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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills5 installs19,223 views
- Neuroai Beyond Bridging Neuroscience AiNeuroAI research roadmap bridging neuroscience and AI - identifies three fundamental capabilities for AI advancement: world modeling, motor control, and biological learning. NSF workshop framework for interdisciplinary research. Keywords: NeuroAI, world models, motor control, biological learning, neuroscience-AI integration.Votes: 0GitHub stars: 3
- Neuroai Fundamental Gaps 2026NeuroAI and Beyond: Bridging Between Advances in Neuroscience and Artificial Intelligence (arXiv:2604.18637). NSF workshop report identifying three fundamental capability gaps in current AI systems from neuroscience perspective. Activation: neuroai, neuroscience AI bridge, AI capability gaps, embodied interaction, continual learning, neuroscience workshop.Votes: 0GitHub stars: 3
- Neuroaps Net Alzheimer Point CloudNeuro-Anatomically Aware Point Cloud Representation (NeuroAPS-Net) for efficient Alzheimer's disease classification from MRI. Converts T1-weighted MRI into anatomically-informed 2D point clouds with region-aware feature encoding. Activation triggers: Alzheimer's classification, neuroanatomical point cloud, MRI analysis, geometric deep learning.Votes: 0GitHub stars: 3
- Neurobiological Craving Signature SocialNeurobiological Craving Signature (NCS) - predicts social craving and social reinstatement from neural activity patterns. Identifies biomarkers for social isolation effects on brain circuits involved in social motivation. Activation: neurobiological craving signature, social craving, NCS biomarker, social isolation neural, craving prediction, social neuroscience.Votes: 0GitHub stars: 3
- Neurocogmap Llm Cognitive OrganizationNeuroCogMap framework for mapping cognitive organization in LLMs using neuroscience-inspired methods, linking LLM internal representations to human cortical functionVotes: 0GitHub stars: 3
- Neurocognitive Governance Ai AgentsNeurocognitive governance framework for autonomous AI agents based on executive function and inhibitory control principles. Maps human self-governance mechanisms to AI decision-making for safety-critical environments. Activation: neurocognitive governance, AI executive function, inhibitory control, autonomous agent governance, deliberation-action loop.Votes: 0GitHub stars: 3
- Neurocybernetic Large Scale Neuroscience V2Integrative Neurocybernetic Modeling framework for large-scale neuroscience research. Treats the brain as a controller pursuing latent objectives in closed-loop coupling with body and environment. Bridges fragmented computational neuroscience efforts through unified cybernetic principles. Keywords: neurocybernetics, large-scale neuroscience, integrative modeling, closed-loop modeling, brain-body-environment coupling.Votes: 0GitHub stars: 3
- Neurocybernetic Large Scale NeuroscienceIntegrative neurocybernetic modeling framework for large-scale neuroscience. Unifies diverse neural datasets across animals, brain areas, and behaviors through cybernetic principles. Addresses fragmentation in computational neuroscience. Keywords: neurocybernetics, large-scale neuroscience, integrative modeling, cross-species, unified framework.Votes: 0GitHub stars: 3
- Neurodegenerative 4d Diffusion V24D (3D×T) diffusion-based generative framework for modeling neurodegenerative brain anatomy progression. Combines spatial and temporal modeling for longitudinal brain imaging and disease progression prediction. Keywords: neurodegenerative disease, 4D diffusion model, longitudinal brain imaging, brain anatomy modeling, disease progression prediction, generative AI.Votes: 0GitHub stars: 3
- Neurodegenerative 4d Diffusion V34D(3D×T)扩散模型用于神经退行性疾病脑解剖结构的纵向生成建模。基于形变的形态测量学(DBM)和平稳速度场(SVF)。Votes: 0GitHub stars: 3
