The Detection Instability task evaluates whether an evolved Dynamic Neural Field (DNF) architecture can reliably detect a transient external stimulus and propagate this detection to an output field.

The desired behaviour is:

1. An external stimulus induces a localised activation peak in the input field.
2. This peak is self-stabilized during stimulus presentation.
3. Activity is transmitted to the output field, which also forms a corresponding peak.
4. After stimulus offset, both fields relax back to baseline (no persistent memory).

This task tests the most fundamental Dynamic Field Theory mechanism: stimulus-driven detection without memory.

---

The highest-fitness solutions consistently converge to a minimal topology:

• Fields: 2 (input → output)
• Hidden fields: 0
• Connections: 1 excitatory feedforward coupling
• Dynamics: Gaussian lateral interaction kernels within each field

phenotype-detection-wbg

The figure above shows:

• Blue: activity during stimulus presentation
• Red: activity after stimulus removal

Both fields exhibit a stimulus-driven peak that disappears once the input is removed, matching the detection instability criterion.

---

Analysed 100 runs; 100 reached the fitness threshold (100.0% success, threshold = 0.950)

• Mean: 1.00
• Median: 1.00
• Std: 0.00

• Mean convergence rate (fitness gain/gen): 0.2267
• Mean fitness improvement/gen: 0.2267

• Hidden fields (mean ± std): 0.00 ± 0.00
• Enabled connections (mean ± std): 1.00 ± 0.00

label	run	value
Highest max fitness	2026年01月23日 10h11m26s	0.974337
Lowest max fitness	2026年01月23日 10h28m18s	0.959235
Fastest to threshold	2026年01月23日 09h46m06s	1.0
Slowest to threshold	2026年01月23日 09h46m06s	1.0
Most hidden fields	2026年01月23日 09h46m06s	0.0
Most enabled connections	2026年01月23日 09h46m06s	1.0

---

This section reports detailed statistics from the evolutionary run that produced the highest-fitness solution for the Detection Instability task.

Final generation: g = 1

• Best fitness: 0.9743
• Target fitness: 0.950
• Average fitness: 0.7251

Overall run statistics

• Max best fitness: 0.9743 (reached at generation 1)
• Mean best fitness over run (AUC): 0.8561
• Mean average fitness over run (AUC): 0.6699
• Longest stagnation period: 0 generations
• Target fitness first reached: generation 1 (best fitness ≈ 0.9743)

Final generation (g = 1)

• Species: 2
• Active species: 2

Across run

• Total distinct species created: 1
• Species extinct by final generation: 0
• Average species per generation: 1.50
• Average active species per generation: 1.50
• Max active species in a generation: 2 (at g = 1)

Species lifetime & size

• Average species lifespan: 1.00 generations
• Longest-lived species: 0 (lifespan 1)
• Average max members per species: 1000.00
• Average offspring per species: 0.00

Final generation (g = 1)

• Avg genome size: 2.15
• Avg field genes: 2.00
• Avg connection genes: 0.15

Growth over run

• Genome size change: +0.15 (≈ +0.146 / gen)
• Field genes change: +0.00 (≈ +0.000 / gen)
• Connection genes change: +0.15 (≈ +0.146 / gen)

Ratios

• Avg connections per field (final gen): 0.07

• Field kernels:

  • Gaussian: 1609 (80.5%)
  • Mexican-hat: 391 (19.6%)

• Interaction kernels: none

Generation: 1 Fitness: 0.9743

Field	Role	Kernel type	Field parameters	Kernel parameters
nf 1	Input	Gaussian	h = -14.98, τ = 91.03	A = 14.04, σ = 9.32, A_glob = -0.19
nf 2	Output	Gaussian	h = -2.12, τ = 84.91	A = 5.95, σ = 9.82, A_glob = -0.13

Interaction gene	From → To	Kernel parameters
gk cg 1-2-0	nf 1 → nf 2	A = 20.49, σ = 3.70, A_glob = -0.05

detection.mp4

The best Detection Instability solution:

• Emerged immediately (generation 1)
• Required no speciation pressure
• Exhibited minimal structural growth
• Used only Gaussian kernels for both fields and interactions

This confirms that detection behaviour lies at the base of the evolutionary search space, serving as a stable attractor for neat-dnfs.

---

Detection Instability is trivially solvable for neat-dnfs:

• Evolution converges in a single generation.
• The minimal architecture is sufficient and consistently rediscovered.
• This task serves as a baseline sanity check for stimulus propagation and transient peak formation.