awesome-cognitive-and-neuroscience-skills

Guides ACT-R cognitive model construction: chunk types, production rules, subsymbolic parameters, and model validation

Domain-validated guidance for designing Alternative Uses Task (AUT) experiments measuring divergent thinking, with parameters for AI-augmented and traditional conditions

Domain-validated guidance for building hierarchical Bayesian cognitive models with Stan/PyMC: prior specification, model structure, MCMC diagnostics, and posterior predictive checks

Advises on functional/effective connectivity methods: PPI, DCM, Granger causality, graph theory

Domain-validated pipeline guidance for calcium imaging data analysis: motion correction, ROI extraction, neuropil correction, spike inference, and quality control

Expert guidance for selecting and parameterizing cognitive psychology experimental paradigms based on research questions

Domain-specific statistical power analysis guidance for cognitive and neuroscience research, encoding effect size priors and sample size recommendations by modality

Domain-specific statistical modeling guidance for cognitive science and neuroscience, encoding when and how to apply mixed models, correction methods, Bayesian approaches, and effect size reporting

Domain-specific visualization best practices for cognitive and neuroscience data, encoding plot type selection, color standards, and publication formatting

One-command skill contribution — generate a SKILL.md from your domain expertise and submit to GitHub Issues for maintainer review

Domain-validated guidance for SEM-based mediation analysis of creative self-efficacy and moderation by baseline creativity in AI-augmented creativity research

Domain-validated multi-dimensional scoring system for divergent thinking tasks, including fluency, flexibility, originality, and automated semantic distance methods

Expert guidance on selecting, fitting, and evaluating drift-diffusion models for two-choice response time data in cognitive science

Expert guidance for designing EEG paradigms optimized to isolate specific ERP components, with domain-validated timing, trial count, and control condition parameters

Guides EEG preprocessing: filtering, artifact rejection (ICA/ASR), re-referencing, interpolation

Domain-validated pipeline and parameter guidance for event-related potential analysis, from preprocessing through statistical testing

Advises on when to use DDM vs. LBA vs. race models for choice-RT data based on experimental design and research goals

Domain-validated guidance for fMRI General Linear Model specification: HRF modeling, design matrix construction, contrast definition, confound regression, and statistical inference

Domain-validated guidance for fMRI preprocessing decisions: motion correction, slice timing, spatial normalization, smoothing, confound regression, and quality control

Guides fMRI task design: block vs. event-related vs. mixed; jittering; contrasts; power for BOLD detection

Designs habituation and preferential-looking paradigms with age-appropriate timing parameters and exclusion criteria

Advises on lesion-symptom mapping methods: VLSM, disconnection analysis, network lesion mapping

Domain-validated methods and decision logic for neural decoding, RSA, temporal generalization, and encoding models in systems neuroscience

Guides dimensionality reduction and latent-variable analysis of neural populations (PCA, GPFA, dPCA)

Sample-size planning for fMRI/EEG studies using effect-size benchmarks and simulation-based power

Simulation-based sample-size planning for neuroimaging studies using effect-size maps

Domain-validated decision logic for selecting neuropsychological test batteries matched to suspected cognitive deficit profiles

Domain-validated decision logic for optogenetic stimulation parameter selection, including opsin choice, light delivery, pulse protocols, fiber placement, and control conditions

Interactive skill that guides extraction of research paradigms and methodological techniques from cognitive science papers into structured, reusable skills

Guides parameter recovery studies to validate model identifiability before trusting fitted parameter values

Guides analysis of eye-tracking reading measures including first fixation, gaze duration, regression path, and total reading time

Core scientific methodology principles: research planning, method justification, assumption checking, and human-in-the-loop decision making for cognitive science and neuroscience

Expert guidance for designing self-paced reading experiments: region segmentation, timing parameters, comprehension probes, and spillover analysis

Specifies norming procedures for linguistic stimuli including cloze probability, plausibility ratings, acceptability judgments, and lexical controls

One-command community case sharing — capture research context from your session and submit to GitHub Discussions

Generate and share anonymized skill usage statistics to help the community understand which skills are most valuable

Domain-validated decision logic, formulas, and interpretation guidelines for applying Signal Detection Theory to cognitive science data

Assists building spiking neural network simulations: neuron models, connectivity, plasticity rules

Selects Theory of Mind tasks matched to target population, age, and construct with psychometric guidance

Interactive skill verification — assess accuracy of parameters, citations, and methodology through structured expert review

Specifies display parameters, set sizes, target-distractor similarity, and randomization constraints for visual search experiments