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• Biologically Plausible Learning via Bidirectional Spike-Based Distillation
  Developing biologically plausible learning algorithms that can achieve performance comparable to error backpropagation remains a longstanding challenge. Existing approaches often compromise biological plausibility by entirely avoiding the use of spikes for err…
  datacite Lv, Changze, Wang, Yifei, Zhang, Yanxun, Lu, Yiyang 等 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data
  Characterizing the relationship between neural population activity and behavioral data is a central goal of neuroscience. While latent variable models (LVMs) are successful in describing high-dimensional time-series data, they are typically only designed for a…
  datacite Gondur, Rabia, Sikandar, Usama Bin, Schaffer, Evan, Aoi, Mikio Christian 等 2023 置信度 0.66 Machine Learning (cs.LG)Neurons and Cognition (q-bio.NC)FOS: Computer and information sciencesFOS: Computer and information sciencesFOS: Biological sciences
• Algorithm-Hardware Co-Design for Artificial Intelligence: From Energy-Efficient Edge Processing to High-Performance GPU Acceleration
  Deep learning has become a cornerstone of modern artificial intelligence (AI), driving transformative advances in fields such as computer vision, natural language processing, and generative models for text and images. However, as the complexity of neural netwo…
  datacite Abillama, Pierre 2025 置信度 0.66 Domain-Specific Hardware AccelerationNeural NetworksLow-Rank CompressionQuantizationStructured Sparsity
• Wandering around: A bioinspired approach to visual attention through object motion sensitivity
  Active vision enables dynamic visual perception, offering an alternative to static feedforward architectures in computer vision, which rely on large datasets and high computational resources. Biological selective attention mechanisms allow agents to focus on s…
  datacite D'Angelo, Giulia, Clerico, Victoria, Bartolozzi, Chiara, Hoffmann, Matej 等 2025 置信度 0.66 Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesFOS: Computer and information sciences
• A brain-constrained neural model of cognition and language with NEST: transitioning from the Felix framework
  We introduce a brain-constrained neurocomputational model designed to simulate higher cognitive functions of the human brain, implemented using NEST, a widely used open-source simulator optimised for high-performance spiking neural network simulations. Previou…
  datacite Carriere, Maxime, Dobler, Fynn, Plesser, Hans Ekkehard, Feledyn, Agata 等 2026 置信度 0.66 Brain-constrained modelLanguage modelHebbian learningNESTNeural network
• Activation-Scaled ANN-to-SNN Conversion with SNN Guardrail: A Unified Framework for AI Interpretability, Hallucination Detection, Real-Time Adversarial Defense, Neural Healing, Brain State Imaging, Hallucination Anatomy, and the Canary Head Paradigm (v9)
  I present a unified framework that extends ANN-to-SNN conversion beyond efficiency optimization to enable novel AI interpretability analysis, real-time adversarial defense, autonomous neural healing, brain state imaging, real-time hallucination anatomy, and th…
  datacite Funasaki, Hiroto 2026 置信度 0.66 spiking neural networksANN-to-SNN conversionneuromorphic computingdeep learningHybrid Architecture
• SynSacc: A Blender-to-V2E Pipeline for Synthetic Neuromorphic Eye-Movement Data and Sim-to-Real Spiking Model Training
  The study of eye movements, particularly saccades and fixations, are fundamental to understanding the mechanisms of human cognition and perception. Accurate classification of these movements requires sensing technologies capable of capturing rapid dynamics wit…
  datacite Iddrisu, Khadija, Shariff, Waseem, Little, Suzanne, OConnor, Noel 2026 置信度 0.66 Computer Vision and Pattern Recognition (cs.CV)FOS: Computer and information sciencesFOS: Computer and information sciences
• Stochastic Spiking Neuron Based SNN Can be Inherently Bayesian
  Uncertainty in biological neural systems appears to be computationally beneficial rather than detrimental. However, in neuromorphic computing systems, device variability often limits performance, including accuracy and efficiency. In this work, we propose a sp…
  datacite Zheng, Huannan, Liu, Jingli, Yang, Kezhou 2026 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Artificial Intelligence (cs.AI)Computer Vision and Pattern Recognition (cs.CV)Emerging Technologies (cs.ET)FOS: Computer and information sciences
• Learning Alzheimer's Disease Signatures by bridging EEG with Spiking Neural Networks and Biophysical Simulations
  As the prevalence of Alzheimer's disease (AD) rises, improving mechanistic insight from non-invasive biomarkers is increasingly critical. Recent work suggests that circuit-level brain alterations manifest as changes in electroencephalography (EEG) spectral fea…
