{
  "id": 7840018,
  "title": "Local recurrence accounts for extended processing during occluded-object recognition",
  "url": "https://urgent.news/2026/09/16/local-recurrence-accounts-for-extended-processing-during-occluded",
  "topic": "science",
  "section": "Science",
  "published": "2026-09-16T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.10.750662v1?rss=1"
  },
  "original_language": "en",
  "account": "A study investigated the neural processes involved in recognizing objects from incomplete visual input. Researchers employed various techniques, including MEG, time-resolved decoding, backward masking, representational Granger causality, and computational modeling, to examine these mechanisms in specific brain regions. They found that occlusion delayed the emergence of category information and triggered a late component that was disrupted by backward masking, indicating a dependence on continued processing. However, no changes were observed in the relative timing of regional responses or interareal interactions, including no increase in feedback among the examined brain regions. To explore computational mechanisms, the researchers compared three model variants: feedforward, local recurrent, and local recurrent with added long-range top-down feedback. The study revealed that local recurrence enhanced recognition under occlusion and increased model-brain correspondence during the mask-sensitive interval, particularly in early visual cortex. Adding the top-down pathway did not provide any consistent additional benefit. The findings suggest that prolonged local recurrent processing is a key factor in supporting occluded-object recognition under the tested conditions.",
  "summary": "Recognizing objects from incomplete visual input often requires processing beyond the initial feedforward sweep, but the relative contributions of local recurrence and long-range top-down feedback remain unclear. We combined source-localized magnetoencephalography (MEG), time-resolved decoding, backward masking, representational Granger causality, and computational modeling to examine these…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}