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RAG Knowledge Base
Drop your own neuroscience knowledge files here to improve LLM interpretations.
Supported formats
JSON files (*.json)
Each JSON file should be a flat object mapping region names to descriptions:
{
"Amygdala (AMY)": "The amygdala processes threat detection and fear conditioning. It receives rapid subcortical visual input via the superior colliculus and pulvinar for fast threat assessment...",
"Hippocampal Formation (HPF)": "The hippocampus is essential for episodic memory encoding and spatial navigation. Place cells in CA1 fire at specific locations..."
}
Region names do not need to match the Allen atlas names exactly -- the system uses semantic similarity (embedding search) to find the most relevant knowledge for any query.
Text files (*.txt)
Use ## Region Name headers to separate entries:
## Amygdala (AMY)
The amygdala processes threat detection and fear conditioning...
## Hippocampal Formation (HPF)
The hippocampus is essential for episodic memory encoding...
Partial coverage is fine
You do not need to cover every brain region. The system merges your files with a built-in fallback knowledge base (21 regions). For any region not covered by your files or the fallback, the LLM uses its own training knowledge.
Priority order:
- Your files in this directory (highest priority)
- Built-in fallback knowledge base (
REGION_KNOWLEDGEinsrc/region_analyzer.py) - LLM's own neuroscience training knowledge
Tips
- More detail is better -- include connectivity, cell types, clinical relevance
- Multiple JSON/TXT files are merged automatically
- If two files define the same region, the last one loaded (alphabetical order) wins
- Changes take effect on the next app startup (no need to rebuild anything)