Distinct classes of pyramidal cells exhibit mutually exclusive firing patterns in hippocampal area CA3b

Formation and retrieval of cell assemblies in a biologically realistic spiking neural network model of area CA3 in the mouse hippocampus

The hippocampal formation is critical for episodic memory, with area Cornu Ammonis 3 (CA3) a necessary substrate for auto-associative pattern completion. Recent theoretical and experimental evidence suggests that the formation and retrieval of cell assemblies enable these functions. Yet, how cell assemblies are formed and retrieved in a full-scale spiking neural network (SNN) of CA3 that incorporates the observed diversity of neurons and connections within this circuit is not well understood. Here, we demonstrate that a data-driven SNN model quantitatively reflecting the neuron type-specific population sizes, intrinsic electrophysiology, connectivity statistics, synaptic signaling, and long-term plasticity of the mouse CA3 is capable of robust auto-association and pattern completion via cell assemblies. Our results show that a broad range of assembly sizes could successfully and systematically retrieve patterns from heavily incomplete or corrupted cues after a limited number of presentations. Furthermore, performance was robust with respect to partial overlap of assemblies through shared cells, substantially enhancing memory capacity. These novel findings provide computational evidence that the specific biological properties of the CA3 circuit produce an effective neural substrate for associative learning in the mammalian brain.

Formation and Retrieval of Cell Assemblies in a Biologically Realistic Spiking Neural Network Model of Area CA3 in the Mouse Hippocampus

The hippocampal formation is critical for episodic memory, with area Cornu Ammonis 3 (CA3) a necessary substrate for auto-associative pattern completion. Recent theoretical and experimental evidence suggests that the formation and retrieval of cell assemblies enable these functions. Yet, how cell assemblies are formed and retrieved in a full-scale spiking neural network (SNN) of CA3 that incorporates the observed diversity of neurons and connections within this circuit is not well understood. Here, we demonstrate that a data-driven SNN model quantitatively reflecting the neuron type-specific population sizes, intrinsic electrophysiology, connectivity statistics, synaptic signaling, and long-term plasticity of the mouse CA3 is capable of robust auto-association and pattern completion via cell assemblies. Our results show that a broad range of assembly sizes could successfully and systematically retrieve patterns from heavily incomplete or corrupted cues after a limited number of presentations. Furthermore, performance was robust with respect to partial overlap of assemblies through shared cells, substantially enhancing memory capacity. These novel findings provide computational evidence that the specific biological properties of the CA3 circuit produce an effective neural substrate for associative learning in the mammalian brain.

Mechanisms of Sustained Increases in γ Power Post-Ketamine in a Computational Model of the Hippocampal CA3: Implications for Ketamine's Antidepressant Mechanism of Action

Subanaesthetic doses of ketamine increase γ oscillation power in neural activity measured using electroencephalography (EEG), and this effect lasts several hours after ketamine administration. The mechanisms underlying this effect are unknown. Using a computational model of the hippocampal cornu ammonis 3 (CA3) network, which is known to reproduce ketamine's acute effects on γ power, we simulated the plasticity of glutamatergic synapses in pyramidal cells to test which of the following hypotheses would best explain this sustained γ power: the direct inhibition hypothesis, which proposes that increased γ power post-ketamine administration may be caused by the potentiation of recurrent collateral synapses, and the disinhibition hypothesis, which proposes that potentiation affects synapses from both recurrent and external inputs. Our results suggest that the strengthening of external connections to pyramidal cells is able to account for the sustained γ power increase observed post-ketamine by increasing the overall activity of and synchrony between pyramidal cells. The strengthening of recurrent pyramidal weights, however, would cause an additional phase shifted voltage increase that ultimately reduces γ power due to partial cancellation. Our results therefore favor the disinhibition hypothesis for explaining sustained γ oscillations after ketamine administration.

A GPU-based computational framework that bridges neuron simulation and artificial intelligence

Biophysically detailed multi-compartment models are powerful tools to explore computational principles of the brain and also serve as a theoretical framework to generate algorithms for artificial intelligence (AI) systems. However, the expensive computational cost severely limits the applications in both the neuroscience and AI fields. The major bottleneck during simulating detailed compartment models is the ability of a simulator to solve large systems of linear equations. Here, we present a novel Dendritic Hierarchical Scheduling (DHS) method to markedly accelerate such a process. We theoretically prove that the DHS implementation is computationally optimal and accurate. This GPU-based method performs with 2-3 orders of magnitude higher speed than that of the classic serial Hines method in the conventional CPU platform. We build a DeepDendrite framework, which integrates the DHS method and the GPU computing engine of the NEURON simulator and demonstrate applications of DeepDendrite in neuroscience tasks. We investigate how spatial patterns of spine inputs affect neuronal excitability in a detailed human pyramidal neuron model with 25,000 spines. Furthermore, we provide a brief discussion on the potential of DeepDendrite for AI, specifically highlighting its ability to enable the efficient training of biophysically detailed models in typical image classification tasks.

Integrin β3 regulates apical dendritic morphology of pyramidal neurons throughout hippocampal CA3

In excitatory hippocampal pyramidal neurons, integrin β3 is critical for synaptic maturation and plasticity in vitro. Itgb3 is a potential autism susceptibility gene that regulates dendritic morphology in the cerebral cortex in a cell-specific manner. However, it is unknown what role Itgb3 could have in regulating hippocampal pyramidal dendritic morphology in vivo, a key feature that is aberrant in many forms of autism and intellectual disability. We found that Itgb3 mRNA is expressed in the stratum pyramidale of CA3. We examined the apical dendritic morphology of CA3 hippocampal pyramidal neurons in conditional Itgb3 knockouts and controls, utilizing the Thy1-GFP-M line. We fully reconstructed the apical dendrite of each neuron and determined each neuron's precise location along the dorsoventral, proximodistal, and radial axes of the stratum pyramidale. We found a very strong effect for Itgb3 expression on CA3 apical dendritic morphology: neurons from conditional Itgb3 knockouts had longer and thinner apical dendrites than controls, particularly in higher branch orders. We also assessed potential relationships between pairs of topographic or morphological variables, finding that most variable pairs were free from any linear relationships to each other. We also found that some neurons from controls, but not conditional Itgb3 knockouts, had a graded pattern of overall diameter along the dorsoventral and proximodistal axes of the stratum pyramidale of CA3. Taken together, Itgb3 is essential for constructing normal dendritic morphology in pyramidal neurons throughout CA3.

Robust Resting-State Dynamics in a Large-Scale Spiking Neural Network Model of Area CA3 in the Mouse Hippocampus

Hippocampal area CA3 performs the critical auto-associative function underlying pattern completion in episodic memory. Without external inputs, the electrical activity of this neural circuit reflects the spontaneous spiking interplay among glutamatergic pyramidal neurons and GABAergic interneurons. However, the network mechanisms underlying these resting-state firing patterns are poorly understood. Leveraging the Hippocampome.org knowledge base, we developed a data-driven, large-scale spiking neural network (SNN) model of mouse CA3 with 8 neuron types, 90,000 neurons, 51 neuron-type specific connections, and 250,000,000 synapses. We instantiated the SNN in the CARLsim4 multi-GPU simulation environment using the Izhikevich and Tsodyks-Markram formalisms for neuronal and synaptic dynamics, respectively. We analyzed the resultant population activity upon transient activation. The SNN settled into stable oscillations with a biologically plausible grand-average firing frequency, which was robust relative to a wide range of transient activation. The diverse firing patterns of individual neuron types were consistent with existing knowledge of cell type-specific activity in vivo. Altered network structures that lacked neuron- or connection-type specificity were neither stable nor robust, highlighting the importance of neuron type circuitry. Additionally, external inputs reflecting dentate mossy fibers shifted the observed rhythms to the gamma band. We freely released the CARLsim4-Hippocampome framework on GitHub to test hippocampal hypotheses. Our SNN may be useful to investigate the circuit mechanisms underlying the computational functions of CA3. Moreover, our approach can be scaled to the whole hippocampal formation, which may contribute to elucidating how the unique neuronal architecture of this system subserves its crucial cognitive roles.