  datacite Mamoń, Szymon, Talanov, Max, Crimi, Alessandro 2026 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Artificial Intelligence (cs.AI)FOS: Computer and information sciencesFOS: Computer and information sciences
• Towards neuromorphic visual SLAM: A spiking neural network for efficient pose estimation and loop closure based on event camera data
  The need for effective Simultaneous Localisation and Mapping (SLAM) solutions has been pivotal across a wide range of applications, including autonomous vehicles, industrial robotics, and mobile service platforms where accurate localisation and environmental p…
  datacite Tenzin, Sangay 2026 置信度 0.66
• FeNN-DMA: A RISC-V SoC for SNN acceleration
  Spiking Neural Networks (SNNs) are a promising, energy-efficient alternative to standard Artificial Neural Networks (ANNs) and are particularly well-suited to spatio-temporal tasks such as keyword spotting and video classification. However, SNNs have a much lo…
  datacite Aizaz, Zainab, Knight, James C., Nowotny, Thomas 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Artificial Intelligence (cs.AI)Hardware Architecture (cs.AR)FOS: Computer and information sciencesFOS: Computer and information sciences
• A neuromorphic model of the insect visual system for natural image processing
  Insect vision supports complex behaviors including associative learning, navigation, and object detection, and has long motivated computational models for understanding biological visual processing. However, many contemporary models prioritize task performance…
  datacite Hines, Adam D., Nordström, Karin, Barron, Andrew B. 2026 置信度 0.66 Computer Vision and Pattern Recognition (cs.CV)Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• Activation-Scaled ANN-to-SNN Conversion with SNN Guardrail: A Unified Framework for AI Interpretability, Hallucination Detection, Real-Time Adversarial Defense, Neural Healing, Brain State Imaging, and Real-Time Hallucination Anatomy (v8)
  I present a unified framework that extends ANN-to-SNN conversion beyond efficiency optimization to enable novel AI interpretability analysis, real-time adversarial defense, autonomous neural healing, brain state imaging, and real-time hallucination anatomy. My…
  datacite Funasaki, Hiroto 2026 置信度 0.66 spiking neural networksANN-to-SNN conversionneuromorphic computingdeep learningHybrid Architecture
• Network models incorporating chloride dynamics predict optimal strategies for terminating status epilepticus
  Status epilepticus (SE), seizures lasting beyond five minutes, is a medical emergency commonly treated with benzodiazepines which enhance GABA receptor (GABAR) conductance. Despite widespread use, benzodiazepines fail in over one-third of patients, potentially…
  datacite Currin, Christopher B, Burman, Richard J, Fedele, Tommaso, Ramantani, Georgia 等 2025 置信度 0.66 610 Medicine & health
• Geometric parallel resonance chip.(neuromorphic/holographic/resonance)
  A novel chip architecture implementing geometric parallel resonance for neuromorphic inference with integrated hardware-level hallucination detection. Unlike conventional neural networks that compute sequentially, ilEcho Genesis activates all connections simul…
  datacite Leaf, Alexander "Eli" McVey, ilEcho Genesis 2026 置信度 0.66 geometric parallel resonance neuromorphic computing holographic memory anti-hallucination UACIL resonance computing spiking neural network hardware safety Leaf's Law pattern persistence AI safety edge inference low-latency inference
• Spiking Neural Belief Propagation Decoder for LDPC Codes with Small Variable Node Degrees
  Spiking neural networks (SNNs) promise energy-efficient data processing by imitating the event-based behavior of biological neurons. In previous work, we introduced the enlarge-likelihood-each-notable-amplitude spiking-neural-network (ELENA-SNN) decoder, a nov…
  datacite Bank, Alexander von, Edelmann, Eike-Manuel, Mandelbaum, Jonathan, Schmalen, Laurent 2024 置信度 0.66 BP DecodingLDPC codesregular LDPC codesspiking neural networks
• Neural Dynamics: A collection of educational Python scripts
  🚀 Release v1.0.0 This is the initial release of the Neural Dynamics repository, featuring a comprehensive collection of educational Python scripts for computational neuroscience. The release includes tutorials on using the NEST Simulator, as well as standalon…
  datacite Fabrizio Musacchio 2026 置信度 0.66
• NeuroGuard-V2X : A Neuromorphic Edge Processing Architecture for Privacy-Preserving Network Monitoring in Connected Vehicles
  This paper introduces NeuroGuard-V2X, a privacy-preserving network monitoring architecture for connected vehicles based on neuromorphic edge processing. By deploying event-driven spiking neural networks directly on vehicles, the proposed system analyzes tempor…
