Firing Rate Research Articles

GABAergic neurons in the central amygdala promote emergence from isoflurane anesthesia in mice.

Recent evidence indicates that general anesthesia and sleep-wake behavior share some overlapping neural substrates. GABAergic neurons in the central amygdala (CeA) have a high firing rate during wakefulness and play a role in regulating arousal-related behaviors. The objective of this study is to investigate whether CeA GABAergic neurons participate in the regulation of isoflurane general anesthesia and uncover the underlying neural circuitry. Fiber photometry recording was used to determine the changes in calcium signals of CeA GABAergic neurons during isoflurane anesthesia in Vgat-Cre mice. Chemogenetic and optogenetic approaches were used to manipulate the activity of CeA GABAergic neurons, and a righting reflex test was used to determine the induction and emergence from isoflurane anesthesia. Cortical electroencephalogram (EEG) recording was used to assess the changes in EEG spectral power and burst-suppression ratio during 0.8% and 1.4% isoflurane anesthesia, respectively. Both male and female mice were used in this study. The calcium signals of CeA GABAergic neurons decreased during the induction of isoflurane anesthesia and was restored during the emergence. Chemogenetic activation of CeA GABAergic neurons delayed induction time (mean ± SD, vehicle vs. clozapine-N-oxide: 58.75±5.42 s vs. 67.63±5.01 s; n=8, P=0.0017) and shortened emergence time (385.50±66.26 s vs. 214.60±40.21 s; n=8, P=0.0017) from isoflurane anesthesia. Optogenetic activation of CeA GABAergic neurons produced a similar effect. Furthermore, optogenetic activation decreased EEG delta power (Pre-stim vs. Stim: 46.63%±4.40% vs. 34.16%±6.47%; n=8, P=0.0195) and burst-suppression ratio (83.39%±5.15% vs. 52.60%±12.98%; n=8, P=0.0002). Moreover, optogenetic stimulation of terminals of CeA GABAergic neurons in the basal forebrain (BF) also promoted cortical activation and accelerated behavioral emergence from isoflurane anesthesia. Our results suggest that CeA GABAergic neurons play a role in general anesthesia regulation, which facilitates behavioral and cortical emergence from isoflurane anesthesia through the GABAergic CeA-BF pathway.

A complex acoustical environment during development enhances auditory perception and coding efficiency in the zebra finch.

The statistics of the sensory inputs animals experience during postnatal development shape cortical circuits and their functional properties, but most studies examining experience-dependent plasticity in the auditory system has employed artificial stimuli with limited relevance to acoustic communication. Here, we examined how the natural social-acoustical environment experienced by zebra finches, a social songbird that breeds in large colonies, influences the development of auditory perception and the underlying auditory cortical circuits. Compared to birds raised in a more impoverished environment, colony-reared birds were better at recognizing songs of other zebra finches and had higher firing rates in the avian homolog to auditory cortex, along with changes to functional connectivity that resulted in more efficient and robust coding of conspecific song.

Emerging many-to-one weighted mapping in hippocampus-amygdala network underlies memory formation

Memories are crucial for daily life, yet the network-level organizing principles governing neural representations of experiences remain unknown. Employing dual-site in vivo recording in freely behaving male mice, here we show that hippocampal dorsal CA1 (dCA1) and basolateral amygdala (BLA) utilize distinct coding strategies for novel experiences. A small assembly of BLA neurons emerged active during memory acquisition and persisted through consolidation, whereas most dCA1 neurons were engaged in both processes. Machine learning decoding revealed that dCA1 population spikes predicted BLA assembly firing rate, suggesting that most dCA1 neurons concurrently index an episodic event by rapidly establishing weighted communication with a specific BLA assembly – a process we term “many-to-one weighted mapping.” We also found that dCA1 reactivations preceded BLA assembly activity preferably during elongated and enlarged dCA1 ripples. Using a closed-loop strategy, we demonstrated that suppressing BLA activity after large dCA1 ripples impaired memory. These findings highlight a many-to-one weighted mapping mechanism underlying both the acquisition and consolidation of new memories.

In Vivo Expression of an SCA27A-linked FGF14 Mutation Results in Haploinsufficiency and Impaired Firing of Cerebellar Purkinje Neurons.

