Spike Potentials Research Articles

A thermophysical mechanism exploration of the brain: Motor cortex modeling with canonical ensemble theory

The brain, recognized as one of the most intricate systems globally, has been a focal point for scientific exploration. Researchers have made efforts to construct models of the brain based on neural dynamics and complex networks to gain insights into its workings. It is crucial to investigate the brain's working principles from various perspectives. This study presents a novel thermophysical model of the motor cortex and examines its potential thermodynamic properties. Utilizing canonical ensemble theory, we constructed the thermophysical model using spike and local field potential (LFP) signals obtained from intracortical brain-machine-interfaces (iBMIs) in two monkeys. The parameters derived from this model—namely internal energy, free energy, and entropy—were employed to assess the thermodynamic properties and observe alterations in these properties during reaching and grasping movements. Furthermore, this proposed model was applied to movement pattern decoding, highlighting its potential in neural decoding tasks. In both LFP- and spike-based thermodynamic models, there was an increase in internal energy and free energy, coupled with a decrease in entropy when the motor cortex was activated across various movement tasks. This suggests that the neural system adheres to the principles of a thermophysical system. Notably, the thermodynamic features demonstrated superior performance in decoding movement intentions compared to traditional LFP and spike features. This study represents the first construction of a comprehensive thermodynamic model of the motor cortex based on LFP and spike signals. The model exhibits remarkable stationarity and holds promise for long-term and stable evaluations of motor cortex functions.

Sub-threshold neuronal activity and the dynamical regime of cerebral cortex

Cortical neurons exhibit temporally irregular spiking patterns and heterogeneous firing rates. These features arise in model circuits operating in a ‘fluctuation-driven regime’, in which fluctuations in membrane potentials emerge from the network dynamics. However, it is still debated whether the cortex operates in such a regime. We evaluated the fluctuation-driven hypothesis by analyzing spiking and sub-threshold membrane potentials of neurons in the frontal cortex of mice performing a decision-making task. We showed that while standard fluctuation-driven models successfully account for spiking statistics, they fall short in capturing the heterogeneity in sub-threshold activity. This limitation is an inevitable outcome of bombarding single-compartment neurons with a large number of pre-synaptic inputs, thereby clamping the voltage of all neurons to more or less the same average voltage. To address this, we effectively incorporated dendritic morphology into the standard models. Inclusion of dendritic morphology in the neuronal models increased neuronal selectivity and reduced error trials, suggesting a functional role for dendrites during decision-making. Our work suggests that, during decision-making, cortical neurons in high-order cortical areas operate in a fluctuation-driven regime.

Dissociative and prioritized modeling of behaviorally relevant neural dynamics using recurrent neural networks

Understanding the dynamical transformation of neural activity to behavior requires new capabilities to nonlinearly model, dissociate and prioritize behaviorally relevant neural dynamics and test hypotheses about the origin of nonlinearity. We present dissociative prioritized analysis of dynamics (DPAD), a nonlinear dynamical modeling approach that enables these capabilities with a multisection neural network architecture and training approach. Analyzing cortical spiking and local field potential activity across four movement tasks, we demonstrate five use-cases. DPAD enabled more accurate neural–behavioral prediction. It identified nonlinear dynamical transformations of local field potentials that were more behavior predictive than traditional power features. Further, DPAD achieved behavior-predictive nonlinear neural dimensionality reduction. It enabled hypothesis testing regarding nonlinearities in neural–behavioral transformation, revealing that, in our datasets, nonlinearities could largely be isolated to the mapping from latent cortical dynamics to behavior. Finally, DPAD extended across continuous, intermittently sampled and categorical behaviors. DPAD provides a powerful tool for nonlinear dynamical modeling and investigation of neural–behavioral data.

Computation Implemented by the Interaction of Chemical Reaction, Clustering, and De-Clustering of Molecules.

A chemical reaction and its reaction environment are intrinsically linked, especially within the confines of narrow cellular spaces. Traditional models of chemical reactions often use differential equations with concentration as the primary variable, neglecting the density heterogeneity in the solution and the interaction between the reaction and its environment. We model the interaction between a chemical reaction and its environment within a geometrically confined space, such as inside a cell, by representing the environment through the size of molecular clusters. In the absence of fluctuations, the interplay between cluster size changes and the activation and inactivation of molecules induces oscillations. However, in unstable environments, the system reaches a fluctuating steady state. When an enzyme is introduced to this steady state, oscillations akin to action potential spike trains emerge. We examine the behavior of these spike trains and demonstrate that they can be used to implement logic gates. We discuss the oscillations and computations that arise from the interaction between a chemical reaction and its environment, exploring their potential for contributing to chemical intelligence.