Heuristic Tree-Partition-Based Parallel Method for Biophysically Detailed Neuron Simulation

Biophysically detailed neuron simulation is a powerful tool to explore the mechanisms behind biological experiments and bridge the gap between various scales in neuroscience research. However, the extremely high computational complexity of detailed neuron simulation restricts the modeling and exploration of detailed network models. The bottleneck is solving the system of linear equations. To accelerate detailed simulation, we propose a heuristic tree-partition-based parallel method (HTP) to parallelize the computation of the Hines algorithm, the kernel for solving linear equations, and leverage the strong parallel capability of the graphic processing unit (GPU) to achieve further speedup. We formulate the problem of how to get a fine parallel process as a tree-partition problem. Next, we present a heuristic partition algorithm to obtain an effective partition to efficiently parallelize the equation-solving process in detailed simulation. With further optimization on GPU, our HTP method achieves 2.2 to 8.5 folds speedup compared to the state-of-the-art GPU method and 36 to 660 folds speedup compared to the typical Hines algorithm.

A spiking computational model for striatal cholinergic interneurons

Cholinergic interneurons in the striatum, also known as tonically active interneurons or TANs, are thought to have a strong effect on corticostriatal plasticity and on striatal activity and outputs, which in turn play a critical role in modulating downstream basal ganglia activity and movement. Striatal TANs can exhibit a variety of firing patterns and responses to synaptic inputs; furthermore, they have been found to display various surges and pauses in activity associated with sensory cues and reward delivery in learning as well as with motor tic production. To help explain the factors that contribute to TAN activity patterns and to provide a resource for future studies, we present a novel conductance-based computational model of a striatal TAN. We show that this model produces the various characteristic firing patterns observed in recordings of TANs. With a single baseline tuning associated with tonic firing, the model also captures a wide range of TAN behaviors found in previous experiments involving a variety of manipulations. In addition to demonstrating these results, we explain how various ionic currents in the model contribute to them. Finally, we use this model to explore the contributions of the acetylcholine released by TANs to the production of surges and pauses in TAN activity in response to strong excitatory inputs. These results provide predictions for future experimental testing that may help with efforts to advance our understanding of the role of TANs in reinforcement learning and in motor disorders such as Tourette's syndrome.

A patient-derived mutation of epilepsy-linked LGI1 increases seizure susceptibility through regulating Kv1.1

BACKGROUND

Autosomal dominant lateral temporal epilepsy (ADLTE) is an inherited syndrome caused by mutations in the leucine-rich glioma inactivated 1 (LGI1) gene. It is known that functional LGI1 is secreted by excitatory neurons, GABAergic interneurons, and astrocytes, and regulates AMPA-type glutamate receptor-mediated synaptic transmission by binding ADAM22 and ADAM23. However, > 40 LGI1 mutations have been reported in familial ADLTE patients, more than half of which are secretion-defective. How these secretion-defective LGI1 mutations lead to epilepsy is unknown.

RESULTS

We identified a novel secretion-defective LGI1 mutation from a Chinese ADLTE family, LGI1-W183R. We specifically expressed mutant LGI1^W183R in excitatory neurons lacking natural LGI1, and found that this mutation downregulated K_v1.1 activity, led to neuronal hyperexcitability and irregular spiking, and increased epilepsy susceptibility in mice. Further analysis revealed that restoring K_v1.1 in excitatory neurons rescued the defect of spiking capacity, improved epilepsy susceptibility, and prolonged the life-span of mice.

CONCLUSIONS

These results describe a role of secretion-defective LGI1 in maintaining neuronal excitability and reveal a new mechanism in the pathology of LGI1 mutation-related epilepsy.

Exact mean-field models for spiking neural networks with adaptation

Networks of spiking neurons with adaption have been shown to be able to reproduce a wide range of neural activities, including the emergent population bursting and spike synchrony that underpin brain disorders and normal function. Exact mean-field models derived from spiking neural networks are extremely valuable, as such models can be used to determine how individual neurons and the network they reside within interact to produce macroscopic network behaviours. In the paper, we derive and analyze a set of exact mean-field equations for the neural network with spike frequency adaptation. Specifically, our model is a network of Izhikevich neurons, where each neuron is modeled by a two dimensional system consisting of a quadratic integrate and fire equation plus an equation which implements spike frequency adaptation. Previous work deriving a mean-field model for this type of network, relied on the assumption of sufficiently slow dynamics of the adaptation variable. However, this approximation did not succeed in establishing an exact correspondence between the macroscopic description and the realistic neural network, especially when the adaptation time constant was not large. The challenge lies in how to achieve a closed set of mean-field equations with the inclusion of the mean-field dynamics of the adaptation variable. We address this problem by using a Lorentzian ansatz combined with the moment closure approach to arrive at a mean-field system in the thermodynamic limit. The resulting macroscopic description is capable of qualitatively and quantitatively describing the collective dynamics of the neural network, including transition between states where the individual neurons exhibit asynchronous tonic firing and synchronous bursting. We extend the approach to a network of two populations of neurons and discuss the accuracy and efficacy of our mean-field approximations by examining all assumptions that are imposed during the derivation. Numerical bifurcation analysis of our mean-field models reveals bifurcations not previously observed in the models, including a novel mechanism for emergence of bursting in the network. We anticipate our results will provide a tractable and reliable tool to investigate the underlying mechanism of brain function and dysfunction from the perspective of computational neuroscience.

Impact of optogenetic pulse design on CA3 learning and replay: A neural model

Optogenetic manipulation of hippocampal circuitry is an important tool for investigating learning in vivo. Numerous approaches to pulse design have been employed to elicit desirable circuit and behavioral outcomes. Here, we systematically test the outcome of different single-pulse waveforms in a rate-based model of hippocampal memory function at the level of mnemonic replay extension and de novo synaptic weight formation in CA3 and CA1. Lower-power waveforms with long forward or forward and backward ramps yield more natural sequence replay dynamics and induce synaptic plasticity that allows for more natural memory replay timing, in contrast to square or backward ramps. These differences between waveform shape and amplitude are preserved with the addition of noise in membrane potential, light scattering, and protein expression, improving the potential validity of predictions for in vivo work. These results inform future optogenetic experimental design choices in the field of learning and memory.

Abnormal innate and learned behavior induced by neuron-microglia miscommunication is related to CA3 reconfiguration

Neuron-microglia communication through the Cx3cr1-Cx3cl1 axis is essential for the development and refinement of neural circuits, which determine their function into adulthood. In the present work we set out to extend the behavioral characterization of Cx3cr1^-/- mice evaluating innate behaviors and spatial navigation, both dependent on hippocampal function. Our results show that Cx3cr1-deficient mice, which show some changes in microglial and synaptic terminals morphology and density, exhibit alterations in activities of daily living and in the rapid encoding of novel spatial information that, nonetheless, improves with training. A neural substrate for these cognitive deficiencies was found in the form of synaptic dysfunction in the CA3 region of the hippocampus, with a marked impact on the mossy fiber (MF) pathway. A network analysis of the CA3 microcircuit reveals the effect of these synaptic alterations on the functional connectivity among CA3 neurons with diminished strength and topological reorganization in Cx3cr1-deficient mice. Neonatal population activity of the CA3 region in Cx3cr1-deficient mice shows a marked reorganization around the giant depolarizing potentials, the first form of network-driven activity of the hippocampus, suggesting that alterations found in adult subjects arise early on in postnatal development, a critical period of microglia-dependent neural circuit refinement. Our results show that interruption of the Cx3cr1-Cx3cl1/neuron-microglia axis leads to changes in CA3 configuration that affect innate and learned behaviors.