- Neurodegenerative 4d Diffusion4D(3D×T)扩散模型用于神经退行性疾病脑解剖结构的纵向生成建模。基于形变的形态测量学。Votes: 0GitHub stars: 3
- Neuroflownet Scalp To IeegNeuroFlowNet — cross-modal generative framework using Conditional Normalizing Flow for reconstructing high-fidelity iEEG signals from non-invasive scalp EEGVotes: 0GitHub stars: 3
- Neurogan 3dNeuroGAN-3D methodology for high-fidelity 3D generative super-resolution of resting-state fMRI (rs-fMRI) spatial maps. Uses a GAN architecture to enhance spatial resolution of volumetric functional brain network maps, enabling more precise localization of functional units, reliable brain parcellation, and detection of subtle spatially-specific neurobiological alterations. Use when working with rs-fMRI super-resolution, volumetric brain map enhancement, generative models for neuroimaging, func...Votes: 0GitHub stars: 3
- Neuroinspector Hierarchical Dataset InspectionNeuroInspector framework for local-first inspection and annotation of hierarchical neuroscience datasets (HDF5/NWB files) using browser-based WebAssembly HDF5 parsing. Provides structural navigation, metadata inspection, sampled data previews, and path-level annotation into portable project packs without modifying original files. Use for neuroscience data workflow inspection tasks.Votes: 0GitHub stars: 3
- Neuromimetic Perceptual CompressionBrain-inspired perceptual compression using evidence-driven neuromimetic principles. Leverages human visual system characteristics for efficient data compression that prioritizes perceptually important information.Votes: 0GitHub stars: 3
- Neuromodulated Synaptic Plasticity神经调节突触可塑性的学习框架。在脉冲神经网络（SNN）中通过梯度下降 训练神经科学启发的可塑性模型，解决在线学习问题。 触发词：突触可塑性、神经调节、脉冲神经网络、在线学习、学习的学习、 synaptic plasticity, neuromodulation, spiking neural network, online learning, meta-learning。Votes: 0GitHub stars: 3
- Neuromodulation Rhythmic Pattern ControlNeuromodulation-based control architecture for dynamically reconfiguring rhythmic patterns in central pattern generators (CPGs) with fixed connectivity. Uses targeted neuromodulatory inputs to enable rapid, localized rhythmic transitions without structural plasticity. Applicable to: CPG control, rhythmic motor pattern generation, neuromodulation modeling, degenerate network dynamics, biological locomotion control, respiratory rhythm control, or dynamical systems analysis of neural circuits.Votes: 0GitHub stars: 3
- Neuromorphic Artificial ConsciousnessNeuromorphic Correlates of Artificial Consciousness (NCAC) — theoretical framework merging neuromorphic design with brain simulations for artificial consciousness. arXiv:2405.02370Votes: 0GitHub stars: 3
- Neuromorphic Continual Nuclear Ics神经形态持续学习方法用于核电厂工业控制系统(ICS)监测的顺序部署。结合脉冲神经网络(SNN)和在线学习，实现关键基础设施的实时异常检测和安全监控，同时防止灾难性遗忘。适用于关键基础设施保护、工业网络安全、边缘AI。Votes: 0GitHub stars: 3
- Neuromorphic Disturbance ObserverBiologically-inspired disturbance observer and control framework that replaces conventional continuous-time signal representations with spike-timing encoding. Uses integrate-and-fire (IF) neuron dynamics for event-driven updates, achieving remarkable robustness and adaptability in uncertain environments.Votes: 0GitHub stars: 3
- Neuromorphic Energy Aware DbsNeuromorphic energy-aware learning for adaptive deep brain stimulation (DBS). Use when working with spiking neural networks (SNNs) for closed-loop neural control, brain-computer interfaces, or neuromorphic hardware deployment. Covers energy-aware RL reward design, spiking Q-networks, knowledge distillation to neuromorphic chips, and co-optimization of actuator + inference energy in implantable medical devices.Votes: 0GitHub stars: 3
- Neuromorphic Energy Aware Learning DbsNeuromorphic Energy-Aware Learning for Adaptive Deep Brain Stimulation — co-optimizes stimulation energy and inference efficiency via deep spiking Q-network on neuromorphic hardware. Achieves 45.2% oscillation suppression with 80% charge reduction at 0.52 mW.Votes: 0GitHub stars: 3