The role of hydrogen as long-duration energy storage and as an international energy carrier for electricity sector decarbonization

With countries and economies around the globe increasingly relying on non-dispatchable variable renewable energy (VRE), the need for effective energy storage and international carriers of low-carbon energy has intensified. This study delves into hydrogen’s prospective, multifaceted contribution to decarbonizing the electricity sector, with emphasis on its utilization as a scalable technology for long-duration energy storage and as an international energy carrier. Using Japan as a case study, based on its ambitious national hydrogen strategy and plans to import liquefied hydrogen as a low-carbon fuel source, we employ advanced models encompassing capacity expansion and hourly dispatch. We explore diverse policy scenarios to unravel the timing, quantity, and operational intricacies of hydrogen deployment within a power system. Our findings highlight the essential role of hydrogen in providing a reliable power supply by balancing mismatches in VRE generation and load over several weeks and months and reducing the costs of achieving a zero-emission power system. The study recommends prioritizing domestically produced hydrogen, leveraging renewables for cost reduction, and strategically employing imported hydrogen as a risk hedge against potential spikes in battery storage and renewable energy costs. Furthermore, the strategic incorporation of hydrogen mitigates system costs and enhances energy self-sufficiency, informing policy design and investment strategies aligned with the dynamic global energy landscape.

Promotion of maturation of human pluripotent stem cell-derived cardiomyocytes via treatment with the peroxisome proliferator-activated receptor alpha agonist Fenofibrate.

As research on in vitro cardiotoxicity assessment and cardiac disease modeling becomes more important, the demand for human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) is increasing. However, it has been reported that differentiated hPSC-CMs are in a physiologically immature state compared to in vivo adult CMs. Since immaturity of hPSC-CMs can lead to poor drug response and loss of acquired heart disease modeling, various approaches have been attempted to promote maturation of CMs. Here, we confirm that peroxisome proliferator-activated receptor alpha (PPARα), one of the representative mechanisms of CM metabolism and cardioprotective effect also affects maturation of CMs. To upregulate PPARα expression, we treated hPSC-CMs with fenofibrate (Feno), a PPARα agonist used in clinical hyperlipidemia treatment, and demonstrated that the structure, mitochondria-mediated metabolism, and electrophysiology-based functions of hPSC-CMs were all mature. Furthermore, as a result of multi electrode array (MEA)-based cardiotoxicity evaluation between control and Feno groups according to treatment with arrhythmia-inducing drugs, drug response was similar in a dose-dependent manner. However, main parameters such as field potential duration, beat period, and spike amplitude were different between the 2 groups. Overall, these results emphasize that applying matured hPSC-CMs to the field of preclinical cardiotoxicity evaluation, which has become an essential procedure for new drug development, is necessary.

On Effect of Chloroform on Electrical Activity of Proteinoids.

Proteinoids, or thermal proteins, produce hollow microspheres in aqueous solutions. Ensembles of the microspheres produce endogenous spikes of electrical activity, similar to that of neurons. To make the first step toward the evaluation of the mechanisms of such electrical behaviour, we decided to expose proteinoids to chloroform. We found that while chloroform does not inhibit the electrical oscillations of proteinoids, it causes substantial changes in the patterns of electrical activity. Namely, incremental chloroform exposure strongly affects proteinoid microsphere electrical activity across multiple metrics. As chloroform levels rise, the spike potential drops from 0.9 mV under control conditions to 0.1 mV at 25 mg/mL. This progressive spike potential decrease suggests chloroform suppresses proteinoid electrical activity. The time between spikes, the interspike period, follows a similar pattern. Minimal chloroform exposure does not change the average interspike period, while higher exposures do. It drops from 23.2 min under control experiments to 3.8 min at 25 mg/mL chloroform, indicating increased frequency of the electrical activity. These findings might lead to a deeper understanding of the electrical activity of proteinoids and their potential application in the domain of bioelectronics.