Cell type-specific mechanisms of information transfer in data-driven biophysical models of hippocampal CA3 principal neurons

The transformation of synaptic input into action potential output is a fundamental single-cell computation resulting from the complex interaction of distinct cellular morphology and the unique expression profile of ion channels that define the cellular phenotype. Experimental studies aimed at uncovering the mechanisms of the transfer function have led to important insights, yet are limited in scope by technical feasibility, making biophysical simulations an attractive complementary approach to push the boundaries in our understanding of cellular computation. Here we take a data-driven approach by utilizing high-resolution morphological reconstructions and patch-clamp electrophysiology data together with a multi-objective optimization algorithm to build two populations of biophysically detailed models of murine hippocampal CA3 pyramidal neurons based on the two principal cell types that comprise this region. We evaluated the performance of these models and find that our approach quantitatively matches the cell type-specific firing phenotypes and recapitulate the intrinsic population-level variability in the data. Moreover, we confirm that the conductance values found by the optimization algorithm are consistent with differentially expressed ion channel genes in single-cell transcriptomic data for the two cell types. We then use these models to investigate the cell type-specific biophysical properties involved in the generation of complex-spiking output driven by synaptic input through an information-theoretic treatment of their respective transfer functions. Our simulations identify a host of cell type-specific biophysical mechanisms that define the morpho-functional phenotype to shape the cellular transfer function and place these findings in the context of a role for bursting in CA3 recurrent network synchronization dynamics.

The hippocampus is comprised of numerous types of neurons, which constitute the cellular substrate for its rich repertoire of network dynamics. Among these are sharp waves, sequential activations of ensembles of neurons that have been shown to be crucially involved in learning and memory. In the CA3 area of the hippocampus, two types of excitatory cells, thorny and a-thorny neurons, are preferentially active during distinct phases of a sharp wave, suggesting a differential role for these cell types in phenomena such as memory consolidation. Using a strictly data-driven approach, we built biophysically realistic models of both thorny and a-thorny cells and used them to investigate the integrative differences between these two cell types. We found that both neuron classes have the capability of integrating incoming synaptic inputs in a supralinear fashion, although only a-thorny cells respond with bursts of action potentials to spatially and temporally clustered synaptic inputs. Additionally, by using a computational approach based on information theory, we show that, owing to this propensity for bursting, a-thorny cells can encode more information in their spiking output than their thorny counterpart. These results shed new light on the computational capabilities of two types of excitatory neurons and suggest that thorny and a-thorny cells may play distinct roles in the generation of hippocampal network synchronization.

Co-expressing fast channelrhodopsin with step-function opsin overcomes spike failure due to photocurrent desensitization in optogenetics: a theoretical study

Objective A fundamental challenge in optogenetics is to elicit long-term high-fidelity neuronal spiking with negligible heating. Fast channelrhodopsins (ChRs) require higher irradiances and cause spike failure due to photocurrent desensitization under sustained illumination, whereas, more light-sensitive step-function opsins (SFOs) exhibit prolonged depolarization with insufficient photocurrent and fast response for high-fidelity spiking. Approach We present a novel method to overcome this fundamental limitation by co-expressing fast ChRs with SFOs. A detailed theoretical analysis of ChETA co-expressed with different SFOs, namely ChR2(C128A), ChR2(C128S), SSFO and SOUL, expressing hippocampal neurons has been carried out by formulating their accurate theoretical models. Main results ChETA-SFO-expressing hippocampal neurons show a more stable photocurrent that overcomes spike failure. Spiking fidelity in these neurons can be sustained even at lower irradiances of subsequent pulses (77 % of initial pulse intensity in ChETA-ChR2(C128A)-expressing neurons) or by using red-shifted light pulses at appropriate intervals. High-fidelity spiking up to 60 Hz can be evoked in ChR2-C128S-ChETA-expressing neurons, which cannot be attained with only SFOs. Significance The present study provides important insights about photostimulation protocols for bi-stable switching of neurons. This new approach provides a means for sustained low-power, high-frequency, and high-fidelity optogenetic switching of neurons, necessary to study various neural functions and neurodegenerative disorders and enhance the utility of optogenetics for biomedical applications.

Functionally-distinct pyramidal cell subpopulations during gamma oscillations in mouse hippocampal area CA3

Gamma oscillations (γ-oscillations) in hippocampal area CA3 are essential for memory function. Particularly, CA3 is involved in the memory related process pattern completion, which is linked with the γ-oscillations in human hippocampus. Recent studies suggest that heterogeneity in the functional properties of pyramidal cells (PCs) in CA3 plays an important role in hippocampal function. By performing concomitant recordings of PC activity and network γ-oscillations in CA3 we found three functionally-different PC subpopulations. PCs with high spike-frequency adaptation (hA_PC) have the strongest action potential gamma phase-coupling, PCs with low adaptation (lA_PC) show lower phase-coupling and PCs displaying a burst-firing pattern (B_PC) remained quiescent. In addition, we discovered that hA_PC display the highest excitatory/inhibitory drive, followed by lA_PC, and lastly B_PC. In conclusion, our data advance the hypothesis that PCs in CA3 are organized into subpopulations with distinct functional roles for cognition-relevant network dynamics and provide new insights in the physiology of hippocampus.

Lamotrigine Attenuates Neuronal Excitability, Depresses GABA Synaptic Inhibition, and Modulates Theta Rhythms in Rat Hippocampus

Theta oscillations generated in hippocampal (HPC) and cortical neuronal networks are involved in various aspects of brain function, including sensorimotor integration, movement planning, memory formation and attention. Disruptions of theta rhythms are present in individuals with brain disorders, including epilepsy and Alzheimer’s disease. Theta rhythm generation involves a specific interplay between cellular (ion channel) and network (synaptic) mechanisms. HCN channels are theta modulators, and several medications are known to enhance their activity. We investigated how different doses of lamotrigine (LTG), an HCN channel modulator, and antiepileptic and neuroprotective agent, would affect HPC theta rhythms in acute HPC slices (in vitro) and anaesthetized rats (in vivo). Whole-cell patch clamp recordings revealed that LTG decreased GABA_A-fast transmission in CA3 cells, in vitro. In addition, LTG directly depressed CA3 and CA1 pyramidal neuron excitability. These effects were partially blocked by ZD 7288, a selective HCN blocker, and are consistent with decreased excitability associated with antiepileptic actions. Lamotrigine depressed HPC theta oscillations in vitro, also consistent with its neuronal depressant effects. In contrast, it exerted an opposite, enhancing effect, on theta recorded in vivo. The contradictory in vivo and in vitro results indicate that LTG increases ascending theta activating medial septum/entorhinal synaptic inputs that over-power the depressant effects seen in HPC neurons. These results provide new insights into LTG actions and indicate an opportunity to develop more precise therapeutics for the treatment of dementias, memory disorders and epilepsy.

Posttranscriptional modulation of KCNQ2 gene expression by the miR-106b microRNA family

MicroRNAs (miRNAs) have recently emerged as important regulators of ion channel expression. We show here that select miR-106b family members repress the expression of the KCNQ2 K⁺ channel protein by binding to the 3'-untranslated region of KCNQ2 messenger RNA. During the first few weeks after birth, the expression of miR-106b family members rapidly decreases, whereas KCNQ2 protein level inversely increases. Overexpression of miR-106b mimics resulted in a reduction in KCNQ2 protein levels. Conversely, KCNQ2 levels were up-regulated in neurons transfected with antisense miRNA inhibitors. By constructing more specific and stable forms of miR-106b controlling systems, we further confirmed that overexpression of precursor-miR-106b-5p led to a decrease in KCNQ current density and an increase in firing frequency of hippocampal neurons, while tough decoy miR-106b-5p dramatically increased current density and decreased neuronal excitability. These results unmask a regulatory mechanism of KCNQ2 channel expression in early postnatal development and hint at a role for miR-106b up-regulation in the pathophysiology of epilepsy.

