Behavioral state and stimulus strength regulate the role of somatostatin interneurons in stabilizing network activity.

Inhibition stabilization enables cortical circuits to encode sensory signals across diverse contexts. Somatostatin-expressing (SST) interneurons are well-suited for this role through their strong recurrent connectivity with excitatory pyramidal cells. We developed a cortical circuit model predicting that SST cells become increasingly important for stabilization as sensory input strengthens. We tested this prediction in mouse primary visual cortex by manipulating excitatory input to SST cells, a key parameter for inhibition stabilization, with a novel cell-type specific pharmacological method to selectively block glutamatergic receptors on SST cells. Consistent with our model predictions, we find antagonizing glutamatergic receptors drives a paradoxical facilitation of SST cells with increasing stimulus contrast. In addition, we find even stronger engagement of SST-dependent stabilization when the mice are aroused. Thus, we reveal that the role of SST cells in cortical processing gradually switches as a function of both input strength and behavioral state.

Reliability Study of Metal-Oxide Semiconductors in Integrated Circuits.

This paper is devoted to the study of CMOS IC parameter degradation during reliability testing. The paper presents a review of literature data on the issue of the reliability of semiconductor devices and integrated circuits and the types of failures leading to the degradation of IC parameters. It describes the tests carried out on the reliability of controlled parameters of integrated circuit TPS54332, such as quiescent current, quiescent current in standby mode, resistance of the open key, and instability of the set output voltage in the whole range of input voltages and in the whole range of load currents. The calculated values of activation energies and acceleration coefficients for different test temperature regimes are given. As a result of the work done, sample rejection tests have been carried out on the TPS54332 IC under study. Experimental fail-safe tests were carried out, with subsequent analysis of the chip samples by the controlled parameter quiescent current. On the basis of the obtained experimental values, the values of activation energy and acceleration coefficient at different temperature regimes were calculated. The dependencies of activation energy and acceleration coefficient on temperature were plotted, which show that activation energy linearly increases with increasing temperature, while the acceleration coefficient, on the contrary, decreases. It was also found that the value of the calculated activation energy of the chip is 0.1 eV less than the standard value of the activation energy.

Agranular frontal cortical microcircuit underlying cognitive control in macaques.

The error-related negativity and an N2-component recorded over medial frontal cortex index core functions of cognitive control. While they are known to originate from agranular frontal areas, the underlying microcircuit mechanisms remain elusive. Most insights about microcircuit function have been derived from variations of the so-called canonical microcircuit model. These microcircuit architectures are based extensively on studies from granular sensory cortical areas in monkeys, cats, and rodents. However, evidence has shown striking cytoarchitectonic differences across species and differences in the functional relationships across cortical layers in agranular compared to granular sensory areas. In this minireview, we outline a tentative microcircuit model underlying cognitive control in the agranular frontal cortex of primates. The model incorporates the main GABAergic interneuron subclasses with specific laminar arrangements and target regions on pyramidal cells. We emphasize the role of layer 5 pyramidal cells in error and conflict detection. We offer several specific questions necessary for creating a specific intrinsic microcircuit model of the agranular frontal cortex.

Activated somatostatin interneurons orchestrate memory microcircuits.

Despite recent advancements in identifying engram cells, our understanding of their regulatory and functional mechanisms remains in its infancy. To provide mechanistic insight into engram cell functioning, we introduced a novel local microcircuit labeling technique that enables the labeling of intraregional synaptic connections. Utilizing this approach, we discovered a unique population of somatostatin (SOM) interneurons in the mouse basolateral amygdala (BLA). These neurons are activated during fear memory formation and exhibit a preference for forming synapses with excitatory engram neurons. Post-activation, these SOM neurons displayed varying excitability based on fear memory retrieval. Furthermore, when we modulated these SOM neurons chemogenetically, we observed changes in the expression of fear-related behaviors, both in a fear-associated context and in a novel setting. Our findings suggest that these activated SOM interneurons play a pivotal role in modulating engram cell activity. They influence the expression of fear-related behaviors through a mechanism that is dependent on memory cues.

