In plain words: They checked whether a wearable scanner could rebuild pictures from brain activity by blurring fMRI data to coarser grids and seeing how well images returned. At 1-cm detail it matched the right image 71% of the time, and their device design can reach it.
Abstract · Progress Towards Decoding Visual Imagery via fNIRS
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.
Michel Adamic, Wellington Avelino, Anna Brandenberger, Bryan Chiang, Hunter Davis, Stephen Fay, Andrew Gregory, Aayush Gupta, Raphael Hotter, Grace Jiang, Fiona Leng, Stephen Polcyn, et al.
arXiv:2406.07662 · eess.IV, cs.AI, cs.CV, cs.LG, q-bio.NC · submitted Jun 11, 2024 · updated Jun 22, 2024
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