- Neuromorphic Fwmav Snn ControlNeuromorphic control of flapping-wing micro aerial vehicles using SNNs on resource-constrained ESP32 microcontroller. Hierarchical SNN framework: state estimation + CPG modulation for wing actuation. 36% latency reduction, 18% power reduction vs ANN. First onboard neuromorphic autonomous flight.Votes: 0GitHub stars: 3
- Neuromorphic Lidar Bev SnnEnd-to-end Spiking Neural Network for 3D LiDAR-based Bird's Eye View object detection in autonomous driving, with neuromorphic energy analysis and learned spike encoding.Votes: 0GitHub stars: 3
- Neuromorphic Spacecraft Pose Event CameraEnd-to-end spacecraft 6-DoF pose estimation using event cameras and BrainChip Akida neuromorphic processor. MobileNet-style keypoint regression on event-frame representations with quantization-aware training (8/4-bit) converted to spiking neural networks. First demonstration of spacecraft pose estimation on Akida hardware. Activation: neuromorphic, event camera, spacecraft pose, Akida, spiking neural network, space robotics, event-based vision.Votes: 0GitHub stars: 3
- Neuromorphic SpiNNaker AslNeuromorphic visual attention framework for sign language recognition on SpiNNaker hardware. Combines event-based vision sensors with spiking neural networks for energy-efficient real-time ASL recognition. Use when: deploying low-power gesture/sign recognition, implementing event-based vision on neuromorphic hardware, building SpiNNaker applications, designing energy-efficient computer vision systems, working with DVS (Dynamic Vision Sensor) data.Votes: 0GitHub stars: 3
- Neuromorphic SupremacyNeuromorphic Supremacy methodology — hybrid astrocytic-spiking neural architectures that outperform classical deep learning in noisy, data-scarce environmentsVotes: 0GitHub stars: 3
- Neuron Dropin NeuroplasticityNeuron-level DropIn and neuroplasticity mechanisms for enhancing deep learning efficiency and performance. Addresses the bottleneck of parameter scaling by enabling targeted neuron replacement and adaptive plasticity.Votes: 0GitHub stars: 3
- Neuron Model Reconstruction从锋电位时间序列快速重构电导神经元模型。 结合深度学习和动态输入电导（DIC）框架，解决神经元简并性问题。 触发词：神经元模型、电导模型、锋电位、模型重构、DIC、 conductance-based model, spike times, neuron reconstruction, degeneracy。Votes: 0GitHub stars: 3
- Neuron Photonic Spiking LaserPhotonic spiking neurons using multi-junction VCSELs (NeuronSEL) with negative differential resistance. Neuromorphic photonics for ultra-fast optical information processing. Triggers: photonic neuron, VCSEL, neuromorphic photonics, spiking laser, optical computing.Votes: 0GitHub stars: 3
- Neuron Surface Emitting Laser Neuronsel SpikingMethodology from paper 'Neuron Surface Emitting Laser (NeuronSEL): Spiking Regimes and Negative Differential Resistance in S...' by Maria Duque-Gijon et al. (2026-04-14). Activation: brain, neural, spiking, neuron, network, physics.opticsVotes: 0GitHub stars: 3
- Neuronal Arithmetic OtsNeuronal arithmetic operators using Ovonic Threshold Switches (OTS) for biologically inspired analog computing. Implements additive integration and divisive gain modulation through synaptic conductance changes and shunting inhibition. Trigger words: Ovonic threshold switch, neuronal arithmetic, analog computing, biologically inspired computing, shunting inhibition, gain modulation, synaptic conductance, neuromorphic arithmetic, OTS neuron, additive integration, divisive normalization.Votes: 0GitHub stars: 3
- Neuronal Murburn Thermodynamic ElectricityMurburn thermodynamic framework for neuronal electrical activity - unified reaction-transport-relaxation model explaining resting potential, excitability, and signal propagation. Activation triggers: murburn, neuronal electricity, electron holding potential, redox thermodynamics, nonlinear dynamics.Votes: 0GitHub stars: 3
