We demonstrate the possibility of reconstructing images from fNIRS brain
activity and start building a prototype to match the required specs. By
training an image reconstruction model on downsampled fMRI data, we discovered
that cm-scale spatial resolution is sufficient for image generation. We
obtained 71% retrieval accuracy with 1-cm resolution, compared to 93% on the
full-resolution fMRI, and 20% with 2-cm resolution. With simulations and
high-density tomography, we found that time-domain fNIRS can achieve 1-cm
resolution, compared to 2-cm resolution for continuous-wave fNIRS. Lastly, we
share designs for a prototype time-domain fNIRS device, consisting of a laser
driver, a single photon detector, and a time-to-digital converter system.

通过训练图像重建模型，我们证明了从 fNIRS 脑活动中重建图像的可能性，并开始构建一个符合要求的原型。我们发现厘米级空间分辨率足以生成图像，通过下采样的 fMRI 数据，我们获得了 1 厘米分辨率的 71％检索准确率，而全分辨率的 fMRI 为 93％，2 厘米分辨率下为 20％。我们的模拟和高密度层析成像结果表明，时间域 fNIRS 可以达到 1 厘米分辨率，而连续波 fNIRS 为 2 厘米分辨率。最后，我们分享了一个原型时间域 fNIRS 设备的设计，包括激光驱动器，单光子探测器和时间数字转换器系统。