Decoding Spatial Attention in the Cocktail Party Problem Using Wearable Whole-head High-Density fNIRS
Sudan DuwadiiD, De’Ja RogersiD, Alex D. Boyd, Laura B. CarltoniD, Yiwen ZhangiD, Anna Kawai Gaona, Aneesa Diya Pathiyaparambath, Ravin Chaudhury, Grace Magee, Bernhard B ZimmermanniD, Walker Joseph O’BrieniD, Alexander von LühmanniD, David A. BoasiD, Meryem A. YüceliD, Kamal SeniD
Abstract
Spatial attention is critical for solving the cocktail party problem, a longstanding problem in neuroscience and artificial speech recognition. The ability to decode where humans are attending in a cocktail party like scene would empower applications in brain computer interfaces and assistive devices such as hearing aids. Here we demonstrate that, in an overt attention task, the attended spatial location can be decoded robustly from single trial hemodynamic responses, using a wearable whole head high density fNIRS system. We also identify critical brain regions that make the highest contribution to decoding accuracy. Specifically, we find that decoding based on a small fraction of channels within the left and right inferior parietal lobule (IPL), achieve maximal decoding accuracy comparable to all channels. These results open the way for the design of novel BCIs and assistive devices integrated with fNIRS, that can be steered by spatial attention.
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