neuro
the domain of minds and brains. neuro covers everything from the axon firing an action potential to the emergence of consciousness in a network of 86 billion neurons. the central puzzle: how does subjective experience arise from objective matter? neuro does not yet answer this, but it maps the territory
for cyber, neuro is the reference architecture. the protocol's vocabulary — neuron, particle, cyberlink, synapse — is borrowed from neuroscience deliberately. a Bostrom neuron (account) links particles (content) through typed cyberlinks (edges) weighted by stake. this mirrors biological neural networks where neurons link through synapses weighted by connection strength. cyberank is the protocol's attention mechanism. the free energy principle — the brain minimizes surprise — is the conceptual ancestor of cyber's focus minimization
scope
cellular — axon, neurons, synapses, neurotransmitters, thalamus, nerves. the hardware of thought. signals propagate electrically along axons and chemically across synapses
circuits — neural networks, brain, cortical layers, hippocampus, cerebellum. specialized circuits process different information: vision, motor control, memory, emotion. the brain is a modular parallel processor
cognition — attention, memory, learning, predictive coding, active inference, Markov blanket, Karl Friston. how the brain builds models of the world and acts on predictions. the free energy principle unifies perception, action, and learning under one objective: minimize surprise
consciousness — consciousness, qualia, self-awareness, whole brain emulation, brain emulation. the hard problem. neuro maps the neural correlates but the explanatory gap persists
collective — distributed cognition, collective computation, stigmergy, swarm intelligence algorithms. minds do not stop at the skull. groups of agents — biological or digital — exhibit emergent intelligence. the cybergraph is designed to be a collective mind
bridges
- neuro → bio: brains are biological organs. neurons are cells. neuroscience is biology at the circuit level
- neuro → info: the brain is an information processor. Shannon entropy quantifies neural signals
- neuro → comp: neural networks inspired artificial ones. brain emulation is computation's attempt to replay biology
- neuro → ai: deep learning is a crude approximation of neural computation. training mimics synaptic plasticity
- neuro → sense: the brain processes sensory input. perception is neural interpretation of signals
- neuro → cyber: the protocol replicates neural architecture at planetary scale. neurons, synapses, weights, attention