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PreprintCC BYbioRxiv

Marmosets adaptively accumulate dynamic sequential evidence to make decisions

  • X. Xia1
  • L. Bo
  • N.-l. Xu
  1. 1School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China.
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Abstract

The bounded accumulation model is a dominant theoretical framework to characterize evidence accumulation during decision-making. Using a dynamic sequential tone accumulation (DSTA) task in marmosets, we found that the contribution of late tones to decisions was greater for weaker than for stronger evidence strength-an effect we term evidence-strength-dependent temporal weighting (ETW). Rigorous exclusionary analyses and drift-diffusion modeling further revealed that the bounded accumulation mechanism alone fails to account for this effect, and the online modulation of attentional engagement was identified as the necessary mechanism in addition to the bounded accumulation. Our work thus establishes that attentional engagement is adaptively modulated by evidence strength during complex decision-making.

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Cite

BibTeXRIS
BibTeX
@misc{xia2026marmosets,
  title = {{Marmosets adaptively accumulate dynamic sequential evidence to make decisions}},
  author = {X. Xia and L. Bo and N.-l. Xu},
  howpublished = {bioRxiv},
  year = {2026},
  month = aug,
  doi = {10.64898/2026.08.31.747938},
  url = {https://www.biorxiv.org/content/10.64898/2026.08.31.747938v1},
  note = {CC BY},
}
RIS
TY  - UNPB
TI  - Marmosets adaptively accumulate dynamic sequential evidence to make decisions
AU  - X. Xia
AU  - L. Bo
AU  - N.-l. Xu
PY  - 2026
DA  - 2026/08/31
PB  - bioRxiv
DO  - 10.64898/2026.08.31.747938
UR  - https://www.biorxiv.org/content/10.64898/2026.08.31.747938v1
AB  - The bounded accumulation model is a dominant theoretical framework to characterize evidence accumulation during decision-making. Using a dynamic sequential tone accumulation (DSTA) task in marmosets, we found that the contribution of late tones to decisions was greater for weaker than for stronger evidence strength-an effect we term evidence-strength-dependent temporal weighting (ETW). Rigorous exclusionary analyses and drift-diffusion modeling further revealed that the bounded accumulation mechanism alone fails to account for this effect, and the online modulation of attentional engagement was identified as the necessary mechanism in addition to the bounded accumulation. Our work thus establishes that attentional engagement is adaptively modulated by evidence strength during complex decision-making.
ER  -