{
  "abstract": "Natural environments often change gradually, making it adaptive to bias decisions on the basis of the recent past — a phenomenon known as serial dependence1–3. Large-scale recordings during behaviour have identified that serial dependence is a common motif for decision-making, with neural representations of past experiences found throughout the brain4–11. However, it remains unclear whether this bias arises from dedicated neural circuits with history-specific computations. Using whole-brain, cellular-resolution imaging in zebrafish performing memory-guided evasive manoeuvres12–14, we identified a hierarchical circuit that maintains past information and biases future choices. Discrete attractors in the dorsal thalamus encoded the position of the most recent obstacle, maintaining a categorical memory via persistent activity lasting 10–20 s. Optogenetic manipulation of the dorsal thalamus abolished or imposed serial bias. A downstream hindbrain integrator received input from the thalamus and combined it with current sensory cues to produce graded responses reflecting multi-trial history. Leveraging a comprehensive brain atlas in zebrafish15, we constructed a whole-brain computational model that recapitulated behaviour and also predicted a key role for heterogeneous inhibitory subtypes in enabling flexible state transitions. This attractor–integrator architecture reveals a hierarchical and modular computation that unifies robust memory retention with flexible sensory integration, providing a general principle for history-biased decisions. Whole-brain, cellular-resolution imaging reveals a hierarchical thalamus–brainstem attractor network that encodes recent history and shapes behavioural bias in zebrafish.",
  "abstract_shown": true,
  "affiliations": [
    "Institute of Neuroscience, State Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China",
    "University of Chinese Academy of Sciences, Beijing, China",
    "School of Psychological and Cognitive Sciences, McGovern Institute for Brain Research, Center of Quantative Biology, PKU-Tsingua Center of Life Sciences, Peking University, Beijing, China",
    "Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China",
    "School of Biomedical Engineering, State Key Laboratory of Digital Medical Engineering, Key Laboratory of Biomedical Engineering of Hainan Province, Hainan University, Haikou, China",
    "School of Psychological and Cognitive Sciences, McGovern Institute for Brain Research, Center of Quantative Biology, PKU-Tsingua Center of Life Sciences, Peking University, Beijing, China. siwu@pku.edu.cn",
    "Institute of Neuroscience, State Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China. my@ion.ac.cn",
    "University of Chinese Academy of Sciences, Beijing, China. my@ion.ac.cn"
  ],
  "article_type": null,
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  "author_total": 18,
  "authors": [
    {
      "affs": [
        0,
        1
      ],
      "name": "Shan Zhao",
      "orcid": "0000-0002-6470-2250"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Heying Shan",
      "orcid": "0009-0009-7653-5435"
    },
    {
      "affs": [
        2
      ],
      "name": "Xiao Liu",
      "orcid": "0000-0002-2855-7367"
    },
    {
      "affs": [
        0
      ],
      "name": "Yu Qian",
      "orcid": "0000-0002-1587-9025"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Jingyao Huang",
      "orcid": "0009-0000-6634-0129"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Yiran Liu",
      "orcid": "0009-0006-1809-318X"
    },
    {
      "affs": [
        3
      ],
      "name": "Zhenfei Jiao"
    },
    {
      "affs": [
        0
      ],
      "name": "Lichen Ye"
    },
    {
      "affs": [
        0
      ],
      "name": "Lin Cong"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Xiaoou Wang",
      "orcid": "0009-0007-4721-9965"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Zhi-Yuan Wang"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Danyang Li"
    },
    {
      "affs": [
        0
      ],
      "name": "Ming-Chuan Chen",
      "orcid": "0000-0001-5964-9398"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Kai Wang",
      "orcid": "0000-0001-7858-944X"
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    {
      "affs": [
        4
      ],
      "name": "Ling Fu",
      "orcid": "0000-0003-2513-1405"
    },
    {
      "affs": [
        0,
        1
      ],
      "name": "Xu-Fei Du",
      "orcid": "0000-0002-4599-0074"
    },
    {
      "affs": [
        5
      ],
      "name": "Si Wu",
      "orcid": "0000-0001-9650-6935"
    },
    {
      "affs": [
        6,
        7
      ],
      "name": "Yu Mu",
      "orcid": "0000-0001-9297-4854"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/92d3gjmbfb1g2.bib",
  "cited_by": 5,
  "doi": "10.1038/s41586-026-10623-3",
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  "id": "92d3gjmbfb1g2",
  "issns": [
    "0028-0836",
    "1476-4687"
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  "landing_url": "https://doi.org/10.1038/s41586-026-10623-3",
  "language": "en",
  "licence": "CC-BY-NC-ND",
  "licence_label": "CC BY-NC-ND",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/",
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  "pdf_url": null,
  "pmcid": null,
  "pmid": "42271064",
  "published": "2026-06-10",
  "publisher": "Nature Portfolio",
  "ris": "https://research.draconitic.com/paper/92d3gjmbfb1g2.ris",
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  "subjects": [
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      "field": "biology",
      "origin": "openalex:2805|Neural dynamics and brain function",
      "subfield": "neuroscience"
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  "title": "A thalamus–brainstem attractor network drives history-biased decisions",
  "title_text": "A thalamus–brainstem attractor network drives history-biased decisions",
  "type": "peer-reviewed",
  "updated_at": "2026-11-13T13:21:09Z",
  "url": "https://research.draconitic.com/paper/92d3gjmbfb1g2",
  "venue": "Nature",
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