  datacite Mohammad Zahangir, Alam 2026 置信度 0.66
• NeuroGuard-V2X : A Neuromorphic Edge Processing Architecture for Privacy-Preserving Network Monitoring in Connected Vehicles
  This paper introduces NeuroGuard-V2X, a privacy-preserving network monitoring architecture for connected vehicles based on neuromorphic edge processing. By deploying event-driven spiking neural networks directly on vehicles, the proposed system analyzes tempor…
  datacite Mohammad Zahangir, Alam 2026 置信度 0.66
• Stable recurrent dynamics in heterogeneous neuromorphic computing systems using excitatory and inhibitory plasticity
  Many neural computations emerge from self-sustained patterns of activity in recurrent neural circuits, which rely on balanced excitation and inhibition. Neuromorphic electronic circuits represent a promising approach for implementing the brain's computational …
  datacite Soldado-Magraner, Saray, Sorbaro, Martino, Laje, Rodrigo, Buonomano, Dean V 等 2025 置信度 0.66 570 Life sciences; biology
• Spiking Neural-Invariant Kalman Fusion for Accurate Localization Using Low-Cost IMUs
  Low-cost inertial measurement units (IMUs) are widely utilized in mobile robot localization due to their affordability and ease of integration. However, their complex, nonlinear, and time-varying noise characteristics often lead to significant degradation in l…
  datacite Liu, Yaohua, Xu, Qiao, Ou, Binkai 2026 置信度 0.66 Robotics (cs.RO)FOS: Computer and information sciencesFOS: Computer and information sciences
• Spiking Neural Networks for Continuous Control via End-to-End Model-Based Learning
  Despite recent progress in training spiking neural networks (SNNs) for classification, their application to continuous motor control remains limited. Here, we demonstrate that fully spiking architectures can be trained end-to-end to control robotic arms with m…
  datacite Huebotter, Justus, Lanillos, Pablo, van Gerven, Marcel, Thill, Serge 2025 置信度 0.66 Robotics (cs.RO)Artificial Intelligence (cs.AI)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Pyramidal Hybrid Neural Network Framework (BrainIAc_v1.0) : Technical Documentation and Experimental Results
  Project Overview Pre-publication technical documentation and experimental validation results for a hybrid neural network framework enabling gradient-based training of heterogeneous spiking neuron populations. Description/Summary: Key Features: Mixed neuron tra…
  datacite Vallois, Théo Henock André 2025 置信度 0.66 spiking neural networksneuromorphic computinghybrid neural networksgradient descentizhikevich neurons
• Pyramidal Hybrid Neural Network Framework (BrainIAc_v1.0) : Technical Documentation and Experimental Results
  Project Overview Pre-publication technical documentation and experimental validation results for a hybrid neural network framework enabling gradient-based training of heterogeneous spiking neuron populations. Description/Summary: Key Features: Mixed neuron tra…
  datacite Vallois, Théo Henock André 2025 置信度 0.66 spiking neural networksneuromorphic computinghybrid neural networksgradient descentizhikevich neurons
• Physical Security of Emerging AI Hardware Accelerators: From Vulnerability to Countermeasures
  The widespread deployment of Artificial Intelligence (AI) at the edge has driven a paradigm shift toward domain-specific hardware accelerators. Emerging architectures-ranging from Analog Compute-in- Memory (CiM) and Non-Volatile Memory (NVM)-centric processors…
  datacite Sapui, Brojogopal 2026 置信度 0.66 AI acceleratorsedge-AIside channelfault injectioncountermeasures
• Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control
  Spiking Neural Networks (SNNs) offer low-latency and energy-efficient decision making on neuromorphic hardware, making them attractive for Reinforcement Learning (RL) in resource-constrained edge devices. However, most RL algorithms for continuous control are …
  datacite Xu, Zijie, Bu, Tong, Hao, Zecheng, Ding, Jianhao 等 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Energy-Efficient Neuromorphic Computing for Edge AI: A Framework with Adaptive Spiking Neural Networks and Hardware-Aware Optimization
  Edge AI applications increasingly require ultra-low-power, low-latency inference. Neuromorphic computing based on event-driven spiking neural networks (SNNs) offers an attractive path, but practical deployment on resource-constrained devices is limited by trai…
  datacite Imanov, Olaf Yunus Laitinen, Kulali, Derya Umut, Yilmaz, Taner, Erisken, Duygu 等 2026 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Emerging Technologies (cs.ET)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Spin splitting torque enabled artificial neuron with self-reset via synthetic antiferromagnetic coupling
