Route:
Problems

P7 · Putting It Together

A mini-project using all routes

A short guided mini-project using all three routes. Do it once with the API and once conversationally, and compare.

Key question: Region → intrinsic types → pick one → visualise → partners → cross-dataset match → expression.

Route A: Python API

A guided mini-project that uses all the tools together.

from vfb_connect import vfb
import navis

# 1. Find neurons in a region
region_neurons = vfb.get_terms_by_region("mushroom body")

# 2. Pick one and get its instances
instances = vfb.get_instances(region_neurons['type'].iloc[0])

# 3. Visualize
skeletons = vfb.get_skeletons(instances['vfb_id'].head(3).tolist())
navis.plot3d(skeletons)

# 4. Get connectivity
partners = vfb.get_neurons_downstream_of(instances['vfb_id'].iloc[0], top_n=5)

# 5. Find cross-dataset matches
matches = vfb.get_similar_neurons(instances['vfb_id'].iloc[0])

# 6. Check expression
expression = vfb.get_transcriptomic_profile(region_neurons['type'].iloc[0])

Route B: MCP Tool

Chain multiple queries together in a conversation.

Example Prompt

Starting from the mushroom body: find its intrinsic neuron types, pick one, show it, list its main partners, find its closest match in another connectome, and summarise any expression data — give me all the VFB IDs so I can reproduce this in vfb_connect.

Route C: VFB Chat

Walk through the same chain one question at a time in chat. Each question builds on the previous answer.

Step-by-step prompts:

  1. “What neuron types are intrinsic to the mushroom body?”
  2. “Show me instances of [type from step 1] with VFB IDs”
  3. “What are the top 5 downstream partners of [ID from step 2]?”
  4. “Find the cross-dataset match for [ID from step 2] in another connectome”
  5. “What expression data exists for [type from step 1]?”

Route D: 3D Circuit Browser

Explore the complete workflow in the Circuit Browser.

When to Reach for Which Route

This is where the three routes complement each other most:

  • Chat/MCP for exploration and hypothesis generation
  • Python API for reproducible analysis and figures
  • 3D Browser for spatial understanding throughout

A good habit: explore with chat/MCP, capture the IDs, then reproduce with vfb_connect.