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Research, evidence gathering, literature, reports, investigation, and synthesis
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Showing 11,857–11,880 of 21,385 skills
- Brain To Text Unified DecodingUnified brain-to-text decoding framework for both speech production and perception in Mandarin Chinese. Uses shared neural representations across modalities with dual-decoder architecture. Activation: brain-to-text decoding, speech BCI, neural speech decoding, unified speech decoding.Votes: 0GitHub stars: 3
- Brain To Language Source AttributionSource attribution framework for MEG-to-audio brain decoding that separates decoding performance into structural shortcuts, stimulus-evoked evidence, and contextual aggregationVotes: 0GitHub stars: 3
- Brain Stimulation Dynamics StateBrain Stimulation Effects on Network DynamicsVotes: 0GitHub stars: 3
- Brain Omnifunctional Foundation ModelBrain-OF unified foundation model for multiple neuroimaging modalities. Activation: omnifunctional model, multi-modal neuroimaging, unified brain analysis.Votes: 0GitHub stars: 3
- Brain Networks Eeg Meg MethodsSkill for EEG/MEG-based brain network analysis covering forward/inverse problems, connectivity measures, and pipelines.Votes: 0GitHub stars: 3
- Brain Llm Memory ComparisonFrom Observation to Intervention: Memory in Brains and Large Language Models - functional comparison framework for memory systems across biological brains and LLMs, focusing on representation, retrieval, updating, and experimental access. Use when analyzing memory mechanisms in AI systems or drawing cross-domain insights between neuroscience and LLM research.Votes: 0GitHub stars: 3
- Brain Llm Key Neurons GrammarBrain-LLM analogy methodology for identifying grammar-specialized neurons in Large Language Models. Uses brain lesion study-inspired approaches to find POS-tag-specific neurons in Llama 3. Activation triggers: grammar neurons, LLM interpretability, part-of-speech, brain-LLM analogy, neuron identification, grammar subspace.Votes: 0GitHub stars: 3
- Brain Inspired Neural Cellular AutomataBrain-inspired Neural Cellular Automata (BraiNCA) for morphogenesis and motor control. Uses biological neighborhood structures beyond regular grids.Votes: 0GitHub stars: 3
- Brain Inspired Gating SnnBrain-inspired gating mechanism for Spiking Neural Networks that unlocks robust computation by incorporating dynamic conductance mechanisms. Addresses limitations of conventional LIF neurons that omit conductance dynamics inherent in biological neurons. Based on arXiv:2509.03281.Votes: 0GitHub stars: 3
- Brain Inspired Capture Evidence DrivenBrain-Inspired Capture (BI-Cap) methodology for evidence-driven neuromimetic perceptual simulation in visual decoding. Trigger words: BI-Cap, neuromimetic, perceptual simulation, visual decoding, HVSVotes: 0GitHub stars: 3
- Brain Guided Llm Reasoning AlignmentBrain-guided language model framework for robust reasoning - using task-fMRI signals from reasoning regions to enhance LLM performance across 10 models with up to 13% accuracy gainVotes: 0GitHub stars: 3
- Brain Foundation Model InversionBrain foundation model inversion methodology using Simulation-Based Inference (SBI) for stimulus reconstruction from synthetic neural activity. Enables reverse application of brain emulators like TRIBEv2 to recover stimuli or their properties from neural responses. Keywords: brain foundation model inversion, SBI, simulation-based inference, TRIBEv2, stimulus reconstruction, neural decoding, inverse problem neuroscience.Votes: 0GitHub stars: 3
- Brain Foundation Model Batch EffectsAnalysis and mitigation of batch effects in fMRI foundation model embeddings. Activation: batch effects, fMRI foundation models, embedding quality.Votes: 0GitHub stars: 3
- Brain Dit Universal Multi StateBrain-DiT universal multi-state fMRI foundation model methodology. Integrates diffusion transformer architecture with fMRI data for generative modeling and brain state analysis. Covers multi-state fMRI generation, brain state transition modeling, and foundation model fine-tuning for neuroscience applications. Use when working with fMRI foundation models, brain state generation, diffusion models for neuroimaging, or multi-state neural dynamics simulation.Votes: 0GitHub stars: 3