Update on neurobiological mechanisms of fear: illuminating the direction of mechanism exploration and treatment development of trauma and fear-related disorders.

Fear refers to an adaptive response in the face of danger, and the formed fear memory acts as a warning when the individual faces a dangerous situation again, which is of great significance to the survival of humans and animals. Excessive fear response caused by abnormal fear memory can lead to neuropsychiatric disorders. Fear memory has been studied for a long time, which is of a certain guiding effect on the treatment of fear-related disorders. With continuous technological innovations, the study of fear has gradually shifted from the level of brain regions to deeper neural (micro) circuits between brain regions and even within single brain regions, as well as molecular mechanisms. This article briefly outlines the basic knowledge of fear memory and reviews the neurobiological mechanisms of fear extinction and relapse, which aims to provide new insights for future basic research on fear emotions and new ideas for treating trauma and fear-related disorders.

neuroAIx-Framework: design of future neuroscience simulation systems exhibiting execution of the cortical microcircuit model 20× faster than biological real-time.

Introduction: Research in the field of computational neuroscience relies on highly capable simulation platforms. With real-time capabilities surpassed for established models like the cortical microcircuit, it is time to conceive next-generation systems: neuroscience simulators providing significant acceleration, even for larger networks with natural density, biologically plausible multi-compartment models and the modeling of long-term and structural plasticity. Methods: Stressing the need for agility to adapt to new concepts or findings in the domain of neuroscience, we have developed the neuroAIx-Framework consisting of an empirical modeling tool, a virtual prototype, and a cluster of FPGA boards. This framework is designed to support and accelerate the continuous development of such platforms driven by new insights in neuroscience. Results: Based on design space explorations using this framework, we devised and realized an FPGA cluster consisting of 35 NetFPGA SUME boards. Discussion: This system functions as an evaluation platform for our framework. At the same time, it resulted in a fully deterministic neuroscience simulation system surpassing the state of the art in both performance and energy efficiency. It is capable of simulating the microcircuit with 20× acceleration compared to biological real-time and achieves an energy efficiency of 48nJ per synaptic event.

Variations on the theme: focus on cerebellum and emotional processing.

The cerebellum operates exploiting a complex modular organization and a unified computational algorithm adapted to different behavioral contexts. Recent observations suggest that the cerebellum is involved not just in motor but also in emotional and cognitive processing. It is therefore critical to identify the specific regional connectivity and microcircuit properties of the emotional cerebellum. Recent studies are highlighting the differential regional localization of genes, molecules, and synaptic mechanisms and microcircuit wiring. However, the impact of these regional differences is not fully understood and will require experimental investigation and computational modeling. This review focuses on the cellular and circuit underpinnings of the cerebellar role in emotion. And since emotion involves an integration of cognitive, somatomotor, and autonomic activity, we elaborate on the tradeoff between segregation and distribution of these three main functions in the cerebellum.

Disynaptic inhibition shapes tuning of OFF-motion detectors in Drosophila.

The circuitry underlying the detection of visual motion in Drosophila melanogaster is one of the best studied networks in neuroscience. Lately, electron microscopy reconstructions, algorithmic models, and functional studies have proposed a common motif for the cellular circuitry of an elementary motion detector based on both supralinear enhancement for preferred direction and sublinear suppression for null-direction motion. In T5 cells, however, all columnar input neurons (Tm1, Tm2, Tm4, and Tm9) are excitatory. So, how is null-direction suppression realized there? Using two-photon calcium imaging in combination with thermogenetics, optogenetics, apoptotics, and pharmacology, we discovered that it is via CT1, the GABAergic large-field amacrine cell, where the different processes have previously been shown to act in an electrically isolated way. Within each column, CT1 receives excitatory input from Tm9 and Tm1 and provides the sign-inverted, now inhibitory input signal onto T5. Ablating CT1 or knocking down GABA-receptor subunit Rdl significantly broadened the directional tuning of T5 cells. It thus appears that the signal of Tm1 and Tm9 is used both as an excitatory input for preferred direction enhancement and, through a sign inversion within the Tm1/Tm9-CT1 microcircuit, as an inhibitory input for null-direction suppression.

