import React from 'react';
const GANGLIONS = [
{ id: 'G1', name: 'Cortex', icon: '🧠', desc: 'Analytical reasoning' },
{ id: 'G2', name: 'Creatif', icon: '🎨', desc: 'Creative generation' },
{ id: 'G3', name: 'Memory', icon: '💾', desc: 'Context retrieval' },
{ id: 'G4', name: 'Social', icon: '👥', desc: 'Social intelligence' },
{ id: 'G5', name: 'Exec', icon: '⚡', desc: 'Task coordination' },
{ id: 'G6', name: 'Finance', icon: '💰', desc: 'Financial decisions' },
{ id: 'G7', name: 'Security', icon: '🛡️', desc: 'Risk assessment' },
{ id: 'G8', name: 'Spatial', icon: '🗺️', desc: 'Data navigation' }
];
function NeuralMeshMini({ ganglions, expanded = false }) {
return (
<div className="neural-mesh-mini">
<h3>Neural Mesh ({ganglions}/8 Active)</h3>
<div className="ganglions-grid">
{GANGLIONS.map((g, idx) => (
<div
key={g.id}
className={`ganglion ${idx < ganglions ? 'active' : ''}`}
title={g.desc}
>
<div className="ganglion-icon">{g.icon}</div>
<div className="ganglion-name">{g.name}</div>
</div>
))}
</div>
{expanded && (
<div style={{ marginTop: '16px', fontSize: '12px', color: 'var(--text-secondary)' }}>
<p>Consensus Protocol: 70% AGREE threshold</p>
<p>Synapse Adaptation: Hebbian learning (+0.01/success)</p>
<p>Quantum Routing: O(1) superposition collapse</p>
</div>
)}
</div>
);
}
export default NeuralMeshMini;
