feat: add 7 consolidated cognitive science & neuroscience skills

[HaoxuanLiTHUAI]

PR: Add 7 Cognitive Science & Neuroscience Skills (Consolidated)

Contribution Checklist

• Follows Agent Skills Specification — valid SKILL.md frontmatter, kebab-case naming, directory structure
• Consistent with existing skill documentation format
• Each skill includes license: "MIT" and metadata.skill-author: "LeavesLi" in frontmatter
• All numerical parameters cited with peer-reviewed sources
• Skills placed in scientific-skills/ directory
• Each skill includes Research Planning Protocol and Verification Notice sections
• Consolidated structure: router SKILL.md (<500 lines) + detailed reference files

Summary

This PR contributes 7 consolidated skills for cognitive science and neuroscience research methodology. Each skill serves as a router that guides users to detailed reference files based on their research question, data type, or analysis stage.

All skills originate from awesome_cognitive_and_neuroscience_skills, an open-source collection with MIT license.

Consolidation approach: Each skill's SKILL.md (<500 lines) provides decision trees, method overviews, and routing logic. Detailed methodological guidance lives in references/*.md files (36 total reference files across the 7 skills).

Skills Overview

1. eeg-erp-analysis (283 lines + 3 references)

Complete pipeline for EEG/ERP research: paradigm design, preprocessing, and statistical analysis

• Router guides users through: paradigm design → preprocessing → statistical analysis
• References:
  • eeg-paradigm-designer.md — ERP component isolation, timing parameters, trial counts
  • eeg-preprocessing-pipeline.md — Filtering, ICA/ASR artifact rejection, re-referencing
  • erp-analysis.md — Time window selection, baseline correction, statistical testing

2. fmri-analysis (354 lines + 3 references)

Complete pipeline for fMRI research: task design, preprocessing, and GLM analysis

• Router guides users through: task design → preprocessing → GLM specification
• References:
  • fmri-task-design.md — Block vs. event-related design, jittering, power for BOLD
  • fmri-preprocessing-pipeline.md — Motion correction, normalization, smoothing, QC
  • fmri-glm-analysis.md — HRF modeling, contrast definition, confound regression

3. cognitive-modeling (422 lines + 6 references)

Computational cognitive modeling: symbolic (ACT-R), Bayesian hierarchical, evidence accumulation (DDM/LBA), spiking networks, and model validation

• Router provides decision tree by data type and modeling goal
• References:
  • act-r-model-builder.md — Chunk types, production rules, subsymbolic parameters
  • bayesian-cognitive-model-builder.md — Hierarchical models with Stan/PyMC
  • drift-diffusion-model.md — DDM fitting for choice-RT data
  • evidence-accumulation-selector.md — DDM vs. LBA vs. race model selection
  • parameter-recovery-checker.md — Model identifiability validation
  • spiking-network-model-builder.md — Spiking neural network simulations

4. neuroscience-methods (378 lines + 7 references)

Systems and experimental neuroscience methods: connectivity analysis, calcium imaging, lesion mapping, neural decoding, population analysis, optogenetics, and neuropsychological assessment

• Router provides decision trees by data type, research question, and spatial scale
• References:
  • brain-connectivity-modeler.md — PPI, DCM, Granger causality, graph theory
  • calcium-imaging-analysis-guide.md — Motion correction, ROI extraction, spike inference
  • lesion-symptom-mapping-guide.md — VLSM, disconnection analysis, network lesion mapping
  • neural-decoding-analysis.md — Decoding, RSA, temporal generalization, encoding models
  • neural-population-analysis-guide.md — PCA, GPFA, dPCA for neural populations
  • optogenetics-protocol-designer.md — Opsin choice, light delivery, pulse protocols
  • neuropsych-battery-selector.md — Test battery selection matched to deficit profiles

5. cogsci-experimental-design (483 lines + 9 references)

Experimental paradigm design for cognitive science and neuroscience: cognitive tasks, developmental methods, psycholinguistics, visual attention, creativity research, and Theory of Mind

• Router provides decision trees by population and domain
• References:
  • cognitive-paradigm-design.md — General paradigm selection and parameterization
  • infant-looking-time-designer.md — Habituation and preferential-looking paradigms
  • visual-search-array-generator.md — Display parameters, set sizes, randomization
  • self-paced-reading-designer.md — Region segmentation, timing, spillover analysis
  • sentence-stimulus-norming.md — Cloze probability, plausibility, acceptability norming
  • alternative-uses-task-designer.md — AUT experiments for divergent thinking
  • tom-task-selector.md — Theory of Mind task selection by population and construct
  • creativity-self-efficacy-mediation.md — SEM mediation analysis for creative self-efficacy
  • divergent-thinking-scoring.md — Multi-dimensional scoring for divergent thinking tasks

6. cogsci-statistics (380 lines + 7 references)

Statistical methods for cognitive science and neuroscience: mixed models, power analysis, visualization, signal detection theory, neuroimaging sample size planning, and reading time analysis

• Router provides decision trees by research stage, data type, and research question
• References:
  • cogsci-statistics.md — Mixed models, corrections, Bayesian approaches
  • cogsci-power-analysis.md — Power analysis with domain-specific effect size priors
  • cogsci-visualization.md — Visualization best practices for neuro/cogsci data
  • signal-detection-analysis.md — SDT decision logic, formulas, interpretation
  • neuroimaging-power-guide.md — Sample-size planning for fMRI/EEG studies
  • neuroimaging-sample-size-calculator.md — Simulation-based sample-size planning
  • reading-time-analysis.md — Eye-tracking reading measures analysis

7. research-literacy (289 lines, standalone)

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

• Standalone skill (not a router) — provides meta-methodological guidance
• Embedded in all other skills via Research Planning Protocol

Format

Each skill includes:

• Router SKILL.md (<500 lines) with:
  • YAML frontmatter (name, description, license, metadata.skill-author, review_status, papers)
  • Research Planning Protocol and Verification Notice sections
  • Decision trees and routing logic
  • Brief method overviews with key parameters
  • Cross-references to detailed reference files
• references/ subdirectory with detailed methodological guidance (36 reference files total)
• All numerical parameters cited with peer-reviewed sources

Review Status

All skills are currently review_status: "ai-generated". Parameters and citations have been cross-referenced with source literature but have not yet received formal expert verification.

New Domain Coverage

These skills add a Cognitive Science & Neuroscience category to the repository, complementing the existing bioinformatics, cheminformatics, clinical, and ML skill sets. This fills a gap for researchers working with:

• Neuroimaging: EEG/ERP, fMRI (design, preprocessing, analysis)
• Computational modeling: ACT-R, Bayesian hierarchical models, DDM/LBA, spiking networks
• Experimental neuroscience: Connectivity, calcium imaging, lesion mapping, decoding, optogenetics
• Experimental design: Cognitive paradigms, developmental methods, psycholinguistics, creativity research
• Statistics: Mixed models, power analysis, visualization, SDT, neuroimaging sample size planning

Consolidation Rationale

This PR consolidates 36 original skills into 7 router skills based on reviewer feedback. The consolidation:

1. Reduces skill count from 36 → 7 while preserving all methodological content
2. Improves discoverability via decision trees and routing logic
3. Maintains detail by moving full content to reference files
4. Follows best practices for skill organization (router + references pattern)

Original skill structure preserved in references/ for users who need detailed guidance.

Compatibility Notes

• No modifications to existing skills or repository structure
• All skills are self-contained with no cross-dependencies on other skills in this repo
• Frontmatter adapted to match the repository's conventions (license, metadata.skill-author)
• All router SKILL.md files under 500 lines per specification guidelines