Biophysical parameters control signal transfer in spiking network.

Introduction: Information transmission and representation in both natural and artificial networks is dependent on connectivity between units. Biological neurons, in addition, modulate synaptic dynamics and post-synaptic membrane properties, but how these relate to information transmission in a population of neurons is still poorly understood. A recent study investigated local learning rules and showed how a spiking neural network can learn to represent continuous signals. Our study builds on their model to explore how basic membrane properties and synaptic delays affect information transfer. Methods: The system consisted of three input and output units and a hidden layer of 300 excitatory and 75 inhibitory leaky integrate-and-fire (LIF) or adaptive integrate-and-fire (AdEx) units. After optimizing the connectivity to accurately replicate the input patterns in the output units, we transformed the model to more biologically accurate units and included synaptic delay and concurrent action potential generation in distinct neurons. We examined three different parameter regimes which comprised either identical physiological values for both excitatory and inhibitory units (Comrade), more biologically accurate values (Bacon), or the Comrade regime whose output units were optimized for low reconstruction error (HiFi). We evaluated information transmission and classification accuracy of the network with four distinct metrics: coherence, Granger causality, transfer entropy, and reconstruction error. Results: Biophysical parameters showed a major impact on information transfer metrics. The classification was surprisingly robust, surviving very low firing and information rates, whereas information transmission overall and particularly low reconstruction error were more dependent on higher firing rates in LIF units. In AdEx units, the firing rates were lower and less information was transferred, but interestingly the highest information transmission rates were no longer overlapping with the highest firing rates. Discussion: Our findings can be reflected on the predictive coding theory of the cerebral cortex and may suggest information transfer qualities as a phenomenological quality of biological cells.

Bayesian Coherence Analysis for Microcircuit Structure Learning.

Functional microcircuits model the coordinated activity of neurons and play an important role in physiological computation and behaviors. Most existing methods to learn microcircuit structures are correlation-based and often generate dense microcircuits that cannot distinguish between direct and indirect association. We treat microcircuit structure learning as a Markov blanket discovery problem and propose Bayesian Coherence Analysis (BCA) which utilizes a Bayesian network architecture called Bayesian network with inverse-tree structure to efficiently and effectively detect Markov blankets for high-dimensional neural activity data. BCA achieved balanced sensitivity and specificity on simulated data. For the real-world anterior lateral motor cortex study, BCA identified microcircuit subtypes that predicted trial types with an accuracy of 0.92. BCA is a powerful method for microcircuit structure learning.

Effect of chemogenetic manipulation of PVN corticotropin-releasing factor-expressing neurons on excitability of presympathetic neurons in SHR / 中国药理学通报