Simple model to incorporate statistical noise based on a modified hodgkin-huxley approach for external electrical field driven neural responses

Noise activity is known to affect neural networks, enhance the system response to weak external signals, and lead to stochastic resonance phenomenon that can effectively amplify signals in nonlinear systems. In most treatments, channel noise has been modeled based on multi-state Markov descriptions or the use stochastic differential equation models. Here we probe a computationally simple approach based on a minor modification of the traditional Hodgkin-Huxley approach to embed noise in neural response. Results obtained from numerous simulations with different excitation frequencies and noise amplitudes for the action potential firing show very good agreement with output obtained from well-established models. Furthermore, results from the Mann–Whitney U Test reveal a statistically insignificant difference. The distribution of the time interval between successive potential spikes obtained from this simple approach compared very well with the results of complicated Fox and Lu type methods at much reduced computational cost. This present method could also possibly be applied to the analysis of spatial variations and/or differences in characteristics of random incident electromagnetic signals.

Discovery of Novel Spike Inhibitors against SARS-CoV-2 Infection.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for the current coronavirus disease pandemic. With the rapid evolution of variant strains, finding effective spike protein inhibitors is a logical and critical priority. Angiotensin-converting enzyme 2 (ACE2) has been identified as the functional receptor for SARS-CoV-2 viral entry, and thus related therapeutic approaches associated with the spike protein-ACE2 interaction show a high degree of feasibility for inhibiting viral infection. Our computer-aided drug design (CADD) method meticulously analyzed more than 260,000 compound records from the United States National Cancer Institute (NCI) database, to identify potential spike inhibitors. The spike protein receptor-binding domain (RBD) was chosen as the target protein for our virtual screening process. In cell-based validation, SARS-CoV-2 pseudovirus carrying a reporter gene was utilized to screen for effective compounds. Ultimately, compounds C2, C8, and C10 demonstrated significant antiviral activity against SARS-CoV-2, with estimated EC50 values of 8.8 μM, 6.7 μM, and 7.6 μM, respectively. Using the above compounds as templates, ten derivatives were generated and robust bioassay results revealed that C8.2 (EC50 = 5.9 μM) exhibited the strongest antiviral efficacy. Compounds C8.2 also displayed inhibitory activity against the Omicron variant, with an EC50 of 9.3 μM. Thus, the CADD method successfully discovered lead compounds binding to the spike protein RBD that are capable of inhibiting viral infection.

Loss of anoctamin 1 reveals a subtle role for BK channels in lymphatic muscle action potentials.

Ca2+ signalling plays a crucial role in determining lymphatic muscle cell excitability and contractility through its interaction with the Ca2+-activated Cl- channel anoctamin 1 (ANO1). In contrast, the large-conductance (BK) Ca2+-activated K+ channel (KCa) and other KCa channels have prominent vasodilatory actions by hyperpolarizing vascular smooth muscle cells. Here, we assessed the expression and contribution of the KCa family to mouse and rat lymphatic collecting vessel contractile function. The BK channel was the only KCa channel consistently expressed in fluorescence-activated cell sorting-purified mouse lymphatic muscle cell lymphatic muscle cells. We used a pharmacological inhibitor of BK channels, iberiotoxin, and small-conductance Ca2+-activated K+ channels, apamin, to inhibit KCa channels acutely in ex vivo isobaric myography experiments and intracellular membrane potential recordings. In basal conditions, BK channel inhibition had little to no effect on either mouse inguinal-axillary lymphatic vessel (MIALV) or rat mesenteric lymphatic vessel contractions or action potentials (APs). We also tested BK channel inhibition under loss of ANO1 either by genetic ablation (Myh11CreERT2-Ano1 fl/fl, Ano1ismKO) or by pharmacological inhibition with Ani9. In both Ano1ismKO MIALVs and Ani9-pretreated MIALVs, inhibition of BK channels increased contraction amplitude, increased peak AP and broadened the peak of the AP spike. In rat mesenteric lymphatic vessels, BK channel inhibition also abolished the characteristic post-spike notch, which was exaggerated with ANO1 inhibition, and significantly increased the peak potential and broadened the AP spike. We conclude that BK channels are present and functional on mouse and rat lymphatic muscle cells but are otherwise masked by the dominance of ANO1. KEY POINTS: Mouse and rat lymphatic muscle cells express functional BK channels. BK channels make little contribution to either rat or mouse lymphatic collecting vessel contractile function in basal conditions across a physiological pressure range. ANO1 limits the peak membrane potential achieved in the action potential and sets a plateau potential limiting the voltage-dependent activation of BK. BK channels are activated when ANO1 is absent or blocked and slightly impair contractile strength by reducing the peak membrane potential achieved in the action potential spike and accelerating the post-spike repolarization.

