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Progress Towards Decoding Visual Imagery via fNIRS

Authors :
Adamic, Michel
Avelino, Wellington
Brandenberger, Anna
Chiang, Bryan
Davis, Hunter
Fay, Stephen
Gregory, Andrew
Gupta, Aayush
Hotter, Raphael
Jiang, Grace
Leng, Fiona
Polcyn, Stephen
Ribeiro, Thomas
Scotti, Paul
Wang, Michelle
Xiong, Marley
Xu, Jonathan
Publication Year :
2024

Abstract

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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2406.07662
Document Type :
Working Paper