{
  "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 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 located within the left and right inferior parietal lobule (IPL) achieves maximal decoding accuracy comparable to all channels. Decoding fell close to chance in a covert auditory condition in which participants held central fixation while attending to the same talkers, indicating that auditory attention alone without orientation is not sufficient for decoding. Finally, control experiments suggest that overt-condition decoding is influenced by sustained eye position/gaze direction, not eye movement. These results support the development of fNIRS-integrated BCIs and assistive devices controlled by overt spatial attention.",
  "abstract_shown": true,
  "affiliations": [
    "Neurophotonics Center, Department of Biomedical Engineering, Boston University, USA; Corresponding authors.",
    "Neurophotonics Center, Department of Biomedical Engineering, Boston University, USA",
    "Intelligent Biomedical Sensing (IBS) Lab, Machine Learning Department, Technical University of Berlin, Berlin, 10587, Germany; BIFOLD – Berlin Institute for the Foundations of Learning and Data, Berlin, 10587, Germany"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 15,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Sudan Duwadi"
    },
    {
      "affs": [
        1
      ],
      "name": "De’Ja Rogers"
    },
    {
      "affs": [
        1
      ],
      "name": "Alex D. Boyd"
    },
    {
      "affs": [
        1
      ],
      "name": "Laura B. Carlton"
    },
    {
      "affs": [
        1
      ],
      "name": "Yiwen Zhang"
    },
    {
      "affs": [
        1
      ],
      "name": "Anna Kawai Gaona"
    },
    {
      "affs": [
        1
      ],
      "name": "Aneesa Diya Pathiyaparambath"
    },
    {
      "affs": [
        1
      ],
      "name": "Ravin Chaudhury"
    },
    {
      "affs": [
        1
      ],
      "name": "Grace Magee"
    },
    {
      "affs": [
        1
      ],
      "name": "Bernhard B Zimmermann"
    },
    {
      "affs": [
        1
      ],
      "name": "Walker J O'Brien"
    },
    {
      "affs": [
        2
      ],
      "name": "Alexander von Lühmann"
    },
    {
      "affs": [
        1
      ],
      "name": "David A. Boas"
    },
    {
      "affs": [
        1
      ],
      "name": "Meryem A. Yücel"
    },
    {
      "affs": [
        0
      ],
      "name": "Kamal Sen"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9k0nfaagrbkah.bib",
  "cited_by": 0,
  "doi": "10.1016/j.neuroimage.2026.122292",
  "fulltext_url": "http://www.sciencedirect.com/science/article/pii/S1053811926006075",
  "id": "9k0nfaagrbkah",
  "issns": [
    "1095-9572",
    "1053-8119"
  ],
  "landing_url": "https://doi.org/10.1016/j.neuroimage.2026.122292",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "RC321-571"
    ],
    [
      "openalex",
      "2805|Neuroscience and Music Perception"
    ]
  ],
  "openalex": "W7222667514",
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/9k0nfaagrbkah.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:43:44Z",
      "native_id": "8e07e05498fe4df9be475140dbcc1f2f",
      "source": "doaj",
      "url": "https://doi.org/10.1016/j.neuroimage.2026.122292"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "openalex:2805|Neuroscience and Music Perception",
      "subfield": "neuroscience"
    }
  ],
  "title": "Decoding spatial attention in the cocktail party problem using whole-head high-density fNIRS",
  "title_text": "Decoding spatial attention in the cocktail party problem using whole-head high-density fNIRS",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:43:44Z",
  "url": "https://research.draconitic.com/paper/9k0nfaagrbkah",
  "venue": "NeuroImage",
  "versions": []
}