Acetylcholine Boosts Dendritic NMDA Spikes in a CA3 Pyramidal Neuron Model

Acetylcholine has been proposed to facilitate the formation of memory ensembles within the hippocampal CA3 network, by enhancing plasticity at CA3-CA3 recurrent synapses. Regenerative NMDA receptor (NMDAR) activation in CA3 neuron dendrites (NMDA spikes) increase synaptic Ca²⁺ influx and can trigger this synaptic plasticity. Acetylcholine inhibits potassium channels which enhances dendritic excitability and therefore could facilitate NMDA spike generation. Here, we investigate NMDAR-mediated nonlinear synaptic integration in stratum radiatum (SR) and stratum lacunosum moleculare (SLM) dendrites in a reconstructed CA3 neuron computational model and study the effect of cholinergic inhibition of potassium conductances on this nonlinearity. We found that distal SLM dendrites, with a higher input resistance, had a lower threshold for NMDA spike generation compared to SR dendrites. Simulating acetylcholine by blocking potassium channels (M-type, A-type, Ca²⁺-activated, and inwardly-rectifying) increased dendritic excitability and reduced the number of synapses required to generate NMDA spikes, particularly in the SR dendrites. The magnitude of this effect was heterogeneous across different dendritic branches within the same neuron. These results predict that acetylcholine facilitates dendritic integration and NMDA spike generation in selected CA3 dendrites which could strengthen connections between specific CA3 neurons to form memory ensembles.

Separable actions of acetylcholine and noradrenaline on neuronal ensemble formation in hippocampal CA3 circuits

In the hippocampus, episodic memories are thought to be encoded by the formation of ensembles of synaptically coupled CA3 pyramidal cells driven by sparse but powerful mossy fiber inputs from dentate gyrus granule cells. The neuromodulators acetylcholine and noradrenaline are separately proposed as saliency signals that dictate memory encoding but it is not known if they represent distinct signals with separate mechanisms. Here, we show experimentally that acetylcholine, and to a lesser extent noradrenaline, suppress feed-forward inhibition and enhance Excitatory-Inhibitory ratio in the mossy fiber pathway but CA3 recurrent network properties are only altered by acetylcholine. We explore the implications of these findings on CA3 ensemble formation using a hierarchy of models. In reconstructions of CA3 pyramidal cells, mossy fiber pathway disinhibition facilitates postsynaptic dendritic depolarization known to be required for synaptic plasticity at CA3-CA3 recurrent synapses. We further show in a spiking neural network model of CA3 how acetylcholine-specific network alterations can drive rapid overlapping ensemble formation. Thus, through these distinct sets of mechanisms, acetylcholine and noradrenaline facilitate the formation of neuronal ensembles in CA3 that encode salient episodic memories in the hippocampus but acetylcholine selectively enhances the density of memory storage.

Bri2 BRICHOS chaperone rescues impaired fast-spiking interneuron behavior and neuronal network dynamics in an AD mouse model in vitro

Synchronized and properly balanced electrical activity of neurons is the basis for the brain's ability to process information, to learn, and to remember. In Alzheimer's disease (AD), which causes cognitive decline in patients, this synchronization and balance is disturbed by the accumulation of neuropathological biomarkers such as amyloid-beta peptide (Aβ42). Failure of Aβ42 clearance mechanisms as well as desynchronization of crucial neuronal classes such as fast-spiking interneurons (FSN) are root causes for the disruption of the cognition-relevant gamma brain rhythm (30-80 Hz) and consequent cognitive impairment observed in AD. Here we show that recombinant BRICHOS molecular chaperone domains from ProSP-C or Bri2, which interfere with Aβ42 aggregation, can rescue the gamma rhythm. We demonstrate that Aβ42 progressively decreases gamma oscillation power and rhythmicity, disrupts the inhibition/excitation balance in pyramidal cells, and desynchronizes FSN firing during gamma oscillations in the hippocampal CA3 network of mice. Application of the more efficacious Bri2 BRICHOS chaperone rescued the cellular and neuronal network performance from all ongoing Aβ42-induced functional impairments. Collectively, our findings offer critical missing data to explain the importance of FSN for normal network function and underscore the therapeutic potential of Bri2 BRICHOS to rescue the disruption of cognition-relevant brain rhythms in AD.

In Vivo Calcium Imaging of CA3 Pyramidal Neuron Populations in Adult Mouse Hippocampus

Neuronal population activity in the hippocampal CA3 subfield is implicated in cognitive brain functions such as memory processing and spatial navigation. However, because of its deep location in the brain, the CA3 area has been difficult to target with modern calcium imaging approaches. Here, we achieved chronic two-photon calcium imaging of CA3 pyramidal neurons with the red fluorescent calcium indicator R-CaMP1.07 in anesthetized and awake mice. We characterize CA3 neuronal activity at both the single-cell and population level and assess its stability across multiple imaging days. During both anesthesia and wakefulness, nearly all CA3 pyramidal neurons displayed calcium transients. Most of the calcium transients were consistent with a high incidence of bursts of action potentials (APs), based on calibration measurements using simultaneous juxtacellular recordings and calcium imaging. In awake mice, we found state-dependent differences with striking large and prolonged calcium transients during locomotion. We estimate that trains of >30 APs over 3 s underlie these salient events. Their abundance in particular subsets of neurons was relatively stable across days. At the population level, we found that co-activity within the CA3 network was above chance level and that co-active neuron pairs maintained their correlated activity over days. Our results corroborate the notion of state-dependent spatiotemporal activity patterns in the recurrent network of CA3 and demonstrate that at least some features of population activity, namely co-activity of cell pairs and likelihood to engage in prolonged high activity, are maintained over days.

Theoretical analysis of optogenetic spiking with ChRmine, bReaChES and CsChrimson-expressing neurons for retinal prostheses

Objective.Optogenetics has emerged as a promising technique for neural prosthetics, especially retinal prostheses, with unprecedented spatiotemporal resolution. Newly discovered opsins with high light sensitivity and fast temporal kinetics can provide sufficient temporal resolution at safe light powers and overcome the limitations of presently used opsins. It is also important to formulate accurate mathematical models for optogenetic retinal prostheses, which can facilitate optimization of photostimulation factors to improve the performance.Approach.A detailed theoretical analysis of optogenetic excitation of model retinal ganglion neurons (RGNs) and hippocampal neurons expressed with already tested opsins for retinal prostheses, namely, ChR2, ReaChR and ChrimsonR, and also with recently discovered potent opsins CsChrimson, bReaChES and ChRmine, was carried out.Main results.Under continuous illumination, ChRmine-expressing RGNs begin to respond at very low irradiances ∼10^-4mW mm^-2, and evoke firing upto ∼280 Hz, highest among other opsin-expressing RGNs, at 10^-2mW mm^-2. Under pulsed illumination at randomized photon fluxes, ChRmine-expressing RGNs respond to changes in pulse to pulse irradiances upto four logs, although very bright pulses >10¹⁴photons mm^-2s^-1block firing in these neurons. The minimum irradiance threshold for ChRmine-expressing RGNs is lower by two orders of magnitude, whereas, the first spike latency in ChRmine-expressing RGNs is shorter by an order of magnitude, alongwith stable latency of subsequest spikes compared to others. Further, a good set of photostimulation parameters were determined to achieve high-frequency control with single spike resolution at minimal power. Although ChrimsonR enables spiking upto 100 Hz in RGNs, it requires very high irradiances. ChRmine provides control at light powers that are two orders of magnitude smaller than that required with experimentally studied opsins, while maintaining single spike temporal resolution upto 40 Hz.Significance.The present study highlights the importance of ChRmine as a potential opsin for optogenetic retinal prostheses.

An update to Hippocampome.org by integrating single-cell phenotypes with circuit function in vivo

Understanding brain operation demands linking basic behavioral traits to cell-type specific dynamics of different brain-wide subcircuits. This requires a system to classify the basic operational modes of neurons and circuits. Single-cell phenotyping of firing behavior during ongoing oscillations in vivo has provided a large body of evidence on entorhinal-hippocampal function, but data are dispersed and diverse. Here, we mined literature to search for information regarding the phase-timing dynamics of over 100 hippocampal/entorhinal neuron types defined in Hippocampome.org. We identified missing and unresolved pieces of knowledge (e.g., the preferred theta phase for a specific neuron type) and complemented the dataset with our own new data. By confronting the effect of brain state and recording methods, we highlight the equivalences and differences across conditions and offer a number of novel observations. We show how a heuristic approach based on oscillatory features of morphologically identified neurons can aid in classifying extracellular recordings of single cells and discuss future opportunities and challenges towards integrating single-cell phenotypes with circuit function.