  Spintronic artificial neurons are intriguing building blocks for energy efficient Neuromorphic Computing (NC). Nevertheless, most contemporary implementations rely on symmetry breaking external in plane magnetic fields (H_X) for neuron operation, which limits …
  datacite Sekh, Badsha, Rahaman, Hasibur, Verma, Ravi Shankar, Maddu, Ramu 等 2026 置信度 0.66 Applied Physics (physics.app-ph)FOS: Physical sciencesFOS: Physical sciences
• Parallel Training in Spiking Neural Networks
  The bio-inspired integrate-fire-reset mechanism of spiking neurons constitutes the foundation for efficient processing in Spiking Neural Networks (SNNs). Recent progress in large models demands that spiking neurons support highly parallel computation to scale …
  datacite Huang, Yanbin, Yao, Man, Pan, Yuqi, Lv, Changze 等 2026 置信度 0.66 Neural and Evolutionary Computing (cs.NE)FOS: Computer and information sciencesFOS: Computer and information sciences
• Recurrent models of orientation selectivity enable robust early-vision processing in mixed-signal neuromorphic hardware
  Mixed signal analog/digital neuromorphic circuits represent an ideal medium for reproducing bio-physically realistic dynamics of biological neural systems in real-time. However, similar to their biological counterparts, these circuits have limited resolution a…
  datacite Baruzzi, Valentina, Indiveri, Giacomo, Sabatini, Silvio P. 2025 置信度 0.66 570 Life sciences; biology
• Neuromorphic dreaming as a pathway to efficient learning in artificial agents
  The computational substrate of biological systems exhibits remarkable abilities to learn complex skills quickly and efficiently. Inspired by this, we implement model-based reinforcement learning using spiking neural networks directly on mixed-signal neuromorph…
  datacite Blakowski, Ingo, Zendrikov, Dmitrii, Indiveri, Giacomo, Capone, Cristiano 2025 置信度 0.66 570 Life sciences; biology
• Event driven neural network on a mixed signal neuromorphic processor for EEG based epileptic seizure detection
  Long-term monitoring of biomedical signals is essential for the modern clinical management of neurological conditions such as epilepsy. However, developing wearable systems that are able to monitor, analyze, and detect epileptic seizures with long-lasting oper…
  datacite Bartels, Jim, Gallou, Olympia, Ito, Hiroyuki, Cook, Matthew 等 2025 置信度 0.66 570 Life sciences; biology
• Scalable Construction of Spiking Neural Networks using up to thousands of GPUs archive
  Diverse scientific and engineering research areas deal with discrete, time-stamped changes in large systems of interacting delay differential equations. Simulating such complex systems at scale on high-performance computing clusters demands efficient managemen…
  datacite Tiddia, Gianmarco, Villamar, José, Golosio, Bruno, Pontisso, Luca 等 2025 置信度 0.66 spiking neural networkslarge-scale simulationsGPUexascale
• Training slow silicon neurons to control extremely fast robots with spiking reinforcement learning
  Air hockey demands split-second decisions at high puck velocities, a challenge we address with a compact network of spiking neurons running on a mixed-signal analog/digital neuromorphic processor. By co-designing hardware and learning algorithms, we train the …
  datacite Ambrosini, Irene, Blakowski, Ingo, Zendrikov, Dmitrii, Capone, Cristiano 等 2026 置信度 0.66 Robotics (cs.RO)Artificial Intelligence (cs.AI)Emerging Technologies (cs.ET)FOS: Computer and information sciencesFOS: Computer and information sciences
• FireFly-P: FPGA-Accelerated Spiking Neural Network Plasticity for Robust Adaptive Control
  Spiking Neural Networks (SNNs) offer a biologically plausible learning mechanism through synaptic plasticity, enabling unsupervised adaptation without the computational overhead of backpropagation. To harness this capability for robotics, this paper presents F…
  datacite Li, Tenglong, Li, Jindong, Shen, Guobin, Zhao, Dongcheng 等 2026 置信度 0.66 Hardware Architecture (cs.AR)FOS: Computer and information sciencesFOS: Computer and information sciences
• STAER: Temporal Aligned Rehearsal for Continual Spiking Neural Network
  Spiking Neural Networks (SNNs) are inherently suited for continuous learning due to their event-driven temporal dynamics; however, their application to Class-Incremental Learning (CIL) has been hindered by catastrophic forgetting and the temporal misalignment …
  datacite Gianferrari, Matteo, Moussadek, Omayma, Salami, Riccardo, Fiorini, Cosimo 等 2026 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Artificial Intelligence (cs.AI)Machine Learning (cs.LG)FOS: Computer and information sciencesFOS: Computer and information sciences
• Fugu Software
  Fugu software tool for spiking neural network algorithms.