- Neuropinns Spiking PinnNeuroPINNs methodology — neuroscience-inspired Physics-Informed Neural Networks using Variable Spiking Neurons for energy-efficient PDE solvingVotes: 0GitHub stars: 3
- Neuroplastic Plasticity OptimizerNeuroPlastic - A plasticity-modulated optimizer for biologically inspired learning dynamics. Incorporates synaptic plasticity mechanisms like Hebbian learning, homeostatic plasticity, and metaplasticity into gradient-based optimization for enhanced learning stability and biological plausibility.Votes: 0GitHub stars: 3
- Neuroring Multi Fpga SnnNeuroRing modular and scalable SNN accelerator based on multi-FPGA bidirectional ring topology and stream-dataflow architecture. Use when scaling Spiking Neural Networks (SNN) across multiple FPGAs; implementing event-driven neuromorphic hardware; designing distributed SNN simulations; optimizing spike communication and synchronization; or integrating FPGA accelerators with NEST simulator. Applicable to computational neuroscience, neuromorphic engineering, and event-driven computing systems.Votes: 0GitHub stars: 3
- Neuroring Multifpga SnnNeuroRing methodology for modular and scalable SNN accelerator based on multi-FPGA bidirectional ring topology and stream-dataflow architectureVotes: 0GitHub stars: 3
- Neuroscience 2607 12403Skill for applying the methods from the arXiv paper: Structured Fluctuations and the Information Dynamics of Self-Maintenance in Growing Neural Cellular Automata (arXiv:2607.12403). This skill provides a framework for analyzing internal fluctuations in neural cellular automata as a functional component for self-maintenance and self-repair.Votes: 0GitHub stars: 3
- Neuroscience Domain Relevance FilteringDomain relevance filtering methodology for neuroscience paper selection in automated research workflows. Provides criteria for determining when arXiv papers are relevant to neuroscience, brain networks, neural dynamics, spiking neural networks, and computational neuroscience domains.Votes: 0GitHub stars: 3
- Neuroscience Eeg Meg Brain NetworksSkill for exploring brain networks using noninvasive electrophysiological measurements (EEG/MEG) based on arXiv:2607.17602v1.Votes: 0GitHub stars: 3
- Neuroscience Frontiers 2026Comprehensive synthesis of cutting-edge neuroscience and NeuroAI research from 2025-2026. Covers NSF NeuroAI workshop findings, CogniSNN random graph architectures, EMBER hybrid cognitive systems, SpikingBrain2.0 foundation models, and Next Generation Neural Mass Models. Integration of brain-inspired AI capabilities for embodied interaction, continual learning, and efficient few-shot learning.Votes: 0GitHub stars: 3
- Neuroscience Graph Operators Virtual SensingNeuroscience-inspired graph neural operators for edge-deployable virtual sensing on irregular geometries. Enables sparse-to-dense reconstruction and real-time full-field physics prediction with latency and energy constraints.Votes: 0GitHub stars: 3
- Neuroscience Of Transformers使用Transformer架构建模脑数据的范式。系统化回顾Transformer在fMRI、EEG、MEG、ECoG等脑信号中的应用，识别输入表示和神经对齐策略等关键设计选择。适用于脑-文本解码、脑-图像重建、脑信号预测。触发词：neuroscience of transformers, brain signal modeling, neural alignment, brain-to-text, brain-to-image, fMRI transformer, EEG transformerVotes: 0GitHub stars: 3
- Neuroscience Transformers Cortical AnalogyMapping Transformer architectures to cortical column organization for understanding brain computation. Analogy framework between transformer operations (attention, contextual selection, routing) and laminar cortical features. Use for: cortical computation analysis, neuroscience-AI bridging, experimental hypothesis generation. Triggers: transformer cortex, cortical column, brain architecture, neuroscience transformers, laminar computation.Votes: 0GitHub stars: 3