Topographic Organization of Correlation Along the Longitudinal and Transverse Axes in Rat Hippocampal CA3 Due to Excitatory Afferents

The topographic organization of afferents to the hippocampal CA3 subfield are well-studied, but their role in influencing the spatiotemporal dynamics of population activity is not understood. Using a large-scale, computational neuronal network model of the entorhinal-dentate-CA3 system, the effects of the perforant path, mossy fibers, and associational system on the propagation and transformation of network spiking patterns were investigated. A correlation map was constructed to characterize the spatial structure and temporal evolution of pairwise correlations which underlie the emergent patterns found in the population activity. The topographic organization of the associational system gave rise to changes in the spatial correlation structure along the longitudinal and transverse axes of the CA3. The resulting gradients may provide a basis for the known functional organization observed in hippocampus.

Presynaptic NMDARs cooperate with local spikes toward GABA release from the reciprocal olfactory bulb granule cell spine

In the rodent olfactory bulb the smooth dendrites of the principal glutamatergic mitral cells (MCs) form reciprocal dendrodendritic synapses with large spines on GABAergic granule cells (GC), where unitary release of glutamate can trigger postsynaptic local activation of voltage-gated Na+-channels (Navs), that is a spine spike. Can such single MC input evoke reciprocal release? We find that unitary-like activation via two-photon uncaging of glutamate causes GC spines to release GABA both synchronously and asynchronously onto MC dendrites. This release indeed requires activation of Navs and high-voltage-activated Ca2+-channels (HVACCs), but also of NMDA receptors (NMDAR). Simulations show temporally overlapping HVACC- and NMDAR-mediated Ca2+-currents during the spine spike, and ultrastructural data prove NMDAR presence within the GABAergic presynapse. This cooperative action of presynaptic NMDARs allows to implement synapse-specific, activity-dependent lateral inhibition, and thus could provide an efficient solution to combinatorial percept synthesis in a sensory system with many receptor channels.

Topographic heterogeneity of intrinsic excitability in mouse hippocampal CA3 pyramidal neurons

Area CA3 in the hippocampus is traditionally thought to act as a homogeneous neural circuit that is vital for spatial navigation and episodic memories. However, recent studies have revealed that CA3 pyramidal neurons in dorsal hippocampus display marked anatomic and functional heterogeneity along the proximodistal (transverse) axis. The hippocampus is also known to be functionally segregated along the dorsoventral (longitudinal) axis, with dorsal hippocampus strongly involved in spatial navigation and ventral hippocampus associated with emotion and anxiety. Surprisingly, however, relatively little is known about CA3 functional heterogeneity along the dorsoventral axis. Here, we carried out mouse-brain-slice patch-clamp recordings and morphological analyses to examine the heterogeneity of CA3 cellular properties along both proximodistal and dorsoventral axes. We find that CA3 pyramidal neurons exhibit considerable heterogeneity of somatodendritic morphology and intrinsic membrane properties, with ventral CA3 (vCA3) displaying more elaborate somatodendritic morphology, lower intrinsic excitability, smaller input resistance, greater cell capacitance, and more prominent hyperpolarization-activated current than dorsal CA3 (dCA3). Furthermore, although both dCA3 and vCA3 exhibit proximal-to-distal gradients in intrinsic properties and neuronal morphology, these proximal-to-distal gradients in vCA3 are more moderate than those in dCA3. Taken together, our results extend previous findings on the proximodistal heterogeneity of dCA3 function and uncover a complex, yet orderly, pattern of topographic organization of CA3 neuronal features that extends to multiple anatomic dimensions and may contribute to its in vivo functional diversity.NEW & NOTEWORTHY Area CA3 is a major hippocampal region that is classically thought to act as a homogeneous neural network vital for spatial navigation and episodic memories. Here, we report that CA3 pyramidal neurons exhibit marked heterogeneity of somatodendritic morphology and cellular electrical properties along both proximodistal and dorsoventral axes. These new results uncover a complex, yet orderly, pattern of topographic organization of CA3 neuronal features that may contribute to its in vivo functional diversity.

Comparison of low-power, high-frequency and temporally precise optogenetic inhibition of spiking in NpHR, eNpHR3.0 and Jaws-expressing neurons

A detailed theoretical analysis of low-power, high-frequency and temporally precise optogenetic inhibition of neuronal spiking, with red-shifted opsins namely, NpHR, eNpHR3.0 and Jaws, has been presented. An accurate model for inhibition of spiking in these opsins expressed hippocampal neurons that includes the important rebound activity of chloride ions across the membrane has been formulated. The effect of various parameters including irradiance, pulse width, frequency, opsin-expression density and chloride concentration has been studied in detail. Theoretical simulations are in very good agreement with reported experimental results. The chloride concentration gradient directly affects the photocurrent and inhibition capacity in all three variants. eNpHR3.0 shows smallest inhibitory post-synaptic potential plateau at higher frequencies. The time delay between light stimulus and target spike is crucial to minimize irradiance and expression density thresholds for suppressing individual spike. Good practical values of photostimulation parameters have been obtained empirically for peak photocurrent, time delay and 100% spiking inhibition, at continuous and pulsed illumination. Under continuous illumination, complete inhibition of neural activity in Jaws-expressing neurons takes place at minimum irradiance of 0.2 mW mm^-2 and expression density of 0.2 mS cm^-2, whereas for pulsed stimulation, it is at minimum irradiance of 0.6 mW mm^-2 and 5 ms pulse width, at 10 Hz. It is shown that Jaws and eNpHR3.0 are able to invoke single spike precise inhibition up to 160 and 200 Hz, respectively. The study is useful in designing new experiments, understanding temporal spike coding and bidirectional control, and curing neurological disorders.

Coincidence Detection within the Excitable Rat Olfactory Bulb Granule Cell Spines

In the mammalian olfactory bulb, the inhibitory axonless granule cells (GCs) feature reciprocal synapses that interconnect them with the principal neurons of the bulb, mitral, and tufted cells. These synapses are located within large excitable spines that can generate local action potentials (APs) upon synaptic input ("spine spike"). Moreover, GCs can fire global APs that propagate throughout the dendrite. Strikingly, local postsynaptic Ca²⁺ entry summates mostly linearly with Ca²⁺ entry due to coincident global APs generated by glomerular stimulation, although some underlying conductances should be inactivated. We investigated this phenomenon by constructing a compartmental GC model to simulate the pairing of local and global signals as a function of their temporal separation Δt. These simulations yield strongly sublinear summation of spine Ca²⁺ entry for the case of perfect coincidence Δt = 0 ms. Summation efficiency (SE) sharply rises for both positive and negative Δt. The SE reduction for coincident signals depends on the presence of voltage-gated Na⁺ channels in the spine head, while NMDARs are not essential. We experimentally validated the simulated SE in slices of juvenile rat brain (both sexes) by pairing two-photon uncaging of glutamate at spines and APs evoked by somatic current injection at various intervals Δt while imaging spine Ca²⁺ signals. Finally, the latencies of synaptically evoked global APs and EPSPs were found to correspond to Δt ≈ 10 ms, explaining the observed approximately linear summation of synaptic local and global signals. Our results provide additional evidence for the existence of the GC spine spike.SIGNIFICANCE STATEMENT Here we investigate the interaction of local synaptic inputs and global activation of a neuron by a backpropagating action potential within a dendritic spine with respect to local Ca²⁺ signaling. Our system of interest, the reciprocal spine of the olfactory bulb granule cell, is known to feature a special processing mode, namely, a synaptically triggered action potential that is restricted to the spine head. Therefore, coincidence detection of local and global signals follows different rules than in more conventional synapses. We unravel these rules using both simulations and experiments and find that signals coincident within ≈±7 ms around 0 ms result in sublinear summation of Ca²⁺ entry because of synaptic activation of voltage-gated Na⁺ channels within the spine.