Autosomal dominant mutations in FGF14 , which encodes intracellular fibroblast growth factor 14 (iFGF14), underlie spinocerebellar ataxia type 27A (SCA27A), a devastating multisystem disorder resulting in progressive deficits in motor coordination and cognitive function. Mice lacking iFGF14 ( Fgf14 -/- ) exhibit similar phenotypes, which have been linked to iFGF14-mediated modulation of the voltage-gated sodium (Nav) channels that control the high frequency repetitive firing of Purkinje neurons, the main output neurons of the cerebellar cortex. To investigate the pathophysiological mechanisms underlying SCA27A, we developed a targeted knock-in strategy to introduce the first point mutation identified in FGF14 into the mouse Fgf14 locus ( Fgf14 F145S ), we determined the impact of in vivo expression of the mutant Fgf14 F145S allele on the motor performance of adult animals and on the firing properties of mature Purkinje neurons in acute cerebellar slices. Electrophysiological experiments revealed that repetitive firing rates are attenuated in adult Fgf14 F145S/+ cerebellar Purkinje neurons, attributed to a hyperpolarizing shift in the voltage-dependence of steady-state inactivation of Nav channels. More severe effects on firing properties and Nav channel inactivation were observed in homozygous Fgf14 F145S/F145S Purkinje neurons. Interestingly, the electrophysiological phenotypes identified in adult Fgf14 F145S/+ and Fgf14 F145S/F145S cerebellar Purkinje neurons mirror those observed in heterozygous Fgf14 +/- and homozygous Fgf14 -/- Purkinje neurons, respectively, suggesting that the mutation results in the loss of the iFGF14 protein. Western blot analysis of lysates from adult heterozygous Fgf14 F145S/+ and homozygous Fgf14 F145S/F145S animals revealed reduced or undetectable, respectively, iFGF14 expression, supporting the hypothesis that the mutant allele results in loss of the iFGF14 protein and that haploinsufficiency underlies SCA27A neurological phenotypes.

Arginine vasopressin induces analgesic effects and inhibits pyramidal cells in the anterior cingulate cortex in spared nerve injured mice.

Neuropathic pain (NP) is a severe disease caused by a primary disease or lesion affecting the somatosensory nervous system. It`s reported that NP is related to the increased activity of glutamatergic pyramidal cells and changed neural oscillations in the anterior cingulate cortex (ACC). Arginine vasopressin (AVP), a neurohypophyseal hormone, has been shown to cause pain-alleviating effects when applied to peripheral system. However, the extent to which, and the mechanisms by which, AVP induces analgesic effects in the central nervous system remain unclear. In the present study, we observed that intranasal delivery of AVP inhibited mechanical pain, thermal pain and spontaneous pain sensitivity in mice with spared nerve injury. Meanwhile, AVP application exclusively reduced the FOS expression in the pyramidal cells but not interneurons in the ACC. In vivo electrophysiological recording of the ACC further showed that AVP application not only inhibited the theta oscillation in local field potential analysis, but also reduced the firing rate of spikes of pyramidal cells in the ACC in neuropathic pain mice. In summary, AVP induce analgesic effects by inhibiting neural theta oscillations and the spiking of pyramidal cells of the ACC in mice with neuropathic pain, which should provide new potential noninvasive methods for clinical treatment of chronic pain.

Impairment of Neuronal Activity in the Dorsolateral Prefrontal Cortex Occurs Early in Parkinsonism.

Parkinson's disease (PD) is often characterized by altered rates and patterns of neuronal activity in the sensorimotor regions of the basal ganglia thalamocortical network. Little is known, however, regarding how neuronal activity in the executive control network of the brain changes in the parkinsonian condition. Investigate the impact of parkinsonism on neuronal activity in the dorsolateral prefrontal cortex (DLPFC), a key region in executive control, during a go/nogo reaching task. Using a within-subject design, single and multi-unit neuronal activity was recorded in the DLPFC of a nonhuman primate before and after the induction of mild parkinsonism using the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Coincident with development of mild parkinsonian motor signs, there was a marked reduction in the percentage of DLPFC cells with significant task-related firing rate modulation during go and nogo conditions. These results suggest that DLPFC dysfunction may occur early in parkinsonism and contribute to cognitive impairments and disrupted executive function often observed in PD patients.

Prior cocaine use diminishes encoding of latent information by orbitofrontal, but not medial, prefrontal ensembles.

