the suppressive signal in the cybergraph where ICBS markets reduce the effective weight of disbelieved cyberlinks. analogous to inhibitory synapses in biological neural networks
mechanism
in a standard graph, every cyberlink contributes positively to attention flow. market inhibition introduces a negative channel: when a prediction market on a link's validity resolves against the link, the market outcome scales down its weight
$$w_{\text{eff}}(\ell) \;=\; w(\ell) \cdot \bigl(1 - \alpha \cdot m(\ell)\bigr)$$
where $w(\ell)$ is the original stake-weighted strength, $m(\ell) \in [0, 1]$ is the market's disbelief signal, and $\alpha$ is the inhibition coefficient
computational equivalence
excitation alone produces a directed weighted graph. adding inhibition makes the cybergraph computationally equivalent to a neural network:
| biological | cyber |
|---|---|
| excitatory synapse | staked cyberlink with positive weight |
| inhibitory synapse | market-suppressed cyberlink |
| neurotransmitter balance | stake vs. disbelief ratio |
the tri-kernel processes both signals simultaneously: diffusion spreads excitation, while market inhibition dampens unreliable paths
economic dynamics
inhibition carries a cost. a neuron that inhibits a link must stake into the ICBS market against it. if the link turns out to be valid, the inhibitor loses stake. this symmetry ensures that both belief and disbelief are costly — cheap talk in either direction is eliminated
see cyberlinks, cybergraph, ICBS, tri-kernel, attention, tru
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