Aim To observe the effect of corticotropin-releasing factor ( CRF) -expressing neurons on presympathetic neurons in hypothalamic paraventricular nucleus ( PVN) of normotensive Wistar Kyoto ( WKY) rats or spontaneously hypertensive rats (SHR) , and to elucidate the underlying neuronal circuit mechanism of central sympathetic hyperexcitability. Methods The expression levels of CRF protein in WKY rats and SHR PVN were determined by Western blot. Meanwhile, the WKY and SHR PVN CRF-expressing neurons and presympathetic neurons were observed by immunofluo-rescent staining. Adult WKY rats and SHR were used in this study. By microinjection of Cre-dependent ade-no-associated viruses ( AAV) that specifically recognized the CRF promoter and AAV of chemogenetics into the PVN, CRF-expressing neurons expressed designer receptors exclusively activated by designer drugs (DREADDs). Human M3 muscarinic DREADD coupled to Gq receptor ( hM3 Dq) was specifically expressed in PVN CRF-expressing neurons in WKY rats, while human M4 muscarinic DREADD coupled to Gi receptor ( hM4Di) was specifically expressed in PVN CRF-expressing neurons in SHR. Clozapine-N-oxide (CNO) , as a designer ligand, would couple to excitatory hM3Dq or inhibitory hM4Di to regulate the excitability of PVN CRF-expressing neurons. Then the PVN presympathetic neurons were retrogradely labeled by microinjection of fluosecent tracer into the intermedio-lateral column (IML) of spinal cord. Lastly, whole cell patch clamp was used to determine the effect of CNO (10 jjumol L~ ) on spontaneous excitatory postsynaptic currents ( sEPSCs) and current-evoked firing of PVN presympathtic neurons of WKY rats and SHR. Results The expression of CRF protein in the PVN of SHR was significantly higher than that of WKY rats, and the activity and number of CRF-expressing neurons in the PVN of SHR were increased. PVN CRF-expressing neurons were expressed with chemogenetic DREADDs and PVN presympathetic neurons were retrogradely labeled with fluorescent tracer in WKY rats and SHR. In SHR expressed with chemogenetic inhibitory hM4Di-mCherry of PVN CRF-expressing neurons, bath application of CNO to the brain slices resulted in a significant decrease in sEPSCs frequency, but no change in their amplitude of labeled PVN presympathetic neurons. In contrast, in WKY rats expressed with excitatory hM3Dq-eGFP of PVN CRF-expressing neurons, CNO had no obvious effect on the sEPSCs frequency and amplitude in PVN presympathetic neurons. Furthermore, bath application of CNO had no significant effect on current-evoked firing of PVN presympathetic neurons of either WKY rats with hM3Dq-eGFP expression in CRF neurons or SHR with hM4Di-mCherry expression in CRF neurons. Conclusions The activity and number of PVN CRF-expressing neurons are increased in SHR, and CRF-expressing neurons enhance the excitability of presympathetic neurons, which acts as a regulatory neuronal microcircuit between CRF neurons and presympathetic neurons in the PVN.

Targeting Frontal Gamma Activity with Neurofeedback to Improve Working Memory in Schizophrenia.

Optimal working memory (WM), the mental ability to internally maintain and manipulate task-relevant information, requires coordinated activity of dorsal-lateral prefrontal cortical (DLPFC) neurons. More specifically, during delay periods of tasks with WM features, DLPFC microcircuits generate persistent, stimulus-specific higher-frequency (e.g., gamma) activity. This activity largely depends on recurrent connections between parvalbumin positive inhibitory interneurons and pyramidal neurons in more superficial DLPFC layers. Due to the size and organization of pyramidal neurons (especially apical dendrites), local field potentials generated by DLPFC microcircuits are strong enough to pass outside the skull and can be detected using electroencephalography (EEG). Since patients with schizophrenia (SCZ) exhibit both DLPFC and WM abnormalities, EEG markers of DLPFC microcircuit activity during WM may serve as effective biomarkers or treatment targets. In this review, we summarize converging evidence from primate and human studies for a critical role of DLPFC microcircuit activity during WM and in the pathophysiology of SCZ. We also present a meta-analysis of studies available in PubMed specifically comparing frontal gamma activity between participants with SCZ and healthy controls, to determine whether frontal gamma activity may be a valid biomarker or treatment target for patients with SCZ. We summarize the complex cognitive and neurophysiologic processes contributing to neural oscillations during tasks with WM features, and how such complexity has stalled the development of neurophysiologic biomarkers and treatment targets. Finally, we summarize promising results from early reports using neuromodulation to target DLPFC neural activity and improve cognitive function in participants with SCZ, including a study from our team demonstrating that gamma-EEG neurofeedback increases frontal gamma power and WM performance in participants with SCZ. From the evidence discussed in this review, we believe the emerging field of neuromodulation, which includes extrinsic (electrical or magnetic stimulation) and intrinsic (EEG neurofeedback) modalities, will, in the coming decade, provide promising treatment options targeting specific neurophysiologic properties of specific brain areas to improve cognitive and behavioral health for patients with SCZ.

