Step 1
Start with a messy research question
A neuroscience question usually arrives with unclear datasets, fragile assumptions, and many possible analysis paths.
Understand BR
From question to reviewable research workflow
Brain Researcher turns a neuroscience question into an evidence-linked plan, a workflow handoff, and a reportable trail that a researcher can inspect.
Question
Evidence
Handoff
Mental model
Question to evidence to workflow to review
The storyboard below is the simplest way to read BR: it is not just a chat box, and it is not just a notebook. It is the connective layer between research intent, evidence, methods, execution surfaces, and human review.
Step 2
Organize the question
BR turns the question into a structured intent: what evidence is needed, what data could support it, and what needs review.
Step 3
Connect evidence and resources
The system links papers, datasets, brain concepts, tools, and prior runs so the plan is not just a prompt.
Step 4
Build a reviewable workflow
BR proposes a plan with visible assumptions, candidate methods, expected inputs, and handoff boundaries.
Step 5
Hand it to the right surface
The same work can move into Hub, Studio, MCP, Cursor, Codex, Claude Code, or a more controlled runtime.
Step 6
Review the result, not just the answer
The researcher checks evidence, report artifacts, assumptions, and failure modes before treating a result as useful.
What BR contains
One research context across multiple surfaces
Each surface has a narrower job. Together they keep the research question, evidence, datasets, workflows, and agents aligned.
Datasets
Find research datasets and inspect readiness before choosing an analysis path.
Workflows
Start from curated analysis workflows instead of rebuilding every plan from scratch.
Knowledge Graph
Use graph-backed concepts, evidence, papers, tasks, datasets, and tools to pressure-test a plan.
MCP
Connect BR to the coding agents and IDEs where research work already happens.
Hub / Studio
Use a browser workspace for notebooks, runs, review context, and research activity.
Demos
Inspect concrete case reports and evidence bundles before starting your own workflow.
BR is
- A planning, evidence, and workflow handoff layer for neuroscience research.
- A way to keep datasets, methods, reports, and agents connected through one research context.
- A review surface where assumptions and execution boundaries stay visible.
BR is not
- Not a guarantee that a scientific conclusion is correct.
- Not a replacement for researcher judgment, peer review, or dataset access rules.
- Not a claim that every workflow is fully executable in every runtime today.
Next step
Move from understanding to inspecting
Start with public case reports, open the hosted workspace, or connect BR to the agent environment where you already work.
For implementation details, read the code map.
Open CodeWiki