diff --git a/index.html b/index.html
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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Exponential Tendrils</title>
+    <style>
+        body {
+            margin: 0;
+            overflow: hidden;
+            background: #0a0a0a;
+            display: flex;
+            justify-content: center;
+            align-items: center;
+            height: 100vh;
+            font-family: 'Courier New', monospace;
+        }
+        canvas {
+            display: block;
+        }
+        #attribution {
+            position: fixed;
+            bottom: 20px;
+            left: 50%;
+            transform: translateX(-50%);
+            color: #555;
+            font-size: 10px;
+            font-family: 'Courier New', monospace;
+            text-align: center;
+        }
+    </style>
+</head>
+<body>
+    <canvas id="canvas"></canvas>
+    <div id="attribution">neurameba · motd.social</div>
+    <script>
+        const canvas = document.getElementById('canvas');
+        const ctx = canvas.getContext('2d');
+
+        function resizeCanvas() {
+            canvas.width = window.innerWidth;
+            canvas.height = window.innerHeight;
+        }
+        window.addEventListener('resize', resizeCanvas);
+        resizeCanvas();
+
+        // Reaction-diffusion parameters adjusted for organism parameters
+        const params = {
+            feedRate: 0.055,
+            killRate: 0.062,
+            diffusionRateA: 1,
+            diffusionRateB: 0.5,
+            timeStep: 1,
+            cellSize: 4,
+            gridWidth: Math.floor(window.innerWidth / 4),
+            gridHeight: Math.floor(window.innerHeight / 4),
+            color1: '#f0f0f0',
+            color2: '#a0a0a0'
+        };
+
+        // Initialize grids
+        const grid = [];
+        const nextGrid = [];
+
+        function initGrids() {
+            for (let y = 0; y < params.gridHeight; y++) {
+                grid[y] = [];
+                nextGrid[y] = [];
+                for (let x = 0; x < params.gridWidth; x++) {
+                    // Sparse initial distribution (density=0.5)
+                    grid[y][x] = Math.random() > 0.95 ? 1 : 0;
+                    nextGrid[y][x] = 0;
+                }
+            }
+        }
+
+        // Laplacian convolution kernel
+        const kernel = [
+            [0.05, 0.2, 0.05],
+            [0.2, -1, 0.2],
+            [0.05, 0.2, 0.05]
+        ];
+
+        function update() {
+            for (let y = 0; y < params.gridHeight; y++) {
+                for (let x = 0; x < params.gridWidth; x++) {
+                    let sumA = 0;
+                    let sumB = 0;
+
+                    // Apply kernel
+                    for (let ky = -1; ky <= 1; ky++) {
+                        for (let kx = -1; kx <= 1; kx++) {
+                            const nx = (x + kx + params.gridWidth) % params.gridWidth;
+                            const ny = (y + ky + params.gridHeight) % params.gridHeight;
+                            const weight = kernel[ky + 1][kx + 1];
+                            sumA += grid[ny][nx] * weight;
+                            sumB += (1 - grid[ny][nx]) * weight;
+                        }
+                    }
+
+                    const cell = grid[y][x];
+                    const laplacianA = sumA;
+                    const laplacianB = sumB;
+
+                    // Gray-Scott reaction-diffusion equations
+                    const reaction = cell * laplacianB;
+                    const newA = cell + (params.diffusionRateA * laplacianA - reaction) * params.timeStep;
+                    const newB = (1 - cell) + (params.diffusionRateB * laplacianB + reaction) * params.timeStep;
+
+                    // Bounded to [0,1]
+                    nextGrid[y][x] = Math.min(Math.max(newA, 0), 1);
+                }
+            }
+
+            // Swap grids
+            [grid, nextGrid] = [nextGrid, grid];
+        }
+
+        function draw() {
+            ctx.clearRect(0, 0, canvas.width, canvas.height);
+
+            const scaleX = canvas.width / params.gridWidth;
+            const scaleY = canvas.height / params.gridHeight;
+
+            for (let y = 0; y < params.gridHeight; y++) {
+                for (let x = 0; x < params.gridWidth; x++) {
+                    const value = grid[y][x];
+                    if (value > 0.2) {
+                        // Complexity creates more intricate patterns
+                        const size = params.cellSize * value * (0.5 + params.complexity);
+                        const alpha = 0.1 + value * 0.9;
+
+                        // Monochrome dryness
+                        ctx.fillStyle = `rgba(240, 240, 240, ${alpha})`;
+                        ctx.beginPath();
+                        ctx.arc(
+                            x * scaleX + scaleX / 2,
+                            y * scaleY + scaleY / 2,
+                            size / 2,
+                            0,
+                            Math.PI * 2
+                        );
+                        ctx.fill();
+                    }
+                }
+            }
+        }
+
+        function animate() {
+            update();
+            draw();
+            requestAnimationFrame(animate);
+        }
+
+        // Start animation
+        initGrids();
+        animate();
+    </script>
+</body>
+</html>
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