Electrodeposition of Phase–Pure n–Type Cu2O: Role of Electrode Reactions and Local pH

Cuprous oxide (Cu2O) thin films, antithetically exhibiting n-type conductivity, were electro–deposited on Fluorine-doped Tin Oxide (FTO) coated glass substrates. Linear sweep voltammetry, chronoamperometry, and chronopotentiometry studies coupled with structural characterization of the deposit identify the occurrence of multiple reduction reactions, including “corrosion” of Cu2O to Cu. Interestingly, an underpotential conversion (negative of +0.039 V vs Ag/AgCl) of the Cu2O film to Cu islands is observed during potentiostatic deposition. The same process is also shown as a potential spike in chronopotentiometry curves, during galvanostatic deposition, at current densities that are cathodic of −0.2 mAcm−1. The reason for the formation of Cu is attributed to the decrease in local pH in the vicinity of the working electrode, whence thermodynamic conditions favor the formation of Cu. The proroguation of Cu formation is achieved by continuously stirring the solution, thereby stabilizing the pH at the electrode. Deferment of film corrosion to increasingly longer times is observed with increasing stirring rates. Mott-Schottky analysis of phase-pure films reveals the formation of degenerately doped n-type Cu2O films (n ∼1020 cm−3). The phase pure Cu2O films could be used as an electron transport layer in several photo-conversion devices and ultimately pave the way for an oxide homojunction device.

Phosphorylation of tau protein based on the activity of kinases and phosphatases in various forms of synaptic plasticity.

The aim of this study is to show the relationship between the change in the strengthening of synaptic plasticity and tau phosphorylation and tau-kinases and phosphatase. The averages of the field excitatory-postsynaptic potential (fEPSP) and population spike (PS) in the last 5 min were used as a measure of LTP, LTD and MP. Total and phosphorylated levels of tau, kinases and phosphatases were evaluated by western blot and mRNA levels were evaluated by RT-qPCR. The stimulation of synapses by HFS and LFS+HFS increased the phosphorylation of total-tau and phospho-tau at the Thr181, Ser202/Thr205, Ser396 and Ser416 residues, and these were accompanied by increased enzymatic activity of Akt, ERK1/2. Theincreased phosphorylation of tau may mediate maintenance of LTP. If the increase in phosphorylation of tau cannot be prevented, together with inhibition of the subsequent LTP, this may indicate that the physiological role of hyperphosphorylated tau in synaptic plasticity may extend to pathological processes.

Multi-Algorithm Artifact Correction (MAAC) procedure part one: Algorithm and example

The Multi-Algorithm Artifact Correction (MAAC) procedure is presented for electroencephalographic (EEG) data, as made freely available in the open-source EP Toolkit (Dien, 2010). First the major EEG artifact correction methods (regression, spatial filters, principal components analysis, and independent components analysis) are reviewed. Contrary to the dominant approach of picking one method that is thought to be most effective, this review concludes that none are globally superior, but rather each has strengths and weaknesses. Then each of the major artifact types are reviewed (Blink, Corneo-Retinal Dipole, Saccadic Spike Potential, and Movement). For each one, it is proposed that one of the major correction methods is best matched to address it, resulting in the MAAC procedure. The MAAC itself is then presented, as implemented in the EP Toolkit, in order to provide a sense of the user experience. The primary goal of this present paper is to make the conceptual argument for the MAAC approach.

Multimodal subspace identification for modeling discrete-continuous spiking and field potential population activity

Objective. Learning dynamical latent state models for multimodal spiking and field potential activity can reveal their collective low-dimensional dynamics and enable better decoding of behavior through multimodal fusion. Toward this goal, developing unsupervised learning methods that are computationally efficient is important, especially for real-time learning applications such as brain–machine interfaces (BMIs). However, efficient learning remains elusive for multimodal spike-field data due to their heterogeneous discrete-continuous distributions and different timescales. Approach. Here, we develop a multiscale subspace identification (multiscale SID) algorithm that enables computationally efficient learning for modeling and dimensionality reduction for multimodal discrete-continuous spike-field data. We describe the spike-field activity as combined Poisson and Gaussian observations, for which we derive a new analytical SID method. Importantly, we also introduce a novel constrained optimization approach to learn valid noise statistics, which is critical for multimodal statistical inference of the latent state, neural activity, and behavior. We validate the method using numerical simulations and with spiking and local field potential population activity recorded during a naturalistic reach and grasp behavior. Main results. We find that multiscale SID accurately learned dynamical models of spike-field signals and extracted low-dimensional dynamics from these multimodal signals. Further, it fused multimodal information, thus better identifying the dynamical modes and predicting behavior compared to using a single modality. Finally, compared to existing multiscale expectation-maximization learning for Poisson–Gaussian observations, multiscale SID had a much lower training time while being better in identifying the dynamical modes and having a better or similar accuracy in predicting neural activity and behavior. Significance. Overall, multiscale SID is an accurate learning method that is particularly beneficial when efficient learning is of interest, such as for online adaptive BMIs to track non-stationary dynamics or for reducing offline training time in neuroscience investigations.