Maladaptive decision-making is a hallmark of substance use disorders (SUDs), though how drugs of abuse alter neural representations supporting adaptive behavior remains poorly understood. Past studies show that the orbitofrontal (OFC) and prelimbic (PL) cortices are important for decision-making, tracking both task-relevant and latent information. However, previous studies have focused on how drugs of abuse impact the firing rates of individual units. More work at the ensemble level is necessary to accurately characterize potential drug-induced changes. Using single-unit recordings in rats during a multidimensional decision-making task and then applying population- and ensemble-level analyses, we show that prior use of cocaine altered the strength and structure of task-relevant and latent representations in the OFC, changes relatable to suboptimal decision-making in this and perhaps other settings. These data expand our understanding of the neuropathological underpinnings of maladaptive decision-making in SUDs, potentially enabling enhanced future treatment strategies.

Integration of rate and phase codes by hippocampal cell-assemblies supports flexible encoding of spatiotemporal context.

Spatial information is encoded by location-dependent hippocampal place cell firing rates and sub-second, rhythmic entrainment of spike times. These rate and temporal codes have primarily been characterized in low-dimensional environments under limited cognitive demands; but how is coding configured in complex environments when individual place cells signal several locations, individual locations contribute to multiple routes and functional demands vary? Quantifying CA1 population dynamics of male rats during a decision-making task, here we show that the phase of individual place cells' spikes relative to the local theta rhythm shifts to differentiate activity in different place fields. Theta phase coding also disambiguates repeated visits to the same location during different routes, particularly preceding spatial decisions. Using unsupervised detection of cell assemblies alongside theoretical simulation, we show that integrating rate and phase coding mechanisms dynamically recruits units to different assemblies, generating spiking sequences that disambiguate episodes of experience and multiplexing spatial information with cognitive context.

Theoretical framework for learning through structural plasticity

A growing body of research indicates that structural plasticity mechanisms are crucial for learning and memory consolidation. Starting from a simple phenomenological model, we exploit a mean-field approach to develop a theoretical framework of learning through this kind of plasticity, capable of taking into account several features of the connectivity and pattern of activity of biological neural networks, including probability distributions of neuron firing rates, selectivity of the responses of single neurons to multiple stimuli, probabilistic connection rules, and noisy stimuli. More importantly, it describes the effects of stabilization, pruning, and reorganization of synaptic connections. This framework is used to compute the values of some relevant quantities used to characterize the learning and memory capabilities of the neuronal network in training and testing procedures as the number of training patterns and other model parameters vary. The results are then compared with those obtained through simulations with firing-rate-based neuronal network models. Published by the American Physical Society 2024

On the rate-limiting dynamics of force development in muscle.

Skeletal muscles produce forces relatively slowly compared with the action potentials that excite them. The dynamics of force production are governed by multiple processes, such as calcium activation, cycling of cross-bridges between myofilaments, and contraction against elastic tissues and the body. These processes have been included piecemeal in some muscle models, but not integrated to reveal which are the most rate limiting. We therefore examined their integrative contributions to force development in two conventional types of muscle models: Hill-type and cross-bridge. We found that no combination of these processes can self-consistently reproduce classic data such as twitch and tetanus. Rather, additional dynamics are needed following calcium activation and facilitating cross-bridge cycling, such as for cooperative myofilament interaction and reconfiguration. We provisionally lump such processes into a simple first-order model of 'force facilitation dynamics' that integrate into a cross-bridge-type muscle model. The proposed model self-consistently reproduces force development for a range of excitations including twitch and tetanus and electromyography-to-force curves. The model's step response reveals relatively small timing contributions of calcium activation (3%), cross-bridge cycling (3%) and contraction (27%) to overall force development of human quadriceps, with the remainder (67%) explained by force facilitation. The same set of model parameters predicts the change in force magnitude (gain) and timing (phase delay) as a function of excitatory firing rate, or as a function of cyclic contraction frequency. Although experiments are necessary to reveal the dynamics of muscle, integrative models are useful for identifying the main rate-limiting processes.

Nanomagnetic Guidance Shapes the Structure-Function Relationship of Developing Cortical Networks.

In this study, we implement large-scale nanomagnetic guidance on cortical neurons to guide dissociated neuronal networks during development. Cortical networks cultured over microelectrode arrays were exposed to functionalized magnetic nanoparticles, followed by magnetic field exposure to guide neurites over 14 days in vitro. Immunofluorescence of the axonal protein Tau revealed a greater number of neurites that were longer and aligned with the nanomagnetic force relative to nonguided networks. This was further confirmed through brightfield imaging on the microelectrode arrays during development. Spontaneous electrophysiological recordings revealed that the guided networks exhibited increased firing rates and frequency in force-aligned connectivity identified through Granger Causality. Applying this methodology across networks with nonuniform force directions increased local activity in target regions, identified as regions in the direction of the nanomagnetic force. Altogether, these results demonstrate that nanomagnetic forces guide the structure and function of dissociated cortical neuron networks at the millimeter scale.