  datacite Krygier, Michael C., Severa, William, Ho, Yang, Rothganger, Fred 等 2026 置信度 0.66 neuromorphic algorithmsspiking neural networks
• Fugu Software
  Fugu software tool for spiking neural network algorithms.
  datacite Krygier, Michael C., Severa, William, Ho, Yang, Rothganger, Fred 等 2026 置信度 0.66 neuromorphic algorithmsspiking neural networks
• Ventral pallidum efferent pathways via mediodorsal thalamus and lateral habenula mediate distinct aspects of default mode network regulation
  Transitions between internal and external focus are fundamental to cognition. These shifts depend on the modulation of the Default Mode Network (DMN), of which the ventral pallidum (VP) is a key subcortical node. Here, we examine which VP efferent pathways med…
  datacite Makedona, Epistimi-Anna, Kuo, Mu-En, Harvey, Michael, Rainer, Gregor 2025 置信度 0.66 FOS: Biological sciencesFOS: Biological sciencesVentral Pallidumdefault mode networkLateral Habenula
• Impact of the entorhinal feed-forward connection to the CA3 on hippocampal coding
  Each sub-region of the hippocampus plays a critical computational role in the formation of episodic learning and memory, but studies have yet to show and interpret the individual spiking dynamics of each region and how that information is passed between each s…
  datacite Lassers, Samuel, Khatri, Shazfa, Chen, Ruiyi, Vakilna, Yash 等 2025 置信度 0.66 FOS: Engineering and technologyFOS: Engineering and technologyspike trainsMemoryNeurons
• Real-time VIM thalamus recordings during peripheral nerve stimulation treatment for essential tremor: DBS intraoperative dataset
  Background: Essential tremor (ET), the most common movement disorder in adults, presents with involuntary shaking of the upper extremities during postural hold and kinetic tasks linked to dysfunction in the cerebellothalamo-cortical network. Recently, transcut…
  datacite Luu, Cuong, Ranum, Jordan, Youn, Youngwon, Perrault, Jennifer 等 2025 置信度 0.66 FOS: Medical engineeringFOS: Medical engineeringEssential tremorPeripheral nerve stimulationNeuromodulation
• Impact of background input on memory consolidation in In-Vitro neural networks
  Memory consolidation is a complex process, that can be divided into two stages: first, memories are temporary stored in hippocampus and in the second stage, repeated replay slowly transfers memories to the neo-cortex for long-term consolidation. This 2nd stage…
  datacite Lamberti, Martina, Kikirikis, Nikolaos, van Putten, Michel J.A.M., le Feber, Joost 2024 置信度 0.66 FOS: Biological sciencesFOS: Biological sciencesSlow-wave SleepMemory consolidationNetwork excitability
• Spatial coding dysfunction and network instability in the aging medial entorhinal cortex
  Across species, spatial memory declines with age, possibly reflecting altered hippocampal and medial entorhinal cortex (MEC) function. However, the integrity of cellular and network-level spatial coding in aged MEC is unknown. Here, we leveraged in vivo electr…
  datacite Herber, Charlotte S., Pratt, Karishma J.B., Shea, Jeremy M., Villeda, Saul A. 等 2025 置信度 0.66 Agingmedial entorhinal cortexgrid cellSpatial memoryFOS: Biological sciences
• Data from: Brain-state mediated modulation of inter-laminar dependencies in visual cortex
  Spatial attention is critical for recognizing behaviorally relevant objects in a cluttered environment. How the deployment of spatial attention aids the hierarchical computations of object recognition remains unclear. We investigated this in the laminar cortic…
  datacite Das, Anirban, Sheffield, Alec, Nandy, Anirvan, Jadi, Monika 2024 置信度 0.66 FOS: Biological sciencesFOS: Biological sciencesMacaqueVisual cortexElectrophysiology
• Spike-timing based coding in neuromimetic tactile system enables dynamic object classification
  Coding dynamic tactile information in spike timing is essential to human haptic exploration and dexterous object manipulation. Conventional electronic skins generate frames of tactile signals upon interaction with objects and are unfortunately ill-suited for e…
  datacite Chen, Libo, Karilanova, Sanja, Chaki, Soumi, Wen, Chenyu 等 2024 置信度 0.66 neuromorphic circuitTactile sensingelectronic skinMachine learningFOS: Electrical engineering, electronic engineering, information engineering
