Von Economo Fast Lane Hypothesis

Network Architecture

• Total neurons: 2,000
• VEN fraction:
  • Typical: 2% VENs
  • Autism-like: 0.4% VENs
  • FTD-like: post-training VEN ablation
• Training paradigm: Spiking cortical circuit trained on social discrimination task
• Evaluation: 10 independent random seeds per condition

Key Results

1. Equivalent accuracy: All configurations achieve ~99.4% asymptotic classification accuracy
2. Speed modulation: VENs modulate decision speed rather than representational capacity
3. First-spike latency: VENs produce median first-spike latencies 4 ms earlier than pyramidal neurons
4. Reaction times (mean ± std):
   • Typical: 20.70 ± 2.02 ms
   • Autism-like: 26.91 ± 9.01 ms (p=0.078 vs typical)
   • FTD-like: significantly slower (t=-23.31, p<0.0001)
5. Evolutionary correspondence: Model-optimal VEN fraction corresponds to primate phylogenetic gradient

Implementation Guide

See references/implementation.md for detailed code patterns including:

• Dual LIF neuron model (VEN + Pyramidal)
• Sparse cortical circuit with VEN pathways
• Social discrimination task setup
• Three clinical condition simulations
• Reaction time and latency analysis

Usage

This skill is applicable when:

• Building biologically plausible models of social cognition
• Investigating speed-accuracy tradeoffs in neural circuits
• Modeling neurological conditions (FTD, autism) with spiking networks
• Studying evolutionary neuroscience through computational models

References

• Paper: "The Fast Lane Hypothesis: Von Economo Neurons Implement a Biological Speed-Accuracy Tradeoff"
• arXiv: 2604.09229v1