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name: spatial-models description: "Build Brian2 2.9.0 morphologies and multicompartment SpatialNeuron models, attach and index sections, load coordinate data safely, and inspect spatial state without confusing current densities with point currents." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Spatial models

Use this route when the task needs a neuronal morphology, a branched or multicompartment SpatialNeuron, geometry-aware compartment state, or spatial selection such as a soma, branch, distance interval, or morphology index.

Route

1. Choose the geometry representation and validate its compartment count. Use Soma, Cylinder, and Section for small schematic models; use Morphology.from_points or Morphology.from_file for reconstructed coordinate data. Follow morphology-workflows.md.
2. Attach sections only to a Morphology object, inspect topology(), and use indices or morphology slices to make selections. Read the API details in api-reference.md.
3. Create SpatialNeuron with a model containing one unflagged Im equation with units of amp/meter**2, and pass explicit, unit-bearing Cm and Ri values for a reproducible workflow. Brian2 2.9.0 supplies defaults for Cm/Ri, but this route treats them as required model inputs. Distinguish distributed surfacic current from an amp point current; see the current and unit checks in troubleshooting.md.
4. Initialize v and per-compartment parameters, then run a short bounded simulation. For spatial traces, use a recording tool such as StateMonitor; detailed monitor selection and analysis belong to the recording route.
5. Check area, distance, diameter, length, volume, space_constant, and time_constant on the exact compartment or subgroup being interpreted. Remember that varying quantities are reported at compartment midpoints.

For a safe end-to-end smoke check, run:

python scripts/spatial_smoke.py --help
python scripts/spatial_smoke.py --constructor-only
python scripts/spatial_smoke.py

The script is intentionally tiny and CPU-oriented. --constructor-only checks morphology, Im, explicit Cm/Ri, and derived geometry without SciPy; the full invocation additionally requires the SciPy-backed NumPy diffusion path. Neither mode replaces a backend-aware validation run, a Rallpack benchmark, or an external morphology review.

Scope boundaries

• Generic unit syntax, equation parsing, state updaters, and differential equation design route to units-and-equations.
• Monitor classes, recording schedules, and trace analysis route to recording after this route supplies the spatial selection.
• Large Rallpack runs, external morphology repositories, native backends, and long simulations are explicit gaps: do not silently launch them from this route.

Failure-first checks

• Missing Im is a construction error, not a default passive model. The constructor does not reliably reject an Im written with total-current dimensions, so validate that Im is amp/meter**2 rather than assuming a failed constructor is the unit check.
• Im is a current density; a total current must be declared as amp (point current) so Brian2 divides it by area.
• Pass Cm as specific capacitance (farad/meter**2) and Ri as shared intracellular resistivity (ohm*meter) with explicit unit-bearing values; finalize Ri before the first run.
• A child section must be attached before the neuron is constructed. After construction, use the copied neuron morphology. neuron.branch includes a branch's descendants, while neuron[morph.branch] selects only that section's own compartments; do not mutate the source tree and expect the neuron to change.
• SWC/points input must be ordered parent-before-child and use seven fields; file input currently supports SWC only.
• If a NumPy-target spatial run reports missing SciPy, install/enable the required package in the active Brian2 environment or choose an explicitly supported backend; do not hide the dependency by changing equations.