• Data for: Brain control of bimanual movement enabled by recurrent neural networks
  Brain-computer interfaces have so far focused largely on enabling the control of a single effector, for example a single computer cursor or robotic arm. Restoring multi-effector motion could unlock greater functionality for people with paralysis (e.g., bimanua…
  datacite Deo, Darrel, Willett, Francis, Avansino, Donald, Hochberg, Leigh 等 2024 置信度 0.66 Biomedical engineeringComputational neuroscienceMachine learningMotor cortexBrain-Computer Interface
• The flow of axonal information among hippocampal subregions: 2. Patterned stimulation sharpens routing of information transmission
  The subregions of the hippocampal formation are essential for episodic learning and memory formation, yet the spike dynamics of each region contributing to this function are poorly understood, in part because of a lack of access to the inter-regional communica…
  datacite Lassers, Samuel, Vakilna, Yash, Tang, William, Brewer, Gregory 2023 置信度 0.66 FOS: Engineering and technologyFOS: Engineering and technologynetworksHippocampuselectrode array
• Stimulus encoding by specific inactivation of cortical neurons
  Neuronal ensembles are groups of neurons with correlated activity associated with sensory, motor, and behavioral functions. To explore how ensembles encode information, we investigated responses of visual cortical neurons in awake mice using volumetric two-pho…
  datacite Pérez-Ortega, Jesús, Akrouh, Alejandro, Yuste, Rafael 2024 置信度 0.66 ensemblesoffsemblesFOS: Biological sciencesFOS: Biological sciencesonsembles
• Extracellular Recordings from Human Brain Organoids Using High-density CMOS Arrays
  Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arra…
  datacite Sharf, Tal 2022 置信度 0.66 FOS: Biological sciencesFOS: Biological scienceshuman brain organoidsfunctional connectivityextracellular recording
• Patch-clamp recordings from dorsal raphe neurons
  This dataset contains whole-cell electrophysiological recordings (patch-clamp recordings) from three cell types in mice: serotonin (5-HT) neurons, somatostatin (SOM)-expressing GABA interneurons, and layer 5 pyramidal neurons. 5-HT and GABA neurons were record…
  datacite Harkin, Emerson, Lynn, Michael, Boucher, Jean-François, Caya-Bissonnette, Léa 等 2023 置信度 0.66 NeuroscienceFOS: Biological sciencesFOS: Biological sciencesSerotoninElectrophysiology
• Ensemble synchronization in the reassembly of Hydra's nervous system
  Although much is known about how the structure of the nervous system develops, it is still unclear how its functional modularity arises. A dream experiment would be to observe the entire development of a nervous system, correlating the emergence of functional …
  datacite Lovas, Jonathan, Yuste, Rafael 2021 置信度 0.66 FOS: Biological sciencesFOS: Biological sciences
• CBMC-V3: A CNS-inspired Control Framework Towards Agile Manipulation with SNN
  As robotic arm applications expand beyond traditional industrial settings into service-oriented domains such as catering, household and retail, existing control algorithms struggle to achieve the level of agile manipulation required in unstructured environment…
  datacite Pang, Yanbo, Li, Qingkai, Zhao, Mingguo 2025 置信度 0.66 Robotics (cs.RO)FOS: Computer and information sciencesFOS: Computer and information sciences
• Data for: Hybrid dedicated and distributed coding in PMd/M1 provides separation and interaction of bilateral arm signals
  Pronounced activity is observed in both hemispheres of the motor cortex during preparation and execution of unimanual movements. The organizational principles of bi-hemispheric signals and the functions they serve throughout motor planning remain unclear. Usin…
  datacite Dixon, Tanner, Merrick, Christina, Wallis, Joni, Ivry, Richard 等 2021 置信度 0.66 FOS: Biological sciencesFOS: Biological sciences
• Smart sensing by analog/digital hybrid neural networks
  In this dissertation, the design, computer simulations, experimental evaluations, and theoretical analyses of new sensing schemes were systematically carried out. A novel power-efficient and low-complexity analog sensor design, which is the foundation of this …