Optogenetically modified human embryonic stem cell-derived otic neurons establish functional synaptic connection with cochlear nuclei

Spiral ganglia neurons (SGNs) impairment can cause deafness. One important therapeutic approach involves utilizing stem cells to restore impaired auditory circuitry. Nevertheless, the inadequate implementation of research methodologies poses a challenge in accurately assessing the functionality of derived cells within the circuit. Here, we describe a novel method for converting human embryonic stem cells (hESCs) into otic neurons (ONs) and assess their functional connectivity using an optogenetic approach with cells or an organotypic slice of rat cochlear nucleus (CN) in coculture. Embryonic stem cell-derived otic neurons (eONs) exhibited SGN marker expression and generated functional synaptic connection when cocultured with cochlear nucleus neurons (CNNs). Synapsin 1 and VGLUT expression are found in the cochlear nucleus of brain slices, where eONs projected processes during the coculture of eONs and CN brain slices. Action potential spikes and INa+/IK+ of CNNs increased in tandem with light stimulations to eONs. These findings provide further evidence that eONs may be a candidate source to treat SGN-deafness.

Effect of High-Energy Milling on Ceria-Zirconia’s Redox Properties

Series of ceria-zirconia (CZ)-based nano-materials with a d50 in the range of 0.2 to 1.3 microns were made using the jar milling, Eiger milling, and steam jet milling (SJM) techniques. The effect of the milling conditions on the morphology and textural properties was studied. High-energy steam jet milling in a quasi-hydrothermal environment (with potential local temperature spikes over 500 °C) significantly impacted the CZ crystal structure by inducing lattice distortions. It was shown that the acquired lattice stress resulted in a significant increase in oxygen mobility, which was manifested by a TPR-H2 Tmax shift from 450–550 to 150–250 °C. CZ materials with fast oxygen mobility are metastable phases, and re-slurring nano-CZ powders in water and impregnation with precious metals had stabilizing effects on fast oxygen mobility. Efficiently enhancing the CZ redox activity milling process took place in the following order: Steam jet milling > Eiger milling > jar milling.

Action potential solitons and waves in axons

We show that the action potential signals generated by the Hodgkin–Huxley cable model are reaction–diffusion-type solitons and waves. Within the framework of the cable equation, action potential spikes generated by injected currents at the middle of the axon originate travelling spikes propagating in opposite directions of the axon. Action potential spikes travelling in opposite directions of the axon annihilate when colliding with each other or with the axon boundaries. Through numerical simulations, we characterise the properties of these action potentials, deriving their characteristic curves and speeds. In the spiking region of the HH model, different spikes have different speeds. We propose several tests to validate or falsify the Hodgkin–Huxley cable model.

Europe's energy security: From Russian dependence to renewable reliance

This paper examines the impact of EU energy policies, namely the National Energy and Climate Plans (NECP19) and REPowerEU (2022), on the European natural gas security of supply. Our analysis shows that the REPowerEU plan significantly cuts gas demand by 133 bcm compared to NECP19. This shift can make Europe independent from Russian gas by 2030. Executing REPowerEU requires faster, clean technology deployment. The EU needs to catch up in installations to reach REPowerEU targets, while NECP19 maintains high gas demand (423 bcm till 2030), potentially exacerbating gas import dependence. NECP19 not only raises gas demand but also brings substantial inter-annual variation (IAV) of demand. In cold years (twice in ten years), demand spikes by 39 bcm, and warm years (three in ten years) decrease it by 23 bcm. REPowerEU, while moderately increasing gas demand variation (around 7% versus NECP19), does not solve the demand variability issue. In extremely cold years (one in forty years), Europe may face a 46 bcm gap, around a quarter of the spot LNG market. Failing REPowerEU not only heightens gas import risk but also risks price spikes under varying climates and global market conditions. We offer policy recommendations to address potential price spikes related to IAV demand.