Quantitative firing pattern phenotyping of hippocampal neuron types

Systematically organizing the anatomical, molecular, and physiological properties of cortical neurons is important for understanding their computational functions. Hippocampome.org defines 122 neuron types in the rodent hippocampal formation based on their somatic, axonal, and dendritic locations, putative excitatory/inhibitory outputs, molecular marker expression, and biophysical properties. We augmented the electrophysiological data of this knowledge base by collecting, quantifying, and analyzing the firing responses to depolarizing current injections for every hippocampal neuron type from published experiments. We designed and implemented objective protocols to classify firing patterns based on 5 transients (delay, adapting spiking, rapidly adapting spiking, transient stuttering, and transient slow-wave bursting) and 4 steady states (non-adapting spiking, persistent stuttering, persistent slow-wave bursting, and silence). This automated approach revealed 9 unique (plus one spurious) families of firing pattern phenotypes while distinguishing potential new neuronal subtypes. Novel statistical associations emerged between firing responses and other electrophysiological properties, morphological features, and molecular marker expression. The firing pattern parameters, experimental conditions, spike times, references to the original empirical evidences, and analysis scripts are released open-source through Hippocampome.org for all neuron types, greatly enhancing the existing search and browse capabilities. This information, collated online in human- and machine-accessible form, will help design and interpret both experiments and model simulations.

Conditioning by subthreshold synaptic input changes the intrinsic firing pattern of CA3 hippocampal neurons

Unlike synaptic strength, intrinsic excitability is assumed to be a stable property of neurons. For example, learning of somatic conductances is generally not incorporated into computational models, and the discharge pattern of neurons in response to test stimuli is frequently used as a basis for phenotypic classification. However, it is increasingly evident that signal processing properties of neurons are more generally plastic on the timescale of minutes. Here we demonstrate that the intrinsic firing patterns of CA3 neurons of the rat hippocampus in vitro undergo rapid long-term plasticity in response to a few minutes of only subthreshold synaptic conditioning. This plasticity on the spike timing could also be induced by intrasomatic injection of subthreshold depolarizing pulses and was blocked by kinase inhibitors, indicating that discharge dynamics are modulated locally. Cluster analysis of firing patterns before and after conditioning revealed systematic transitions toward adapting and intrinsic burst behaviors, irrespective of the patterns initially exhibited by the cells. We used a conductance-based model to decide appropriate pharmacological blockade and found that the observed transitions are likely due to recruitment of low-voltage calcium and Kv7 potassium conductances. We conclude that CA3 neurons adapt their conductance profile to the subthreshold activity of their input, so that their intrinsic firing pattern is not a static signature, but rather a reflection of their history of subthreshold activity. In this way, recurrent output from CA3 neurons may collectively shape the temporal dynamics of their embedding circuits.NEW & NOTEWORTHY Although firing patterns are widely conserved across the animal phyla, it is still a mystery why nerve cells present such diversity of discharge dynamics upon somatic step currents. Adding a new timing dimension to the intrinsic plasticity literature, here we show that CA3 neurons rapidly adapt through the space of known firing patterns in response to the subthreshold signals that they receive from their embedding circuit, potentially adjusting their network processing to the temporal statistics of their circuit.

Capsaicin-Induced Impairment of Functional Network Dynamics in Mouse Hippocampus via a TrpV1 Receptor-Independent Pathway: Putative Involvement of Na+/K+-ATPase

The vanilloid compound capsaicin (Cp) is best known to bind to and activate the transient receptor potential vanilloid receptor-1 (TrpV1). A growing number of studies use capsaicin as a tool to study the role of TrpV1 in the central nervous system (CNS). Although most of capsaicin’s CNS effects have been reported to be mediated by TrpV1 activation, evidence exists that capsaicin can also trigger functional changes in hippocampal activity independently of TrpV1. Recently, we have reported that capsaicin induces impairment in hippocampal gamma oscillations via a TrpV1-independent pathway. Here, we dissect the underlying mechanisms of capsaicin-induced alterations to functional network dynamics. We found that capsaicin induces a reduction in action potential (AP) firing rate and a subsequent loss of synchronicity in pyramidal cell (PC) spiking activity in hippocampus. Moreover, capsaicin induces alterations in PC spike-timing since increased first-spike latency was observed after capsaicin treatment. First-spike latency can be regulated by the voltage-dependent potassium current D (I_D) or Na⁺/K⁺-ATPase. Selective inhibition of I_D via low 4-AP concentration and Na⁺/K⁺-ATPase using its blocker ouabain, we found that capsaicin effects on AP spike timing were completely inhibited by ouabain but not with 4-AP. In conclusion, our study shows that capsaicin in a TrpV1-independent manner and possibly involving Na⁺/K⁺-ATPase activity can impair cognition-relevant functional network dynamics such as gamma oscillations and provides important data regarding the use of capsaicin as a tool to study TrpV1 function in the CNS.

Diverse synaptic and dendritic mechanisms of complex spike burst generation in hippocampal CA3 pyramidal cells

Complex spike bursts (CSBs) represent a characteristic firing pattern of hippocampal pyramidal cells (PCs). In CA1PCs, CSBs are driven by regenerative dendritic plateau potentials, produced by correlated entorhinal cortical and CA3 inputs that simultaneously depolarize distal and proximal dendritic domains. However, in CA3PCs neither the generation mechanisms nor the computational role of CSBs are well elucidated. We show that CSBs are induced by dendritic Ca²⁺ spikes in CA3PCs. Surprisingly, the ability of CA3PCs to produce CSBs is heterogeneous, with non-uniform synaptic input-output transformation rules triggering CSBs. The heterogeneity is partly related to the topographic position of CA3PCs; we identify two ion channel types, HCN and Kv2 channels, whose proximodistal activity gradients contribute to subregion-specific modulation of CSB propensity. Our results suggest that heterogeneous dendritic integrative properties, along with previously reported synaptic connectivity gradients, define functional subpopulations of CA3PCs that may support CA3 network computations underlying associative memory processes.

Sharp-wave ripple features in macaques depend on behavioral state and cell-type specific firing

Sharp-wave ripples (SWRs) are spontaneous, synchronized neural population events in the hippocampus widely thought to play a role in memory consolidation and retrieval. They occur predominantly in sleep and quiet immobility, and in primates, they also appear during active visual exploration. Typical measures of SWRs in behaving rats include changes in the rate of occurrence, or in the incidence of specific neural ensemble activity contained within the categorical SWR event. Much less is known about the relevance of spatiotemporal SWR features, though they may index underlying activity of specific cell types including ensemble-specific internally generated sequences. Furthermore, changes in SWR features during active exploratory states are unknown. In this study, we recorded hippocampal local-field potentials and single-units during periods of quiescence and as macaques performed a memory-guided visual search task. We observed that (a) ripples during quiescence have greater amplitudes and larger postripple waves (PRW) compared to those in task epochs, and (b) during "remembered" trials, ripples have larger amplitudes than during "forgotten" trials, with no change in duration or PRWs. We further found that spiking activity influences SWR features as a function of cell type and ripple timing. As expected, larger ripple amplitudes were associated with putative pyramidal or putative basket interneuron (IN) activity, even when the spikes in question exceed the duration of the ripple. In contrast, the PRW was attenuated with activity from low firing rate cells and enhanced with activity from high firing rate cells, with putative IN spikes during ripples leading to the most prominent PRW peaks. The selective changes in SWR features as a function of time window, cell type, and cognitive/vigilance states suggest that this mesoscopic field event can offer additional information about the local network and animal's state than would be appreciated from SWR event rates alone.