Distinct transcriptional programs define a heterogeneous neuronal ensemble for social interaction.

Reliable representations of information regarding complex behaviors including social interactions require the coordinated activity of heterogeneous cell types within distributed brain regions. Activity in the medial prefrontal cortex is critical in regulating social behavior, but our understanding of the specific cell types which comprise the social ensemble has been limited by available mouse lines and molecular tagging strategies which rely on the expression of a single marker gene. Here we sought to quantify the heterogeneous neuronal populations which are recruited during social interaction in parallel in a non-biased manner and determine how distinct cell types are differentially active during social interactions. We identify distinct populations of prefrontal neurons activated by social interaction by quantification of immediate early gene (IEG) expression in transcriptomically clustered neurons. This approach revealed variability in the recruitment of different excitatory and inhibitory populations within the medial prefrontal cortex. Furthermore, evaluation of the populations of IEGs recruited following social interaction revealed both cell-type and region-specific transcriptional programs, suggesting that reliance on a single molecular marker is insufficient to quantify activation across all cell types. Our findings provide a comprehensive description of cell-type specific transcriptional programs invoked by social interactions and reveal new insights into the heterogeneous neuronal populations which compose the social ensemble.

Characteristic columnar connectivity caters to cortical computation: Replication, simulation, and evaluation of a microcircuit model.

The neocortex, and with it the mammalian brain, achieves a level of computational efficiency like no other existing computational engine. A deeper understanding of its building blocks (cortical microcircuits), and their underlying computational principles is thus of paramount interest. To this end, we need reproducible computational models that can be analyzed, modified, extended and quantitatively compared. In this study, we further that aim by providing a replication of a seminal cortical column model. This model consists of noisy Hodgkin-Huxley neurons connected by dynamic synapses, whose connectivity scheme is based on empirical findings from intracellular recordings. Our analysis confirms the key original finding that the specific, data-based connectivity structure enhances the computational performance compared to a variety of alternatively structured control circuits. For this comparison, we use tasks based on spike patterns and rates that require the systems not only to have simple classification capabilities, but also to retain information over time and to be able to compute nonlinear functions. Going beyond the scope of the original study, we demonstrate that this finding is independent of the complexity of the neuron model, which further strengthens the argument that it is the connectivity which is crucial. Finally, a detailed analysis of the memory capabilities of the circuits reveals a stereotypical memory profile common across all circuit variants. Notably, the circuit with laminar structure does not retain stimulus any longer than any other circuit type. We therefore conclude that the model's computational advantage lies in a sharper representation of the stimuli.

Synaptic determinants of cholinergic interneurons hyperactivity during parkinsonism.