The Effects of the Fraction Isolated from Iranian Buthotus shach Scorpion Venom on Synaptic Plasticity, Learning, Memory, and Seizure Susceptibility.

Epilepsy, as a neurological disease, can be defined as frequent seizure attacks. Further, it affects many other aspects of patients' mental activities, such as learning and memory. Scorpion venoms have gained notice as compounds with potential antiepileptic properties. Among them, Buthotus schach (BS) is one of the Iranian scorpions studied by Aboutorabi et al., who fractionated, characterized, and tested this compound using electrophysiological techniques in brain slices (patch-clamp recording). In the present study, the fraction obtained from gel electrophoresis was investigated through behavioral and electrophysiological assays. At first, ventricular cannulation was performed in rats, and then the active fraction (i.e., F3), carbamazepine, and the vehicle were microinjected into the brain before seizure induction by the subcutaneous (SC) injection of pentylenetetrazol (PTZ). Seizure behaviors were scaled according to Racine stages. Memory and learning were evaluated using the Y-maze and passive avoidance tests. Other groups entered evoked field potential recording after microinjection and seizure induction. Population spike (PS) and field excitatory postsynaptic potential (fEPSP) were measured. The F3 fraction could prevent the fifth stage and postpone the third stage of seizure compared to the control (carbamazepine) group. There was no significant improvement in memory and learning in the group treated with the F3 fraction. Also, PS amplitude and fEPSP slope increased significantly, and long-term potentiation was successfully formed after the high-frequency stimulation of the performant pathway. Our results support the antiepileptic effects of the F3 fraction of BS venom, evidenced by behavioral and electrophysiological studies. However, the effects of this fraction on memory and learning were not in the same direction, suggesting the involvement of two different pathways.

A Pathogenic Missense Mutation in Kainate Receptors Elevates Dendritic Excitability and Synaptic Integration through Dysregulation of SK Channels.

Numerous rare variants that cause neurodevelopmental disorders (NDDs) occur within genes encoding synaptic proteins, including ionotropic glutamate receptors. However, in many cases, it remains unclear how damaging missense variants affect brain function. We determined the physiological consequences of an NDD causing missense mutation in the GRIK2 kainate receptor (KAR) gene, that results in a single amino acid change p.Ala657Thr in the GluK2 receptor subunit. We engineered this mutation in the mouse Grik2 gene, yielding a GluK2(A657T) mouse, and studied mice of both sexes to determine how hippocampal neuronal function is disrupted. Synaptic KAR currents in hippocampal CA3 pyramidal neurons from heterozygous A657T mice exhibited slow decay kinetics, consistent with incorporation of the mutant subunit into functional receptors. Unexpectedly, CA3 neurons demonstrated elevated action potential spiking because of downregulation of the small-conductance Ca2+ activated K+ channel (SK), which mediates the post-spike afterhyperpolarization. The reduction in SK activity resulted in increased CA3 dendritic excitability, increased EPSP-spike coupling, and lowered the threshold for the induction of LTP of the associational-commissural synapses in CA3 neurons. Pharmacological inhibition of SK channels in WT mice increased dendritic excitability and EPSP-spike coupling, mimicking the phenotype in A657T mice and suggesting a causative role for attenuated SK activity in aberrant excitability observed in the mutant mice. These findings demonstrate that a disease-associated missense mutation in GRIK2 leads to altered signaling through neuronal KARs, pleiotropic effects on neuronal and dendritic excitability, and implicate these processes in neuropathology in patients with genetic NDDs.SIGNIFICANCE STATEMENT Damaging mutations in genes encoding synaptic proteins have been identified in various neurodevelopmental disorders, but the functional consequences at the cellular and circuit level remain elusive. By generating a novel knock-in mutant mouse, this study examined the role of a pathogenic mutation in the GluK2 kainate receptor (KAR) subunit, a subclass of ionotropic glutamate receptors. Analyses of hippocampal CA3 pyramidal neurons determined elevated action potential firing because of an increase in dendritic excitability. Increased dendritic excitability was attributable to reduced activity of a Ca2+ activated K+ channel. These results indicate that a pathogenic KAR mutation results in dysregulation of dendritic K+ channels, which leads to an increase in synaptic integration and backpropagation of action potentials into distal dendrites.