hiyenwong/ai_collection - Page 32

music-perception-brain-network

音乐感知脑网络建模方法论。使用FitzHugh-Nagumo模型和经验脑连接数据研究听觉刺激对神经网络动力学的影响，分析同步与频率/振幅的关系。触发词：音乐感知、脑网络、听觉刺激、神经同步、FitzHugh-Nagumo、gamma同步、music perception、brain network、auditory stimulus。

Source text: Chinese

mzeqas-zero-shot-quantum-nas

Zero-shot quantum neural architecture search methodology using QNTK convergence and MCTS for VQA circuit design. Eliminates repeated training costs. Activation: quantum NAS, neural architecture search, zero-shot, VQA, MCTS, 量子架构搜索.

naimark-qnn-measurement-circuits

Quantum measurement circuit design comparing Naimark extension, hybrid Naimark-QNN, and fully QNN measurements for state discrimination. Use when: quantum measurement implementation, POVM circuits, minimum-error measurement, maximum-confidence measurement,…

native-active-perception-reasoning

Native active perception methodology for omni-modal understanding using POMDP-based Observation-Thought-Action cycle, Agentic Supervised Fine-Tuning (ASFT), and TAURA turn-level credit assignment.

naturalistic-computational-cognitive-science

Framework for building generalizable cognitive science models using naturalistic experimental paradigms and AI integration. Argues that naturalistic stimuli/tasks elicit distinct neural and behavioral patterns not captured by controlled experiments. Use when:…

nbox-memristor-visuotactile-snn

Self-oscillating NbOx memristor neuron for ultra-low-latency visuotactile perception. NbOx devices leverage intrinsic Mott metal-insulator transition and parasitic capacitance for simultaneous TTFS (time-to-first-spike) + rate encoding with 260 ns first-spike…

neocortex-error-driven-predictive-learning

Neocortex learning framework via error-driven predictive learning with temporal derivatives, corticothalamic circuits, and competitive kinase synaptic plasticity. Three-criteria account of neocortex learning: computational, algorithmic, and implementational.…

neocortex-learning-error-driven-predictive

Neocortex learning framework via error-driven predictive learning using temporal derivatives, corticothalamic circuits, and competitive kinase synaptic plasticity. Activation: neocortex learning, cortical learning, predictive learning, thalamocortical, kinase…

neocortex-learning-predictive-error-driven

Neocortex learning framework via error-driven predictive learning using temporal derivatives, corticothalamic circuits, and competitive kinase synaptic plasticity. Implemented in Axon spiking neural simulation framework. Activation: neocortex learning,…

nerve-brain-fc-tokenization

NERVE (Network-Aware Representations of Brain Functional Connectivity via Bilinear Tokenization) - self-supervised learning framework for brain functional connectivity (FC) representation learning. Redefines FC matrix tokenization by partitioning into…

nerve-fc-bilinear-tokenization

NERVE: Network-Aware Bilinear Tokenization for Brain Functional Connectivity representation learning. Self-supervised learning framework that redefines FC tokenization via structured bilinear factorization, aligning with large-scale brain network…

network-quantum-sensing-certification

Certification methodology for network quantum sensing — resolving the tension between quantum metrology and cryptography for distributed sensor networks. Framework for certifying security and precision guarantees simultaneously in noisy, insecure quantum…

neural-behavioral-whole-body-movement-monkeys

Neural-behavioral representation framework for natural whole-body movement in primates. Combines large-scale epidural cortical signals with synchronized multi-view motion capture to decode unconstrained whole-body kinematics. Use when: (1) decoding natural…

neural-brain-framework

Neuroscience-inspired framework for embodied AI agents. Use when building embodied agents, designing neural brain architectures, integrating multimodal sensing with cognition, implementing neuroplasticity-based memory systems, or optimizing neuromorphic…

neural-code-dynamics-analysis

神经编码动力学分析框架 - 整合计算神经科学、机器学习和临界态理论，研究生物与人工神经网络编码表示动力学。涵盖临界脑假说、雪崩动力学、信息几何与动力学不变量。Activation: neural coding, dynamics analysis, critical brain hypothesis, avalanche dynamics, information geometry, dynamical invariants, neural representation, encoding dynamics,…

Source text: Chinese

neural-code-language-characterization

Closed-loop framework for automated neuron characterization using natural language descriptions. Translates neuron activation patterns into semantic hypotheses, verifies them via in silico experiments using neural digital twins. Use when: neuron selectivity…

neural-code-speak

Automated characterization of individual neurons through natural language using generative models and neural digital twins. Use when: studying neuron selectivity in visual cortex, building closed-loop frameworks for neural characterization, generating…

neural-computation-without-slots

Biologically plausible memory and attention without dedicated storage slots. Extends Modern Hopfield Networks (MHN) to K-winner ensembles for improved continual learning retention, and demonstrates MHN can capture slot-based memory functions of LLMs.…

neural-connectivity-matrix-viewer

脑连接矩阵交互式可视化工具。基于HTML5/JavaScript的浏览器端应用，支持EEG、ECoG、MEG、fMRI等高维神经连接数据的3D堆叠矩阵可视化，实时交互探索连接模式。适用于脑连接分析、神经数据可视化、连接组学。触发词：脑连接可视化、连接矩阵、神经网络可视化、connectivity matrix、brain connectivity visualization、EEG connectivity、MEG connectivity。