Neuronal sequences in population bursts encode information in human cortex.

Neural coding has traditionally been examined through changes in firing rates and latencies in response to different stimuli1-5. However, populations of neurons can also exhibit transient bursts of spiking activity, wherein neurons fire in a specific temporal order or sequence6-8. The human brain may utilize these neuronal sequences within population bursts to efficiently represent information9-12, thereby complementing the well-known neural code based on spike rate or latency. Here we examined this possibility by recording the spiking activity of populations of single units in the human anterior temporal lobe as eight participants performed a visual categorization task. We find that population spiking activity organizes into bursts during the task. The temporal order of spiking across the activated units within each burst varies across stimulus categories, creating unique stereotypical sequences for individual categories as well as for individual exemplars within a category. The information conveyed by the temporal order of spiking activity is separable from and complements the information conveyed by the units' spike rates or latencies following stimulus onset. Collectively, our data provide evidence that the human brain contains a complementary code based on the neuronal sequence within bursts of population spiking to represent information.

Inducing post-activation potentiation alters human motor unit behavior of the elbow extensors during unconstrained velocity contractions.

The purpose was to test whether inducing post-activation potentiation (PAP) altered motor unit (MU) activity during dynamic isotonic contractions. From 12 participants (3 females), 39 MUs were recorded from the anconeus (n=31) and lateral triceps brachii (n=8) with fine-wire electrodes during elbow extensions at 50 and 75% of peak power with, and without PAP. To induce PAP participants produced a 2s ramp conditioning contraction (CC) up to maximal isometric elbow extension with a 3s hold. Following the CC (~2s), independent electrical stimulation to the triceps and anconeus showed twitch torques were potentiated by 84 and 66%, respectively, (both p<0.001). Compared to baseline (i.e., without PAP), at both intensities (50 and 75%) PAP increased MU recruitment thresholds (40% and 80%, p<0.001) with lowered mean MU rates (-20 and -26%), and instantaneous rates at recruitment threshold (-26 and -25%) (all p<0.001). Firing rates increased 20% (p<0.001) from 50 to 75% power, but rates during potentiated contractions targeting 75% were lower than baseline at 50% (-10%, p<0.001). Dynamic contractions provide a more functional paradigm to assess MU activity with PAP and showed larger effects across a wider range of contractile intensities compared to previously described isometric tasks. Findings indicate that peripheral feedback from the potentiated muscle is likely not the primary mechanism in modifying MU behaviors as changes occurred at recruitment which is relatively insensitive to afferent feedback. Therefore, MU activity during dynamic contractions is responsive to activation history force potentiation and can make compensatory adjustments to optimize contractile output.

Neuronal activity in the ventral tegmental area during goal-directed navigation recorded by low-curvature microelectrode arrays

Navigating toward destinations with rewards is a common behavior among animals. The ventral tegmental area (VTA) has been shown to be responsible for reward coding and reward cue learning, and its response to other variables, such as kinematics, has also been increasingly studied. These findings suggest a potential relationship between animal navigation behavior and VTA activity. However, the deep location and small volume of the VTA pose significant challenges to the precision of electrode implantation, increasing the uncertainty of measurement results during animal navigation and thus limiting research on the role of the VTA in goal-directed navigation. To address this gap, we innovatively designed and fabricated low-curvature microelectrode arrays (MEAs) via a novel backside dry etching technique to release residual stress. Histological verification confirmed that low-curvature MEAs indeed improved electrode implantation precision. These low-curvature MEAs were subsequently implanted into the VTA of the rats to observe their electrophysiological activity in a freely chosen modified T-maze. The results of the behavioral experiments revealed that the rats could quickly learn the reward probability corresponding to the left and right paths and that VTA neurons were deeply involved in goal-directed navigation. Compared with those in no-reward trials, VTA neurons in reward trials presented a significantly greater firing rate and larger local field potential (LFP) amplitude during the reward-consuming period. Notably, we discovered place fields mapped by VTA neurons, which disappeared or were reconstructed with changes in the path–outcome relationship. These results provide new insights into the VTA and its role in goal-directed navigation. Our designed and fabricated low-curvature microelectrode arrays can serve as a new device for precise deep brain implantation in the future.

Pallidal neuronal activity in Gilles de la Tourette syndrome and dystonic patients: A comparative study.

