The Problem: Visualizing Complexity
Traditional 2D representations fail to capture the full complexity of neural activity patterns. This is especially true for volumetric datasets that require multi-scale visualization and interactive exploration.
// Sample code from neural renderer
class NeuralMesh {
constructor(webGPUDevice) {
this.vertexBuffer = webGPUDevice.createBuffer({
size: numVertices * Float32Array.BYTES_PER_ELEMENT * 6,
usage: GPUBufferUsage.VERTEX | GPUBufferUsage.COPY_DST
});
// Initialize simulation parameters
this.synapticStrengthMap = new GPUTexture({
size: [512, 512, 1],
format: 'rgba16float',
usage: GPUTextureUsage.TEXTURE_BINDING | GPUTextureUsage.RENDER_ATTACHMENT
});
}
render() {
// GPU compute pipeline execution
this.computePass.setPipeline(this.computePipeline);
this.computePass.dispatchWorkgroups(this.workgroupCountX, this.workgroupCountY, 1);
// Rendering pipeline setup
const renderPass = this.device.createRenderPassDescriptor({
colorAttachments: [{
view: presentationView,
clearValue: { r: 0.1, g: 0.1, b: 0.1, a: 1.0 },
loadOp: 'clear',
storeOp: 'store'
}]
});
renderPass.setPipeline(this.renderPipeline);
renderPass.setVertexBuffer(0, this.vertexBuffer);
renderPass.draw(6 * this.numVertices, 1, 0, 0);
}
}