Suite No. 1: Computational Biophysics¶

This notebook teaches the public jaxfne grammar.

cfg = jtfne.Configuration()
model = jtfne.construct(cfg)
signals = jtfne.simulate(model, ...)
objectives = jtfne.rate_targets(...)
optimizer = jtfne.agsdr(...)
result = model.tune(objectives=objectives, optimizer=optimizer)

Learning objectives¶

Configure single-neuron Izhikevich dynamics.
Build an E/I population model.
Compute source, field, and probe proxy readouts.
Run multi-objective AGSDR tuning.

Runtime settings¶

duration_ms = 1000.0
dt_ms = 0.1
dtype = float32
deterministic seed
JSON-safe summaries
PNG figures

Figures¶

The notebook writes PNG files under:

figures/suite_no1/

Core figures:

voltage/state trace
source proxy
population raster
population rate
connectivity matrix
laminar readout
tuning summary