Parkinson's disease is a neurodegenerative ailment generated by the loss of dopamine in the basal ganglia, mainly in the striatum. The disease courses with increased striatal levels of acetylcholine, disrupting the balance among these modulatory transmitters. These modifications disturb the excitatory and inhibitory balance in the striatal circuitry, as reflected in the activity of projection striatal neurons. In addition, changes in the firing pattern of striatal tonically active interneurons during the disease, including cholinergic interneurons (CINs), are being searched. Dopamine-depleted striatal circuits exhibit pathological hyperactivity as compared to controls. One aim of this study was to show how striatal CINs contribute to this hyperactivity. A second aim was to show the contribution of extrinsic synaptic inputs to striatal CINs hyperactivity. Electrophysiological and calcium imaging recordings in Cre-mice allowed us to evaluate the activity of dozens of identified CINs with single-cell resolution in ex vivo brain slices. CINs show hyperactivity with bursts and silences in the dopamine-depleted striatum. We confirmed that the intrinsic differences between the activity of control and dopamine-depleted CINs are one source of their hyperactivity. We also show that a great part of this hyperactivity and firing pattern change is a product of extrinsic synaptic inputs, targeting CINs. Both glutamatergic and GABAergic inputs are essential to sustain hyperactivity. In addition, cholinergic transmission through nicotinic receptors also participates, suggesting that the joint activity of CINs drives the phenomenon; since striatal CINs express nicotinic receptors, not expressed in striatal projection neurons. Therefore, CINs hyperactivity is the result of changes in intrinsic properties and excitatory and inhibitory inputs, in addition to the modification of local circuitry due to cholinergic nicotinic transmission. We conclude that CINs are the main drivers of the pathological hyperactivity present in the striatum that is depleted of dopamine, and this is, in part, a result of extrinsic synaptic inputs. These results show that CINs may be a main therapeutic target to treat Parkinson's disease by intervening in their synaptic inputs.

Microscale electrophysiological functional connectivity in human cortico-basal ganglia network.

OBJECTIVE: We investigated the electrophysiological relationships in the cortico-basal ganglia network on a sub-centimeter scale to increase our understanding of neural functional relationships in Parkinson's disease (PD). METHODS: Data was intraoperatively recorded from 2 sources in the human brain-a microelectrode in the subthalamic nucleus (STN) and a micro-electrocorticography grid on the motor association cortex-during bilateral deep brain stimulation (DBS) electrode placement. STN neurons and local field potential (LFP) were defined as functionally connected when the 99.7% confidence intervals of the action potential (AP)-aligned average LFP and control did not overlap. RESULTS: APs from STN neurons were functionally connected to the STN LFP for 18/46 STN neurons. This functional connection was observed between STN neuron APs and cortical LFP for 25/46 STN neurons. The cortical patterns of electrophysiological functional connectivity differed for each neuron. CONCLUSIONS: A subset of single neurons in the STN exhibited functional connectivity with electrophysiological activity in the STN and at a distance with the motor association cortex surveyed on a sub-centimeter spatial scale. These connections show a per neuron differential topography on the cortex. SIGNIFICANCE: The cortico-basal ganglia circuit is organized on a sub-centimeter scale, and plays an important role in the mechanisms of PD and DBS.

Neurogliaform cells mediate feedback inhibition in the medial entorhinal cortex.

Layer I of the medial entorhinal cortex (MEC) contains converging axons from several brain areas and dendritic tufts originating from principal cells located in multiple layers. Moreover, specific GABAergic interneurons are also located in the area, but their inputs, outputs, and effect on local network events remain elusive. Neurogliaform cells are the most frequent and critically positioned inhibitory neurons in layer I. They are considered to conduct feed-forward inhibition via GABAA and GABAB receptors on pyramidal cells located in several cortical areas. Using optogenetic experiments, we showed that layer I neurogliaform cells receive excitatory inputs from layer II pyramidal cells, thereby playing a critical role in local feedback inhibition in the MEC. We also found that neurogliaform cells are evenly distributed in layer I and do not correlate with the previously described compartmentalization ("cell islands") of layer II. We concluded that the activity of neurogliaform cells in layer I is largely set by layer II pyramidal cells through excitatory synapses, potentially inhibiting the apical dendrites of all types of principal cells in the MEC.

Rate and oscillatory switching dynamics of a multilayer visual microcircuit model.

The neocortex is organized around layered microcircuits consisting of a variety of excitatory and inhibitory neuronal types which perform rate- and oscillation-based computations. Using modeling, we show that both superficial and deep layers of the primary mouse visual cortex implement two ultrasensitive and bistable switches built on mutual inhibitory connectivity motives between somatostatin, parvalbumin, and vasoactive intestinal polypeptide cells. The switches toggle pyramidal neurons between high and low firing rate states that are synchronized across layers through translaminar connectivity. Moreover, inhibited and disinhibited states are characterized by low- and high-frequency oscillations, respectively, with layer-specific differences in frequency and power which show asymmetric changes during state transitions. These findings are consistent with a number of experimental observations and embed firing rate together with oscillatory changes within a switch interpretation of the microcircuit.