Gilles de la Tourette syndrome (GTS) and dystonia (DYS) are both hyperkinetic movement disorders effectively treated by deep brain stimulation (DBS) of the internal part of the globus pallidus (GPi). In this study, we compared single-neuron activity in the GPi between 18 GTS patients (with an average of 41 cells per patient) and 17 DYS patients (with an average of 54 cells per patient), all of whom underwent bilateral pallidal stimulation surgery, under general anesthesia or while awake at rest. We found no significant differences in GPi neuronal activity characteristics between patients operated on under general anesthesia versus those who were awake, irrespective of their diagnosis (GTS or DYS). We found higher firing rates, firing rate in bursts, pause duration and interspike interval coefficient of variation in GTS patients compared to DYS patients. On the opposite, we found higher number of pauses and bursts frequency in DYS patients. Lastly, we found a higher proportion of GPi oscillatory activities in DYS compared to GTS patients, with predominant activity within the low-frequency band (theta/alpha) in both patient groups. These findings underscore the complex relationship between the different neuronal discharge characteristic such as oscillatory or bursting activity within the GPi in shaping the clinical phenotypes of hyperkinetic disorders. Further research is warranted to deepen our understanding of how neuronal patterns are transmitted within deep brain structures and to develop strategies aimed at normalizing these pathological activities, by refining DBS techniques to enhance treatment efficacy and individual outcomes.

A preserved neural code for temporal order between memory formation and recall in the human medial temporal lobe.

Temporal memory enables us to remember the temporal order of events happening in our life. The human medial temporal lobe (MTL) appears to contain neural representations supporting temporal memory formation, but the cellular mechanisms that preserve temporal order information for recall are largely unknown. Here, we examined whether human MTL neuronal activity represents the temporal position of events during memory formation and recall, using invasive single and multi-unit recordings in human epilepsy patients (n = 19). Participants freely navigated a virtual environment in order to explore and remember locations and temporal positions of objects. During each exploration period, they sequentially encountered two or three different objects, placed in different locations. This allowed us to examine single- and multi-unit neuronal firing rates (FR) as a function of the temporal position the objects were presented in. We found that a significant number of multi-units and single-units in various MTL regions including the hippocampus showed selectivity to the temporal position of objects during the exploration period. During recall, patients were asked to indicate which one of two objects from the same trial was found latter. Neural firing rates during recall showed a selectivity supporting recall of temporal positions. Interestingly, most of the selective single-units that stayed selective during encoding and recall preserved their temporal position preference. Our results thus suggest that neuronal activity in the human MTL contains a preserved neural code for temporal order in memory formation and recall.

Single-neuron representations of odours in the human brain

Olfaction is a fundamental sensory modality that guides animal and human behaviour1,2. However, the underlying neural processes of human olfaction are still poorly understood at the fundamental—that is, the single-neuron—level. Here we report recordings of single-neuron activity in the piriform cortex and medial temporal lobe in awake humans performing an odour rating and identification task. We identified odour-modulated neurons within the piriform cortex, amygdala, entorhinal cortex and hippocampus. In each of these regions, neuronal firing accurately encodes odour identity. Notably, repeated odour presentations reduce response firing rates, demonstrating central repetition suppression and habituation. Different medial temporal lobe regions have distinct roles in odour processing, with amygdala neurons encoding subjective odour valence, and hippocampal neurons predicting behavioural odour identification performance. Whereas piriform neurons preferably encode chemical odour identity, hippocampal activity reflects subjective odour perception. Critically, we identify that piriform cortex neurons reliably encode odour-related images, supporting a multimodal role of the human piriform cortex. We also observe marked cross-modal coding of both odours and images, especially in the amygdala and piriform cortex. Moreover, we identify neurons that respond to semantically coherent odour and image information, demonstrating conceptual coding schemes in olfaction. Our results bridge the long-standing gap between animal models and non-invasive human studies and advance our understanding of odour processing in the human brain by identifying neuronal odour-coding principles, regional functional differences and cross-modal integration.