- 3dpalsynet A Facial Palsy Grading And Motion Recognition Framework Using Fully 3d Convolutional Neural Networks**arXiv ID:** 1905.13607 **Authors:** Gary Storey, Richard Jiang, Shelagh Keogh, Ahmed Bouridane, Chang-Tsun Li **Published:** 2019-05-31T13:24:30Z **Abstract:** The capability to perform facial analysis from video sequences has significant potential to positively impact in many areas of life. One such area relates to the medical domain to specifically aid in the diagnosis and rehabilitation of patients with facial palsy. With this application in mind, this paper presents an end-to-end framew...Votes: 0GitHub stars: 3
- A Computational Framework Of Cortical Microcircuits Approximates Signconcordant Random Backpropagation**arXiv ID:** 2205.07292 **Authors:** Yukun Yang, Peng Li **Published:** 2022-05-15T14:22:03Z **Abstract:** Several recent studies attempt to address the biological implausibility of the well-known backpropagation (BP) method. While promising methods such as feedback alignment, direct feedback alignment, and their variants like sign-concordant feedback alignment tackle BP's weight transport problem, their validity remains controversial owing to a set of other unsolved issues. In this work, we...Votes: 0GitHub stars: 3
- A Frugal Spiking Neural Network For Unsupervised Classification Of Continuous Multivariate Temporal Data**arXiv ID:** 2408.12608 **Authors:** Sai Deepesh Pokala, Marie Bernert, Takuya Nanami, Takashi Kohno, Timothée Lévi, Blaise Yvert **Published:** 2024-08-08T08:15:51Z **Abstract:** As neural interfaces become more advanced, there has been an increase in the volume and complexity of neural data recordings. These interfaces capture rich information about neural dynamics that call for efficient, real-time processing algorithms to spontaneously extract and interpret patterns of neural dynamics. M...Votes: 0GitHub stars: 3
- A General Framework For Development Of The Cortexlike Visual Object Recognition System Waves Of Spikes Predictive Coding And Universal Dictionary Of Features**arXiv ID:** 1102.2739 **Authors:** Sergey S. Tarasenko **Published:** 2011-02-14T11:40:08Z **Abstract:** This study is focused on the development of the cortex-like visual object recognition system. We propose a general framework, which consists of three hierarchical levels (modules). These modules functionally correspond to the V1, V4 and IT areas. Both bottom-up and top-down connections between the hierarchical levels V4 and IT are employed. The higher the degree of matching between the i...Votes: 0GitHub stars: 3
- A Genetic Algorithmbased Approach For Automated Optimization Of Kolmogorovarnold Networks In Classification Tasks**arXiv ID:** 2501.17411 **Authors:** Quan Long, Bin Wang, Bing Xue, Mengjie Zhang **Published:** 2025-01-29T04:32:36Z **Abstract:** To address the issue of interpretability in multilayer perceptrons (MLPs), Kolmogorov-Arnold Networks (KANs) are introduced in 2024. However, optimizing KAN structures is labor-intensive, typically requiring manual intervention and parameter tuning. This paper proposes GA-KAN, a genetic algorithm-based approach that automates the optimization of KANs, requiring ...Votes: 0GitHub stars: 3
- A Neurocomputational Account Of Flexible Goaldirected Cognition And Consciousness The Goalaligning Representation Internal Manipulation Theory Garim**arXiv ID:** 1912.13490 **Authors:** Giovanni Granato, Gianluca Baldassarre **Published:** 2019-12-31T18:45:33Z **Abstract:** Goal-directed manipulation of representations is a key element of human flexible behaviour, while consciousness is often related to several aspects of higher-order cognition and human flexibility. Currently these two phenomena are only partially integrated (e.g., see Neurorepresentationalism) and this (a) limits our understanding of neuro-computational processes that ...Votes: 0GitHub stars: 3