- Brain Dit Fmri Foundation ModelBrain-DiT universal multi-state fMRI foundation model with metadata-conditioned diffusion pretraining. Trigger words: Brain-DiT, fMRI foundation model, diffusion transformer, multi-state, metadata-conditionedVotes: 0GitHub stars: 3
- Brain Dit Fmri Foundation Model V6Brain-DiT v6 universal multi-state fMRI foundation model with metadata-conditioned pretraining across 24 datasets covering resting, task, naturalistic, disease, and sleep states. Use when working with fMRI foundation models, brain state decoding, or multi-state neuroimaging.Votes: 0GitHub stars: 3
- Brain Digital Twins Execution Semantics V3Framework for brain digital twins centered on execution semantics, bridging computational brain models to executable systems. Unifies fragmented data pipelines, model classes, and temporal scales. Activation: brain-digital-twins, execution-semantics, neuromorphic, modeling, neuroscience, brain, neuralVotes: 0GitHub stars: 3
- Brain Criticality Milro AssessmentMemory-Induced Long-Range Order (MILRO) assessment framework challenging the brain criticality hypothesis. Analyzes scale-invariant correlations in neural activity as stable phase rather than critical point. Keywords: brain criticality, MILRO, scale-free, neural correlations, memory-induced orderVotes: 0GitHub stars: 3
- Brain Criticality Hypothesis AssessmentCritical assessment methodology for evaluating the brain criticality hypothesis. Proposes Memory-Induced Long-Range Order (MILRO) as an alternative explanation for scale-invariant correlations in neural activity. Use for analyzing neural avalanches, criticality claims, and brain dynamics theory. Keywords: brain criticality, MILRO, neural avalanches, scale-invariant correlations, memory-induced long-range order, critical point.Votes: 0GitHub stars: 3
- Brain Criticality AssessmentCritical assessment methodology for evaluating the brain criticality hypothesis using rigorous statistical and computational approaches. Use for analyzing criticality in neural systems, avalanche dynamics, and evaluating claims of critical brain states. Keywords: criticality, neural avalanches, brain networks, critical states, statistical mechanics, power laws.Votes: 0GitHub stars: 3
- Brain Critical Dynamics HierarchicalHierarchical organization of critical brain dynamics. Analyze how brain networks exhibit critical behavior across multiple scales, including neuronal avalanches, power-law distributions, and long-range temporal correlations. Use when studying brain criticality, neural avalanches, scale-free dynamics, phase transitions in neural systems, or multi-scale brain network analysis. Combines renormalization group theory, statistical physics, and network science approaches.Votes: 0GitHub stars: 3
- Brain Cliplm Semantic Compression EegBrain-CLIPLM semantic compression framework for EEG-to-text decoding. Two-stage methodology: semantic anchor recovery via contrastive learning + anchor-guided sentence reconstruction with retrieval-grounded LLM. Key principle: granularity matching - aligns decoding complexity with recoverable neural information scale. Use when: (1) EEG language decoding tasks, (2) brain-to-text translation, (3) neural signal semantic extraction, (4) cognitive state reconstruction from EEG, (5) sentence-level ...Votes: 0GitHub stars: 3
- Brain Cause Causal Visual RepresentationsBrainCause methodology for discovering and causally validating visual representations in the human brain using generative models, counterfactual stimulus synthesis, and fMRI encoding models. Use when: (1) studying causal vs correlational brain representations, (2) designing controlled fMRI experiments with counterfactual stimuli, (3) validating whether brain regions truly represent specific visual concepts beyond activation-based localization, or (4) applying generative AI to neuroscience bra...Votes: 0GitHub stars: 3
- Brain Cause Causal Visual RepresentationCausal visual representation discovery framework for neuroscience. Use when analyzing brain region representations through causal testing rather than mere activation maximization. Covers counterfactual stimulus generation, image-to-fMRI encoding models, automated functional localization validation, and follow-up experiment design. Triggers: causal neuroscience, brain representation, counterfactory fMRI, visual concept localization, activation causality, functional localization validation, Bra...Votes: 0GitHub stars: 3