  datacite Hsieh, Yung-Ting 2026 置信度 0.66
• Network-Optimised Spiking Neural Network for Event-Driven Networking
  Delay-coupled systems often require low-latency decisions from sparse telemetry, where dense fixed-step neural inference is wasteful and can degrade near stability margins. We introduce Network-Optimised Spiking (NOS), a trainable two-state event-driven dynami…
  datacite Bilal, Muhammad 2025 置信度 0.66 Neural and Evolutionary Computing (cs.NE)Machine Learning (cs.LG)Networking and Internet Architecture (cs.NI)Optimization and Control (math.OC)FOS: Computer and information sciences
• Taming neuronal noise with large networks
  How does reliable computation emerge from networks of noisy neurons? While individual neurons are intrinsically noisy, the collective dynamics of populations of neurons taken as a whole can be almost deterministic, supporting the hypothesis that, in the brain,…
  datacite Schmutz, Valentin Marc 2022 置信度 0.66 spiking neuronsnonlinear Hawkes processesmean-field approximationsspike-frequency adaptationshort-term synaptic plasticity
• Data from: Input-dependent frequency modulation of cortical gamma oscillations shapes spatial synchronization and enables phase coding
  Fine-scale temporal organization of cortical activity in the gamma range (~25–80Hz) may play a significant role in information processing, for example by neural grouping (‘binding’) and phase coding. Recent experimental studies have shown that the precise freq…
  datacite Lowet, Eric, Roberts, Mark, Hadjipapas, Avgis, Peter, Alina 等 2015 置信度 0.66 Arnold tonguegamma oscillationneural coding
• Data from: Computing the local field potential (LFP) from integrate-and-fire network models
  Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of ne…
  datacite Mazzoni, Alberto, Lindén, Henrik Anders, Cuntz, Hermann, Lansner, Anders 等 2016 置信度 0.66 Local Field Potentialintegrate and firesimulations
• How random connectivity shapes the fluctuating dynamics of finite-size neural populations
  Mesoscopic models of finite-size neuronal populations are crucial to understand the dynamics of neural networks in the brain, especially their fluctuations and response to stimuli. However, current theories to derive such models are based on homogeneous all-to…
  datacite Greven, Nils E., Ranft, Jonas, Schwalger, Tilo 2024 置信度 0.66 Neurons and Cognition (q-bio.NC)FOS: Biological sciencesFOS: Biological sciences
• Multi-memristive synaptic architectures for training neural networks
  Highly data-centric AI workloads require that new computing paradigms be adopted because the performance of traditional CPU- and GPU-based systems are limited by data access and transfer. Training deep neural networks with millions of tunable parameters takes …
  datacite Boybat Kara, Irem 2020 置信度 0.66 In-memory computingneuromorphic computingmemristive devicemulti-memristive synaptic architectureneural network training
• Privacy-Preserving Federated Spiking Neural Networks for Real-Time Target Detection in Distributed ISAC Edge Systems
  This study proposes a privacy-preserving federated spiking neural network (SNN) framework for real-time target detection in integrated sensing and communication (ISAC) edge networks. The framework enables distributed vehicular nodes operating at 28 GHz to coll…
  datacite Mohammad Zahangir Alam 2026 置信度 0.66
• Flexible Working Memory Model in Spiking Neural Network With Two Types of Plasticity
  preprints 2023 置信度 0.74
• A lightweight data-driven spiking neural network model of <i>Drosophila</i> olfactory nervous system with dedicated hardware support
  preprints 2023 置信度 0.74
• A Biologically Plausible Spiking Neural Network for Decoding Kinematics in the Hippocampus and Premotor Cortex
  preprints 2022 置信度 0.74
• BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network
  preprints 2023 置信度 0.74
• BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network
  preprints 2023 置信度 0.74
• Hippocampome.org v2.0: a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits
  preprints 2023 置信度 0.74
• Modelling Spontaneous Firing Activity of the Motor Cortex in a Spiking Neural Network with Random and Local Connectivity
