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V1-PFC Dual Column

Open in Colab

Two cortical columns (V1 and PFC) with inter-areal connections. Explore cross-area dynamics.

Configuration

import jaxfne as jtfne

cfg = (
    jtfne.configuration()
    .network(
        n=1200,
        areas={"V1": 600, "PFC": 600},
        layers={"V1": ["L1", "L2/3", "L4", "L5", "L6"], "PFC": ["L1", "L2/3", "L5", "L6"]},
        inter_areal_connectivity={"V1→PFC": 0.15, "PFC→V1": 0.10}
    )
    .emitter(family="izhikevich", preset="cortical_eig")
    .field(domain="dual_laminar_column")
    .probe(name="v1_pfc_dual", modes=["spikes", "LFP", "traveling_waves"])
)

model = jtfne.construct(cfg)

Explore inter-areal dynamics

signals = model.simulate(...)

readouts = model.compute_readout(signals, [
    jtfne.readout_spec("V1_rate", "spike_rate_hz"),
    jtfne.readout_spec("PFC_rate", "spike_rate_hz"),
    jtfne.readout_spec("cross_area_coherence", "coherence"),
])

Key features

  • Bi-directional V1 ↔ PFC connections
  • Laminar specificity: V1 L4 → PFC L1, PFC L5 → V1 L1
  • LFP-proxy shows areal-specific spectral signatures
  • Traveling-wave analysis (reserved) for inter-areal phase dynamics

Applications

  • Attention and gain modulation (V1 ← PFC feedback)
  • Perceptual binding and temporal coordination
  • Visual working memory circuits

Next steps

See Guides for how-to articles on extending these models.