A developmental switch between electrical and neuropeptide communication in the ventromedial hypothalamus.

Dissecting neural connectivity patterns within local brain regions is an essential step to understanding the function of the brain.1 Neural microcircuits in brain regions, such as the neocortex and the hippocampus, have been extensively studied.2 By contrast, the microcircuit in the hypothalamus remains largely uncharacterized. The hypothalamus is crucial for animals' survival and reproduction.3 Knowledge of how different hypothalamic nuclei coordinate with each other and outside brain regions for hypothalamus-related functions has been significantly advanced.4-9 Although there are limited studies on the neural microcircuit in the lateral hypothalamus (LHA)10,11 and the suprachiasmatic nucleus (SCN),12,13 the patterns of neural microcircuits in most of the given hypothalamic nuclei remain largely unknown. This study applied combinatory approaches to address the local neural circuit pattern in the ventromedial hypothalamus (VMH) and other hypothalamic nuclei. We discovered a unique neural circuit design in the VMH. Neurons in the VMH were electrically coupled at the early postnatal stage like ones in the neocortex.14 However, unlike neocortical neurons,14,15 they developed very few chemical synapses after the disappearance of electrical synapses. Instead, VMH neurons communicated with neuropeptides. The similar scarceness of synaptic connectivity found in other hypothalamic nuclei further indicated that the lack of synaptic connections is a unique feature for local neural circuits in most adult hypothalamic nuclei. Thus, our findings provide a solid synaptic basis at the cellular level to understand hypothalamic functions better.

Functional Investigation of a Neuronal Microcircuit in the CA1 Area of the Hippocampus Reveals Synaptic Dysfunction in Dravet Syndrome Mice.

Dravet syndrome is severe childhood-onset epilepsy, caused by loss of function mutations in the SCN1A gene, encoding for the voltage-gated sodium channel NaV1.1. The leading hypothesis is that Dravet is caused by selective reduction in the excitability of inhibitory neurons, due to hampered activity of NaV1.1 channels in these cells. However, these initial neuronal changes can lead to further network alterations. Here, focusing on the CA1 microcircuit in hippocampal brain slices of Dravet syndrome (DS, Scn1a A1783V/WT) and wild-type (WT) mice, we examined the functional response to the application of Hm1a, a specific NaV1.1 activator, in CA1 stratum-oriens (SO) interneurons and CA1 pyramidal excitatory neurons. DS SO interneurons demonstrated reduced firing and depolarized threshold for action potential (AP), indicating impaired activity. Nevertheless, Hm1a induced a similar AP threshold hyperpolarization in WT and DS interneurons. Conversely, a smaller effect of Hm1a was observed in CA1 pyramidal neurons of DS mice. In these excitatory cells, Hm1a application resulted in WT-specific AP threshold hyperpolarization and increased firing probability, with no effect on DS neurons. Additionally, when the firing of SO interneurons was triggered by CA3 stimulation and relayed via activation of CA1 excitatory neurons, the firing probability was similar in WT and DS interneurons, also featuring a comparable increase in the firing probability following Hm1a application. Interestingly, a similar functional response to Hm1a was observed in a second DS mouse model, harboring the nonsense Scn1a R613X mutation. Furthermore, we show homeostatic synaptic alterations in both CA1 pyramidal neurons and SO interneurons, consistent with reduced excitation and inhibition onto CA1 pyramidal neurons and increased release probability in the CA1-SO synapse. Together, these results suggest global neuronal alterations within the CA1 microcircuit extending beyond the direct impact of NaV1.1 dysfunction.