  preprints 2022 置信度 0.74
• Artificial cerebellum on FPGA: Realistic real-time cerebellar spiking neural network model capable of real-world adaptive motor control
  preprints 2023 置信度 0.74
• Dynamic Control of Eye-Head Gaze Shifts by a Spiking Neural Network Model of the Superior Colliculus
  preprints 2022 置信度 0.74
• Synaptic Transistor with Multiple Biological Function Based on Metal-Organic Frameworks Combined with LIF Model of Spiking Neural Network to Recognize Temporal Information
  preprints 2023 置信度 0.74
• Brain-inspired spiking neural network controller for a neurorobotic whisker system
  preprints 2021 置信度 0.74
• CIRM-SNN: Certainty Interval Reset Mechanism Spiking Neuron for Enabling High Accuracy Spiking Neural Network
  preprints 2022 置信度 0.74
• A Spiking Neural Network Model of Rodent Head Direction calibrated with Landmark Free Learning
  preprints 2022 置信度 0.74
• A spiking neural network model for the control of oscillatory phase differences between multiple brain areas
  preprints 2022 置信度 0.74
• An All-in-One Biomimetic 2D Spiking Neural Network
  preprints 2021 置信度 0.74
• Production of adaptive movement patterns via an insect inspired Spiking Neural Network Central Pattern Generator
  preprints 2022 置信度 0.74
• Prediction and Detection of Virtual Reality induced Cybersickness: A Spiking Neural Network Approach Using Spatiotemporal EEG Brain Data and Heart Rate Variability
  preprints 2022 置信度 0.74
• A spiking neural network model of the Superior Colliculus that is robust to changes in the spatial-temporal input
  preprints 2021 置信度 0.74
• A Brief Review on Spiking Neural Network - A Biological Inspiration<b> </b>
  preprints 2021 置信度 0.74
• Disynaptic Effect of Hilar Cells on Pattern Separation in A Spiking Neural Network of Hippocampal Dentate Gyrus
  preprints 2021 置信度 0.74
• Unsupervised Learning Method for SAR Image Classification Based on Spiking Neural Network
  preprints 2021 置信度 0.74
• A Spiking Neural Network Model for Category Learning
  preprints 2020 置信度 0.74
• Predicting the Influence of Axon Myelination on Sound Localization Precision Using a Spiking Neural Network Model of Auditory Brainstem
  preprints 2021 置信度 0.74
• A Neuroscience-Inspired Spiking Neural Network for Auditory Spatial Attention Detection Using Single-Trial EEG
  preprints 2021 置信度 0.74
• A spiking neural-network model of goal-directed behaviour
  preprints 2019 置信度 0.74
• An integrate-and-fire spiking neural network model simulating artificially induced cortical plasticity
  preprints 2020 置信度 0.74
• Learning the synaptic and intrinsic membrane dynamics underlying working memory in spiking neural network models
  preprints 2020 置信度 0.74
• Spike: A GPU Optimised Spiking Neural Network Simulator
  preprints 2018 置信度 0.74
• Microstimulation in a spiking neural network model of the midbrain superior colliculus
  preprints 2018 置信度 0.74
• FL-SNNIDS: Federated Spiking Neural Networks for Energy-Efficient Intrusion Detection in Agricultural SDN-IoT Networks
  europepmc 2026 置信度 0.80
• Fully unsupervised online spike sorting based on an artificial spiking neural network
  preprints 2017 置信度 0.74
• Spike-Aware Propagation Approximation for Conductance-Based LIF Equations
  europepmc 2026 置信度 0.80
• Embedding Formal Worst-Case Latency Proofs and Memory-Safety Certificates into the snn-mlir MLIR Lowering Pipeline for IEC 62304-Compliant Edge Deployment of Spiking Neural Networks
  europepmc 2026 置信度 0.80
• Multiplication-Free Blood Glucose Estimation via Spiking Neural Networks on Wearable Impedance Biosensors
  europepmc 2026 置信度 0.80
• Graph theory for the analysis of micro-electrode array recordings of human brain slices – framework and benchmarking
  europepmc 2026 置信度 0.80
• Estimation of the time course of excitatory and inhibitory conductance during oscillatory periods
  europepmc 2026 置信度 0.80
• Biologically Plausible Dopamine-Modulated STDP Model of Pavlovian Learning in Spiking Neural Networks
  europepmc 2026 置信度 0.80
• Titration of the Generational Memory Window: Engine and Brake in the Evolutionary Substrate
  europepmc 2026 置信度 0.80
• Ephaptic coupling improves the neural population code
  europepmc 2026 置信度 0.80