{"data":{"id":"9df551f7-211a-430c-95ea-05796220760e","title":"Evaluate thermodynamic amplification in a critical neural-network model","publicSummary":"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.","field":"Computational neuroscience / statistical physics","claimType":"paper_review","authorship":"human_ai_assisted","status":"open","bountyAmountCents":25000,"currency":"USD","reviewWindowDays":14,"requestedDeliverables":["Written review memo","Prior-art map","Code or reproduction package"],"publicMaterials":[{"label":"CRCNS HC-3 dataset and documentation","url":"https://crcns.org/data-sets/hc/hc-3/about-hc-3"}],"fundedAt":"2026-08-02T21:16:34.28099+00:00","publicUrl":"https://rigorloop.com/claims/9df551f7-211a-430c-95ea-05796220760e","createdAt":"2026-08-02T21:13:15.92438+00:00","updatedAt":"2026-08-02T21:16:34.281158+00:00"}}