Source text: Chinese

neural-critical-dynamics-theory

Theory of critical dynamics and information processing in neural networks. Neural systems at critical points exhibit optimal information processing, maximal dynamic range, and power-law distributed avalanches. Provides methods for identifying, analyzing, and…

neural-digital-twins-bci

Neural Digital Twins framework for Brain-Computer Interfaces (BCIs). Addresses neuroplasticity-induced recalibration, session-to-session variability, and real-time adaptation through personalized brain models.

neural-dynamics-analysis-methodology

Comprehensive framework for neural dynamics analysis integrating multiple methodologies: (1) Neural population decoding and encoding, (2) Brain network dynamics modeling, (3) Neural criticality assessment, (4) Spiking neural network dynamics, (5)…

neural-dynamics-decision-making

Neural Dynamics Decision-Making Models

Source text: Chinese

neural-dynamics-universal-translator-foundation

Foundation model for neural spiking data using multi-task masking (MtM) to translate across population, region, and single-neuron levels. Enables zero-shot and few-shot brain decoding across multiple brain areas. Activation triggers: neural translator,…

neural-dynamics-universal-translator

神经动力学通用翻译器方法论。在单细胞、单脉冲分辨率下翻译不同神经模型的动力学，实现跨模型动力学对齐。适用于神经元模型转换、动力学分析、计算神经科学。触发词：神经动力学、模型翻译、脉冲分辨率、神经元模型、neural dynamics、universal translator、single-spike。

Source text: Chinese

neural-emulator-theory

Neural Emulator Theory

neural-encoding-evaluation-ground-truth

Systematic audit methodology for EEG foundation model interpretability. Decomposes what models learn, what they use, and how much can be explained using layer-wise ridge probing, LEACE cross-covariance erasure, and transparent classifiers. Use when: EEG…

neural-encoding-evaluation-meeg

Evaluation framework for neural encoding models using MEEG (Mutual-information-based Estimation of Encoding model goodness-of-fit). Provides systematic methodology for assessing how well neural models predict brain activity, with information-theoretic metrics…

Source text: Chinese

neural-eso-robust-control

Neural Extended State Observer (Neural-ESO) dual-pathway architecture for provably robust learning-based control systems. Combines neural network feedforward disturbance estimation with classical ESO corrective pathway, guaranteeing uniform ultimate…

neural-fields-world-models

Neural Fields as World Models methodology — isomorphic world models that preserve sensory topology for physics prediction as geometric propagation rather than abstract state transition. Motor-gated neural fields with local lateral connectivity and…

neural-interface-safety-audit

Safety audit framework for neural interface models. Identifies three alignment failures: verification insufficiency (certificates pass while accuracy drops), proxy-fidelity divergence (task optimization damages neural signals), and latent information…

neural-inverse-design-scintillator-medical

Neural network inverse design of nanophotonic scintillators for medical imaging. Uses physics-informed neural networks to learn scintillation cascade processes from incident particles to photon emission, enabling end-to-end differentiable optimization of…

neural-lyapunov-verification

Sound and complete verification of neural Lyapunov candidates for nonlinear control systems. Uses hyperplane partitioning of ReLU networks to verify stability guarantees. Use when: (1) verifying neural network controller stability, (2) Lyapunov function…

neural-manifold-dynamics-learning

Neural Manifold Learning Dynamics methodology for analyzing population activity in high-dimensional neural state spaces. Extracts low-dimensional structure from neural recordings to understand computation and behavior. Combines dimensionality reduction with…

neural-manifold-learning-dynamics

Neural manifold learning dynamics methodology for analyzing population activity in high-dimensional neural state spaces. Extracts low-dimensional structure from neural recordings to understand computation and behavior. Activation triggers: neural manifold,…

neural-manifolds-crystallized-embeddings

Neural manifolds as crystallized embeddings: a synthesis of free energy principle, generalized synchronization, and Hebbian plasticity. Proposes that neural manifolds emerge developmentally through three interacting processes: dynamical contraction (free…

neural-mass-models-unified

Unified Rosetta Stone framework for neural mass models. Provides mathematical tools connecting different neural mass model formulations for brain dynamics analysis across scales from single-neuron spiking to macroscopic fMRI/MEG/EEG. Applies to: brain…

neural-network-quantum-states-grand-canonical

Neural network quantum state (NQS) architecture for grand canonical ensemble bosonic systems. Enables variational Monte Carlo with variable particle number in Fock space. Activation: neural quantum states, grand canonical ensemble, bosonic wavefunctions, Fock…

neural-operator-adaptive-pde-control

Dual-learning architecture combining online adaptive control with offline neural operator approximation for backstepping control of nonlinear hyperbolic PDEs with unknown Volterra series. Use when controlling PDE systems where gain computation is…

neural-operator-stability-discovery

Neural operator framework for data-driven discovery of stability and receptivity properties in physical systems. Activation: neural operator, stability discovery, receptivity analysis, dynamical systems.