The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow

Every neuron is part of a network, exerting its function by transforming multiple spatiotemporal synaptic input patterns into a single spiking output. This function is specified by the particular shape and passive electrical properties of the neuronal membrane, and the composition and spatial distribution of ion channels across its processes. For a variety of physiological or pathological reasons, the intrinsic input/output function may change during a neuron's lifetime. This process results in high variability in the peak specific conductance of ion channels in individual neurons. The mechanisms responsible for this variability are not well understood, although there are clear indications from experiments and modeling that degeneracy and correlation among multiple channels may be involved. Here, we studied this issue in biophysical models of hippocampal CA1 pyramidal neurons and interneurons. Using a unified data-driven simulation workflow and starting from a set of experimental recordings and morphological reconstructions obtained from rats, we built and analyzed several ensembles of morphologically and biophysically accurate single cell models with intrinsic electrophysiological properties consistent with experimental findings. The results suggest that the set of conductances expressed in any given hippocampal neuron may be considered as belonging to two groups: one subset is responsible for the major characteristics of the firing behavior in each population and the other is responsible for a robust degeneracy. Analysis of the model neurons suggests several experimentally testable predictions related to the combination and relative proportion of the different conductances that should be expressed on the membrane of different types of neurons for them to fulfill their role in the hippocampus circuitry.

A novel pyramidal cell type promotes sharp-wave synchronization in the hippocampus

To support cognitive function, the CA3 region of the hippocampus performs computations involving attractor dynamics. Understanding how cellular and ensemble activities of CA3 neurons enable computation is critical for elucidating the neural correlates of cognition. Here we show that CA3 comprises not only classically described pyramid cells with thorny excrescences, but also includes previously unidentified 'athorny' pyramid cells that lack mossy-fiber input. Moreover, the two neuron types have distinct morphological and physiological phenotypes and are differentially modulated by acetylcholine. To understand the contribution of these athorny pyramid neurons to circuit function, we measured cell-type-specific firing patterns during sharp-wave synchronization events in vivo and recapitulated these dynamics with an attractor network model comprising two principal cell types. Our data and simulations reveal a key role for athorny cell bursting in the initiation of sharp waves: transient network attractor states that signify the execution of pattern completion computations vital to cognitive function.

Altered Chloride Homeostasis Decreases the Action Potential Threshold and Increases Hyperexcitability in Hippocampal Neurons

Chloride ions play an important role in controlling excitability of principal neurons in the central nervous system. When neurotransmitter GABA is released from inhibitory interneurons, activated GABA type A (GABA_A) receptors on principal neurons become permeable to chloride. Typically, chloride flows through activated GABA_A receptors into the neurons causing hyperpolarization or shunting inhibition, and in turn inhibits action potential (AP) generation. However, in situations when intracellular chloride concentration is increased, chloride ions can flow in opposite direction, depolarize neurons, and promote AP generation. It is generally recognized that altered chloride homeostasis per se has no effect on the AP threshold. Here, we demonstrate that chloride overload of mouse principal CA3 pyramidal neurons not only makes these cells more excitable through GABA_A receptor activation but also lowers the AP threshold, further aggravating excitability. This phenomenon has not been described in principal neurons and adds to our understanding of mechanisms regulating neuronal and network excitability, particularly in developing brain and during pathological situations with altered chloride homeostasis. This finding further broadens the spectrum of neuronal plasticity regulated by ionic compositions across the cellular membrane.

T2N as a new tool for robust electrophysiological modeling demonstrated for mature and adult-born dentate granule cells

Compartmental models are the theoretical tool of choice for understanding single neuron computations. However, many models are incomplete, built ad hoc and require tuning for each novel condition rendering them of limited usability. Here, we present T2N, a powerful interface to control NEURON with Matlab and TREES toolbox, which supports generating models stable over a broad range of reconstructed and synthetic morphologies. We illustrate this for a novel, highly detailed active model of dentate granule cells (GCs) replicating a wide palette of experiments from various labs. By implementing known differences in ion channel composition and morphology, our model reproduces data from mouse or rat, mature or adult-born GCs as well as pharmacological interventions and epileptic conditions. This work sets a new benchmark for detailed compartmental modeling. T2N is suitable for creating robust models useful for large-scale networks that could lead to novel predictions. We discuss possible T2N application in degeneracy studies.

Distance-dependent inhibition facilitates focality of gamma oscillations in the dentate gyrus

Gamma oscillations (30-150 Hz) in neuronal networks are associated with the processing and recall of information. We measured local field potentials in the dentate gyrus of freely moving mice and found that gamma activity occurs in bursts, which are highly heterogeneous in their spatial extensions, ranging from focal to global coherent events. Synaptic communication among perisomatic-inhibitory interneurons (PIIs) is thought to play an important role in the generation of hippocampal gamma patterns. However, how neuronal circuits can generate synchronous oscillations at different spatial scales is unknown. We analyzed paired recordings in dentate gyrus slices and show that synaptic signaling at interneuron-interneuron synapses is distance dependent. Synaptic strength declines whereas the duration of inhibitory signals increases with axonal distance among interconnected PIIs. Using neuronal network modeling, we show that distance-dependent inhibition generates multiple highly synchronous focal gamma bursts allowing the network to process complex inputs in parallel in flexibly organized neuronal centers.Perisomatic-inhibitory interneurons (PIIs) contribute to the generation of gamma oscillations in the hippocampus. Here the authors demonstrate distance-dependent inhibition between PIIs in freely moving mice, and use computational analysis to show that distance-dependent inhibition supports the emergence of focal gamma bursts.

Plasticity of intrinsic firing response gain in principal hippocampal neurons following pilocarpine-induced status epilepticus

OBJECTIVE

In experimental models of temporal lobe epilepsy (TLE), brain neurons manifest multiple changes in intrinsic excitability that contribute to neuronal network hyperexcitability. We have investigated whether the intrinsic firing response gain, quantified by the slope of the function relating the number of evoked spikes (Ns) to input excitatory current intensity (I), is modified in principal rat hippocampal neurons in the pilocarpine-status epilepticus (SE) model of TLE.

METHODS

Intracellular recordings were made in CA3 and CA1 pyramidal cells (PCs) and dentate granule cells (GCs) in acute hippocampal slices obtained 7-36days after pilocarpine-SE. Firing response gains were determined empirically from Ns/I relationships and compared to other measured neuronal properties.

RESULTS

The firing response gain in all three types of principal neurons, particularly in CA3 PCs, was markedly multiplied following pilocarpine-SE. Analyses of persistent changes in active and passive properties of CA3 PCs suggested that this increase is multifactorial in origin, the major factors being a reduction in amplitude of the slow afterhyperpolarization and an increase in the fraction of bursting neurons.

SIGNIFICANCE

Here we show that pilocarpine-SE causes multiplication of the firing response gain in the three principal neurons in the hippocampal trisynaptic pathway. This alteration undoubtedly would contribute to hippocampal hyperexcitability in SE-induced TLE.

Mechanisms of memory storage in a model perirhinal network

The perirhinal cortex supports recognition and associative memory. Prior unit recording studies revealed that recognition memory involves a reduced responsiveness of perirhinal cells to familiar stimuli whereas associative memory formation is linked to increasing perirhinal responses to paired stimuli. Both effects are thought to depend on perirhinal plasticity but it is unclear how the same network could support these opposite forms of plasticity. However, a recent study showed that when neocortical inputs are repeatedly activated, depression or potentiation could develop, depending on the extent to which the stimulated neocortical activity recruited intrinsic longitudinal connections. We developed a biophysically realistic perirhinal model that reproduced these phenomena and used it to investigate perirhinal mechanisms of associative memory. These analyzes revealed that associative plasticity is critically dependent on a specific subset of neurons, termed conjunctive cells (CCs). When the model network was trained with spatially distributed but coincident neocortical inputs, CCs acquired excitatory responses to the paired inputs and conveyed them to distributed perirhinal sites via longitudinal projections. CC ablation during recall abolished expression of the associative memory. However, CC ablation during training did not prevent memory formation because new CCs emerged, revealing that competitive synaptic interactions governs the formation of CC assemblies.

