can generate the persistent activity that underlies working memory.

Emergence of ultrafast sparsely synchronized rhythms and their responses to external stimuli in an inhomogeneous small-world complex neuronal network

We consider an inhomogeneous small-world network (SWN) composed of inhibitory short-range (SR) and long-range (LR) interneurons, and investigate the effect of network architecture on emergence of synchronized brain rhythms by varying the fraction of LR interneurons p_long. The betweenness centralities of the LR and SR interneurons (characterizing the potentiality in controlling communication between other interneurons) are distinctly different. Hence, in view of the betweenness, SWNs we consider are inhomogeneous, unlike the "canonical" Watts-Strogatz SWN with nearly the same betweenness centralities. For small p_long, the load of communication traffic is much concentrated on a few LR interneurons. However, as p_long is increased, the number of LR connections (coming from LR interneurons) increases, and then the load of communication traffic is less concentrated on LR interneurons, which leads to better efficiency of global communication between interneurons. Sparsely synchronized rhythms are thus found to emerge when passing a small critical value p_long^(c)(≃0.16). The population frequency of the sparsely synchronized rhythm is ultrafast (higher than 100 Hz), while the mean firing rate of individual interneurons is much lower (∼30 Hz) due to stochastic and intermittent neural discharges. These dynamical behaviors in the inhomogeneous SWN are also compared with those in the homogeneous Watts-Strogatz SWN, in connection with their network topologies. Particularly, we note that the main difference between the two types of SWNs lies in the distribution of betweenness centralities. Unlike the case of the Watts-Strogatz SWN, dynamical responses to external stimuli vary depending on the type of stimulated interneurons in the inhomogeneous SWN. We consider two cases of external time-periodic stimuli applied to sub-populations of the LR and SR interneurons, respectively. Dynamical responses (such as synchronization suppression and enhancement) to these two cases of stimuli are studied and discussed in relation to the betweenness centralities of stimulated interneurons, representing the effectiveness for transfer of stimulation effect in the whole network.