Evaluate thermodynamic amplification in a critical neural-network model

This project proposes that a small perturbation applied to highly connected nodes near a neural network’s critical point can produce a much larger system-wide response. Small-world Ising-network simulations report substantial changes in network magnetization after biasing approximately 10% of the highest-degree nodes. The model’s avalanche behavior was compared with derived neural-avalanche measurements from six selected sessions in the CRCNS HC-3 rat hippocampal dataset. This Research Bounty seeks an independent technical assessment of whether the reported amplification represents a meaningful mechanism beyond the expected sensitivity of a critical network, how strongly the computational evidence supports that interpretation, and what experiment would most decisively test it.