{
  "id": 12855301,
  "title": "Neural latent representation of implicit perceptual decision confidence signatures from brain-wide intracranial EEG",
  "url": "https://urgent.news/2026/10/08/neural-latent-representation-of-implicit-perceptual-decision",
  "topic": "science",
  "section": "Science",
  "published": "2026-10-08T00:00:00.000Z",
  "source": {
    "name": "bioRxiv",
    "slug": "biorxiv",
    "url": "https://www.biorxiv.org/content/10.64898/2026.09.30.755781v1?rss=1"
  },
  "original_language": "en",
  "account": "Human perception of decision confidence has been linked to brain-wide signaling, but the consistency across studies is questionable. The researchers aimed to determine if more robust neural latent representations could be found, especially for implicit confidence. They utilized various machine learning techniques on extensive brain-wide intracranial electroencephalography (iEEG) data that did not include explicit confidence reports. By employing explainable feature selection methods, they identified key spatiotemporal iEEG components, primarily in the frontal cortex, which could effectively differentiate confidence characteristics associated with correct decisions, difficulty, and speed. These characteristics were also transferable across different motor modalities. Although there were inconsistencies in the features identified across the different methods and conditions, dimensionality reductions still revealed robust low-dimensional neural latent representations. Moreover, the neural trajectories within a shared subspace enhanced the distinguishability of these confidence characteristics. In summary, the findings shed light on low-dimensional spatial and temporal neural latent representations that are fundamental to human implicit perceptual decision confidence, demonstrating their robustness across various analytical methods and decision conditions.",
  "summary": "Human perceptual decision confidence has been associated with brain-wide signalling, albeit with inconsistencies across studies. It remains unclear whether more robust neural latent representations exist, particularly for implicit confidence. We address this by applying complementary machine learning approaches to comprehensive, brain-wide intracranial electroencephalography (iEEG) data acquired…",
  "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."
}