Individual skill
tooluniverse-neurosynth-meta-analysis
Meta-analytic decoding of human fMRI coordinates using the Neurosynth coordinate database (14,371 studies, ~3,228 cognitive/neuroscience terms) — given an MNI brain coordinate, statistically identify which cognitive terms are over-represented in studies reporting activation there ("reverse inference"); given a term, find the studies and coordinates most associated with it ("forward" lookup). Use when someone asks "what does this brain coordinate/region do", "decode this fMRI activation peak", "what terms are associated with [MNI coordinate]", "find studies about [cognitive term] and their activation coordinates", or "reverse-infer cognitive function from a brain location". This is real local analysis on a downloaded, cached coordinate database — not a live API — following ToolUniverse's honesty-contract pattern (real computed statistics, no fabricated term associations).
plugin/skills/tooluniverse-neurosynth-meta-analysis/SKILL.md
Source commit 5598a9fc97e32964fe9b703818e7d0747142f179
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 5, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 1,779
- Repository last updated
- Nov 8, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agents Repository topic
- reasoning-agent Repository topic
- reasoning-language-models Repository topic
- tool-use Repository topic
- ai-agents Repository topic
- ai-scientists Repository topic
- automated-science Repository topic
- co-pilot Repository topic
- co-scientist Repository topic
- ai-for-science Repository topic
- data Derived category
- legal Derived category
- data-databases Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 7,301 bytesSKILL.mdcore · 7,301 bytesSKILL.mdcore · 7,301 bytesSKILL.mdcore · 7,301 bytesreferences/method.mddoc · 5,287 bytesscripts/_neurosynth_data.pyruns · 2,382 bytesscripts/decode_coordinate.pyruns · 6,509 bytesscripts/download_data.pyruns · 4,318 bytesscripts/search_by_term.pyruns · 4,112 bytes
Read excerpt
# Neurosynth Meta-Analytic Coordinate Decoding
Statistically decode human fMRI brain coordinates against ~14,000 published neuroimaging studies, or look up which studies/coordinates are associated with a cognitive term — using the real, freely-downloadable Neurosynth coordinate database (no API key, no login).
## Honesty contract (read first)
This skill downloads a real coordinate database and runs real statistics on it. It must never fabricate a term association, a study result, or a p-value.
1. **Preflight before anything.** Run `scripts/download_data.py` first. If any file fails to download, STOP and report the failure — do not proceed with partial data or describe hypothetical decoding results.
2. **Never guess a term.** `search_by_term.py` requires an exact (case-sensitive) vocabulary match. If the term isn't found, it returns suggestions (substring matches, or close spellings when there are none, e.g. `hipocampus` → `hippocampus`) — use those, don't invent a plausible-sounding term.
3. **Report the multiple-testing caveat every time.** `decode_coordinate.py` tests ~3,228 terms simultaneously per query. Uncorrected p-values will produce false positives at this scale — always surface the FDR-corrected `fdr_q_value`, not just the raw `p_value`, when characterizing how confident a result is.
4. **This is a simplified reverse-inference test, not a full meta-analysis pipeline.** It does binary term-presence comparison (near-coordinate studies vs. rest of corpus) via a two-proportion z-test — a real, defensible statistical test, but not the same as running NiMARE's full activation-likelihood-estimation (ALE) or multilevel kernel density analysis (MKDA) methods. Say so if precision matters (e.g., the user is drafting something for publication).
5. **Never overwrite the cached data files** — `download_data.py` writes to a dedicated cache directory and is idempotent (skips re-download if already cached, unless `--force`).