Fractional-order spike-timing-dependent gradient descent for multi-layer spiking neural networks

Accumulated detailed knowledge about the neuronal activities in human brains has brought more attention to bio-inspired spiking neural networks (SNNs). In contrast to non-spiking deep neural networks (DNNs), SNNs can encode and transmit spatiotemporal information more efficiently by exploiting biologically realistic and low-power event-driven neuromorphic architectures. However, the supervised learning of SNNs still remains a challenge because the spike-timing-dependent plasticity (STDP) of connected spiking neurons is difficult to implement and interpret in existing backpropagation learning schemes. This paper proposes a fractional-order spike-timing-dependent gradient descent (FO-STDGD) learning model by considering a derived nonlinear activation function that describes the relationship between the quasi-instantaneous firing rate and the temporal membrane potentials of nonleaky integrate-and-fire neurons. The training strategy can be generalized to any fractional orders between 0 and 2 since the FO-STDGD incorporates the fractional gradient descent method into the calculation of spike-timing-dependent loss gradients. The proposed FO-STDGD model is tested on the MNIST and DVS128 Gesture datasets and its accuracy under different network structure and fractional orders is analyzed. It can be found that the classification accuracy increases as the fractional order increases, and specifically, the case of fractional order 1.9 improves by 155 % relative to the case of fractional order 1 (traditional gradient descent). In addition, our scheme demonstrates the state-of-the-art computational efficacy for the same SNN structure and training epochs.

A new approach for neural decoding by inspiring of hyperdimensional computing for implantable intra-cortical BMIs

In the field of Brain Machine Interface (BMI), the process of translating motor intention into a machine command is denoted as decoding. However, despite recent advancements, decoding remains a formidable challenge within BMI. The utilization of current decoding algorithms in the field of BMI often involves computational complexity and requires the use of computers. This is primarily due to the reliance on mathematical models to address the decoding issue and perform subsequent output calculations. Unfortunately, computers are not feasible for implantable BMI systems due to their size and power consumption. To address this predicament, this study proposes a pioneering approach inspired by hyperdimensional computing. This approach first involves identifying the pattern of each stimulus by considering the normal firing rate distribution of each neuron. Subsequently, the newly observed firing pattern for each input is compared with the patterns detected at each moment for each neuron. The algorithm, which shares similarities with hyperdimensional computing, identifies the most similar pattern as the final output. This approach reduces the dependence on mathematical models. The efficacy of this method is assessed through the utilization of an authentic dataset acquired from the Frontal Eye Field (FEF) of two male rhesus monkeys. The output space encompasses eight possible angles. The results demonstrate an accuracy rate of 51.5% while exhibiting significantly low computational complexity, involving a mere 2050 adder operators. Furthermore, the proposed algorithm is implemented on a field-programmable gate array (FPGA) and as an ASIC designe in a standard CMOS 180 nm technology, underscoring its suitability for real-time implantable BMI applications. The implementation required only 2.3 Kbytes of RAM, occupied an area of 2.2 mm2, and consumed 9.32 µW at a 1.8 V power supply. Consequently, the proposed solution represents an accurate, low computational complexity, hardware-friendly, and real-time approach.

Heterozygous KCNJ10 Variants Affecting Kir4.1 Channel Cause Paroxysmal Kinesigenic Dyskinesia.

More than 60% of paroxysmal kinesigenic dyskinesia (PKD) cases are of uncertain variants. The aim was to elucidate novel genetic contribution to PKD. A total of 476 probands with uncertain genetic causes were enrolled for whole-exome sequencing. A method of case-control analysis was applied to identify the candidate genes. Whole-cell patch-clamp recording was applied to verify the electrophysiological impact of the identified variants. A mouse model with cerebellar heterozygous knockout of the candidate gene was developed via adeno-associated virus injection, and dystonia-like phenotype inducement and rotarod tests were performed. In vivo multiunit electrical recording was applied to investigate the change in neural excitability in knockout mice. Heterozygous variants of potassium inwardly rectifying channel subfamily J member 10 (KCNJ10) clustered in PKD patients were compared with those in the control groups. Fifteen variants were detected in 16 of 522 probands (frequency = 3.07%). Patients with KCNJ10 variants tended to have a milder manifestation compared to those with PRRT2 (proline-rich transmembrane protein 2) variants. KCNJ10 variants partially altered the transmembrane location of inwardly rectifying potassium channel 4.1 (Kir4.1). The Kcnj10 expression is consistent with the natural course of PKD. Variants resulted in different degrees of reduction in cell Kir4.1 currents, and mice with heterozygous conditional knockout of Kcnj10 in the cerebellum presented dystonic posture, together with poor motor coordination and motor learning ability in rotarod tests. The firing rate of deep cerebellar nuclei was significantly elevated in Kcnj10-cKO mice. We identified heterozygous variants of KCNJ10 in PKD. Impaired function of Kir4.1 might lead to abnormal neuronal excitability, which attributed to PKD. © 2024 International Parkinson and Movement Disorder Society.