Premature changes in neuronal excitability account for hippocampal network impairment and autistic-like behavior in neonatal BTBR T+tf/J mice

Coherent network oscillations (GDPs), generated in the immature hippocampus by the synergistic action of GABA and glutamate, both depolarizing and excitatory, play a key role in the construction of neuronal circuits. In particular, GDPs-associated calcium transients act as coincident detectors for enhancing synaptic efficacy at emerging GABAergic and glutamatergic synapses. Here, we show that, immediately after birth, in the CA3 hippocampal region of the BTBR T+tf/J mouse, an animal model of idiopathic autism, GDPs are severely impaired. This effect was associated with an increased GABAergic neurotransmission and a reduced neuronal excitability. In spite its depolarizing action on CA3 pyramidal cells (in single channel experiments E_GABA was positive to E_m), GABA exerted at the network level an inhibitory effect as demonstrated by isoguvacine-induced reduction of neuronal firing. We implemented a computational model in which experimental findings could be interpreted as the result of two competing effects: a reduction of the intrinsic excitability of CA3 principal cells and a reduction of the shunting activity in GABAergic interneurons projecting to principal cells. It is therefore likely that premature changes in neuronal excitability within selective hippocampal circuits of BTBR mice lead to GDPs dysfunction and behavioral deficits reminiscent of those found in autistic patients.

Distinct current modules shape cellular dynamics in model neurons

Numerous intrinsic currents are known to collectively shape neuronal membrane potential dynamics, or neuronal signatures. Although how sets of currents shape specific signatures such as spiking characteristics or oscillations has been studied individually, it is less clear how a neuron's suite of currents jointly shape its entire set of signatures. Biophysical conductance-based models of neurons represent a viable tool to address this important question. We hypothesized that currents are grouped into distinct modules that shape specific neuronal characteristics or signatures, such as resting potential, sub-threshold oscillations, and spiking waveforms, for several classes of neurons. For such a grouping to occur, the currents within one module should have minimal functional interference with currents belonging to other modules. This condition is satisfied if the gating functions of currents in the same module are grouped together on the voltage axis; in contrast, such functions are segregated along the voltage axis for currents belonging to different modules. We tested this hypothesis using four published example case models and found it to be valid for these classes of neurons. This insight into the neurobiological organization of currents also suggests an intuitive, systematic, and robust methodology to develop biophysical single-cell models with multiple biological characteristics applicable for both hand- and automated-tuning approaches. We illustrate the methodology using two example case rodent pyramidal neurons, from the lateral amygdala and the hippocampus. The methodology also helped reveal that a single-core compartment model could capture multiple neuronal properties. Such biophysical single-compartment models have potential to improve the fidelity of large network models.

Network models provide insights into how oriens-lacunosum-moleculare and bistratified cell interactions influence the power of local hippocampal CA1 theta oscillations

Hippocampal theta is a 4–12 Hz rhythm associated with episodic memory, and although it has been studied extensively, the cellular mechanisms underlying its generation are unclear. The complex interactions between different interneuron types, such as those between oriens–lacunosum-moleculare (OLM) interneurons and bistratified cells (BiCs), make their contribution to network rhythms difficult to determine experimentally. We created network models that are tied to experimental work at both cellular and network levels to explore how these interneuron interactions affect the power of local oscillations. Our cellular models were constrained with properties from patch clamp recordings in the CA1 region of an intact hippocampus preparation in vitro. Our network models are composed of three different types of interneurons: parvalbumin-positive (PV+) basket and axo-axonic cells (BC/AACs), PV+ BiCs, and somatostatin-positive OLM cells. Also included is a spatially extended pyramidal cell model to allow for a simplified local field potential representation, as well as experimentally-constrained, theta frequency synaptic inputs to the interneurons. The network size, connectivity, and synaptic properties were constrained with experimental data. To determine how the interactions between OLM cells and BiCs could affect local theta power, we explored how the number of OLM-BiC connections and connection strength affected local theta power. We found that our models operate in regimes that could be distinguished by whether OLM cells minimally or strongly affected the power of network theta oscillations due to balances that, respectively, allow compensatory effects or not. Inactivation of OLM cells could result in no change or even an increase in theta power. We predict that the dis-inhibitory effect of OLM cells to BiCs to pyramidal cell interactions plays a critical role in the resulting power of network theta oscillations. Overall, our network models reveal a dynamic interplay between different classes of interneurons in influencing local theta power.

Kv1.2 mediates heterosynaptic modulation of direct cortical synaptic inputs in CA3 pyramidal cells

KEY POINTS

We investigated the cellular mechanisms underlying mossy fibre-induced heterosynaptic long-term potentiation of perforant path (PP) inputs to CA3 pyramidal cells. Here we show that this heterosynaptic potentiation is mediated by downregulation of Kv1.2 channels. The downregulation of Kv1.2 preferentially enhanced PP-evoked EPSPs which occur at distal apical dendrites. Such enhancement of PP-EPSPs required activation of dendritic Na(+) channels, and its threshold was lowered by downregulation of Kv1.2. Our results may provide new insights into the long-standing question of how mossy fibre inputs constrain the CA3 network to sparsely represent direct cortical inputs.

ABSTRACT

A short high frequency stimulation of mossy fibres (MFs) induces long-term potentiation (LTP) of direct cortical or perforant path (PP) synaptic inputs in hippocampal CA3 pyramidal cells (CA3-PCs). However, the cellular mechanism underlying this heterosynaptic modulation remains elusive. Previously, we reported that repetitive somatic firing at 10 Hz downregulates Kv1.2 in the CA3-PCs. Here, we show that MF inputs induce similar somatic firing and downregulation of Kv1.2 in the CA3-PCs. The effect of Kv1.2 downregulation was specific to PP synaptic inputs that arrive at distal apical dendrites. We found that the somatodendritic expression of Kv1.2 is polarized to distal apical dendrites. Compartmental simulations based on this finding suggested that passive normalization of synaptic inputs and polarized distributions of dendritic ionic channels may facilitate the activation of dendritic Na(+) channels preferentially at distal apical dendrites. Indeed, partial block of dendritic Na(+) channels using 10 nm tetrodotoxin brought back the enhanced PP-evoked excitatory postsynaptic potentials (PP-EPSPs) to the baseline level. These results indicate that activity-dependent downregulation of Kv1.2 in CA3-PCs mediates MF-induced heterosynaptic LTP of PP-EPSPs by facilitating activation of Na(+) channels at distal apical dendrites.

Integration of exteroceptive and interoceptive information within the hippocampus: a computational study

Many episodic memory studies have critically implicated the hippocampus in the rapid binding of sensory information from the perception of the external environment, reported by exteroception. Other structures in the medial temporal lobe, especially the amygdala, have been more specifically linked with emotional dimension of episodic memories, reported by interoception. The hippocampal projection to the amygdala is proposed as a substrate important for the formation of extero-interoceptive associations, allowing adaptive behaviors based on past experiences. Recently growing evidence suggests that hippocampal activity observed in a wide range of behavioral tasks could reflect associations between exteroceptive patterns and their emotional valences. The hippocampal computational models, therefore, need to be updated to elaborate better interpretation of hippocampal-dependent behaviors. In earlier models, interoceptive features, if not neglected, are bound together with other exteroceptive features through autoassociative learning mechanisms. This way of binding integrates both kinds of features at the same level, which is not always suitable for example in the case of pattern completion. Based on the anatomical and functional heterogeneity along the septotemporal and transverse axes of the hippocampus, we suggest instead that distinct hippocampal subregions may be engaged in the representation of these different types of information, each stored apart in autoassociative memories but linked together in a heteroassociative way. The model is developed within the hard constraint of rapid, even single trial, learning of episodic memories. The performance of the model is assessed quantitatively and its resistance to interference is demonstrated through a series of numerical experiments. An experiment of reversal learning in patients with amnesic cognitive impairment is also reproduced.